💻 ble_based_indoor_localization_analysis_performance_improvement_2024.html
html · 3085 lines · ⬇️ Download
<!DOCTYPE html>
<html lang="en" >
<head >
<meta charset="UTF-8" />
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="HandheldFriendly" content="True" />
<meta name="MobileOptimized" content="320" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="stylesheet" href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/base_style-BxRs1iOp.css" />
<script type="module" crossorigin="" src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/base_style-D-jH62-1.js"></script>
<link rel="stylesheet" href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/article_style-B67IZFds.css" />
<link rel="stylesheet" href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/style-D77LS1kY.css" />
<script type="module" crossorigin="" src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/article_style-CTAd1LmM.js"></script>
<style>
@media screen and (min-width: 64em) {
div.pmc-wm {
background: repeat-y;
background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='20' height='350' xmlns:xlink='http://www.w3.org/1999/xlink'%3E%3Cdefs%3E%3Cfilter x='-.02' y='0' width='1.05' height='1' id='c'%3E%3CfeFlood flood-color='%23FFF'/%3E%3CfeComposite in='SourceGraphic'/%3E%3C/filter%3E%3Ctext id='b' font-family='Helvetica' font-size='11pt' style='opacity:1;fill:%23005ea2;stroke:none;text-anchor:middle' x='175' y='14'%3E%3C/text%3E%3Cpath id='a' style='fill:%23005ea2' d='M0 8h350v3H0z'/%3E%3C/defs%3E%3Cuse xlink:href='%23a' transform='rotate(90 10 10)'/%3E%3Cuse xlink:href='%23b' transform='rotate(90 10 10)' filter='url(%23c)'/%3E%3C/svg%3E");
padding-left: 3rem;
}
}
</style>
<link rel="apple-touch-icon"
sizes="180x180"
href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/apple-touch-icon.png" />
<link rel="icon"
type="image/png"
sizes="48x48"
href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/favicon-48x48.png" />
<link rel="icon"
type="image/png"
sizes="32x32"
href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/favicon-32x32.png" />
<link rel="icon"
type="image/png"
sizes="16x16"
href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/favicon-16x16.png" />
<link rel="manifest" href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/site.webmanifest" />
<link rel="mask-icon"
href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/safari-pinned-tab.svg"
color="#0071bc" />
<meta name="msapplication-config"
content="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/favicons/browserconfig.xml" />
<meta name="theme-color" content="#ffffff" />
<title>
BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement - PMC
</title>
<meta name="ncbi_app" content="cloudpmc-viewer" />
<meta name="ncbi_db" content="pmc" />
<meta name="ncbi_phid" content="1A8158F49E0AD0130E58F4002610AF20.m_1" />
<meta name="ncbi_pinger_stat_url" content="https://pmc.ncbi.nlm.nih.gov/stat" />
<meta name="ncbi_pdid" content="article" />
<link rel="preconnect" href="https://www.google-analytics.com" />
<link rel="preconnect" href="https://cdn.ncbi.nlm.nih.gov" />
<script src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/uswds-init.js"></script>
<meta name="ncbi_domain" content="sensors">
<meta name="ncbi_type" content="fulltext">
<meta name="ncbi_pcid" content="journal">
<meta name="ncbi_feature" content="associated_data">
<link rel="canonical" href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/">
<meta name="robots" content="INDEX,NOFOLLOW,NOARCHIVE">
<meta name="citation_journal_title" content="Sensors (Basel, Switzerland)">
<meta name="citation_title" content="BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement">
<meta name="citation_author" content="Filippo Milano">
<meta name="citation_author_institution" content="Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy; ferrigno@unicas.it">
<meta name="citation_author" content="Helbert da Rocha">
<meta name="citation_author_institution" content="Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)">
<meta name="citation_author_institution" content="Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal">
<meta name="citation_author" content="Marco Laracca">
<meta name="citation_author_institution" content="Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, 00185 Rome, Italy; marco.laracca@uniroma1.it">
<meta name="citation_author" content="Luigi Ferrigno">
<meta name="citation_author_institution" content="Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy; ferrigno@unicas.it">
<meta name="citation_author" content="António Espírito Santo">
<meta name="citation_author_institution" content="Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)">
<meta name="citation_author_institution" content="Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal">
<meta name="citation_author" content="José Salvado">
<meta name="citation_author_institution" content="Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)">
<meta name="citation_author_institution" content="Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal">
<meta name="citation_author" content="Vincenzo Paciello">
<meta name="citation_author_institution" content="Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy; vpaciello@unisa.it">
<meta name="citation_publication_date" content="2024 Jan 8">
<meta name="citation_volume" content="24">
<meta name="citation_issue" content="2">
<meta name="citation_firstpage" content="0">
<meta name="citation_doi" content="10.3390/s24020376">
<meta name="citation_pmid" content="38257468">
<meta name="citation_abstract_html_url" content="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/">
<meta name="citation_fulltext_html_url" content="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/">
<meta name="citation_pdf_url" content="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/pdf/sensors-24-00376.pdf">
<meta name="description" content="This paper addresses indoor localization using an anchor-based system based on Bluetooth Low Energy (BLE) 5.0 technology, adopting the Received Signal Strength Indicator (RSSI) for the distance estimation. Different solutions have been proposed in ...">
<meta name="og:title" content="BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement">
<meta name="og:type" content="article">
<meta name="og:site_name" content="PubMed Central (PMC)">
<meta name="og:description" content="This paper addresses indoor localization using an anchor-based system based on Bluetooth Low Energy (BLE) 5.0 technology, adopting the Received Signal Strength Indicator (RSSI) for the distance estimation. Different solutions have been proposed in ...">
<meta name="og:url" content="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/">
<meta name="og:image" content="https://cdn.ncbi.nlm.nih.gov/pmc/cms/images/pmc-card-share.jpg?_=0">
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:site" content="@ncbi">
</head>
<body >
<a class="usa-skipnav " href="#main-content">
Skip to main content
</a>
<section class="usa-banner " aria-label="Official website of the United States government" >
<div class="usa-accordion">
<header class="usa-banner__header">
<div class="usa-banner__inner">
<div class="grid-col-auto">
<img aria-hidden="true"
class="usa-banner__header-flag"
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/us_flag.svg"
alt="" />
</div>
<div class="grid-col-fill tablet:grid-col-auto" aria-hidden="true">
<p class="usa-banner__header-text">
An official website of the United States government
</p>
<span class="usa-banner__header-action">Here's how you know</span>
</div>
<button
type="button"
class="usa-accordion__button usa-banner__button
"
aria-expanded="false"
aria-controls="gov-banner-default"
data-testid="storybook-django-banner"
>
<span class="usa-banner__button-text">Here's how you know</span>
</button>
</div>
</header>
<div class="usa-banner__content usa-accordion__content"
id="gov-banner-default"
hidden>
<div class="grid-row grid-gap-lg">
<div class="usa-banner__guidance tablet:grid-col-6">
<img class="usa-banner__icon usa-media-block__img"
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/icon-dot-gov.svg"
alt=""
aria-hidden="true" />
<div class="usa-media-block__body">
<p>
<strong>Official websites use .gov</strong>
<br />
A
<strong>.gov</strong> website belongs to an official
government organization in the United States.
</p>
</div>
</div>
<div class="usa-banner__guidance tablet:grid-col-6">
<img class="usa-banner__icon usa-media-block__img"
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/icon-https.svg"
alt=""
aria-hidden="true" />
<div class="usa-media-block__body">
<p>
<strong>Secure .gov websites use HTTPS</strong>
<br />
A <strong>lock</strong> (
<span class="icon-lock">
<svg xmlns="http://www.w3.org/2000/svg"
width="52"
height="64"
viewBox="0 0 52 64"
class="usa-banner__lock-image"
role="graphics-symbol"
aria-labelledby="banner-lock-description"
focusable="false">
<title id="banner-lock-title">Lock</title>
<desc id="banner-lock-description">
Locked padlock icon
</desc>
<path fill="#000000"
fill-rule="evenodd"
d="M26 0c10.493 0 19 8.507 19 19v9h3a4 4 0 0 1 4 4v28a4 4 0 0 1-4 4H4a4 4 0 0 1-4-4V32a4 4 0 0 1 4-4h3v-9C7 8.507 15.507 0 26 0zm0 8c-5.979 0-10.843 4.77-10.996 10.712L15 19v9h22v-9c0-6.075-4.925-11-11-11z" />
</svg>
</span>) or <strong>https://</strong> means you've safely
connected to the .gov website. Share sensitive
information only on official, secure websites.
</p>
</div>
</div>
</div>
</div>
</div>
</section>
<div class="usa-overlay">
</div>
<header class="usa-header usa-header--extended usa-header--wide" data-header data-testid="header" >
<div class="ncbi-header">
<div class="ncbi-header__container">
<a class="ncbi-header__logo-container"
href="https://www.ncbi.nlm.nih.gov/">
<img alt="NCBI home page"
class="ncbi-header__logo-image"
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/ncbi-logos/nih-nlm-ncbi--white.svg"
width="410"
height="100" />
</a>
<button
type="button"
class="usa-menu-btn ncbi-header__hamburger-button
"
aria-label="Show menu"
data-testid="navMenuButton"
>
<svg aria-hidden="true"
class="ncbi-hamburger-icon"
fill="none"
focusable="false"
height="21"
viewBox="0 0 31 21"
width="31"
xmlns="http://www.w3.org/2000/svg">
<path clip-rule="evenodd"
d="M0.125 20.75H30.875V17.3333H0.125V20.75ZM0.125 12.2083H30.875V8.79167H0.125V12.2083ZM0.125 0.25V3.66667H30.875V0.25H0.125Z"
fill="#F1F1F1"
fill-rule="evenodd" />
</svg>
</button>
<div class="ncbi-header__desktop-buttons">
<button
type="button"
class="usa-button
usa-button--unstyled ncbi-header__desktop-button
"
aria-expanded="false"
aria-controls="search-field-desktop-navigation"
aria-label="Show search overlay"
data-testid="toggleSearchPanelButton"
data-toggle-search-panel-button
>
<img
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/search.svg"
class="usa-icon "
aria-hidden="true"
/>
Search
</button>
<div class="ncbi-header__login-dropdown">
<button
type="button"
class="usa-button
usa-button--unstyled ncbi-header__desktop-button ncbi-header__login-dropdown-button
"
aria-expanded="false"
aria-controls="login-dropdown-menu"
aria-label="Show login menu"
data-testid="toggleLoginMenuDropdown"
data-desktop-login-button
>
<img
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/person.svg"
class="usa-icon "
aria-hidden="true"
/>
<span data-login-dropdown-text>Log in</span>
<img
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/expand_less.svg"
class="usa-icon ncbi-header__login-dropdown-icon ncbi-header__login-dropdown-icon--expand-less ncbi-header__login-dropdown-icon--hidden"
aria-hidden="true"
data-login-dropdown-up-arrow
/>
<img
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/expand_more.svg"
class="usa-icon ncbi-header__login-dropdown-icon ncbi-header__login-dropdown-icon--expand-more ncbi-header__login-dropdown-icon--hidden"
aria-hidden="true"
data-login-dropdown-down-arrow
/>
</button>
<ul class="usa-nav__submenu ncbi-header__login-dropdown-menu"
id="login-dropdown-menu"
data-desktop-login-menu-dropdown
hidden>
<li class="usa-nav__submenu-item">
<a href="https://www.ncbi.nlm.nih.gov/myncbi/" class="usa-link " >
Dashboard
</a>
</li>
<li class="usa-nav__submenu-item">
<a href="https://www.ncbi.nlm.nih.gov/myncbi/collections/bibliography/" class="usa-link " >
Publications
</a>
</li>
<li class="usa-nav__submenu-item">
<a href="https://www.ncbi.nlm.nih.gov/account/settings/" class="usa-link " >
Account settings
</a>
</li>
<li class="usa-nav__submenu-item">
<button
type="button"
class="usa-button
usa-button--outline ncbi-header__login-dropdown-logout-button
"
data-testid="desktopLogoutButton"
data-desktop-logout-button
>
Log out
</button>
</li>
</ul>
</div>
</div>
</div>
</div>
<div class="ncbi-search-panel ncbi--show-only-at-desktop"
data-header-search-panel
hidden>
<div class="ncbi-search-panel__container">
<form action="https://www.ncbi.nlm.nih.gov/search/all/"
autocomplete="off"
class="usa-search usa-search--big ncbi-search-panel__form"
data-testid="desktop-navigation-search-form"
method="GET"
role="search">
<label class="usa-sr-only" for="search-field-desktop-navigation">
Search…
</label>
<input class="usa-input"
id="search-field-desktop-navigation"
name="term"
placeholder="Search NCBI"
type="search"
value="" />
<button
type="submit"
class="usa-button
"
>
<span class="usa-search__submit-text">
Search NCBI
</span>
</button>
</form>
</div>
</div>
<nav aria-label="Primary navigation" class="usa-nav">
<p class="usa-sr-only" id="primary-navigation-sr-only-title">
Primary site navigation
</p>
<button
type="button"
class="usa-nav__close ncbi-nav__close-button
"
aria-label="Close navigation menu"
data-testid="navCloseButton"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/usa-icons/close.svg" alt="Close" />
</button>
<form class="usa-search usa-search--small ncbi--hide-at-desktop"
action="https://www.ncbi.nlm.nih.gov/search/all/"
autocomplete="off"
data-testid="mobile-navigation-search-form"
method="GET"
role="search">
<label class="usa-sr-only" for="search-field-mobile-navigation">
Search
</label>
<input class="usa-input"
id="search-field-mobile-navigation"
type="search"
placeholder="Search NCBI"
name="term" />
<button
type="submit"
class="usa-button
"
>
<img src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjI0Ij48cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZmlsbD0iI2ZmZiIgZD0iTTE1LjUgMTRoLS43OWwtLjI4LS4yN0E2LjQ3MSA2LjQ3MSAwIDAgMCAxNiA5LjUgNi41IDYuNSAwIDEgMCA5LjUgMTZjMS42MSAwIDMuMDktLjU5IDQuMjMtMS41N2wuMjcuMjh2Ljc5bDUgNC45OUwyMC40OSAxOWwtNC45OS01em0tNiAwQzcuMDEgMTQgNSAxMS45OSA1IDkuNVM3LjAxIDUgOS41IDUgMTQgNy4wMSAxNCA5LjUgMTEuOTkgMTQgOS41IDE0eiIvPjwvc3ZnPg=="
class="usa-search__submit-icon"
alt="Search" />
</button>
</form>
<div class="ncbi-nav__mobile-login-menu ncbi--hide-at-desktop"
data-mobile-login-menu
hidden>
<p class="ncbi-nav__mobile-login-menu-status">
Logged in as:
<strong class="ncbi-nav__mobile-login-menu-email"
data-mobile-login-email-text></strong>
</p>
<ul class="usa-nav__primary usa-accordion">
<li class="usa-nav__primary-item">
<a href="https://www.ncbi.nlm.nih.gov/myncbi/" class="usa-link " >
Dashboard
</a>
</li>
<li class="usa-nav__primary-item">
<a href="https://www.ncbi.nlm.nih.gov/myncbi/collections/bibliography/" class="usa-link " >
Publications
</a>
</li>
<li class="usa-nav__primary-item">
<a href="https://www.ncbi.nlm.nih.gov/account/settings/" class="usa-link " >
Account settings
</a>
</li>
</ul>
</div>
<button
type="button"
class="usa-button
ncbi-nav__mobile-login-button ncbi--hide-at-desktop
"
data-testid="mobileLoginButton"
data-mobile-login-button
>
Log in
</button>
</nav>
</header>
<section class="pmc-header pmc-header--basic" aria-label="PMC Header with search box">
<div class="pmc-nav-container">
<div class="pmc-header__bar">
<div class="pmc-header__logo">
<a href="/" title="Home" aria-label="PMC Home"></a>
</div>
<button
type="button"
class="usa-button usa-button--unstyled pmc-header__search__button"
aria-label="Open search"
data-ga-category="search"
data-ga-action="PMC"
data-ga-label="pmc_search_panel_mobile"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/search.svg" alt="PMC search open icon" aria-hidden="true" class="usa-icon usa-icon--size-4 pmc-icon__open" />
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/close.svg" alt="PMC search close ison" aria-hidden="true" class="usa-icon usa-icon--size-4 pmc-icon__close" />
</button>
</div>
<div class="pmc-header__search">
<form class="usa-search usa-search--extra usa-search--article-right-column pmc-header__search__form" id="pmc-search-form" autocomplete="off" role="search">
<label class="usa-sr-only" for="pmc-search">Search PMC Full-Text Archive</label>
<span class="autoComplete_wrapper flex-1">
<input class="usa-input width-full maxw-none" required="required" placeholder="Search PMC Full-Text Archive" id="pmc-search" type="search" name="term" data-autocomplete-url="https://pmc.ncbi.nlm.nih.gov/autocomp/search/autocomp/"/>
</span>
<button
class="usa-button"
type="submit"
formaction="https://pmc.ncbi.nlm.nih.gov/search/"
data-ga-category="search"
data-ga-action="PMC"
data-ga-label="PMC_search_button"
>
<span class="usa-search__submit-text">Search in PMC</span>
<img
src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/usa-icons-bg/search--white.svg"
class="usa-search__submit-icon"
alt="Search"
/>
</button>
</form>
<div class="display-flex flex-column tablet:flex-row tablet:flex-justify flex-justify-center flex-align-center width-full desktop:maxw-44">
<ul class="pmc-header__search__menu">
<li>
<a class="usa-link" href="/journals/" data-ga-action="featured_link" data-ga-label="journal list">
Journal List
</a>
</li>
<li>
<a class="usa-link" href="/about/userguide/" data-ga-action="featured_link"
data-ga-label="user guide">
User Guide
</a>
</li>
</ul>
</div>
</div>
</div>
</section>
<div class="usa-section padding-top-0 desktop:padding-top-6 pmc-article-section" data-article-db="pmc" data-article-id="11154453">
<div class="grid-container pmc-actions-bar" aria-label="Actions bar" role="complementary">
<div class="grid-row">
<div class="grid-col-fill display-flex">
<div class="display-flex">
<ul class="usa-list usa-list--unstyled usa-list--horizontal">
<li class="margin-right-2 mobile-lg:margin-right-4 display-flex mob">
<button
type="button"
class="usa-button pmc-sidenav__container__open usa-button--unstyled width-auto display-flex"
aria-label="Open resources"
data-extra-class="is-visible-resources"
data-ga-category="resources_accordion"
data-ga-action="click"
data-ga-label="mobile_icon"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/more_vert.svg" alt="Open resources icon" class="usa-icon usa-icon--size-4 usa-icon--link" />
</button>
</li>
<li class="margin-right-2 mobile-lg:margin-right-4 display-flex mob">
<a
href="https://doi.org/10.3390/s24020376"
class="usa-link display-flex usa-tooltip"
role="button"
target="_blank"
rel="noreferrer noopener"
title="View on publisher site"
data-position="bottom"
aria-label="View on publisher site"
data-ga-category="actions"
data-ga-action="click"
data-ga-label="publisher_link_mobile"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/launch.svg" alt="View on publisher site icon" class="usa-icon usa-icon--size-4 usa-icon--link" />
</a>
</li>
<li class="margin-right-2 mobile-lg:margin-right-4 display-flex">
<a
href="pdf/sensors-24-00376.pdf"
class="usa-link display-flex usa-tooltip"
role="button"
title="Download PDF"
data-position="bottom"
aria-label="Download PDF"
data-ga-category="actions"
data-ga-action="click"
data-ga-label="pdf_download_mobile"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/file_download.svg" alt="Download PDF icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link" />
</a>
</li>
<li class="margin-right-2 mobile-lg:margin-right-4 display-flex">
<button
class="usa-button usa-button--unstyled usa-tooltip collections-dialog-trigger collections-button display-flex collections-button-empty"
title="Add to Collections"
data-position="bottom"
aria-label="Save article in MyNCBI collections."
data-ga-category="actions"
data-ga-action="click"
data-ga-label="collections_button_mobile"
data-collections-open-dialog-enabled="false"
data-collections-open-dialog-url="https://account.ncbi.nlm.nih.gov/?back_url=https%3A%2F%2Fpmc.ncbi.nlm.nih.gov%2Farticles%2FPMC11154453%2F%23open-collections-dialog"
data-in-collections="false"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/action-bookmark-full.svg" alt="Collections icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link usa-icon--bookmark-full" />
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/action-bookmark-empty.svg" alt="Collections icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link usa-icon--bookmark-empty" />
</button>
</li>
<li class="margin-right-2 mobile-lg:margin-right-4 display-flex">
<button role="button" class="usa-button usa-button--unstyled usa-tooltip citation-dialog-trigger display-flex"
aria-label="Open dialog with citation text in different styles"
title="Cite"
data-position="bottom"
data-ga-category="actions"
data-ga-action="open"
data-ga-label="cite_mobile"
data-all-citations-url="/resources/citations/11154453/"
data-citation-style="nlm"
data-download-format-link="/resources/citations/11154453/export/"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/format_quote.svg" alt="Cite icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link" />
</button>
</li>
<li class="pmc-permalink display-flex" >
<button
type="button"
title="Permalink"
data-position="bottom"
class="usa-button usa-button--unstyled display-flex usa-tooltip"
aria-label="Show article permalink"
aria-expanded="false"
aria-haspopup="true"
data-ga-category="actions"
data-ga-action="open"
data-ga-label="permalink_mobile"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/share.svg" alt="Show article permalink icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link" />
</button>
<div class="pmc-permalink__dropdown" hidden>
<div class="pmc-permalink__dropdown__container">
<h2 class="usa-modal__heading margin-top-0 margin-bottom-2 text-uppercase font-sans-xs">PERMALINK</h2>
<div class="pmc-permalink__dropdown__content">
<input type="text" class="usa-input" value="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/" aria-label="Article permalink">
<button class="usa-button display-inline-flex pmc-permalink__dropdown__copy__btn margin-right-0" title="Copy article permalink" data-ga-category="save_share" data-ga-action="link" data-ga-label="copy_link">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/content_copy.svg" alt="Copy icon" aria-hidden="true" class="usa-icon usa-icon--white" />
<span class="margin-left-1">Copy</span>
</button>
</div>
</div>
</div>
</li>
</ul>
</div>
<button
type="button"
class="usa-button pmc-sidenav__container__open usa-button--unstyled width-auto display-flex"
aria-label="Open article navigation"
data-extra-class="is-visible-in-page"
data-ga-category="actions"
data-ga-action="open"
data-ga-label="article_nav_mobile"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/list.svg" alt="Open article navigation icon" aria-hidden="true" class="usa-icon usa-icon--size-4 usa-icon--link" />
</button>
</div>
</div>
</div>
<div class="grid-container desktop:padding-left-6">
<div id="article-container" class="grid-row grid-gap">
<div class="grid-col-12 desktop:grid-col-8 order-2 pmc-layout__content">
<div class="grid-container padding-left-0 padding-right-0">
<div class="grid-row desktop:margin-left-neg-6">
<div class="grid-col-12">
<div class="pmc-layout__disclaimer" role="complementary" aria-label="Disclaimer note">
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with,
the contents by NLM or the National Institutes of Health.<br/>
Learn more:
<a class="usa-link" data-ga-category="Link click" data-ga-action="Disclaimer" data-ga-label="New disclaimer box" href="/about/disclaimer/">PMC Disclaimer</a>
|
<a class="usa-link" data-ga-category="Link click" data-ga-action="PMC Copyright Notice" data-ga-label="New disclaimer box" href="/about/copyright/">
PMC Copyright Notice
</a>
</div>
</div>
</div>
<div class="grid-row pmc-wm desktop:margin-left-neg-6">
<main
id="main-content"
class="usa-layout-docs__main usa-layout-docs grid-col-12 pmc-layout pmc-prose padding-0"
>
<section class="pmc-journal-banner text-center line-height-none" aria-label="Journal banner"><img src="https://cdn.ncbi.nlm.nih.gov/pmc/banners/logo-sensors.png" alt="Sensors (Basel, Switzerland) logo" usemap="#pmc-banner-imagemap" width="500" height="75"><map name="pmc-banner-imagemap"><area alt="Link to Sensors (Basel, Switzerland)" title="Link to Sensors (Basel, Switzerland)" shape="default" href="http://www.mdpi.com/journal/sensors" target="_blank" rel="noopener noreferrer"></map></section><article lang="en"><section aria-label="Article citation and metadata"><section class="pmc-layout__citation font-secondary font-xs"><div>
<div class="display-inline-block"><button type="button" class="cursor-pointer text-no-underline bg-transparent border-0 padding-0 text-left margin-0 text-normal text-primary" aria-controls="journal_context_menu">Sensors (Basel)</button></div>. 2024 Jan 8;24(2):0. doi: <a href="https://doi.org/10.3390/s24020376" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">10.3390/s24020376</a>
</div>
<nav id="journal_context_menu" hidden="hidden"><ul class="menu-list font-family-ui" role="menu">
<li role="presentation"><a href='https://pmc.ncbi.nlm.nih.gov/search/?term="Sensors%20(Basel)"[jour]' class="usa-link" role="menuitem">Search in PMC</a></li>
<li role="presentation"><a href='https://pubmed.ncbi.nlm.nih.gov/?term="Sensors%20(Basel)"[jour]' lang="en" class="usa-link" role="menuitem">Search in PubMed</a></li>
<li role="presentation"><a href='https://www.ncbi.nlm.nih.gov/nlmcatalog?term="Sensors%20(Basel)"[Title%20Abbreviation]' class="usa-link" role="menuitem">View in NLM Catalog</a></li>
<li role="presentation"><a href='?term="Sensors%20(Basel)"[jour]' class="usa-link" role="menuitem" data-add-to-search="true">Add to search</a></li>
</ul></nav></section><section class="front-matter"><div class="ameta p font-secondary font-xs">
<hgroup><h1>BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement</h1></hgroup><div class="cg p">
<a href='https://pubmed.ncbi.nlm.nih.gov/?term="Milano%20F"[Author]' class="usa-link" aria-describedby="id1"><span class="name western">Filippo Milano</span></a><div hidden="hidden" id="id1">
<h3><span class="name western">Filippo Milano</span></h3>
<div class="p">
<sup>1</sup>Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy; ferrigno@unicas.it</div>
<div>Conceptualization, Methodology, Software, Validation, Writing – original draft</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Milano%20F"[Author]' class="usa-link"><span class="name western">Filippo Milano</span></a>
</div>
</div>
<sup>1,</sup><sup>*</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="da%20Rocha%20H"[Author]' class="usa-link" aria-describedby="id2"><span class="name western">Helbert da Rocha</span></a><div hidden="hidden" id="id2">
<h3><span class="name western">Helbert da Rocha</span></h3>
<div class="p">
<sup>2</sup>Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)</div>
<div class="p">
<sup>3</sup>Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="da%20Rocha%20H"[Author]' class="usa-link"><span class="name western">Helbert da Rocha</span></a>
</div>
</div>
<sup>2,</sup><sup>3</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Laracca%20M"[Author]' class="usa-link" aria-describedby="id3"><span class="name western">Marco Laracca</span></a><div hidden="hidden" id="id3">
<h3><span class="name western">Marco Laracca</span></h3>
<div class="p">
<sup>4</sup>Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, 00185 Rome, Italy; marco.laracca@uniroma1.it</div>
<div>Conceptualization, Methodology, Validation, Writing – original draft</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Laracca%20M"[Author]' class="usa-link"><span class="name western">Marco Laracca</span></a>
</div>
</div>
<sup>4</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Ferrigno%20L"[Author]' class="usa-link" aria-describedby="id4"><span class="name western">Luigi Ferrigno</span></a><div hidden="hidden" id="id4">
<h3><span class="name western">Luigi Ferrigno</span></h3>
<div class="p">
<sup>1</sup>Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy; ferrigno@unicas.it</div>
<div>Conceptualization, Methodology, Writing – original draft</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Ferrigno%20L"[Author]' class="usa-link"><span class="name western">Luigi Ferrigno</span></a>
</div>
</div>
<sup>1</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Esp%C3%ADrito%20Santo%20A"[Author]' class="usa-link" aria-describedby="id5"><span class="name western">António Espírito Santo</span></a><div hidden="hidden" id="id5">
<h3><span class="name western">António Espírito Santo</span></h3>
<div class="p">
<sup>2</sup>Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)</div>
<div class="p">
<sup>3</sup>Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Esp%C3%ADrito%20Santo%20A"[Author]' class="usa-link"><span class="name western">António Espírito Santo</span></a>
</div>
</div>
<sup>2,</sup><sup>3</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Salvado%20J"[Author]' class="usa-link" aria-describedby="id6"><span class="name western">José Salvado</span></a><div hidden="hidden" id="id6">
<h3><span class="name western">José Salvado</span></h3>
<div class="p">
<sup>2</sup>Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)</div>
<div class="p">
<sup>3</sup>Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal</div>
<div>Conceptualization, Methodology, Validation, Writing – original draft</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Salvado%20J"[Author]' class="usa-link"><span class="name western">José Salvado</span></a>
</div>
</div>
<sup>2,</sup><sup>3</sup>, <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Paciello%20V"[Author]' class="usa-link" aria-describedby="id7"><span class="name western">Vincenzo Paciello</span></a><div hidden="hidden" id="id7">
<h3><span class="name western">Vincenzo Paciello</span></h3>
<div class="p">
<sup>5</sup>Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy; vpaciello@unisa.it</div>
<div>Conceptualization, Methodology, Writing – original draft</div>
<div class="p">Find articles by <a href='https://pubmed.ncbi.nlm.nih.gov/?term="Paciello%20V"[Author]' class="usa-link"><span class="name western">Vincenzo Paciello</span></a>
</div>
</div>
<sup>5</sup>
</div>
<div class="cg p">Editor: <span class="name western">Elena Simona Lohan</span>
</div>
<ul class="d-buttons inline-list">
<li><button class="d-button" aria-controls="aip_a" aria-expanded="false">Author information</button></li>
<li><button class="d-button" aria-controls="anp_a" aria-expanded="false">Article notes</button></li>
<li><button class="d-button" aria-controls="clp_a" aria-expanded="false">Copyright and License information</button></li>
</ul>
<div class="d-panels font-secondary-light">
<div id="aip_a" class="d-panel p" style="display: none">
<div class="p" id="af1-sensors-24-00376">
<sup>1</sup>Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy; ferrigno@unicas.it</div>
<div id="af2-sensors-24-00376">
<sup>2</sup>Department of Electromechanical Engineering, University of Beira Interior, 6200-001 Covilhã, Portugal; helbert.rocha@ubi.pt (H.d.R.); aes@ubi.pt (A.E.S.); jose.salvado@ubi.pt (J.S.)</div>
<div id="af3-sensors-24-00376">
<sup>3</sup>Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal</div>
<div id="af4-sensors-24-00376">
<sup>4</sup>Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, 00185 Rome, Italy; marco.laracca@uniroma1.it</div>
<div id="af5-sensors-24-00376">
<sup>5</sup>Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy; vpaciello@unisa.it</div>
<div class="author-notes p"><div class="fn" id="c1-sensors-24-00376">
<sup>*</sup><p class="display-inline">Correspondence: <span>filippo.milano@unicas.it</span></p>
</div></div>
<h4 class="font-secondary">Roles</h4>
<div class="p">
<strong class="contrib"><span class="name western">Filippo Milano</span></strong>: <span class="role">Conceptualization, Methodology, Software, Validation, Writing – original draft</span>
</div>
<div>
<strong class="contrib"><span class="name western">Marco Laracca</span></strong>: <span class="role">Conceptualization, Methodology, Validation, Writing – original draft</span>
</div>
<div>
<strong class="contrib"><span class="name western">Luigi Ferrigno</span></strong>: <span class="role">Conceptualization, Methodology, Writing – original draft</span>
</div>
<div>
<strong class="contrib"><span class="name western">José Salvado</span></strong>: <span class="role">Conceptualization, Methodology, Validation, Writing – original draft</span>
</div>
<div>
<strong class="contrib"><span class="name western">Vincenzo Paciello</span></strong>: <span class="role">Conceptualization, Methodology, Writing – original draft</span>
</div>
<div class="p">
<strong class="contrib"><span class="name western">Elena Simona Lohan</span></strong>: <span class="role">Academic Editor</span>
</div>
</div>
<div id="anp_a" class="d-panel p" style="display: none"><div class="notes p"><section id="historyarticle-meta1" class="history"><p>Received 2023 Nov 2; Revised 2023 Dec 22; Accepted 2024 Jan 5; Collection date 2024 Jan.</p></section></div></div>
<div id="clp_a" class="d-panel p" style="display: none">
<div>© 2024 by the authors.</div>
<p>Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (<a href="https://creativecommons.org/licenses/by/4.0/" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">https://creativecommons.org/licenses/by/4.0/</a>).</p>
<div class="p"><a href="/about/copyright/" class="usa-link">PMC Copyright notice</a></div>
</div>
</div>
<div>PMCID: PMC11154453 PMID: <a href="https://pubmed.ncbi.nlm.nih.gov/38257468/" class="usa-link">38257468</a>
</div>
</div></section></section><section aria-label="Article content"><section class="body main-article-body"><section class="abstract" id="abstract1"><h2>Abstract</h2>
<p>This paper addresses indoor localization using an anchor-based system based on Bluetooth Low Energy (BLE) 5.0 technology, adopting the Received Signal Strength Indicator (RSSI) for the distance estimation. Different solutions have been proposed in the scientific literature to improve the performance of this localization technology, but a detailed performance comparison of these solutions is still missing. The aim of this work is to make an experimental analysis combining different solutions for the performance improvement of BLE-based indoor localization, identifying the most effective one. The considered solutions involve different RSSI signals’ conditioning, the use of anchor–tag distance estimation techniques, as well as approaches for estimating the unknown tag position. An experimental campaign was executed in a complex indoor environment, characterized by the continuous presence in the movement of working staff and numerous obstacles. The exploitation of multichannel transmission using RSSI signal aggregation techniques showed the greater performance improvement of the localization system, reducing the positioning error (from 1.5 m to about 1 m). The other examined solutions have shown a lesser impact in the performance improvement with a decrease or an increase in the positioning errors, depending on the considered combination of the adopted solutions.</p>
<section id="kwd-group1" class="kwd-group"><p><strong>Keywords:</strong> indoor localization, Bluetooth Low Energy, localization solutions</p></section></section><section id="sec1-sensors-24-00376"><h2 class="pmc_sec_title">1. Introduction</h2>
<p>Indoor localization has become increasingly important in modern applications, from navigation within large facilities, such as airports and shopping malls [<a href="#B1-sensors-24-00376" class="usa-link" aria-describedby="B1-sensors-24-00376">1</a>,<a href="#B2-sensors-24-00376" class="usa-link" aria-describedby="B2-sensors-24-00376">2</a>], to quality controls in the industrial field [<a href="#B3-sensors-24-00376" class="usa-link" aria-describedby="B3-sensors-24-00376">3</a>]; to use in medicine for therapeutic monitoring [<a href="#B4-sensors-24-00376" class="usa-link" aria-describedby="B4-sensors-24-00376">4</a>]; to provide location-based services to enhance the user experience [<a href="#B5-sensors-24-00376" class="usa-link" aria-describedby="B5-sensors-24-00376">5</a>,<a href="#B6-sensors-24-00376" class="usa-link" aria-describedby="B6-sensors-24-00376">6</a>]; to track and monitor elderly or people with disabilities [<a href="#B7-sensors-24-00376" class="usa-link" aria-describedby="B7-sensors-24-00376">7</a>]; to manage the energy consumption based on the occupancy in smart buildings [<a href="#B8-sensors-24-00376" class="usa-link" aria-describedby="B8-sensors-24-00376">8</a>]; and to infer occupancy in buildings for crisis management [<a href="#B9-sensors-24-00376" class="usa-link" aria-describedby="B9-sensors-24-00376">9</a>]. Indoor localization can be implemented using a variety of technologies, including Wi-Fi, RFID, Ultra-Wideband, and Bluetooth Low Energy (BLE) [<a href="#B10-sensors-24-00376" class="usa-link" aria-describedby="B10-sensors-24-00376">10</a>]. Among these technologies, thanks to its specific features, BLE has gained significant popularity in different application fields, including indoor localization. Moreover, the BLE has the advantage of low-power operation compared to Wi-Fi. The location of devices that use the Wi-Fi network requires that the device acquire transmission power from the network in a particular location. The most significant difference to the proposal is that here, it is the device that wants to know its position that works in advertising mode. In this way, energy is only consumed at the time of localization. The BLE was introduced in 2010 as an evolution of classic Bluetooth technology, starting from the version named Bluetooth 4.0, to be energy efficient with a low data rate focused in power constrained and low cost devices [<a href="#B11-sensors-24-00376" class="usa-link" aria-describedby="B11-sensors-24-00376">11</a>]. One of the key advantages of using BLE over other indoor localization technologies is its wide availability. BLE technology is integrated into most modern mobile devices, such as smartphones and tablets, making it widely accessible and easily adoptable. A BLE device that is used only for data transmission without receiving data is called a beacon [<a href="#B12-sensors-24-00376" class="usa-link" aria-describedby="B12-sensors-24-00376">12</a>]. Beacons are used by large companies, such as Apple, Google, and Facebook, for the development of new standards and products, and are also used by academia and industry for indoor localization, proximity detection, sensing applications, and so on. BLE beacons are inexpensive, small-sized, low-power devices that allow for easy installation and long battery life. In addition to the above-mentioned advantages of BLE technology, it also offers a significant increase in communication range over previous versions [<a href="#B13-sensors-24-00376" class="usa-link" aria-describedby="B13-sensors-24-00376">13</a>]. This feature allows for larger areas to be covered with fewer beacon devices, reducing deployment costs and simplifying the management of the considered application. All these specific features of the BLE technology enabled a wide usage in localization systems with an obtainable localization accuracy of about 1 m [<a href="#B14-sensors-24-00376" class="usa-link" aria-describedby="B14-sensors-24-00376">14</a>,<a href="#B15-sensors-24-00376" class="usa-link" aria-describedby="B15-sensors-24-00376">15</a>].</p>
<p>The localization systems developed using wireless communication technologies and, specifically, the BLE, are composed by means of an anchor-based approach [<a href="#B16-sensors-24-00376" class="usa-link" aria-describedby="B16-sensors-24-00376">16</a>]. In detail, the localization system involves the use of some BLE beacons positioned at fixed and known locations (named anchors) and a tag that is a BLE receiver whose unknown position needs to be estimated. For an anchor-based localization system, several quantities can be measured in order to estimate the tag position. For example, approaches based on measures of the Angle of Arrival (AoA), Time of Flight (ToF), and Received Signal Strength Indicator (RSSI) are established in the literature. The AoA-based localization techniques offer high accuracy and is not affected by obstacles or signal reflections [<a href="#B17-sensors-24-00376" class="usa-link" aria-describedby="B17-sensors-24-00376">17</a>]. However, it requires expensive and complex hardware to implement, and the coverage is limited by the need for a direct line of sight. The ToF-based techniques provide high accuracy and robustness against interference and noise [<a href="#B18-sensors-24-00376" class="usa-link" aria-describedby="B18-sensors-24-00376">18</a>]. However, they require accurate synchronization of anchor clocks and can be affected by reflections and multiple paths, requiring complex algorithms for compensation. The RSSI-based technique is affordable and simple to implement with standard hardware [<a href="#B19-sensors-24-00376" class="usa-link" aria-describedby="B19-sensors-24-00376">19</a>]. It has wider coverage and does not require a direct line of sight. However, RSSI has limited accuracy due to environmental variables and can be subject to interference [<a href="#B20-sensors-24-00376" class="usa-link" aria-describedby="B20-sensors-24-00376">20</a>,<a href="#B21-sensors-24-00376" class="usa-link" aria-describedby="B21-sensors-24-00376">21</a>]. Focusing the attention on the RSSI-based techniques applied to develop localization systems, different solutions have been proposed in the literature to improve the performance of this technology. Many scientific papers propose processing solutions, such as RSSI signal aggregation techniques [<a href="#B14-sensors-24-00376" class="usa-link" aria-describedby="B14-sensors-24-00376">14</a>], Kalman filtering of the acquired data [<a href="#B15-sensors-24-00376" class="usa-link" aria-describedby="B15-sensors-24-00376">15</a>], transformation models between the RSSI signal and distance [<a href="#B22-sensors-24-00376" class="usa-link" aria-describedby="B22-sensors-24-00376">22</a>], and positioning approaches based on optimization algorithms or Machine Learning (ML) [<a href="#B23-sensors-24-00376" class="usa-link" aria-describedby="B23-sensors-24-00376">23</a>].</p>
<p>Despite the wide scientific literature proposing different solutions for BLE indoor localization based on RSSI technology, it is still unclear which combination of solutions is the most effective in achieving accurate and reliable localization performance.</p>
<p>The main contributions of this work are listed below.</p>
<ul class="list" style="list-style-type:disc">
<li><p>Provide a methodology for analyzing different techniques that have the greatest impact on the performance of a BLE-based indoor localization system. In particular, some of the solutions already proposed in the literature are considered and implemented, also considering different combination schemes.</p></li>
<li><p>The analysis was carried out via an experimental campaign in a complex indoor environment characterized by the presence of working staff and numerous obstacles.</p></li>
<li><p>The obtained performance results are compared using different combination schemes of the analyzed solutions in order to identify the solution (or a combination of them) that most contributes to the improvement of a BLE-based indoor localization system.</p></li>
</ul>
<p>The performed comparative analysis aims to provide a better understanding of the most effective and reliable solutions for achieving more accurate BLE-based indoor localization. The proposed methodology could help designers of indoor localization systems in identifying which techniques should definitely be used in order to meet the performance requirements of specific applications.</p>
<p>This paper is organized as follows. <a href="#sec2-sensors-24-00376" class="usa-link">Section 2</a> reports a brief description of the used BLE technology, in particular version 5.0, <a href="#sec3-sensors-24-00376" class="usa-link">Section 3</a> discusses the analyzed localization solutions for BLE indoor localization, and <a href="#sec4-sensors-24-00376" class="usa-link">Section 4</a> introduces the experimental set-up used to test the solutions described in <a href="#sec3-sensors-24-00376" class="usa-link">Section 3</a>. Finally, the results are shown in <a href="#sec5-sensors-24-00376" class="usa-link">Section 5</a> and the conclusion is provided in <a href="#sec6-sensors-24-00376" class="usa-link">Section 6</a>.</p></section><section id="sec2-sensors-24-00376"><h2 class="pmc_sec_title">2. Brief Notes of BLE 5.0 Technology</h2>
<p>Bluetooth Low Energy (BLE) technology has become increasingly popular in the context of low-power wireless applications. BLE technology offers 40 transmission channels operating in a 2 MHz frequency band. There are 37 channels for data and 3 channels for advertising (Ch 37, Ch 38, and Ch 39). The introduction of version 5.0 was a significant step in improving the functionality offered by this technology. In this Section, the main benefits and key features of BLE 5.0 technology will be reviewed, with a special focus on its applications in the context of indoor localization. The key advantages of the BLE 5.0 are listed below.</p>
<ul class="list" style="list-style-type:disc">
<li><p>Reduced energy consumption: BLE 5.0 technology is designed to provide very low power consumption, enabling extended battery life for battery-powered devices. In fact, in BLE, 5.0 devices can have up to 50% lower power consumption than previous versions [<a href="#B13-sensors-24-00376" class="usa-link" aria-describedby="B13-sensors-24-00376">13</a>].</p></li>
<li><p>Wide coverage: BLE 5.0 offers a significant increase in range over previous versions. The transmission range can reach up to 200 m in optimal outdoor conditions, enabling wider coverage even in indoor environments by reaching coverage distances of 40 m [<a href="#B13-sensors-24-00376" class="usa-link" aria-describedby="B13-sensors-24-00376">13</a>]. This translates into greater flexibility in anchor placement and coverage of larger areas with fewer devices, reducing deployment costs.</p></li>
<li><p>Higher data rates: BLE 5.0 technology supports a data rate of up to 2 Mbps, offering increased information transfer capability. This data rate allows for large amounts of data to be sent efficiently, enabling fast and reliable communication among location devices [<a href="#B13-sensors-24-00376" class="usa-link" aria-describedby="B13-sensors-24-00376">13</a>].</p></li>
</ul>
<p>BLE devices operating in beacon mode and receiver mode were used in this paper. A BLE beacon is an autonomous transmitter device that sends periodic signals to transmit data to surrounding devices [<a href="#B12-sensors-24-00376" class="usa-link" aria-describedby="B12-sensors-24-00376">12</a>]. It operates mainly in advertisement mode and transmits data packets containing information such as beacon identification, transmitted power data, or other useful information. The BLE beacon is generally powered by a battery and has a compact, portable, and low-cost design. BLE beacons are commonly used in indoor localization applications, localization-based marketing, and proximal notifications [<a href="#B24-sensors-24-00376" class="usa-link" aria-describedby="B24-sensors-24-00376">24</a>]. On the other hand, a BLE receiver is a device that receives signals transmitted by BLE beacons or other BLE devices [<a href="#B25-sensors-24-00376" class="usa-link" aria-describedby="B25-sensors-24-00376">25</a>]. The BLE receiver can detect, decode, and interpret the transmitted BLE data packets. It can be integrated into smartphones, tablets, computers, or other devices capable of supporting BLE connectivity. BLE receivers can detect signals from beacons and use this information for purposes such as localization.</p></section><section id="sec3-sensors-24-00376"><h2 class="pmc_sec_title">3. The Analyzed Localization Solutions</h2>
<p>In this paper, we propose an anchor-based positioning system for the tag localization in indoor environments using BLE 5.0 technology. To do this, we use BLE devices operating in beacon mode as system anchors and a BLE receiver as a tag. Details about the implementation of the positioning system are provided in <a href="#sec4-sensors-24-00376" class="usa-link">Section 4</a>.</p>
<p>The paper aims to carry out a performance analysis of some solutions, detailed below, adopted in the literature to improve the localization performance typically obtained using BLE technology. In particular, the analyzed solutions cover the processing of the RSSI data (measured by the tag for all anchors to evaluate the tag position), the techniques used to estimate the anchor–tag distances from the RSSI data, and the algorithms used to estimate the tag position. More in detail, in this paper, the analyzed solutions were suitably combined; for each combination, the localization performance was evaluated, and finally, a comparison in terms of localization performance was carried out.</p>
<section id="sec3dot1-sensors-24-00376"><h3 class="pmc_sec_title">3.1. Use of Multichannel Transmission</h3>
<p>The BLE technology is characterized by the availability of three advertising transmission channels (Ch 37, Ch 38, and Ch 39) to establish the connection between the BLE devices. The users that develop the BLE-based localization system can define the number of channels to be used for the purpose. On one hand, the use of only one transmission channel allows for simple and low consumption localization systems. From the other hand, the use of multiple transmission channels enable the possibility to make some aggregation strategies to compensate for interference, improving the localization performance (e.g., since the transmission on the three channels takes place with a negligible time interval concerning the tag speed [<a href="#B25-sensors-24-00376" class="usa-link" aria-describedby="B25-sensors-24-00376">25</a>], the use of aggregation techniques could reduce the fast-fading effects and interference with Wi-Fi signals [<a href="#B20-sensors-24-00376" class="usa-link" aria-describedby="B20-sensors-24-00376">20</a>]). In addition, repetitive measurement of the RSSIs on the transmission channels can be used to both increase the localization capabilities and allow for statistical analysis. <a href="#sensors-24-00376-t001" class="usa-link">Table 1</a> shows an example of the RSSI values that can be acquired on all three channels, considering N repeated measurements for each channel.</p>
<section class="tw xbox font-sm" id="sensors-24-00376-t001"><h4 class="obj_head">Table 1.</h4>
<div class="caption p"><p>RSSI measured by the tag for each anchor.</p></div>
<div class="tbl-box p" tabindex="0"><table class="content" frame="hsides" rules="groups">
<thead><tr>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Samples</th>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Ch 37</th>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Ch 38</th>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Ch 39</th>
</tr></thead>
<tbody>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">1</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm60" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>37</mn><mo>,</mo><mn>1</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm61" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>38</mn><mo>,</mo><mn>1</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm62" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>39</mn><mo>,</mo><mn>1</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">2</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm63" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>37</mn><mo>,</mo><mn>2</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm64" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>38</mn><mo>,</mo><mn>2</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm65" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>39</mn><mo>,</mo><mn>2</mn></mrow></msub></mrow></mrow></math>
</span>
</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">
<em>i</em>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm66" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>37</mn><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm67" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>38</mn><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm68" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>39</mn><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
<td align="center" valign="middle" rowspan="1" colspan="1">⋮</td>
</tr>
<tr>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">
<em>N</em>
</td>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm69" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>37</mn><mo>,</mo><mi>N</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm70" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>38</mn><mo>,</mo><mi>N</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">
<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm71" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>39</mn><mo>,</mo><mi>N</mi></mrow></msub></mrow></mrow></math>
</span>
</td>
</tr>
</tbody>
</table></div>
<div class="p text-right font-secondary"><a href="table/sensors-24-00376-t001/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div></section><p>In order to exploit multichannel transmission as a method of improving the performance, in this paper, we compare three different techniques [<a href="#B14-sensors-24-00376" class="usa-link" aria-describedby="B14-sensors-24-00376">14</a>] to aggregate the RSSI measured by the three advertising transmission channels as described below.</p>
<ol class="list" style="list-style-type:decimal">
<li>
<p>
<strong>Maximum technique</strong>
</p>
<div class="p">In this case, the aggregated data coincides with the maximum RSSI measured on the three transmission channels
<table class="disp-formula p" id="FD1-sensors-24-00376"><tr>
<td class="formula"><math id="mm1" display="block" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>a</mi><mi>x</mi><mo>,</mo><mi>i</mi></mrow></msub><mo>=</mo><mo movablelimits="true" form="prefix">max</mo><mrow><mo>{</mo><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>37</mn><mo>,</mo><mi>i</mi></mrow></msub><mo>,</mo><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>38</mn><mo>,</mo><mi>i</mi></mrow></msub><mo>,</mo><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mn>39</mn><mo>,</mo><mi>i</mi></mrow></msub><mo>}</mo></mrow><mo>,</mo></mrow></mrow></math></td>
<td class="label">(1)</td>
</tr></table>
where <em>i</em> denotes the <em>i</em>-th repeated measurement. In the rest of the paper, we will refer to this technique as the <em>max technique</em>.</div>
</li>
<li>
<p>
<strong>Mean technique</strong>
</p>
<div class="p">The second adopted technique aggregates the data, considering the arithmetic average of the measured RSSI on the three transmission channels
<table class="disp-formula p" id="FD2-sensors-24-00376"><tr>
<td class="formula"><math id="mm2" display="block" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>e</mi><mi>a</mi><mi>n</mi><mo>,</mo><mi>i</mi></mrow></msub><mo>=</mo><munderover><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>37</mn></mrow><mn>39</mn></munderover><mfrac><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>j</mi><mo>,</mo><mi>i</mi></mrow></msub></mrow><mn>3</mn></mfrac><mo>,</mo></mrow></mrow></math></td>
<td class="label">(2)</td>
</tr></table>
where <em>i</em> denotes the <em>i</em>-<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm3" overflow="linebreak"><mrow><mrow><mi>th</mi></mrow></mrow></math>
</span> repeated measurement. In the rest of the paper, we will refer to this technique as the <em>mean technique</em>.</div>
</li>
<li>
<p>
<strong>Maximum ratio combining technique</strong>
</p>
<div class="p">With the principle of the maximum ratio combining technique, a weighted average is carried out on the RSSI measured by the three transmission channels
<table class="disp-formula p" id="FD3-sensors-24-00376"><tr>
<td class="formula"><math id="mm4" display="block" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>r</mi><mi>c</mi><mo>,</mo><mi>i</mi></mrow></msub><mo>=</mo><munderover><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>37</mn></mrow><mn>39</mn></munderover><mfrac><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>j</mi><mo>,</mo><mi>i</mi></mrow></msub><mo>−</mo><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow><mrow><msubsup><mo>∑</mo><mrow><mi>h</mi><mo>=</mo><mn>37</mn></mrow><mn>39</mn></msubsup><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>h</mi><mo>,</mo><mi>i</mi></mrow></msub><mo>−</mo><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow></mfrac><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>j</mi><mo>,</mo><mi>i</mi></mrow></msub></mrow></mrow></math></td>
<td class="label">(3)</td>
</tr></table>
where <em>i</em> denotes the <em>i</em>-<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm5" overflow="linebreak"><mrow><mrow><mi>t</mi><mi>h</mi></mrow></mrow></math>
</span> repeated measurement. Consequently, the channel with the highest (lowest) RSSI will have the highest (lowest) weight in the computation of the aggregated RSSI. The <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm6" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow></mrow></math>
</span> value is a constant that represents the receiver sensitivity taken from the datasheet of the adopted BLE device. In the rest of the paper, we will refer to this technique as the <em>mrc technique</em>.</div>
</li>
</ol>
<p>Due to the complexity of indoor environments, the measured RSSI data are not reliable due to the presence of obstacles that lead to reflections, attenuation, and multipath effects. To mitigate these problems, data filtering techniques [<a href="#B26-sensors-24-00376" class="usa-link" aria-describedby="B26-sensors-24-00376">26</a>] are used to increase the goodness of the RSSI data, allowing us to smooth them from any outliers present in the measurements.</p></section><section id="sec3dot2-sensors-24-00376"><h3 class="pmc_sec_title">3.2. RSSI Filtering</h3>
<p>A very important conditioning to be performed on signals before processing them is filtering. In fact, this operation is represented by a transformation function on the spectral structure of the input signal with the purpose of eliminating some unwanted components while leaving others untouched. In the scenario considered in this paper, different types of filters can be used (low-pass, moving average, Savitzky–Golay, etc.). Among the filtering techniques present in the literature, the Kalman filter is considered in the proposed performance analysis since it has proved to be more suitable for solving localization problems also in the static scenario [<a href="#B15-sensors-24-00376" class="usa-link" aria-describedby="B15-sensors-24-00376">15</a>,<a href="#B27-sensors-24-00376" class="usa-link" aria-describedby="B27-sensors-24-00376">27</a>,<a href="#B28-sensors-24-00376" class="usa-link" aria-describedby="B28-sensors-24-00376">28</a>]. The Kalman filter represents a state estimator applicable to a stochastic system. In detail, in the following is reported the stationary linear model in discrete time of the system to be filtered.
</p>
<table class="disp-formula p" id="FD4-sensors-24-00376"><tr>
<td class="formula"><math id="mm7" display="block" overflow="linebreak"><mrow><mfenced separators="" open="{" close=""><mtable displaystyle="true"><mtr><mtd columnalign="left"><mrow><mi>x</mi><mo>(</mo><mi>k</mi><mo>+</mo><mn>1</mn><mo>)</mo><mo>=</mo><mi>x</mi><mo>(</mo><mi>k</mi><mo>)</mo><mo>+</mo><mi>w</mi><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mtd></mtr><mtr><mtd columnalign="left"><mrow><mi>y</mi><mo>(</mo><mi>k</mi><mo>)</mo><mo>=</mo><mi>x</mi><mo>(</mo><mi>k</mi><mo>)</mo><mo>+</mo><mi>v</mi><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mtd></mtr></mtable></mfenced></mrow></math></td>
<td class="label">(4)</td>
</tr></table>
<p>
where</p>
<ul class="list" style="list-style-type:disc">
<li><p><em>k</em> represents the the discrete time instant;</p></li>
<li><p><em>x</em> represents the filtered RSSI data (state variable);</p></li>
<li><p><em>w</em> represents the process noise;</p></li>
<li><p><em>y</em> represents the measured RSSI data (output variable);</p></li>
<li><p><em>v</em> represents the measurement noise.</p></li>
</ul>
<p>The Kalman filter involves the execution of two phases: the prediction and the update. The equations to execute these phases are applied to the stationary linear model reported in (<a href="#FD4-sensors-24-00376" class="usa-link">4</a>).</p>
<p>In particular, for the prediction phase in which an estimate of the state variable is carried out based on the system model, we have the following equations:</p>
<table class="disp-formula p" id="FD5-sensors-24-00376"><tr>
<td class="formula"><math id="mm8" display="block" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>+</mo><mn>1</mn><mo>)</mo></mrow><mo>=</mo><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math></td>
<td class="label">(5)</td>
</tr></table>
<table class="disp-formula p" id="FD6-sensors-24-00376"><tr>
<td class="formula"><math id="mm9" display="block" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>+</mo><mn>1</mn><mo>)</mo></mrow><mo>=</mo><mi>P</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>+</mo><msub><mi>R</mi><mi>w</mi></msub></mrow></mrow></math></td>
<td class="label">(6)</td>
</tr></table>
<p>
where <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm10" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm11" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math>
</span> represent the <em>a posteriori</em> and <em>a priori</em> estimate of the state variable, respectively; <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm12" overflow="linebreak"><mrow><mrow><mi>P</mi><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm13" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math>
</span> represent the <em>a posteriori</em> and <em>a priori</em> state covariance estimate, respectively; and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm14" overflow="linebreak"><mrow><msub><mi>R</mi><mi>w</mi></msub></mrow></math>
</span> represents the process noise covariance matrix.</p>
<p>The update operation that connects the noisy measurements to the state current estimate is described by the measurement update equations:</p>
<table class="disp-formula p" id="FD7-sensors-24-00376"><tr>
<td class="formula"><math id="mm15" display="block" overflow="linebreak"><mrow><mrow><mi>K</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>=</mo><mfrac><mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow><mrow><msub><mi>R</mi><mi>v</mi></msub><mo>+</mo><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mfrac></mrow></mrow></math></td>
<td class="label">(7)</td>
</tr></table>
<table class="disp-formula p" id="FD8-sensors-24-00376"><tr>
<td class="formula"><math id="mm16" display="block" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>=</mo><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>+</mo><mi>K</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mrow><mo>(</mo><mi>y</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>−</mo><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mrow></math></td>
<td class="label">(8)</td>
</tr></table>
<table class="disp-formula p" id="FD9-sensors-24-00376"><tr>
<td class="formula"><math id="mm17" display="block" overflow="linebreak"><mrow><mrow><mi>P</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>=</mo><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mi>K</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>)</mo></mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math></td>
<td class="label">(9)</td>
</tr></table>
<p>
where <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm18" overflow="linebreak"><mrow><mrow><mi>K</mi><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></math>
</span> represents the Kalman filter gain and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm19" overflow="linebreak"><mrow><msub><mi>R</mi><mi>v</mi></msub></mrow></math>
</span> represents the measurement noise covariance matrix. The initial values of <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm20" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mn>0</mn><mo>)</mo></mrow></mrow></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm21" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mn>0</mn><mo>)</mo></mrow></mrow></mrow></math>
</span> and the setting values of the <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm22" overflow="linebreak"><mrow><msub><mi>R</mi><mi>w</mi></msub></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm23" overflow="linebreak"><mrow><msub><mi>R</mi><mi>v</mi></msub></mrow></math>
</span> matrices are provided in <a href="#sec5-sensors-24-00376" class="usa-link">Section 5</a>. It is worth noting that the unknown of the problem is represented by <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm24" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></mrow></math>
</span>, because it is the state estimate at instant <em>k</em> that also uses the measurements at the same instant.</p>
<p>In the localization scenario considered in this paper (static, as will be discussed in subsequent Sections), the Kalman filter is used to estimate noisy constant quantities (RSSI). This represents a simplified case in which to apply the Kalman filter, as it finds its fullest application in dynamic localization scenarios in which a motion dynamics model must be considered.</p></section><section id="sec3dot3-sensors-24-00376"><h3 class="pmc_sec_title">3.3. Distance Estimation</h3>
<p>For the estimation of the distances among each anchor and the tag, two different approaches are used in this paper.</p>
<ul class="list" style="list-style-type:disc">
<li><div class="p">The first approach is made by means of an empirical path loss propagation model based on a logarithmic relationship between the measured RSSI and the distance (<a href="#FD10-sensors-24-00376" class="usa-link">10</a>). The estimate of the distance <em>d</em> is performed by measuring the RSSI and inverting (<a href="#FD10-sensors-24-00376" class="usa-link">10</a>), as shown in (<a href="#FD11-sensors-24-00376" class="usa-link">11</a>). The values of <em>A</em> and <em>n</em> must be estimated during a calibration phase: <em>A</em> represents the measured RSSI when <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm25" overflow="linebreak"><mrow><mrow><mi>d</mi><mo>=</mo><mn>1</mn></mrow></mrow></math>
</span> and <em>n</em> identifies the path loss exponent.
<table class="disp-formula p" id="FD10-sensors-24-00376"><tr>
<td class="formula"><math id="mm26" display="block" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><mi>I</mi><mo>=</mo><mi>A</mi><mo>−</mo><mn>10</mn><mi>n</mi><mo>·</mo><mo form="prefix">log</mo><mo>(</mo><mi>d</mi><mo>)</mo></mrow></mrow></math></td>
<td class="label">(10)</td>
</tr></table>
<table class="disp-formula p" id="FD11-sensors-24-00376"><tr>
<td class="formula"><math id="mm27" display="block" overflow="linebreak"><mrow><mrow><mi>d</mi><mo>=</mo><msup><mn>10</mn><mfrac><mrow><mi>A</mi><mo>−</mo><mi>R</mi><mi>S</mi><mi>S</mi><mi>I</mi></mrow><mrow><mn>10</mn><mi>n</mi></mrow></mfrac></msup></mrow></mrow></math></td>
<td class="label">(11)</td>
</tr></table>
</div></li>
<li><p>The second approach is based on a Machine Learning (ML) model, as detailed in the <a href="#sec3dot4-sensors-24-00376" class="usa-link">Section 3.4</a>.</p></li>
</ul>
<p>The RSSI used for the distance estimation can be the raw measured values or the conditioned ones, applying the aggregation techniques and/or the RSSI filtering described in <a href="#sec3dot1-sensors-24-00376" class="usa-link">Section 3.1</a> and <a href="#sec3dot2-sensors-24-00376" class="usa-link">Section 3.2</a>, respectively.</p></section><section id="sec3dot4-sensors-24-00376"><h3 class="pmc_sec_title">3.4. Positioning Approaches</h3>
<p>Three different approaches are analyzed in this paper for the estimation of the unknown position: the first is based on numerical optimization, the second uses an ML model integrated with solving an optimization problem, and finally, the last one is completely based on an ML model.</p>
<ol class="list" style="list-style-type:decimal">
<li>
<p>
<strong>Numerical optimization</strong>
</p>
<div class="p">In this case, we define the unknown tag position <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm28" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>ϑ</mi><mo stretchy="false">^</mo></mover><mo>=</mo><msup><mrow><mo>[</mo><msub><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>,</mo><msub><mover accent="true"><mi>y</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>]</mo></mrow><mi>T</mi></msup></mrow></mrow></math>
</span> as the result of a minimization process defined in (<a href="#FD12-sensors-24-00376" class="usa-link">12</a>), where the objective function <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm29" overflow="linebreak"><mrow><mrow><mi>F</mi><mo>(</mo><mi>ϑ</mi><mo>)</mo></mrow></mrow></math>
</span> is defined in (<a href="#FD13-sensors-24-00376" class="usa-link">13</a>).
<table class="disp-formula p" id="FD12-sensors-24-00376"><tr>
<td class="formula"><math id="mm30" display="block" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>ϑ</mi><mo stretchy="false">^</mo></mover><mo>=</mo><mo form="prefix">arg</mo><munder><mo movablelimits="true" form="prefix">min</mo><mi>ϑ</mi></munder><mi>F</mi><mrow><mo>(</mo><mi>ϑ</mi><mo>)</mo></mrow></mrow></mrow></math></td>
<td class="label">(12)</td>
</tr></table>
<table class="disp-formula p" id="FD13-sensors-24-00376"><tr>
<td class="formula"><math id="mm31" display="block" overflow="linebreak"><mrow><mrow><mi>F</mi><mrow><mo>(</mo><mi>ϑ</mi><mo>)</mo></mrow><mo>=</mo><munderover><mo>∑</mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>M</mi></munderover><msup><mrow><mo>[</mo><msub><mover accent="true"><mi>d</mi><mo stretchy="false">˜</mo></mover><mi>i</mi></msub><mo>−</mo><msub><mi>d</mi><mi>i</mi></msub><mrow><mo>(</mo><mi>ϑ</mi><mo>)</mo></mrow><mo>]</mo></mrow><mn>2</mn></msup></mrow></mrow></math></td>
<td class="label">(13)</td>
</tr></table>
</div>
<p>In (<a href="#FD13-sensors-24-00376" class="usa-link">13</a>), <em>M</em> indicates the number of anchors used in the experimental set-up, <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm32" overflow="linebreak"><mrow><msub><mover accent="true"><mi>d</mi><mo stretchy="false">˜</mo></mover><mi>i</mi></msub></mrow></math>
</span> indicates the estimated distance between the <em>i</em>-th anchor and the tag, while <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm34" overflow="linebreak"><mrow><mrow><msub><mi>d</mi><mi>i</mi></msub><mrow><mo>(</mo><mi>ϑ</mi><mo>)</mo></mrow></mrow></mrow></math>
</span> represents the theoretical distance between the <em>i</em>-th anchor and the tag if the tag position is equal to <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm36" overflow="linebreak"><mrow><mi>ϑ</mi></mrow></math>
</span>. Therefore, <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm37" overflow="linebreak"><mrow><mover accent="true"><mi>ϑ</mi><mo stretchy="false">^</mo></mover></mrow></math>
</span> is obtained by minimizing the error between the measured and the theoretical quantity for each anchor considered in the experimental set-up. The minimization problem is solved by the Nelder–Mead algorithm [<a href="#B29-sensors-24-00376" class="usa-link" aria-describedby="B29-sensors-24-00376">29</a>]. In the rest of the paper, we will refer to this approach as the <em>numerical optimization approach</em>.</p>
</li>
<li>
<p>
<strong>Assisted-ML approach</strong>
</p>
<p>The ML approaches use a regression model based on a two-layer Feed-Forward Neural Network (FNN). The structure of the adopted FNN is shown in <a href="#sensors-24-00376-f001" class="usa-link">Figure 1</a> and it was designed in the MATLAB environment. Details about the FNN are given in the following:</p>
<ul class="list" style="list-style-type:disc">
<li><p>the input is represented by the aggregate RSSI, obtained with any of the algorithms described in <a href="#sec3dot1-sensors-24-00376" class="usa-link">Section 3.1</a> and filtered; the size of the RSSI vector is equal to the number of anchors installed in the experimental set-up;</p></li>
<li><p>the hidden layer consists of 20 neurons. It was explored by the authors that this choice represents a good compromise between the computational cost and accurate estimation performance obtained with the FNN considered;</p></li>
<li><p>the activation functions of the hidden layer and the output layer are sigmoid and linear, respectively;</p></li>
<li><p>the type of result is represented by the estimated distances between the tag and each anchor used in the experimental set-up; therefore, the number of neurons in the output layer coincides with the number of anchors present in the experimental set-up.</p></li>
</ul>
<p>This approach uses the designed FNN to estimate the RSSI-distance model and, subsequently minimizing an objective function (applying the numerical optimization described above), derives the unknown tag position (see left in <a href="#sensors-24-00376-f001" class="usa-link">Figure 1</a>). Consequently, in the rest of the paper, we will refer to this approach as the <em>assisted-ML approach</em>, since only a part of the problem is solved through the use of ML models.</p>
</li>
<li>
<p>
<strong>Full-ML approach</strong>
</p>
<p>The FNN described in <a href="#sensors-24-00376-f001" class="usa-link">Figure 1</a> is used to directly obtain the tag position (see right in <a href="#sensors-24-00376-f001" class="usa-link">Figure 1</a>). Given the RSSI vector as input, it returns the tag position in Cartesian coordinates as a result. Consequently, in this case, the output layer of the FNN consists of two neurons associated with the size of the results (<em>x</em> and <em>y</em> coordinates).</p>
</li>
</ol>
<figure class="fig xbox font-sm" id="sensors-24-00376-f001"><h4 class="obj_head">Figure 1.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g001.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/c661e54e88b5/sensors-24-00376-g001.jpg" loading="lazy" height="613" width="722" alt="Figure 1"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f001/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Structure adopted two-layer Feed-Forward Neural Network (FNN) and schematic representations of the Assisted-ML and Full-ML approaches.</p></figcaption></figure><p>As described in <a href="#sensors-24-00376-f001" class="usa-link">Figure 1</a>, both ML-based approaches take the aggregated and filtered RSSI signal as input and aim to estimate the unknown position of the tag. To do this, the assisted-ML approach uses FNN to estimate the anchor–tag distances, and then it is necessary to use the numerical optimization approach to estimate the unknown position of the tag. Instead, using the full-ML approach via FNN directly obtains the unknown position of the tag from the input.</p></section></section><section id="sec4-sensors-24-00376"><h2 class="pmc_sec_title">4. Adopted Experimental Set-Up</h2>
<p>This section reports the main features of the adopted BLE devices and provides details on the implementation of the experimental set-up for the tag localization in an indoor environment.</p>
<p>Blue Gecko Wireless System on Chip (SoC) devices provided by Silicon Labs are used to develop the experimental set-up. Specifically, the devices belong to the EFR32BG13 family [<a href="#B30-sensors-24-00376" class="usa-link" aria-describedby="B30-sensors-24-00376">30</a>] and are compatible with the BLE 5.0 standard. <a href="#sensors-24-00376-t002" class="usa-link">Table 2</a> summarizes the main features of the adopted devices. Furthermore, a Wireless Starter Kit (WSK) mainboard is used to program the devices in the different operating modes, using the Simplicity Studio software (<a href="https://www.silabs.com/developers/simplicity-studio" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">https://www.silabs.com/developers/simplicity-studio</a>, accessed on 1 December 2023). Once the devices have been programmed, to allow for their autonomous operation (without using the WSK mainboard), a suitable PCB board has been designed and realized as shown in <a href="#sensors-24-00376-f002" class="usa-link">Figure 2</a>. In detail, the board has been designed to debug the code loaded on the BLE device, but it also allows for different power supply strategies, including both battery-powered and energy-harvesting systems. Thanks to the PCB board, in previous work [<a href="#B31-sensors-24-00376" class="usa-link" aria-describedby="B31-sensors-24-00376">31</a>], the BLE devices used to build the experimental set-up were characterized from an energetic point of view. In the future, the ability to use an energy harvesting system as a power source could remove the problems associated with recharging or replacing batteries.</p>
<section class="tw xbox font-sm" id="sensors-24-00376-t002"><h3 class="obj_head">Table 2.</h3>
<div class="caption p"><p>Main features of the adopted Bluetooth devices.</p></div>
<div class="tbl-box p" tabindex="0"><table class="content" frame="hsides" rules="groups"><tbody>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Device code</td>
<td align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">EFR32BG13P632F512GM48-D</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Supported protocol</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">BLE 5.0</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Operating band</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">2402–2480 MHz</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Maximum transmit power</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">+10 dBm</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Sensitivity (<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm72" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow></mrow></math>
</span>)</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">−94 dBm</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Integrated antenna</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Printed inverted–F</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">MCU</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">32–bit 40 MHz ARM Cortex–M4</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Flash memory</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">512 kB</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">RAM</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">64 kB</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Main integrated functionality</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Debug and packet trace; Advanced Energy Monitoring; Virtual COM Port</td>
</tr>
</tbody></table></div>
<div class="p text-right font-secondary"><a href="table/sensors-24-00376-t002/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div></section><figure class="fig xbox font-sm" id="sensors-24-00376-f002"><h3 class="obj_head">Figure 2.</h3>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g002.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/96db8f7a7352/sensors-24-00376-g002.jpg" loading="lazy" height="563" width="680" alt="Figure 2"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f002/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Adopted BLE device with dedicated PCB board.</p></figcaption></figure><p>To test the localization solutions to be analyzed in this paper (as described in <a href="#sec3-sensors-24-00376" class="usa-link">Section 3</a>), a suitable experimental set-up was developed inside the Instrumentation and Measurement Laboratory (IML) of the University of Beira Interior, Covilhã, Portugal, as shown in <a href="#sensors-24-00376-f003" class="usa-link">Figure 3</a>. The localization domain identified by the laboratory considers an area of about 30 m<sup>2</sup>. The positioning system consists of six anchors placed in a fixed and known position and a tag free to move within the localization domain. The anchors were powered by batteries and their positions within the localization domain are shown in <a href="#sensors-24-00376-t003" class="usa-link">Table 3</a>. The transmission power level considered for the anchors has been set as equal to −16 dBm. The tag was connected to a PC via a USB interface to be powered and to transfer the RSSI measurements sensed from each anchor.</p>
<figure class="fig xbox font-sm" id="sensors-24-00376-f003"><h3 class="obj_head">Figure 3.</h3>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g003.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/4fd25d9c98ae/sensors-24-00376-g003.jpg" loading="lazy" height="565" width="753" alt="Figure 3"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f003/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Localization domain inside the Instrumentation and Measurement Laboratory (IML) of the University of Beira Interior, Covilhã, Portugal.</p></figcaption></figure><section class="tw xbox font-sm" id="sensors-24-00376-t003"><h3 class="obj_head">Table 3.</h3>
<div class="caption p"><p>Positions of the anchors inside the localization domain.</p></div>
<div class="tbl-box p" tabindex="0"><table class="content" frame="hsides" rules="groups">
<thead><tr>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Anchors</th>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">
<em>x</em> [m]</th>
<th align="center" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">
<em>y</em> [m]</th>
</tr></thead>
<tbody>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">A1</td>
<td align="center" valign="middle" rowspan="1" colspan="1">0</td>
<td align="center" valign="middle" rowspan="1" colspan="1">0</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">A2</td>
<td align="center" valign="middle" rowspan="1" colspan="1">2.5</td>
<td align="center" valign="middle" rowspan="1" colspan="1">0</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">A3</td>
<td align="center" valign="middle" rowspan="1" colspan="1">5</td>
<td align="center" valign="middle" rowspan="1" colspan="1">0</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">A4</td>
<td align="center" valign="middle" rowspan="1" colspan="1">5</td>
<td align="center" valign="middle" rowspan="1" colspan="1">3</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="1" colspan="1">A5</td>
<td align="center" valign="middle" rowspan="1" colspan="1">2.5</td>
<td align="center" valign="middle" rowspan="1" colspan="1">6</td>
</tr>
<tr>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">A6</td>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">0</td>
<td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">3</td>
</tr>
</tbody>
</table></div>
<div class="p text-right font-secondary"><a href="table/sensors-24-00376-t003/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div></section></section><section id="sec5-sensors-24-00376"><h2 class="pmc_sec_title">5. Obtained Results</h2>
<p>In this section, the considered localization solutions are combined and tested via the implemented experimental set-up. It should be noted that the localization domain used to carry out the experimental tests, i.e., IML, constitutes a real scenario in which the typical problems of indoor environments can be encountered. In fact, inside the IML, there are constantly people, interfering signals such as Wi-Fi, obstacles, and walls that can affect the transmission and reception of BLE signals with behavior that is not constant over time.</p>
<p>Some aspects related to the examined procedures and described in <a href="#sec3-sensors-24-00376" class="usa-link">Section 3</a> are initially discussed, also providing numerical details about some parameters considered within the analyzed techniques. Subsequently, the results of localization tests using different combinations of the considered procedures are shown.</p>
<section id="sec5dot1-sensors-24-00376"><h3 class="pmc_sec_title">5.1. Preliminary Considerations</h3>
<ol class="list" style="list-style-type:decimal">
<li>
<p>
<strong>Multichannel transmission and aggregation techniques</strong>
</p>
<p>Initially, we want to discuss the use of the analyzed aggregation techniques to exploit multichannel transmission. This represents the first processing operation on the acquired signals within the localization procedures, typically adopted in the literature, considered in this paper. We need to specify the value of the <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm39" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow></mrow></math>
</span> parameter in order to compute the mrc algorithm. Based on the datasheet of the considered devices [<a href="#B30-sensors-24-00376" class="usa-link" aria-describedby="B30-sensors-24-00376">30</a>], the value of <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm40" overflow="linebreak"><mrow><mrow><mi>R</mi><mi>S</mi><mi>S</mi><msub><mi>I</mi><mrow><mi>m</mi><mi>i</mi><mi>n</mi></mrow></msub></mrow></mrow></math>
</span> is <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm41" overflow="linebreak"><mrow><mrow><mo>−</mo><mn>94</mn></mrow></mrow></math>
</span> dBm.</p>
<p><a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a> shows an example of the RSSI signals that can be acquired between an anchor and the tag. In particular, the raw RSSI signals acquired on the three primary transmission channels and the aggregate signals obtained with the three aggregation algorithms are shown. The acquisitions were carried out, keeping the anchor and tag stationary, and the considered anchor–tag distances are 2.7 m and 5.2 m for <a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a>a,b, respectively. About eighty acquisition samples were collected. Some considerations are highlighted below.</p>
<ul class="list" style="list-style-type:disc">
<li><p>Acquired signals may exhibit high variability. This is shown by the signal Ch 38 in <a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a>a which presents a difference between the maximum and minimum values of 13 dB. Obviously, due to the complexity of indoor environments, this variability makes the localization process inaccurate.</p></li>
<li><p>The max algorithm sometimes coincides with the signal present on a single channel (as shown in <a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a>a), while other times, it alternates the selection among different channels (as shown in <a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a>b). So, the max algorithm considers more signals if they are close to each other, otherwise it selects only the values of the signal with higher intensity.</p></li>
<li><p>Unlike the max algorithm, the mean and mrc algorithms always consider the characteristics of all three primary transmission channels. The difference between the two algorithms is that in one case, a simple average is performed (mean algorithm), while on the other hand, a weighted average is performed in which the lower intensity signal has a lower weight than the higher intensity signals (mrc algorithm).</p></li>
<li><p>The localization process can be affected by the choices made in the number of the adopted transmission channels, by the chosen transmission channels (if less than the available ones), and by the aggregation algorithm to be used for the combination of the RSSI signals.</p></li>
</ul>
<p>In conclusion, the information acquired on the three primary transmission channels contribute, all or in part, depending on the adopted aggregation algorithm, to the formation of an overall aggregate signal to be processed.</p>
<p>The particular configuration of the room or the building, and the aspects of radio propagation of signal, such as the environment conditions, the obstacles, and the interference due to reflections, have an impact on the level of the signals received. Also, the particular characteristics of the hardware used, namely, the transmitter output power, the sensitivity of the receiver, and the antenna gains, can influence the results. Therefore, by considering another environment configuration (room/building), or using a different hardware setup, can lead to different values of RSSI, although it does not compromise the generality and the applicability of the methodology proposed.</p>
</li>
<li>
<p>
<strong>The effect of the filtering procedure</strong>
</p>
<p>As shown in <a href="#sensors-24-00376-f004" class="usa-link">Figure 4</a>a, variability of the acquired signals is present both on the RSSI values coming from the single transmission channel, and on the RSSI values obtained after the application of the aggregation algorithms. The shown variability is the reason for which even if the aggregation algorithms are applied, the RSSI signals are typically filtered. In <a href="#sensors-24-00376-f005" class="usa-link">Figure 5</a>, it is shown an example of the effect of the Kalman filtering approach described in <a href="#sec3dot2-sensors-24-00376" class="usa-link">Section 3.2</a>, applied to the signal aggregated by means of the mean aggregation algorithm. The acquisitions were carried out keeping the anchor and tag stationary at a distance equal to 2.7 m. It is noted how all the oscillations present on the aggregate signal are reduced on the filtered signal and how any drift of the aggregate signal in the filtered signal is slowed down. The filtering operation also allows for the discard of possible outliers present in the measurements. As far as the specific settings of the adopted filter, <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm42" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>x</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mn>0</mn><mo>)</mo></mrow></mrow></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm43" overflow="linebreak"><mrow><mrow><mover accent="true"><mi>P</mi><mo stretchy="false">¯</mo></mover><mrow><mo>(</mo><mn>0</mn><mo>)</mo></mrow></mrow></mrow></math>
</span> have been set as equal to <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm44" overflow="linebreak"><mrow><mrow><mi>y</mi><mo>(</mo><mn>0</mn><mo>)</mo></mrow></mrow></math>
</span> (i.e., the first available RSSI measurement) and to 1, respectively; while, via empirical tests, the values of <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm45" overflow="linebreak"><mrow><msub><mi>R</mi><mi>w</mi></msub></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm46" overflow="linebreak"><mrow><msub><mi>R</mi><mi>v</mi></msub></mrow></math>
</span> have been determined as equal to 1 and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm47" overflow="linebreak"><mrow><mrow><mn>1</mn><mo>/</mo><mn>20</mn></mrow></mrow></math>
</span>. This is a common practice when it is necessary to set the parameters of the Kalman filter, as highlighted in [<a href="#B14-sensors-24-00376" class="usa-link" aria-describedby="B14-sensors-24-00376">14</a>]. It can be seen that in our procedure, the model has more weight than the measurement process, since the filter is applied to estimate a quantity (RSSI) that is ideally constant.</p>
</li>
<li>
<p>
<strong>Calibration and training of the distance/position estimation</strong>
</p>
<p>Some considerations can be made on both the estimation of distances/positions from the RSSI data and the quality of the calibration/training procedures depending on the chosen distance/estimation approaches. As far as distance estimation using the empirical path loss propagation model described in <a href="#sec3dot3-sensors-24-00376" class="usa-link">Section 3.3</a>, the RSSI–distance relationship has to be estimated via a preliminary calibration phase. The calibration phase is made by means of an experimental campaign carried out using all the anchors installed in the experimental set-up (see <a href="#sensors-24-00376-f003" class="usa-link">Figure 3</a>). In particular, sixteen training points located within the localization domain were considered. <a href="#sensors-24-00376-f006" class="usa-link">Figure 6</a> shows the schematic diagram of the identified training points (the training points in the center of the localization domain have not been considered because this area is occupied by a work table, see <a href="#sensors-24-00376-f003" class="usa-link">Figure 3</a>). For each training point, 100 repeated RSSI measurements were performed for each anchor in different times and with environmental conditions. It is important to note that all data used for calibration comes exclusively from experimental tests and there are no data augmentation procedures via numerically simulated training points. In fact, in our opinion, the numerical generation of data, in a complex scenario such as the indoor one where propagation problems are not kept under control, is not reliable given the difficulty in identifying an accurate model for predicting signals.</p>
<p>RSSI–distance relationships were estimated for each anchor of the experimental set-up using the experimental campaign performed in the calibration phase. In detail, for each anchor, the experimental data were fitted with an analytical model given by (<a href="#FD11-sensors-24-00376" class="usa-link">11</a>). <a href="#sensors-24-00376-f007" class="usa-link">Figure 7</a> shows an example of the result obtained for one of the considered anchors (A2 in <a href="#sensors-24-00376-f006" class="usa-link">Figure 6</a>) using the RSSI data aggregated with the maximum algorithm and filtered. In this example, a Root Mean Square Error (RMSE) of 1.0658 m, a maximum error of 2.3395 m, and a coefficient of determination <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm48" overflow="linebreak"><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></math>
</span> of 0.7224 were obtained on the entire calibration curve shown in <a href="#sensors-24-00376-f007" class="usa-link">Figure 7</a>. The obtained results in terms of the coefficients of the model (<a href="#FD11-sensors-24-00376" class="usa-link">11</a>) are equal to <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm49" overflow="linebreak"><mrow><mrow><mi>A</mi><mo>=</mo><mo>−</mo><mn>51.58</mn></mrow></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm50" overflow="linebreak"><mrow><mrow><mi>n</mi><mo>=</mo><mn>2.18</mn></mrow></mrow></math>
</span>. By examining <a href="#sensors-24-00376-f007" class="usa-link">Figure 7</a>, it is possible to highlight, as the expected linear behavior of the relationship between the distance and the RSSI (in logarithmic scale) is not perfectly satisfied. This is also confirmed by a low value of the coefficient of determination <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm51" overflow="linebreak"><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></math>
</span>. This is caused by the complexity of the indoor environments with several obstacles and interference signals. The effect is a reduction on the expected accuracy in the tag localization.</p>
<p>As discussed in <a href="#sec3dot4-sensors-24-00376" class="usa-link">Section 3.4</a>, the ML models-based positioning approaches use FNNs (different depending on the specific approach) that need to be trained. The training phase took place with the experimental data obtained during the calibration phase described above. After an arrangement of the collected measurement data, 1600 training points (observations) were obtained for each anchor to be used for the FNN training phase. All available training points have been divided as follows: 70% for training, 15% for validation, and 15% for testing. The FNNs were trained in the MATLAB environment, in which a loss function based on the Mean Squared Error (MSE) was used for training, validation, and testing procedures. <a href="#sensors-24-00376-f008" class="usa-link">Figure 8</a> and <a href="#sensors-24-00376-f009" class="usa-link">Figure 9</a> show the obtained results in terms of regression plots for the assisted-ML and full-ML approaches, respectively. Furthermore, <a href="#sensors-24-00376-t004" class="usa-link">Table 4</a> and <a href="#sensors-24-00376-t005" class="usa-link">Table 5</a> summarize the results in terms of the used number of observations, MSE, and coefficient of determination <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm52" overflow="linebreak"><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></math>
</span> for training, validation, and testing. The obtained results show good linearity for all used datasets and for both proposed approaches.</p>
</li>
</ol>
<figure class="fig xbox font-sm" id="sensors-24-00376-f004"><h4 class="obj_head">Figure 4.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g004.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/4e93e46184e9/sensors-24-00376-g004.jpg" loading="lazy" height="885" width="744" alt="Figure 4"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f004/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Examples of measured RSSI on the three primary transmission channels (Ch 37, Ch 38, and Ch 39) and adopting the three aggregation techniques (max algorithm, mean algorithm, and mrc algorithm) described in <a href="#sec3dot1-sensors-24-00376" class="usa-link">Section 3.1</a>, considering a single anchor-tag pair: (<strong>a</strong>) anchor-tag distance equal to 2.7 m; (<strong>b</strong>) anchor-tag distance equal to 5.2 m.</p></figcaption></figure><figure class="fig xbox font-sm" id="sensors-24-00376-f005"><h4 class="obj_head">Figure 5.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g005.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/e09aba8bbeb1/sensors-24-00376-g005.jpg" loading="lazy" height="451" width="745" alt="Figure 5"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f005/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Example of filtering an aggregate signal with mean algorithm.</p></figcaption></figure><figure class="fig xbox font-sm" id="sensors-24-00376-f006"><h4 class="obj_head">Figure 6.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g006.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/d9a2bb7a6225/sensors-24-00376-g006.jpg" loading="lazy" height="508" width="734" alt="Figure 6"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f006/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Location of the training points for the calibration phase.</p></figcaption></figure><figure class="fig xbox font-sm" id="sensors-24-00376-f007"><h4 class="obj_head">Figure 7.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g007.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/2696eb3073ee/sensors-24-00376-g007.jpg" loading="lazy" height="463" width="743" alt="Figure 7"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f007/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Example of RSSI−distance relationship obtained for anchor A2 and using the RSSI data aggregated with the maximum algorithm and filtered.</p></figcaption></figure><figure class="fig xbox font-sm" id="sensors-24-00376-f008"><h4 class="obj_head">Figure 8.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g008.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/edd01f722ca8/sensors-24-00376-g008.jpg" loading="lazy" height="911" width="734" alt="Figure 8"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f008/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Example of a regression plot obtained for the assisted-ML approach in the following cases: (<strong>a</strong>) training dataset; (<strong>b</strong>) validation dataset; (<strong>c</strong>) test dataset; and (<strong>d</strong>) all datasets.</p></figcaption></figure><figure class="fig xbox font-sm" id="sensors-24-00376-f009"><h4 class="obj_head">Figure 9.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g009.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/7eed1396b88e/sensors-24-00376-g009.jpg" loading="lazy" height="901" width="743" alt="Figure 9"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f009/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Example of a regression plot obtained for the full-ML approach in the following cases: (<strong>a</strong>) training dataset; (<strong>b</strong>) validation dataset; (<strong>c</strong>) test dataset; and (<strong>d</strong>) all datasets.</p></figcaption></figure><section class="tw xbox font-sm" id="sensors-24-00376-t004"><h4 class="obj_head">Table 4.</h4>
<div class="caption p"><p>Training results for each dataset for the assisted-ML approach.</p></div>
<div class="tbl-box p" tabindex="0"><table class="content" frame="hsides" rules="groups">
<thead><tr>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">
</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Observation</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">MSE [m<sup>2</sup>]</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">R<sup>2</sup>
</th>
</tr></thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="1" colspan="1">Training</td>
<td align="left" valign="middle" rowspan="1" colspan="1">1098</td>
<td align="left" valign="middle" rowspan="1" colspan="1">4.3666 × 10<sup>7</sup>
</td>
<td align="left" valign="middle" rowspan="1" colspan="1">1.0000</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="1" colspan="1">Validation</td>
<td align="left" valign="middle" rowspan="1" colspan="1">235</td>
<td align="left" valign="middle" rowspan="1" colspan="1">1.1190 × 10<sup>−5</sup>
</td>
<td align="left" valign="middle" rowspan="1" colspan="1">1.0000</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Test</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">235</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">6.1233 × 10<sup>−5</sup>
</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">1.0000</td>
</tr>
</tbody>
</table></div>
<div class="p text-right font-secondary"><a href="table/sensors-24-00376-t004/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div></section><section class="tw xbox font-sm" id="sensors-24-00376-t005"><h4 class="obj_head">Table 5.</h4>
<div class="caption p"><p>Training results for each dataset for the full-ML approach.</p></div>
<div class="tbl-box p" tabindex="0"><table class="content" frame="hsides" rules="groups">
<thead><tr>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">
</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">Observation</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">MSE [m<sup>2</sup>]</th>
<th align="left" valign="middle" style="border-bottom:solid thin;border-top:solid thin" rowspan="1" colspan="1">R<sup>2</sup>
</th>
</tr></thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="1" colspan="1">Training</td>
<td align="left" valign="middle" rowspan="1" colspan="1">1098</td>
<td align="left" valign="middle" rowspan="1" colspan="1">4.9483 × 10<sup>−4</sup>
</td>
<td align="left" valign="middle" rowspan="1" colspan="1">0.9999</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="1" colspan="1">Validation</td>
<td align="left" valign="middle" rowspan="1" colspan="1">235</td>
<td align="left" valign="middle" rowspan="1" colspan="1">8.3280 × 10<sup>−4</sup>
</td>
<td align="left" valign="middle" rowspan="1" colspan="1">0.9998</td>
</tr>
<tr>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Test</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">235</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">9.0197 × 10<sup>−4</sup>
</td>
<td align="left" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">0.9998</td>
</tr>
</tbody>
</table></div>
<div class="p text-right font-secondary"><a href="table/sensors-24-00376-t005/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div></section></section><section id="sec5dot2-sensors-24-00376"><h3 class="pmc_sec_title">5.2. Positioning Results</h3>
<p>To verify the localization performance of the considered procedures, a testing phase was carried out. Specifically, as shown in <a href="#sensors-24-00376-f010" class="usa-link">Figure 10</a>, 31 positioning points were considered. For each positioning point, 10 repeated RSSI measurements were collected for each transmission channel, resulting in an available dataset consisting of 930 RSSI measurements for each anchor.</p>
<figure class="fig xbox font-sm" id="sensors-24-00376-f010"><h4 class="obj_head">Figure 10.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g010.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/ae4560edbee0/sensors-24-00376-g010.jpg" loading="lazy" height="505" width="731" alt="Figure 10"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f010/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Location of the positioning points for the testing phase.</p></figcaption></figure><p>Since the purpose of the paper is to compare the effectiveness of all the considered procedures described in <a href="#sec3-sensors-24-00376" class="usa-link">Section 3</a>, the way they were combined is reported below.</p>
<ul class="list" style="list-style-type:disc">
<li><p><strong>case #1 –> no aggregation, no filtering</strong>: no conditioning on the acquired signals is carried out. During the calibration phase, the propagation models are estimated for each transmission channel (Ch 37, Ch 38, and Ch 39) using the empirical path loss propagation models. During the testing phase, the obtained propagation models are used to estimate anchor–tag distances, and the estimation of the unknown tag positions is carried out via the numerical optimization approach.</p></li>
<li><p><strong>case #2 –> no aggregation, yes filtering</strong>: the signals from the transmission channels (Ch 37, Ch 38, and Ch 39) are filtered. During the calibration phase, they are used to estimate the propagation models for each transmission channel (Ch 37, Ch 38, and Ch 39) using the empirical path loss propagation models. During the testing phase, the obtained propagation models are used to estimate anchor–tag distances, and the estimation of the unknown tag positions is carried out via the numerical optimization approach.</p></li>
<li><p><strong>case #3 –> yes aggregation, no filtering</strong>: the signals from the transmission channels (Ch 37, Ch 38, and Ch 39) are aggregated with all aggregation algorithm (max, mean, and mrc). During the calibration phase, they are used to estimate the propagation models for each aggregation algorithm (max, mean, and mrc) using the empirical path loss propagation models. During the testing phase, the obtained propagation models are used to estimate anchor–tag distances, and the estimation of the unknown tag positions is carried out via the numerical optimization approach.</p></li>
<li><p><strong>case #4 –> yes aggregation, yes filtering</strong>: the signals from the transmission channels (Ch 37, Ch 38, and Ch 39) are aggregated with all aggregation algorithm (max, mean, and mrc) and filtered. During the calibration phase, they are used to estimate the propagation models for each aggregation algorithm (max, mean, and mrc) using the empirical path loss propagation models. During the testing phase, the obtained propagation models are used to estimate anchor–tag distances, and the estimation of the unknown tag positions is carried out via the numerical optimization approach.</p></li>
<li><p><strong>case #5 –> assisted-ML</strong>: the signals from the transmission channels (Ch 37, Ch 38, and Ch 39) are aggregated with all aggregation algorithms (max, mean, and mrc) and filtered. During the calibration phase, they are used to train the FNN used in the assisted-ML approach, for each aggregation algorithm (max, mean, and mrc). During the testing phase, the trained FNNs are used to estimate anchor–tag distances, and the estimation of the unknown tag positions is carried out via the numerical optimization approach.</p></li>
<li><p><strong>case #6 –> full–ML</strong>: the signals from the transmission channels (Ch 37, Ch 38, and Ch 39) are aggregated with all aggregation algorithm (max, mean, and mrc) and filtered. During the calibration phase, they are used to train the FNN used in the full-ML approach, for each aggregation algorithm (max, mean, and mrc). During the testing phase, the trained FNNs are used to directly estimate the unknown tag positions.</p></li>
</ul>
<p>All these procedures were applied to the full experimental dataset of unknown tag positions (310 positioning points). To evaluate the performance of each considered procedure (cases #1 to #6), the positioning error <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm53" overflow="linebreak"><mrow><mi>ε</mi></mrow></math>
</span> has been used. It defines the distance between the true and estimated position of the tag, respectively. The mathematical definition is given by (<a href="#FD14-sensors-24-00376" class="usa-link">14</a>) where <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm54" overflow="linebreak"><mrow><mi>ε</mi></mrow></math>
</span> represents the Euclidean distance, while <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm55" overflow="linebreak"><mrow><msup><mrow><mo>[</mo><msub><mi>x</mi><mi>t</mi></msub><mo>,</mo><msub><mi>y</mi><mi>t</mi></msub><mo>]</mo></mrow><mi>T</mi></msup></mrow></math>
</span> and <span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm56" overflow="linebreak"><mrow><msup><mrow><mo>[</mo><msub><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>,</mo><msub><mover accent="true"><mi>y</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>]</mo></mrow><mi>T</mi></msup></mrow></math>
</span> represent the Cartesian coordinates of the true and estimated position of the tag, respectively.
</p>
<table class="disp-formula p" id="FD14-sensors-24-00376"><tr>
<td class="formula"><math id="mm57" display="block" overflow="linebreak"><mrow><mrow><mi>ε</mi><mo>=</mo><msqrt><mrow><msup><mrow><mo>(</mo><msub><mi>x</mi><mi>t</mi></msub><mo>−</mo><msub><mover accent="true"><mi>x</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>)</mo></mrow><mn>2</mn></msup><mo>+</mo><msup><mrow><mo>(</mo><msub><mi>y</mi><mi>t</mi></msub><mo>−</mo><msub><mover accent="true"><mi>y</mi><mo stretchy="false">^</mo></mover><mi>t</mi></msub><mo>)</mo></mrow><mn>2</mn></msup></mrow></msqrt></mrow></mrow></math></td>
<td class="label">(14)</td>
</tr></table>
<p>Finally, for each considered case, the mean positioning errors (<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm58" overflow="linebreak"><mrow><msub><mi>ε</mi><mi>μ</mi></msub></mrow></math>
</span>) and the corresponding uncertainties on all the analyzed positioning points were estimated. <a href="#sensors-24-00376-f011" class="usa-link">Figure 11</a> summarizes the obtained results.</p>
<figure class="fig xbox font-sm" id="sensors-24-00376-f011"><h4 class="obj_head">Figure 11.</h4>
<p class="img-box line-height-none margin-x-neg-2 tablet:margin-x-0 text-center"><a class="tileshop" target="_blank" href="https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11154453_sensors-24-00376-g011.jpg"><img class="graphic zoom-in" src="https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3b0/11154453/d6ce29be5b0e/sensors-24-00376-g011.jpg" loading="lazy" height="397" width="717" alt="Figure 11"></a></p>
<div class="p text-right font-secondary"><a href="figure/sensors-24-00376-f011/" class="usa-link" target="_blank" rel="noopener noreferrer">Open in a new tab</a></div>
<figcaption><p>Obtained localization performance in terms of mean positioning errors (<span xmlns:mml="http://www.w3.org/1998/Math/MathML">
<math id="mm59" overflow="linebreak"><mrow><msub><mi>ε</mi><mi>μ</mi></msub></mrow></math>
</span>) and uncertainty on the mean positioning error, for each considered procedures.</p></figcaption></figure><p>In all the considered cases the mean positioning error is always lower than 1.6 m with a maximum uncertainty of 0.06 m. The worst performance, with a mean positioning error of about 1.6 m, are obtained in the first two analyzed cases, case #1 and case #2. In both these cases, multichannel transmission was not exploited since no aggregation algorithm was applied. The filtering effect does not allow any localization improvement since the performances are very similar between case #1 and case #2. In addition, it is possible to highlight, as the chosen transmission channel does not have any significant effect on the localization performance. Regarding the other analyzed cases, we obtain consistently better performance compared with case #1 and case #2 (about 1.0 m as the mean positioning error). The key contribution to achieve the performance improvement is related to the use of the aggregation algorithms. In fact, all four cases (from case #3 to case #6) apply the three considered aggregation algorithms. As far as the used aggregation algorithm, there is no trend towards improvement. In some cases, it is better to use the max algorithm (cases #3 and #4); in others, the mean or the mrc algorithm, depending on the used ML approach. Regarding the comparison among the considered positioning procedures, it is necessary to refer to cases #4, #5, and #6 as they share the same operating conditions (RSSI measurements are aggregated with all the considered aggregation algorithms and filtered). Having fixed the operating conditions, in case #4, the empirical path loss propagation model is used to estimate the anchor–tag distances and then the numerical optimization algorithm is used to estimate the unknown tag positions. In case #5, the anchor–tag distances are estimated via the FNN employed in the ML-assisted approach, and then via the numerical optimization algorithm, the unknown tag positions were estimated. Finally, in case #6, via the FNN employed in the full-ML approach, the unknown tag position were directly estimated from the RSSI measurements. Using the mean as the aggregation algorithm, the assisted-ML approach guarantees the best performance compared to the previous ones, while it exhibits worse performance using max and mrc as aggregation algorithms. Of course, these considerations are valid with respect to the adopted conditions of algorithm setting and the considered testing scenario. Anyway, a limited performance variation (mean positioning error) can be observed. In all the considered cases (cases from #1 to #6), a limited variation in the uncertainty of the mean positioning error was observed, not allowing any relation with the chosen procedures.</p></section><section id="sec5dot3-sensors-24-00376"><h3 class="pmc_sec_title">5.3. Discussion</h3>
<p>The proposed analysis highlighted as the localization performance using BLE technologies are strictly connected on the use of multiple transmission channels that enable the application of aggregation algorithms. If a worse performance is acceptable, it is possible to apply a single transmission channel, and no suitable choices on the transmission channel to be used have to be made. If a better performance is needed, the multiple transmission channel must be enabled and the choice of the positioning algorithms can be substantially made, considering the minimum computational cost. The suggested methodology may assist indoor localization system designers in determining which solutions must be employed to satisfy the demands of particular applications in terms of performance.</p>
<p>Certainly, several activities can be carried out in the future to extend the methodology proposed in this paper. For example, a more exhaustive analysis concerns the execution of the experimental campaign in larger working environments, or varying the density and the geometric placement of beacons within the localization domain and verifying whether the claimed best solutions remain so as these conditions vary. Other important activities include conducting experimental tests in a dynamic localization context and testing the generality of the considered techniques (especially ML-based approaches) by considering greater variability in the data used for both training and testing. Such variability could come from experimental campaigns carried out on different working environments. In addition, it is possible to consider improved versions of the considered and implemented solutions (e.g., regarding the propagation model or neural network), but also to add other techniques (e.g., regarding filtering or positioning) which are not considered in this paper.</p></section></section><section id="sec6-sensors-24-00376"><h2 class="pmc_sec_title">6. Conclusions</h2>
<p>In the framework of the localization techniques based on Bluetooth Low Energy (BLE) 5.0 technology using the Received Signal Strength Indicator (RSSI), different solutions have been proposed in the literature to improve the localization performance. An experimental campaign in a complex indoor environment was carried out to identify the solution (or a combination of them) that most contributes to the improvement of BLE-based indoor localization systems. The obtained results showed that the exploitation of multichannel transmission through the use of RSSI signal aggregation techniques is the most crucial aspect for achieving optimal performance. The multichannel approach, based on combining RSSI signals from the different transmission channels (Ch 37, Ch 38, and Ch 39), takes full advantage of the potential of BLE 5.0 technology, allowing us to reduce the positioning error of about 35% (from 1.5 m to 1 m). Other solutions have been considered and analyzed, also in combination among them: the RSSI signal filtering; distance estimation adopting an empirical propagation model or Machine Learning (ML); numerical optimization; and ML models for estimating the unknown position of the tag. These solutions have showed a lesser impact in the improvement of the localization accuracy with an increase or a decrease in the positioning error that goes from 2% to 23%, depending on the combination of the used solutions. The results of this analysis can be useful for the designers to choose the solutions to be implemented, depending on the target accuracy of the localization system to be developed. Certainly, the obtained results have full validity for the conditions tested and considered in this paper, but they might be subject to variations considering other operating conditions.</p></section><section id="notes1"><h2 class="pmc_sec_title">Author Contributions</h2>
<p>Conceptualization, F.M., H.d.R., M.L., L.F., A.E.S., J.S. and V.P.; methodology, F.M., H.d.R., M.L., L.F., A.E.S., J.S. and V.P.; software, F.M. and H.d.R.; experimental apparatus, F.M., A.E.S. and J.S.; experiment and validation, F.M. and H.d.R.; writing, F.M., H.d.R., M.L., L.F., A.E.S., J.S. and V.P. All authors have read and agreed to the published version of the manuscript.</p></section><section id="notes2"><h2 class="pmc_sec_title">Institutional Review Board Statement</h2>
<p>Not applicable.</p></section><section id="notes3"><h2 class="pmc_sec_title">Informed Consent Statement</h2>
<p>Not applicable.</p></section><section id="notes4"><h2 class="pmc_sec_title">Data Availability Statement</h2>
<p>Data are contained within the article.</p></section><section id="notes5"><h2 class="pmc_sec_title">Conflicts of Interest</h2>
<p>The authors declare no conflicts of interest.</p></section><section id="funding-statement1" lang="en"><h2 class="pmc_sec_title">Funding Statement</h2>
<p>Helbert da Rocha and Antonio Espirito Santo were financially supported by Project GreenAuto: Green Innovation for the Automotive Industry, n° C644867037-00000013, investment project nr. 54, from the Incentive System to Mobilizing Agendas for Business Innovation, funded by the Recovery and Resilience Plan and by European Funds NextGenerationEU.</p></section><section id="fn-group1" class="fn-group"><h2 class="pmc_sec_title">Footnotes</h2>
<div class="fn-group p font-secondary-light font-sm"><div class="fn p" id="fn1"><p><strong>Disclaimer/Publisher’s Note:</strong> The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.</p></div></div></section><section id="ref-list1" class="ref-list"><h2 class="pmc_sec_title">References</h2>
<section id="ref-list1_sec2"><ul class="ref-list font-sm" style="list-style-type:none">
<li id="B1-sensors-24-00376">
<span class="label">1.</span><cite>Zaim D., Bellafkih M. Bluetooth Low Energy (BLE) based geomarketing system; Proceedings of the 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA); Mohammedia, Morocco. 19–20 October 2016; pp. 1–6.</cite> [<a href="https://doi.org/10.1109/SITA.2016.7772263" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202016%2011th%20International%20Conference%20on%20Intelligent%20Systems:%20Theories%20and%20Applications%20(SITA)&title=Bluetooth%20Low%20Energy%20(BLE)%20based%20geomarketing%20system&author=D.%20Zaim&author=M.%20Bellafkih&pages=1-6&doi=10.1109/SITA.2016.7772263&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B2-sensors-24-00376">
<span class="label">2.</span><cite>Guerreiro J.A., Ahmetovic D., Sato D., Kitani K., Asakawa C. Airport Accessibility and Navigation Assistance for People with Visual Impairments; Proceedings of the CHI’19: 2019 CHI Conference on Human Factors in Computing Systems; Glasgow, UK. 4–9 May 2019; pp. 1–14.</cite> [<a href="https://doi.org/10.1145/3290605.3300246" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%20CHI%E2%80%9919:%202019%20CHI%20Conference%20on%20Human%20Factors%20in%20Computing%20Systems&title=Airport%20Accessibility%20and%20Navigation%20Assistance%20for%20People%20with%20Visual%20Impairments&author=J.A.%20Guerreiro&author=D.%20Ahmetovic&author=D.%20Sato&author=K.%20Kitani&author=C.%20Asakawa&pages=1-14&doi=10.1145/3290605.3300246&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B3-sensors-24-00376">
<span class="label">3.</span><cite>Cerro G., Ferrigno L., Laracca M., Milano F., Carbone P., Comuniello A., De Angelis A., Moschitta A. Probe Localization by Magnetic Measurements in Eddy-Current Nondestructive Testing Environment; Proceedings of the 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace); Rome, Italy. 20–22 June 2018; pp. 45–49.</cite> [<a href="https://doi.org/10.1109/MetroAeroSpace.2018.8453551" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202018%205th%20IEEE%20International%20Workshop%20on%20Metrology%20for%20AeroSpace%20(MetroAeroSpace)&title=Probe%20Localization%20by%20Magnetic%20Measurements%20in%20Eddy-Current%20Nondestructive%20Testing%20Environment&author=G.%20Cerro&author=L.%20Ferrigno&author=M.%20Laracca&author=F.%20Milano&author=P.%20Carbone&pages=45-49&doi=10.1109/MetroAeroSpace.2018.8453551&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B4-sensors-24-00376">
<span class="label">4.</span><cite>Ferrigno L., Miele G., Milano F., Rodio A., Santoni F., De Angelis A., Moschitta A., Carbone P., Cerro G. A real-time tracking system for tremor and trajectory estimation in Parkinson’s disease affected patients; Proceedings of the 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA); Bari, Italy. 1 June–1 July 2020; pp. 1–6.</cite> [<a href="https://doi.org/10.1109/MeMeA49120.2020.9137210" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202020%20IEEE%20International%20Symposium%20on%20Medical%20Measurements%20and%20Applications%20(MeMeA)&title=A%20real-time%20tracking%20system%20for%20tremor%20and%20trajectory%20estimation%20in%20Parkinson%E2%80%99s%20disease%20affected%20patients&author=L.%20Ferrigno&author=G.%20Miele&author=F.%20Milano&author=A.%20Rodio&author=F.%20Santoni&pages=1-6&doi=10.1109/MeMeA49120.2020.9137210&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B5-sensors-24-00376">
<span class="label">5.</span><cite>Giuliano R., Cardarilli G.C., Cesarini C., Di Nunzio L., Fallucchi F., Fazzolari R., Mazzenga F., Re M., Vizzarri A. Indoor Localization System Based on Bluetooth Low Energy for Museum Applications. Electronics. 2020;9:1055. doi: 10.3390/electronics9061055.</cite> [<a href="https://doi.org/10.3390/electronics9061055" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Electronics&title=Indoor%20Localization%20System%20Based%20on%20Bluetooth%20Low%20Energy%20for%20Museum%20Applications&author=R.%20Giuliano&author=G.C.%20Cardarilli&author=C.%20Cesarini&author=L.%20Di%20Nunzio&author=F.%20Fallucchi&volume=9&publication_year=2020&pages=1055&doi=10.3390/electronics9061055&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B6-sensors-24-00376">
<span class="label">6.</span><cite>Zualkernan I.A., Pasquier M., Shahriar S., Towheed M., Sujith S. Using BLE beacons and Machine Learning for Personalized Customer Experience in Smart Cafés; Proceedings of the 2020 International Conference on Electronics, Information, and Communication (ICEIC); Barcelona, Spain. 19–22 January 2020; pp. 1–6.</cite> [<a href="https://doi.org/10.1109/ICEIC49074.2020.9051187" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202020%20International%20Conference%20on%20Electronics,%20Information,%20and%20Communication%20(ICEIC)&title=Using%20BLE%20beacons%20and%20Machine%20Learning%20for%20Personalized%20Customer%20Experience%20in%20Smart%20Caf%C3%A9s&author=I.A.%20Zualkernan&author=M.%20Pasquier&author=S.%20Shahriar&author=M.%20Towheed&author=S.%20Sujith&pages=1-6&doi=10.1109/ICEIC49074.2020.9051187&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B7-sensors-24-00376">
<span class="label">7.</span><cite>Bai L., Ciravegna F., Bond R., Mulvenna M. A low cost indoor positioning system using bluetooth low energy. IEEE Access. 2020;8:136858–136871. doi: 10.1109/ACCESS.2020.3012342.</cite> [<a href="https://doi.org/10.1109/ACCESS.2020.3012342" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=IEEE%20Access&title=A%20low%20cost%20indoor%20positioning%20system%20using%20bluetooth%20low%20energy&author=L.%20Bai&author=F.%20Ciravegna&author=R.%20Bond&author=M.%20Mulvenna&volume=8&publication_year=2020&pages=136858-136871&doi=10.1109/ACCESS.2020.3012342&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B8-sensors-24-00376">
<span class="label">8.</span><cite>Tekler Z.D., Low R., Yuen C., Blessing L. Plug-Mate: An IoT-based occupancy-driven plug load management system in smart buildings. Build. Environ. 2022;223:109472. doi: 10.1016/j.buildenv.2022.109472.</cite> [<a href="https://doi.org/10.1016/j.buildenv.2022.109472" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Build.%20Environ.&title=Plug-Mate:%20An%20IoT-based%20occupancy-driven%20plug%20load%20management%20system%20in%20smart%20buildings&author=Z.D.%20Tekler&author=R.%20Low&author=C.%20Yuen&author=L.%20Blessing&volume=223&publication_year=2022&pages=109472&doi=10.1016/j.buildenv.2022.109472&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B9-sensors-24-00376">
<span class="label">9.</span><cite>Filippoupolitis A., Oliff W., Loukas G. Bluetooth Low Energy Based Occupancy Detection for Emergency Management; Proceedings of the 2016 15th International Conference on Ubiquitous Computing and Communications and 2016 International Symposium on Cyberspace and Security (IUCC-CSS); Granada, Spain. 14–16 December 2016; pp. 31–38.</cite> [<a href="https://doi.org/10.1109/IUCC-CSS.2016.013" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202016%2015th%20International%20Conference%20on%20Ubiquitous%20Computing%20and%20Communications%20and%202016%20International%20Symposium%20on%20Cyberspace%20and%20Security%20(IUCC-CSS)&title=Bluetooth%20Low%20Energy%20Based%20Occupancy%20Detection%20for%20Emergency%20Management&author=A.%20Filippoupolitis&author=W.%20Oliff&author=G.%20Loukas&pages=31-38&doi=10.1109/IUCC-CSS.2016.013&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B10-sensors-24-00376">
<span class="label">10.</span><cite>Tekler Z.D., Chong A. Occupancy prediction using deep learning approaches across multiple space types: A minimum sensing strategy. Build. Environ. 2022;226:109689. doi: 10.1016/j.buildenv.2022.109689.</cite> [<a href="https://doi.org/10.1016/j.buildenv.2022.109689" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Build.%20Environ.&title=Occupancy%20prediction%20using%20deep%20learning%20approaches%20across%20multiple%20space%20types:%20A%20minimum%20sensing%20strategy&author=Z.D.%20Tekler&author=A.%20Chong&volume=226&publication_year=2022&pages=109689&doi=10.1016/j.buildenv.2022.109689&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B11-sensors-24-00376">
<span class="label">11.</span><cite>SIG I.B. The Bluetooth® Low Energy Primer|Bluetooth® Technology Website, White Paper. [(accessed on 27 June 2023)]. Available online: <a href="https://www.bluetooth.com/wp-content/uploads/2022/05/Bluetooth_LE_Primer_Paper.pdf" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">https://www.bluetooth.com/wp-content/uploads/2022/05/Bluetooth_LE_Primer_Paper.pdf</a>.</cite>
</li>
<li id="B12-sensors-24-00376">
<span class="label">12.</span><cite>SIG I.B. An Introduction to Bluetooth Beacons, White Paper. [(accessed on 28 June 2023)]. Available online: <a href="http://pages.silabs.com/rs/634-SLU-379/images/Whitepaper-Developing-Beacons-with-Bluetooth-Low-Energy-Technology.pdf" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">http://pages.silabs.com/rs/634-SLU-379/images/Whitepaper-Developing-Beacons-with-Bluetooth-Low-Energy-Technology.pdf</a>.</cite>
</li>
<li id="B13-sensors-24-00376">
<span class="label">13.</span><cite>Collotta M., Pau G., Talty T., Tonguz O.K. Bluetooth 5: A Concrete Step Forward toward the IoT. IEEE Commun. Mag. 2018;56:125–131. doi: 10.1109/MCOM.2018.1700053.</cite> [<a href="https://doi.org/10.1109/MCOM.2018.1700053" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=IEEE%20Commun.%20Mag.&title=Bluetooth%205:%20A%20Concrete%20Step%20Forward%20toward%20the%20IoT&author=M.%20Collotta&author=G.%20Pau&author=T.%20Talty&author=O.K.%20Tonguz&volume=56&publication_year=2018&pages=125-131&doi=10.1109/MCOM.2018.1700053&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B14-sensors-24-00376">
<span class="label">14.</span><cite>Cantón Paterna V., Calveras Auge A., Paradells Aspas J., Perez Bullones M.A. A bluetooth low energy indoor positioning system with channel diversity, weighted trilateration and kalman filtering. Sensors. 2017;17:2927. doi: 10.3390/s17122927.</cite> [<a href="https://doi.org/10.3390/s17122927" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="/articles/PMC5750706/" class="usa-link">PMC free article</a>] [<a href="https://pubmed.ncbi.nlm.nih.gov/29258195/" class="usa-link">PubMed</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Sensors&title=A%20bluetooth%20low%20energy%20indoor%20positioning%20system%20with%20channel%20diversity,%20weighted%20trilateration%20and%20kalman%20filtering&author=V.%20Cant%C3%B3n%20Paterna&author=A.%20Calveras%20Auge&author=J.%20Paradells%20Aspas&author=M.A.%20Perez%20Bullones&volume=17&publication_year=2017&pages=2927&pmid=29258195&doi=10.3390/s17122927&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B15-sensors-24-00376">
<span class="label">15.</span><cite>Röbesaat J., Zhang P., Abdelaal M., Theel O. An improved BLE indoor localization with Kalman-based fusion: An experimental study. Sensors. 2017;17:951. doi: 10.3390/s17050951.</cite> [<a href="https://doi.org/10.3390/s17050951" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="/articles/PMC5461075/" class="usa-link">PMC free article</a>] [<a href="https://pubmed.ncbi.nlm.nih.gov/28445421/" class="usa-link">PubMed</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Sensors&title=An%20improved%20BLE%20indoor%20localization%20with%20Kalman-based%20fusion:%20An%20experimental%20study&author=J.%20R%C3%B6besaat&author=P.%20Zhang&author=M.%20Abdelaal&author=O.%20Theel&volume=17&publication_year=2017&pages=951&pmid=28445421&doi=10.3390/s17050951&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B16-sensors-24-00376">
<span class="label">16.</span><cite>Capriglione D., Cerro G., Ferrigno L., Milano F., Moschitta A. A multi-frequency approach to mitigate the performance degradation of a magnetic positioning system under CW disturbance conditions. Measurement. 2020;161:107842. doi: 10.1016/j.measurement.2020.107842.</cite> [<a href="https://doi.org/10.1016/j.measurement.2020.107842" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Measurement&title=A%20multi-frequency%20approach%20to%20mitigate%20the%20performance%20degradation%20of%20a%20magnetic%20positioning%20system%20under%20CW%20disturbance%20conditions&author=D.%20Capriglione&author=G.%20Cerro&author=L.%20Ferrigno&author=F.%20Milano&author=A.%20Moschitta&volume=161&publication_year=2020&pages=107842&doi=10.1016/j.measurement.2020.107842&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B17-sensors-24-00376">
<span class="label">17.</span><cite>Arbula D., Ljubic S. Indoor Localization Based on Infrared Angle of Arrival Sensor Network. Sensors. 2020;20:6278. doi: 10.3390/s20216278.</cite> [<a href="https://doi.org/10.3390/s20216278" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="/articles/PMC7663400/" class="usa-link">PMC free article</a>] [<a href="https://pubmed.ncbi.nlm.nih.gov/33158151/" class="usa-link">PubMed</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Sensors&title=Indoor%20Localization%20Based%20on%20Infrared%20Angle%20of%20Arrival%20Sensor%20Network&author=D.%20Arbula&author=S.%20Ljubic&volume=20&publication_year=2020&pages=6278&pmid=33158151&doi=10.3390/s20216278&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B18-sensors-24-00376">
<span class="label">18.</span><cite>Wang H., Rajagopal N., Rowe A., Sinopoli B., Gao J. Efficient Beacon Placement Algorithms for Time-of-Flight Indoor Localization; Proceedings of the SIGSPATIAL’19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems; Chicago, IL, USA. 5–8 November 2019; pp. 119–128.</cite> [<a href="https://doi.org/10.1145/3347146.3359344" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%20SIGSPATIAL%E2%80%9919:%2027th%20ACM%20SIGSPATIAL%20International%20Conference%20on%20Advances%20in%20Geographic%20Information%20Systems&title=Efficient%20Beacon%20Placement%20Algorithms%20for%20Time-of-Flight%20Indoor%20Localization&author=H.%20Wang&author=N.%20Rajagopal&author=A.%20Rowe&author=B.%20Sinopoli&author=J.%20Gao&pages=119-128&doi=10.1145/3347146.3359344&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B19-sensors-24-00376">
<span class="label">19.</span><cite>Yang B., Guo L., Guo R., Zhao M., Zhao T. A Novel Trilateration Algorithm for RSSI-Based Indoor Localization. IEEE Sens. J. 2020;20:8164–8172. doi: 10.1109/JSEN.2020.2980966.</cite> [<a href="https://doi.org/10.1109/JSEN.2020.2980966" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=IEEE%20Sens.%20J.&title=A%20Novel%20Trilateration%20Algorithm%20for%20RSSI-Based%20Indoor%20Localization&author=B.%20Yang&author=L.%20Guo&author=R.%20Guo&author=M.%20Zhao&author=T.%20Zhao&volume=20&publication_year=2020&pages=8164-8172&doi=10.1109/JSEN.2020.2980966&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B20-sensors-24-00376">
<span class="label">20.</span><cite>Shao C., Roh H., Lee W. BuSAR: Bluetooth Slot Availability Randomization for Better Coexistence With Dense Wi-Fi Networks. IEEE Trans. Mob. Comput. 2021;20:846–860. doi: 10.1109/TMC.2019.2955080.</cite> [<a href="https://doi.org/10.1109/TMC.2019.2955080" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=IEEE%20Trans.%20Mob.%20Comput.&title=BuSAR:%20Bluetooth%20Slot%20Availability%20Randomization%20for%20Better%20Coexistence%20With%20Dense%20Wi-Fi%20Networks&author=C.%20Shao&author=H.%20Roh&author=W.%20Lee&volume=20&publication_year=2021&pages=846-860&doi=10.1109/TMC.2019.2955080&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B21-sensors-24-00376">
<span class="label">21.</span><cite>Capriglione D., Ferrigno L., D’Orazio E., Paciello V., Pietrosanto A. Reliability analysis of RSSI for localization in small scale WSNs; Proceedings of the 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings; Graz, Austria. 13–16 May 2012; pp. 935–940.</cite> [<a href="https://doi.org/10.1109/I2MTC.2012.6229301" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202012%20IEEE%20International%20Instrumentation%20and%20Measurement%20Technology%20Conference%20Proceedings&title=Reliability%20analysis%20of%20RSSI%20for%20localization%20in%20small%20scale%20WSNs&author=D.%20Capriglione&author=L.%20Ferrigno&author=E.%20D%E2%80%99Orazio&author=V.%20Paciello&author=A.%20Pietrosanto&pages=935-940&doi=10.1109/I2MTC.2012.6229301&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B22-sensors-24-00376">
<span class="label">22.</span><cite>Li G., Geng E., Ye Z., Xu Y., Lin J., Pang Y. Indoor Positioning Algorithm Based on the Improved RSSI Distance Model. Sensors. 2018;18:2820. doi: 10.3390/s18092820.</cite> [<a href="https://doi.org/10.3390/s18092820" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="/articles/PMC6165244/" class="usa-link">PMC free article</a>] [<a href="https://pubmed.ncbi.nlm.nih.gov/30150521/" class="usa-link">PubMed</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Sensors&title=Indoor%20Positioning%20Algorithm%20Based%20on%20the%20Improved%20RSSI%20Distance%20Model&author=G.%20Li&author=E.%20Geng&author=Z.%20Ye&author=Y.%20Xu&author=J.%20Lin&volume=18&publication_year=2018&pages=2820&pmid=30150521&doi=10.3390/s18092820&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B23-sensors-24-00376">
<span class="label">23.</span><cite>Jain C., Sashank G.V.S., N V., Markkandan S. Low-cost BLE based Indoor Localization using RSSI Fingerprinting and Machine Learning; Proceedings of the 2021 Sixth International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET); Chennai, India. 25–27 March 2021; pp. 363–367.</cite> [<a href="https://doi.org/10.1109/WiSPNET51692.2021.9419388" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%202021%20Sixth%20International%20Conference%20on%20Wireless%20Communications,%20Signal%20Processing%20and%20Networking%20(WiSPNET)&title=Low-cost%20BLE%20based%20Indoor%20Localization%20using%20RSSI%20Fingerprinting%20and%20Machine%20Learning&author=C.%20Jain&author=G.V.S.%20Sashank&author=V.%20N&author=S.%20Markkandan&pages=363-367&doi=10.1109/WiSPNET51692.2021.9419388&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B24-sensors-24-00376">
<span class="label">24.</span><cite>Jeon K.E., She J., Soonsawad P., Ng P.C. BLE Beacons for Internet of Things Applications: Survey, Challenges, and Opportunities. IEEE Internet Things J. 2018;5:811–828. doi: 10.1109/JIOT.2017.2788449.</cite> [<a href="https://doi.org/10.1109/JIOT.2017.2788449" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=IEEE%20Internet%20Things%20J.&title=BLE%20Beacons%20for%20Internet%20of%20Things%20Applications:%20Survey,%20Challenges,%20and%20Opportunities&author=K.E.%20Jeon&author=J.%20She&author=P.%20Soonsawad&author=P.C.%20Ng&volume=5&publication_year=2018&pages=811-828&doi=10.1109/JIOT.2017.2788449&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B25-sensors-24-00376">
<span class="label">25.</span><cite>Bluetooth SIG Proprietary Bluetooth 4.0 Core Specification. [(accessed on 4 July 2022)]. Available online: <a href="https://www.bluetooth.org/docman/handlers/downloaddoc.ashx?doc_id=456433" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">https://www.bluetooth.org/docman/handlers/downloaddoc.ashx?doc_id=456433</a>.</cite>
</li>
<li id="B26-sensors-24-00376">
<span class="label">26.</span><cite>Kaduskar A., Vengurlekar O., Shinde V. RSSI filtering methods applied to localization using Bluetooth low energy. Int. J. Recent Technol. Eng. (IJRTE) 2020;9:2277–3878. doi: 10.35940/ijrte.C4413.099320.</cite> [<a href="https://doi.org/10.35940/ijrte.C4413.099320" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Int.%20J.%20Recent%20Technol.%20Eng.%20(IJRTE)&title=RSSI%20filtering%20methods%20applied%20to%20localization%20using%20Bluetooth%20low%20energy&author=A.%20Kaduskar&author=O.%20Vengurlekar&author=V.%20Shinde&volume=9&publication_year=2020&pages=2277-3878&doi=10.35940/ijrte.C4413.099320&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B27-sensors-24-00376">
<span class="label">27.</span><cite>Qureshi U.M., Umair Z., Hancke G.P. Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision. Sensors. 2019;19:3282. doi: 10.3390/s19153282.</cite> [<a href="https://doi.org/10.3390/s19153282" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="/articles/PMC6696175/" class="usa-link">PMC free article</a>] [<a href="https://pubmed.ncbi.nlm.nih.gov/31349727/" class="usa-link">PubMed</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Sensors&title=Evaluating%20the%20Implications%20of%20Varying%20Bluetooth%20Low%20Energy%20(BLE)%20Transmission%20Power%20Levels%20on%20Wireless%20Indoor%20Localization%20Accuracy%20and%20Precision&author=U.M.%20Qureshi&author=Z.%20Umair&author=G.P.%20Hancke&volume=19&publication_year=2019&pages=3282&pmid=31349727&doi=10.3390/s19153282&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B28-sensors-24-00376">
<span class="label">28.</span><cite>Zhou C., Yuan J., Liu H., Qiu J. Bluetooth Indoor Positioning Based on RSSI and Kalman Filter. Wirel. Pers. Commun. 2017;96:4115–4130. doi: 10.1007/s11277-017-4371-4.</cite> [<a href="https://doi.org/10.1007/s11277-017-4371-4" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Wirel.%20Pers.%20Commun.&title=Bluetooth%20Indoor%20Positioning%20Based%20on%20RSSI%20and%20Kalman%20Filter&author=C.%20Zhou&author=J.%20Yuan&author=H.%20Liu&author=J.%20Qiu&volume=96&publication_year=2017&pages=4115-4130&doi=10.1007/s11277-017-4371-4&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B29-sensors-24-00376">
<span class="label">29.</span><cite>Lagarias J.C., Reeds J.A., Wright M.H., Wright P.E. Convergence properties of the Nelder–Mead simplex method in low dimensions. SIAM J. Optim. 1998;9:112–147. doi: 10.1137/S1052623496303470.</cite> [<a href="https://doi.org/10.1137/S1052623496303470" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=SIAM%20J.%20Optim.&title=Convergence%20properties%20of%20the%20Nelder%E2%80%93Mead%20simplex%20method%20in%20low%20dimensions&author=J.C.%20Lagarias&author=J.A.%20Reeds&author=M.H.%20Wright&author=P.E.%20Wright&volume=9&publication_year=1998&pages=112-147&doi=10.1137/S1052623496303470&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
<li id="B30-sensors-24-00376">
<span class="label">30.</span><cite>EFR32BG13 Blue Gecko Bluetooth® Low Energy SoC Family Data Sheet. [(accessed on 4 July 2022)]. Available online: <a href="https://www.silabs.com/documents/public/data-sheets/efr32bg13-datasheet.pdf" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">https://www.silabs.com/documents/public/data-sheets/efr32bg13-datasheet.pdf</a>.</cite>
</li>
<li id="B31-sensors-24-00376">
<span class="label">31.</span><cite>Ferrigno L., Milano F., Espírito-Santo A., Salvado J., Laracca M., Paciello V. On the Power Consumption of a Bluetooth Device Operating in Beacon Mode; Proceedings of the IECON 2021—47th Annual Conference of the IEEE Industrial Electronics Society; Toronto, ON, Canada. 13–16 October 2021; pp. 1–6.</cite> [<a href="https://doi.org/10.1109/IECON48115.2021.9589601" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">DOI</a>] [<a href="https://scholar.google.com/scholar_lookup?journal=Proceedings%20of%20the%20IECON%202021%E2%80%9447th%20Annual%20Conference%20of%20the%20IEEE%20Industrial%20Electronics%20Society&title=On%20the%20Power%20Consumption%20of%20a%20Bluetooth%20Device%20Operating%20in%20Beacon%20Mode&author=L.%20Ferrigno&author=F.%20Milano&author=A.%20Esp%C3%ADrito-Santo&author=J.%20Salvado&author=M.%20Laracca&pages=1-6&doi=10.1109/IECON48115.2021.9589601&" class="usa-link usa-link--external" data-ga-action="click_feat_suppl" target="_blank" rel="noopener noreferrer">Google Scholar</a>]</li>
</ul></section></section><section id="_ad93_" lang="en" class="associated-data"><h2 class="pmc_sec_title">Associated Data</h2>
<p class="font-secondary"><em>This section collects any data citations, data availability statements, or supplementary materials included in this article.</em></p>
<section id="_adda93_" lang="en" class="data-availability-statement"><h3 class="pmc_sec_title">Data Availability Statement</h3>
<p>Data are contained within the article.</p></section></section></section><footer class="p courtesy-note font-secondary font-sm text-center"><hr class="headless">
<p>Articles from Sensors (Basel, Switzerland) are provided here courtesy of <strong>Multidisciplinary Digital Publishing Institute (MDPI)</strong></p></footer></section></article>
</main>
</div>
</div>
</div>
<div class="pmc-sidenav desktop:grid-col-4 display-flex">
<section class="pmc-sidenav__container" aria-label="Article resources and navigation">
<button type="button" class="pmc-sidenav__container__close">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/usa-icons/close.svg" role="img" alt="Close" />
</button>
<div class="display-none desktop:display-block">
<section class="margin-top-4 desktop:margin-top-0">
<h2 class="margin-top-0">ACTIONS</h2>
<ul class="usa-list usa-list--unstyled usa-list--actions">
<li>
<a
href="https://doi.org/10.3390/s24020376"
class="usa-button usa-button--outline width-24 font-xs display-inline-flex flex-align-center flex-justify-start padding-left-1"
target="_blank"
rel="noreferrer noopener"
data-ga-category="actions"
data-ga-action="click"
data-ga-label="publisher_link_desktop"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/launch.svg" alt="View on publisher site icon" class="usa-icon usa-icon--size-3 usa-icon--link"/>
<span class="display-inline-flex flex-justify-center flex-1 padding-right-2">View on publisher site</span>
</a>
</li>
<li>
<a
href="pdf/sensors-24-00376.pdf"
class="usa-button usa-button--outline width-24 display-inline-flex flex-align-center flex-justify-start padding-left-1"
data-ga-category="actions"
data-ga-action="click"
data-ga-label="pdf_download_desktop"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/file_download.svg" alt="Download PDF icon" class="usa-icon usa-icon--size-3 usa-icon--link"/>
<span class="display-inline-flex flex-justify-center flex-1">PDF (1.9 MB)</span>
</a>
</li>
<li>
<button role="button" class="usa-button width-24 citation-dialog-trigger display-inline-flex flex-align-center flex-justify-start padding-left-1"
aria-label="Open dialog with citation text in different styles"
data-ga-category="actions"
data-ga-action="open"
data-ga-label="cite_desktop"
data-all-citations-url="/resources/citations/11154453/"
data-citation-style="nlm"
data-download-format-link="/resources/citations/11154453/export/"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/format_quote.svg" alt="Cite icon" class="usa-icon usa-icon--size-3 usa-icon--white"/>
<span class="display-inline-flex flex-justify-center flex-1 button-label">Cite</span>
</button>
</li>
<li>
<button class="usa-button width-24 collections-dialog-trigger collections-button display-inline-flex flex-align-center flex-justify-start padding-left-1 collections-button-empty"
aria-label="Save article in MyNCBI collections."
data-ga-category="actions"
data-ga-action="click"
data-ga-label="collections_button_desktop"
data-collections-open-dialog-enabled="false"
data-collections-open-dialog-url="https://account.ncbi.nlm.nih.gov/?back_url=https%3A%2F%2Fpmc.ncbi.nlm.nih.gov%2Farticles%2FPMC11154453%2F%23open-collections-dialog"
data-in-collections="false">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/action-bookmark-full.svg" alt="Collections icon" class="usa-icon usa-icon--size-3 usa-icon--white usa-icon--bookmark-full" hidden />
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/action-bookmark-empty.svg" alt="Collections icon" class="usa-icon usa-icon--size-3 usa-icon--white usa-icon--bookmark-empty" hidden />
<span class="display-inline-flex flex-justify-center flex-1">Collections</span>
</button>
</li>
<li class="pmc-permalink">
<button
type="button"
class="usa-button width-24 display-inline-flex flex-align-center flex-justify padding-left-1 shadow-none"
aria-label="Show article permalink"
aria-expanded="false"
aria-haspopup="true"
data-ga-category="actions"
data-ga-action="open"
data-ga-label="permalink_desktop"
>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/share.svg" alt="Permalink icon" class="usa-icon usa-icon--size-3 usa-icon--white"/>
<span class="display-inline-flex flex-justify-center flex-1 button-label">Permalink</span>
</button>
<div class="pmc-permalink__dropdown" hidden>
<div class="pmc-permalink__dropdown__container">
<h2 class="usa-modal__heading margin-top-0 margin-bottom-2 text-uppercase font-sans-xs">PERMALINK</h2>
<div class="pmc-permalink__dropdown__content">
<input type="text" class="usa-input" value="https://pmc.ncbi.nlm.nih.gov/articles/PMC11154453/" aria-label="Article permalink">
<button class="usa-button display-inline-flex pmc-permalink__dropdown__copy__btn margin-right-0" title="Copy article permalink" data-ga-category="save_share" data-ga-action="link" data-ga-label="copy_link">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/content_copy.svg" alt="Copy icon" aria-hidden="true" class="usa-icon usa-icon--white" />
<span class="margin-left-1">Copy</span>
</button>
</div>
</div>
</div>
</li>
</ul>
</section>
</div>
<section class="pmc-resources margin-top-6 desktop:margin-top-4" data-page-path="/articles/PMC11154453/">
<h2 class="margin-top-0">RESOURCES</h2>
<div class="usa-accordion usa-accordion--multiselectable" data-allow-multiple>
<h3 class="usa-accordion__heading">
<button
type="button"
class="usa-accordion__button"
aria-expanded="false"
aria-controls="resources-similar-articles"
data-ga-category="resources_accordion"
data-ga-action="open_similar_articles"
data-ga-label="/articles/PMC11154453/"
data-action-open="open_similar_articles"
data-action-close="close_similar_articles"
>
Similar articles
</button>
</h3>
<div
id="resources-similar-articles"
class="usa-accordion__content usa-prose"
data-source-url="/resources/similar-article-links/38257468/"
>
</div>
<h3 class="usa-accordion__heading">
<button
type="button"
class="usa-accordion__button"
aria-expanded="false"
aria-controls="resources-cited-by-other-articles"
data-ga-category="resources_accordion"
data-ga-action="open_cited_by"
data-ga-label="/articles/PMC11154453/"
data-action-open="open_cited_by"
data-action-close="close_cited_by"
>
Cited by other articles
</button>
</h3>
<div
id="resources-cited-by-other-articles"
class="usa-accordion__content usa-prose"
data-source-url="/resources/cited-by-links/38257468/"
>
</div>
<h3 class="usa-accordion__heading">
<button
type="button"
class="usa-accordion__button"
aria-expanded="false"
aria-controls="resources-links-to-ncbi-databases"
data-ga-category="resources_accordion"
data-ga-action="open_NCBI_links"
data-ga-label="/articles/PMC11154453/"
data-action-open="open_NCBI_links"
data-action-close="close_NCBI_link"
>
Links to NCBI Databases
</button>
</h3>
<div
id="resources-links-to-ncbi-databases"
class="usa-accordion__content usa-prose"
data-source-url="/resources/db-links/11154453/"
>
</div>
</div>
</section>
<section
class="usa-in-page-nav usa-in-page-nav--wide margin-top-6 desktop:margin-top-4"
data-title-text="On this page"
data-title-heading-level="h2"
data-scroll-offset="0"
data-root-margin="-10% 0px -80% 0px"
data-main-content-selector="main"
data-threshold="1"
hidden
></section>
</section>
</div>
<div class="overlay" role="dialog" aria-label="Citation Dialog" hidden>
<div class="dialog citation-dialog" aria-hidden="true">
<div class="display-inline-flex flex-align-center flex-justify width-full margin-bottom-2">
<h2 class="usa-modal__heading margin-0">Cite</h2>
<button type="button" class="usa-button usa-button--unstyled close-overlay text-black width-auto" tabindex="1">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/close.svg" alt="Close icon" class="usa-icon usa-icon--size-3 usa-icon--button" />
</button>
</div>
<div class="citation-text-block">
<div class="citation-text margin-bottom-2"></div>
<ul class="usa-list usa-list--unstyled display-inline-flex flex-justify width-full flex-align-center">
<li>
<button
class="usa-button usa-button--unstyled text-no-underline display-flex flex-align-center copy-button dialog-focus"
data-ga-category="save_share"
data-ga-action="cite"
data-ga-label="copy"
tabindex="2">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/content_copy.svg" alt="Copy icon" class="usa-icon usa-icon--size-3 usa-icon--link" />
<span>Copy</span>
</button>
</li>
<li>
<a
href="#"
role="button"
class="usa-button usa-button--unstyled text-no-underline display-flex flex-align-center export-button"
data-ga-category="save_share"
data-ga-action="cite"
data-ga-label="download"
title="Download a file for external citation management software"
tabindex="3">
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/file_download.svg" alt="Download icon" aria-hidden="true" class="usa-icon usa-icon--size-3 usa-icon--link" />
<span class="display-none mobile-lg:display-inline">Download .nbib</span>
<span class="display-inline mobile-lg:display-none">.nbib</span>
</a>
</li>
<li>
<div class="display-inline-flex flex-align-center">
<label class="usa-label margin-top-0">Format:</label>
<select aria-label="Format" class="usa-select citation-style-selector padding-1 margin-top-0 border-0 padding-right-4" tabindex="4" >
<option data-style-url-name="ama"
value="AMA"
>
AMA
</option>
<option data-style-url-name="apa"
value="APA"
>
APA
</option>
<option data-style-url-name="mla"
value="MLA"
>
MLA
</option>
<option data-style-url-name="nlm"
value="NLM"
selected="selected">
NLM
</option>
</select>
</div>
</li>
</ul>
</div>
</div>
</div>
<div class="overlay" role="dialog" hidden>
<div id="collections-action-dialog" class="dialog collections-dialog" aria-hidden="true">
<div class="display-inline-flex flex-align-center flex-justify width-full margin-bottom-2">
<h2 class="usa-modal__heading margin-0">Add to Collections</h2>
</div>
<div class="collections-action-panel action-panel">
<form id="collections-action-dialog-form"
class="usa-form maxw-full collections-action-panel-form action-panel-content action-form action-panel-smaller-selectors"
data-existing-collections-url="/list-existing-collections/"
data-add-to-existing-collection-url="/add-to-existing-collection/"
data-create-and-add-to-new-collection-url="/create-and-add-to-new-collection/"
data-myncbi-max-collection-name-length="100"
data-collections-root-url="https://www.ncbi.nlm.nih.gov/myncbi/collections/">
<input type="hidden" name="csrfmiddlewaretoken" value="xEyrImbYE3BgzxNYTs7jKjVBKlseWOaAHJG8tzCD4JZCciSh4ubV7l0d3enej2ZN">
<fieldset class="usa-fieldset margin-bottom-2">
<div class="usa-radio">
<input type="radio"
id="collections-action-dialog-new"
class="usa-radio__input usa-radio__input--tile collections-new margin-top-0"
name="collections"
value="new"
data-ga-category="collections_button"
data-ga-action="click"
data-ga-label="collections_radio_new" />
<label class="usa-radio__label" for="collections-action-dialog-new">Create a new collection</label>
</div>
<div class="usa-radio">
<input type="radio"
id="collections-action-dialog-existing"
class="usa-radio__input usa-radio__input--tile collections-existing"
name="collections"
value="existing"
checked="true"
data-ga-category="collections_button"
data-ga-action="click"
data-ga-label="collections_radio_existing" />
<label class="usa-radio__label" for="collections-action-dialog-existing">Add to an existing collection</label>
</div>
</fieldset>
<fieldset class="usa-fieldset margin-bottom-2">
<div class="action-panel-control-wrap new-collections-controls">
<label for="collections-action-dialog-add-to-new" class="usa-label margin-top-0">
Name your collection
<abbr title="required" class="usa-hint usa-hint--required text-no-underline">*</abbr>
</label>
<input
type="text"
name="add-to-new-collection"
id="collections-action-dialog-add-to-new"
class="usa-input collections-action-add-to-new"
pattern="[^"&=<>/]*" title="The following characters are not allowed in the Name field: "&=<>/"
maxlength=""
data-ga-category="collections_button"
data-ga-action="create_collection"
data-ga-label="non_favorties_collection"
required
/>
</div>
<div class="action-panel-control-wrap existing-collections-controls">
<label for="collections-action-dialog-add-to-existing" class="usa-label margin-top-0">
Choose a collection
</label>
<select id="collections-action-dialog-add-to-existing"
class="usa-select collections-action-add-to-existing"
data-ga-category="collections_button"
data-ga-action="select_collection"
data-ga-label="($('.collections-action-add-to-existing').val() === 'Favorites') ? 'Favorites' : 'non_favorites_collection'">
</select>
<div class="collections-retry-load-on-error usa-input-error-message selection-validation-message">
Unable to load your collection due to an error<br>
<a href="#">Please try again</a>
</div>
</div>
</fieldset>
<div class="display-inline-flex">
<button class="usa-button margin-top-0 action-panel-submit"
type="submit"
data-loading-label="Adding..."
data-pinger-ignore
data-ga-category="collections_button"
data-ga-action="click"
data-ga-label="add">
Add
</button>
<button class="usa-button usa-button--outline margin-top-0 action-panel-cancel"
aria-label="Close 'Add to Collections' panel"
ref="linksrc=close_collections_panel"
data-ga-category="collections_button"
data-ga-action="click"
data-ga-label="cancel">
Cancel
</button>
</div>
</form>
</div>
</div>
</div>
</div>
</div>
</div>
<footer class="ncbi-footer ncbi-dark-background " >
<div class="ncbi-footer__icon-section">
<div class="ncbi-footer__social-header">
Follow NCBI
</div>
<div class="grid-container ncbi-footer__ncbi-social-icons-container">
<a href="https://twitter.com/ncbi"
class="ncbi-footer__social-icon ncbi-footer__social-icon--gray"
target="_blank"
rel="noreferrer noopener">
<svg width="40"
height="40"
viewBox="0 0 40 40"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="m6.067 8 10.81 13.9L6 33.2h4.2l8.4-9.1 7.068 9.1H34L22.8 18.5 31.9 8h-3.5l-7.7 8.4L14.401 8H6.067Zm3.6 1.734h3.266l16.8 21.732H26.57L9.668 9.734Z">
</path>
</svg>
<span class="usa-sr-only">NCBI on X (formerly known as Twitter)</span>
</a>
<a href="https://www.facebook.com/ncbi.nlm"
class="ncbi-footer__social-icon ncbi-footer__social-icon--gray"
target="_blank"
rel="noreferrer noopener">
<svg width="16"
height="29"
focusable="false"
aria-hidden="true"
viewBox="0 0 16 29"
fill="none"
xmlns="http://www.w3.org/2000/svg">
<path d="M3.8809 21.4002C3.8809 19.0932 3.8809 16.7876 3.8809 14.478C3.8809 14.2117 3.80103 14.1452 3.54278 14.1492C2.53372 14.1638 1.52334 14.1492 0.514288 14.1598C0.302626 14.1598 0.248047 14.0972 0.248047 13.8936C0.256034 12.4585 0.256034 11.0239 0.248047 9.58978C0.248047 9.37013 0.302626 9.30224 0.528931 9.3049C1.53798 9.31688 2.54837 9.3049 3.55742 9.31555C3.80103 9.31555 3.8809 9.26097 3.87957 9.00272C3.87158 8.00565 3.85428 7.00592 3.90753 6.00884C3.97142 4.83339 4.31487 3.73115 5.04437 2.78467C5.93095 1.63318 7.15699 1.09005 8.56141 0.967577C10.5582 0.79319 12.555 0.982221 14.5518 0.927641C14.7102 0.927641 14.7462 0.99287 14.7449 1.13664C14.7449 2.581 14.7449 4.02668 14.7449 5.47104C14.7449 5.67604 14.6517 5.68669 14.4946 5.68669C13.4523 5.68669 12.4113 5.68669 11.3703 5.68669C10.3506 5.68669 9.92057 6.10868 9.90593 7.13904C9.89661 7.7647 9.91525 8.39303 9.89794 9.01869C9.88995 9.26364 9.96583 9.31822 10.2015 9.31688C11.7204 9.30623 13.2393 9.31688 14.7595 9.3049C15.0257 9.3049 15.0723 9.3728 15.0444 9.62439C14.89 10.9849 14.7515 12.3467 14.6144 13.7085C14.5691 14.1571 14.5785 14.1585 14.1458 14.1585C12.8386 14.1585 11.5313 14.1665 10.2254 14.1518C9.95119 14.1518 9.89794 14.2317 9.89794 14.4899C9.90593 19.0799 9.89794 23.6752 9.91125 28.2612C9.91125 28.5674 9.8407 28.646 9.53186 28.6433C7.77866 28.6273 6.02414 28.6366 4.27094 28.634C3.82499 28.634 3.87158 28.6992 3.87158 28.22C3.87602 25.9472 3.87913 23.6739 3.8809 21.4002Z">
</path>
</svg>
<span class="usa-sr-only">NCBI on Facebook</span>
</a>
<a href="https://www.linkedin.com/company/ncbinlm"
class="ncbi-footer__social-icon ncbi-footer__social-icon--gray"
target="_blank"
rel="noreferrer noopener">
<svg width="25"
height="23"
viewBox="0 0 26 24"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="M14.6983 9.98423C15.6302 9.24808 16.5926 8.74754 17.6762 8.51991C19.673 8.09126 21.554 8.30824 23.1262 9.7526C24.2351 10.7723 24.7529 12.1115 25.0165 13.5612C25.1486 14.3363 25.2105 15.1218 25.2015 15.9081C25.2015 18.3043 25.2015 20.6898 25.2082 23.0806C25.2082 23.3468 25.1549 23.444 24.8621 23.4414C23.1297 23.4272 21.3992 23.4272 19.6704 23.4414C19.4041 23.4414 19.3429 23.3588 19.3442 23.1019C19.3535 20.5194 19.3442 17.9368 19.3442 15.3543C19.3442 14.0005 18.3258 12.9448 17.0266 12.9488C15.7273 12.9528 14.6983 14.0071 14.6983 15.361C14.6983 17.9328 14.6917 20.5047 14.6983 23.0753C14.6983 23.3708 14.6198 23.444 14.3296 23.4427C12.6185 23.4294 10.9079 23.4294 9.19779 23.4427C8.93155 23.4427 8.86099 23.3735 8.86232 23.1086C8.8783 19.7619 8.88628 16.4144 8.88628 13.066C8.88628 11.5688 8.87874 10.0708 8.86365 8.57182C8.86365 8.3575 8.90758 8.27896 9.14054 8.28029C10.9048 8.29094 12.6687 8.29094 14.4321 8.28029C14.6464 8.28029 14.6983 8.34818 14.6983 8.54653C14.6903 9.00047 14.6983 9.45441 14.6983 9.98423Z">
</path>
<path d="M6.55316 15.8443C6.55316 18.2564 6.55316 20.6699 6.55316 23.082C6.55316 23.3629 6.48127 23.4388 6.19906 23.4374C4.47737 23.4241 2.75568 23.4241 1.03399 23.4374C0.767751 23.4374 0.69986 23.3629 0.701191 23.1006C0.709178 18.2648 0.709178 13.4281 0.701191 8.59053C0.701191 8.34026 0.765089 8.27237 1.01669 8.2737C2.74991 8.28435 4.48048 8.28435 6.20838 8.2737C6.47462 8.2737 6.5465 8.33627 6.54517 8.6065C6.54783 11.0186 6.55316 13.4308 6.55316 15.8443Z">
</path>
<path d="M3.65878 0.243898C5.36804 0.243898 6.58743 1.45529 6.58743 3.1406C6.58743 4.75801 5.32145 5.95742 3.60819 5.96807C3.22177 5.97614 2.83768 5.90639 2.47877 5.76299C2.11985 5.61959 1.79344 5.40546 1.51897 5.13334C1.24449 4.86123 1.02755 4.53668 0.881058 4.17902C0.734563 3.82136 0.661505 3.43788 0.666231 3.05141C0.67555 1.42601 1.9362 0.242566 3.65878 0.243898Z">
</path>
</svg>
<span class="usa-sr-only">NCBI on LinkedIn</span>
</a>
<a href="https://github.com/ncbi"
class="ncbi-footer__social-icon ncbi-footer__social-icon--gray"
target="_blank"
rel="noreferrer noopener">
<svg width="28"
height="27"
viewBox="0 0 28 28"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="M16.7228 20.6334C17.5057 20.5527 18.2786 20.3944 19.0301 20.1608C21.3108 19.4193 22.5822 17.8259 22.963 15.4909C23.1228 14.5112 23.1814 13.5287 22.9883 12.5437C22.8106 11.6423 22.4013 10.8028 21.8007 10.1076C21.7526 10.0605 21.7197 10 21.7064 9.934C21.6931 9.86799 21.7 9.79952 21.7262 9.73748C22.0856 8.6206 21.9711 7.51969 21.601 6.42677C21.582 6.3497 21.5345 6.2827 21.468 6.23923C21.4016 6.19577 21.3211 6.17906 21.2429 6.19248C20.7329 6.21649 20.2313 6.33051 19.7611 6.52928C19.1103 6.7908 18.4899 7.12198 17.9104 7.51703C17.84 7.56996 17.7581 7.60551 17.6713 7.62078C17.5846 7.63605 17.4954 7.6306 17.4112 7.60489C15.2596 7.05882 13.0054 7.06203 10.8554 7.61421C10.7806 7.63586 10.7018 7.63967 10.6253 7.62534C10.5487 7.611 10.4766 7.57892 10.4148 7.53167C9.64788 7.03247 8.85171 6.58918 7.96368 6.33359C7.65781 6.24338 7.34123 6.19458 7.02239 6.18849C6.94879 6.17986 6.87462 6.19893 6.81432 6.242C6.75402 6.28507 6.71191 6.34904 6.69621 6.42145C6.32342 7.51437 6.2209 8.61527 6.56307 9.73348C6.59635 9.84264 6.64694 9.93316 6.54177 10.0516C5.47666 11.2604 5.09988 12.6834 5.19574 14.2676C5.2663 15.4244 5.46201 16.5466 6.01454 17.5769C6.84399 19.1171 8.21664 19.9119 9.85158 20.3352C10.3938 20.4706 10.9444 20.5698 11.4998 20.632C11.5384 20.7492 11.4506 20.7798 11.408 20.8291C11.1734 21.1179 10.9894 21.4441 10.8634 21.7942C10.7622 22.0458 10.8315 22.4039 10.6065 22.5516C10.263 22.7766 9.83827 22.8485 9.42421 22.8871C8.17936 23.0056 7.26471 22.4877 6.6283 21.4348C6.25552 20.8184 5.76956 20.3325 5.08523 20.0663C4.76981 19.9325 4.42139 19.8967 4.08537 19.9638C3.7898 20.029 3.73788 20.1901 3.93891 20.4111C4.03639 20.5234 4.14989 20.6207 4.27575 20.6999C4.9796 21.1318 5.51717 21.7884 5.80152 22.5636C6.37002 23.9973 7.48039 24.5697 8.93825 24.6323C9.43741 24.6575 9.93768 24.615 10.4254 24.5058C10.5892 24.4672 10.6531 24.4872 10.6517 24.6762C10.6451 25.4936 10.6637 26.3123 10.6517 27.131C10.6517 27.6635 10.1684 27.9297 9.58663 27.7393C8.17396 27.2671 6.84977 26.5631 5.66838 25.656C2.59555 23.2891 0.720966 20.1861 0.217704 16.3376C-0.357453 11.9127 0.911353 8.00824 3.98551 4.73881C6.11909 2.42656 8.99932 0.939975 12.1203 0.540191C16.5351 -0.0601815 20.4347 1.14323 23.7232 4.16373C26.2449 6.47869 27.724 9.37672 28.1048 12.7726C28.5828 17.0325 27.3686 20.7945 24.4768 23.9827C22.9762 25.6323 21.0956 26.8908 18.9982 27.6488C18.8783 27.6927 18.7585 27.738 18.636 27.7726C18.0356 27.9404 17.6189 27.6395 17.6189 27.0098C17.6189 25.7452 17.6308 24.4806 17.6295 23.2159C17.6329 22.9506 17.6128 22.6856 17.5696 22.4238C17.4325 21.6664 17.3419 21.484 16.7228 20.6334Z">
</path>
</svg>
<span class="usa-sr-only">NCBI on GitHub</span>
</a>
<a href="https://ncbiinsights.ncbi.nlm.nih.gov/"
class="ncbi-footer__social-icon ncbi-footer__social-icon--gray"
target="_blank"
rel="noreferrer noopener">
<svg width="26"
height="26"
viewBox="0 0 27 27"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="M23.7778 26.4574C23.1354 26.3913 22.0856 26.8024 21.636 26.3087C21.212 25.8444 21.4359 24.8111 21.324 24.0347C19.9933 14.8323 14.8727 8.80132 6.09057 5.85008C4.37689 5.28406 2.58381 4.99533 0.779072 4.99481C0.202773 4.99481 -0.0229751 4.83146 0.00455514 4.21479C0.0660406 3.08627 0.0660406 1.95525 0.00455514 0.826734C-0.0413285 0.0815827 0.259669 -0.0193618 0.896534 0.00266238C6.96236 0.222904 12.3693 2.24179 16.9889 6.16209C22.9794 11.2478 26.1271 17.7688 26.4372 25.648C26.4629 26.294 26.3179 26.5271 25.6609 26.4684C25.0827 26.417 24.4991 26.4574 23.7778 26.4574Z">
</path>
<path d="M14.8265 26.441C14.0924 26.441 13.2371 26.6795 12.6626 26.3786C12.0092 26.0372 12.3781 25.0644 12.246 24.378C11.1154 18.5324 6.6849 14.5497 0.74755 14.1001C0.217135 14.0615 -0.0104482 13.9422 0.0134113 13.3659C0.0519536 12.1454 0.0482829 10.9213 0.0134113 9.69524C-0.00127145 9.14464 0.196946 9.03268 0.703502 9.04736C9.21217 9.27128 16.5994 16.2511 17.2804 24.7231C17.418 26.4446 17.418 26.4446 15.6579 26.4446H14.832L14.8265 26.441Z">
</path>
<path d="M3.58928 26.4555C2.64447 26.4618 1.73584 26.0925 1.06329 25.4289C0.39073 24.7653 0.00933763 23.8617 0.0030097 22.9169C-0.00331824 21.9721 0.365937 21.0635 1.02954 20.3909C1.69315 19.7184 2.59675 19.337 3.54156 19.3306C4.48637 19.3243 5.39499 19.6936 6.06755 20.3572C6.7401 21.0208 7.1215 21.9244 7.12782 22.8692C7.13415 23.814 6.7649 24.7226 6.10129 25.3952C5.43768 26.0677 4.53409 26.4491 3.58928 26.4555Z">
</path>
</svg>
<span class="usa-sr-only">NCBI RSS feed</span>
</a>
</div>
</div>
<div data-testid="gridContainer"
class="grid-container ncbi-footer__container">
<div class="grid-row ncbi-footer__main-content-container"
data-testid="grid">
<div class="ncbi-footer__column">
<p class="ncbi-footer__circled-icons-heading">
Connect with NLM
</p>
<div class="ncbi-footer__circled-icons-list">
<a href=https://twitter.com/nlm_nih class="ncbi-footer__social-icon ncbi-footer__social-icon--circled" target="_blank" rel="noreferrer noopener">
<svg width="32"
height="32"
viewBox="0 0 40 40"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="m6.067 8 10.81 13.9L6 33.2h4.2l8.4-9.1 7.068 9.1H34L22.8 18.5 31.9 8h-3.5l-7.7 8.4L14.401 8H6.067Zm3.6 1.734h3.266l16.8 21.732H26.57L9.668 9.734Z">
</path>
</svg>
<span class="usa-sr-only">NLM on X (formerly known as Twitter)</span>
</a>
<a href=https://www.facebook.com/nationallibraryofmedicine class="ncbi-footer__social-icon ncbi-footer__social-icon--circled" target="_blank" rel="noreferrer noopener">
<svg width="13"
height="24"
viewBox="0 0 13 24"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="M4.11371 23.1369C4.11371 23.082 4.11371 23.0294 4.11371 22.9745V12.9411H0.817305C0.6709 12.9411 0.670898 12.9411 0.670898 12.8016C0.670898 11.564 0.670898 10.3287 0.670898 9.09341C0.670898 8.97903 0.705213 8.95158 0.815017 8.95158C1.8673 8.95158 2.91959 8.95158 3.97417 8.95158H4.12057V8.83263C4.12057 7.8055 4.12057 6.7738 4.12057 5.74897C4.1264 4.92595 4.31387 4.11437 4.66959 3.37217C5.12916 2.38246 5.94651 1.60353 6.95717 1.1921C7.64827 0.905008 8.3913 0.764035 9.13953 0.778051C10.0019 0.791777 10.8644 0.830666 11.7268 0.860404C11.8869 0.860404 12.047 0.894717 12.2072 0.90158C12.2964 0.90158 12.3261 0.940469 12.3261 1.02968C12.3261 1.5421 12.3261 2.05452 12.3261 2.56465C12.3261 3.16857 12.3261 3.7725 12.3261 4.37642C12.3261 4.48165 12.2964 4.51367 12.1912 4.51138C11.5369 4.51138 10.8804 4.51138 10.2261 4.51138C9.92772 4.51814 9.63058 4.5526 9.33855 4.61433C9.08125 4.6617 8.84537 4.78881 8.66431 4.97766C8.48326 5.16652 8.3662 5.40755 8.32972 5.66661C8.28476 5.89271 8.26027 6.1224 8.25652 6.35289C8.25652 7.19014 8.25652 8.02969 8.25652 8.86923C8.25652 8.89439 8.25652 8.91955 8.25652 8.95615H12.0219C12.1797 8.95615 12.182 8.95616 12.1614 9.10714C12.0768 9.76596 11.9876 10.4248 11.9029 11.0813C11.8312 11.6319 11.7626 12.1824 11.697 12.733C11.6719 12.9434 11.6787 12.9434 11.4683 12.9434H8.26338V22.899C8.26338 22.979 8.26338 23.0591 8.26338 23.1392L4.11371 23.1369Z">
</path>
</svg>
<span class="usa-sr-only">NLM on Facebook</span>
</a>
<a href=https://www.youtube.com/user/NLMNIH class="ncbi-footer__social-icon ncbi-footer__social-icon--circled" target="_blank" rel="noreferrer noopener">
<svg width="21"
height="15"
viewBox="0 0 21 15"
fill="none"
xmlns="http://www.w3.org/2000/svg"
focusable="false"
aria-hidden="true">
<path d="M19.2561 1.47914C18.9016 1.15888 18.5699 0.957569 17.2271 0.834039C15.5503 0.678484 13.2787 0.655608 11.563 0.65332H9.43556C7.71987 0.65332 5.4483 0.678484 3.77151 0.834039C2.43098 0.957569 2.097 1.15888 1.74242 1.47914C0.813665 2.32097 0.619221 4.62685 0.598633 6.89384C0.598633 7.31781 0.598633 7.74101 0.598633 8.16345C0.626084 10.4121 0.827391 12.686 1.74242 13.521C2.097 13.8412 2.4287 14.0425 3.77151 14.1661C5.4483 14.3216 7.71987 14.3445 9.43556 14.3468H11.563C13.2787 14.3468 15.5503 14.3216 17.2271 14.1661C18.5676 14.0425 18.9016 13.8412 19.2561 13.521C20.1712 12.6929 20.3725 10.451 20.3999 8.22064C20.3999 7.74025 20.3999 7.25986 20.3999 6.77946C20.3725 4.54907 20.1689 2.30724 19.2561 1.47914ZM8.55942 10.5311V4.65201L13.5601 7.50005L8.55942 10.5311Z"
fill="white" />
</svg>
<span class="usa-sr-only">NLM on YouTube</span>
</a>
</div>
</div>
<address class="ncbi-footer__address ncbi-footer__column">
<p>
<a class="usa-link usa-link--external"
href="https://www.google.com/maps/place/8600+Rockville+Pike,+Bethesda,+MD+20894/%4038.9959508,
-77.101021,17z/data%3D!3m1!4b1!4m5!3m4!1s0x89b7c95e25765ddb%3A0x19156f88b27635b8!8m2!3d38.9959508!
4d-77.0988323"
rel="noopener noreferrer" target="_blank">National Library of Medicine
<br/> 8600 Rockville Pike<br/> Bethesda, MD 20894</a>
</p>
</address>
<ul class="usa-list usa-list--unstyled ncbi-footer__vertical-list ncbi-footer__column">
<li class="ncbi-footer__vertical-list-item">
<a href="https://www.nlm.nih.gov/web_policies.html" class="usa-link usa-link--alt ncbi-footer__link" >
Web Policies
</a>
</li>
<li class="ncbi-footer__vertical-list-item">
<a href="https://www.nih.gov/institutes-nih/nih-office-director/office-communications-public-liaison/freedom-information-act-office" class="usa-link usa-link--alt ncbi-footer__link" >
FOIA
</a>
</li>
<li class="ncbi-footer__vertical-list-item">
<a href="https://www.hhs.gov/vulnerability-disclosure-policy/index.html" class="usa-link usa-link--external usa-link--alt ncbi-footer__link" rel="noreferrer noopener" target='_blank' >
HHS Vulnerability Disclosure
</a>
</li>
</ul>
<ul class="usa-list usa-list--unstyled ncbi-footer__vertical-list ncbi-footer__column">
<li class="ncbi-footer__vertical-list-item">
<a href="https://support.nlm.nih.gov/" class="usa-link usa-link--alt ncbi-footer__link" >
Help
</a>
</li>
<li class="ncbi-footer__vertical-list-item">
<a href="https://www.nlm.nih.gov/accessibility.html" class="usa-link usa-link--alt ncbi-footer__link" >
Accessibility
</a>
</li>
<li class="ncbi-footer__vertical-list-item">
<a href="https://www.nlm.nih.gov/careers/careers.html" class="usa-link usa-link--alt ncbi-footer__link" >
Careers
</a>
</li>
</ul>
</div>
<div class="grid-row grid-col-12" data-testid="grid">
<ul class="ncbi-footer__bottom-links-list">
<li class="ncbi-footer__bottom-list-item">
<a href="https://www.nlm.nih.gov/" class="usa-link usa-link--alt ncbi-footer__link" >
NLM
</a>
</li>
<li class="ncbi-footer__bottom-list-item">
<a href="https://www.nih.gov/" class="usa-link usa-link--alt ncbi-footer__link" >
NIH
</a>
</li>
<li class="ncbi-footer__bottom-list-item">
<a href="https://www.hhs.gov/" class="usa-link usa-link--external usa-link--alt ncbi-footer__link" rel="noreferrer noopener" target='_blank' >
HHS
</a>
</li>
<li class="ncbi-footer__bottom-list-item">
<a href="https://www.usa.gov/" class="usa-link usa-link--external usa-link--alt ncbi-footer__link" rel="noreferrer noopener" target='_blank' >
USA.gov
</a>
</li>
</ul>
</div>
</div>
</footer>
<script type="text/javascript" src="https://cdn.ncbi.nlm.nih.gov/core/pinger/pinger.js"> </script>
<button class="back-to-top" data-ga-category="pagination" data-ga-action="back_to_top">
<label>Back to Top</label>
<img src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/img/arrow_upward.svg" alt="back to top icon" class="usa-icon usa-icon--size-3 order-0 usa-icon--white" />
</button>
<div id="icon-container" style="display: none;"></div>
<script type="application/javascript">
window.ncbi = window.ncbi || {};
window.ncbi.pmc = window.ncbi.pmc || {};
window.ncbi.pmc.options = {
logLevel: 'INFO',
staticEndpoint: 'https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/',
citeCookieName: 'pmc-cf',
};
</script>
<script type="module" crossorigin="" src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/base-Cp_Il6gk.js"></script>
<link href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/vendor-Co8Vdmw2.js" type="text/javascript" crossorigin="anonymous" rel="modulepreload" as="script" />
<script type="text/javascript" src="https://cdn.ncbi.nlm.nih.gov/core/jquery/jquery-3.6.0.min.js"> </script>
<script type="text/javascript">
jQuery.getScript("https://cdn.ncbi.nlm.nih.gov/core/alerts/alerts.js", function () {
galert(['div.nav_and_browser', 'div.header', '#universal_header', '.usa-banner', 'body > *:nth-child(1)'])
});
</script>
<script type="text/javascript">var exports = {};</script>
<script src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/CACHE/js/output.4e25b6297b38.js"></script>
<script type="module" crossorigin="" src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/article-BxyWTbsj.js"></script>
<link href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/vendor-Co8Vdmw2.js" type="text/javascript" crossorigin="anonymous" rel="modulepreload" as="script" />
<link href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/index-DXSA0fsx.js" type="text/javascript" crossorigin="anonymous" rel="modulepreload" as="script" />
<link href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/secure-cookie-Br6x5jtB.js" type="text/javascript" crossorigin="anonymous" rel="modulepreload" as="script" />
<script type="module" crossorigin="" src="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/math-CjjrG8hn.js"></script>
<link href="https://cdn.ncbi.nlm.nih.gov/pmc/pd-medc-pmc-cloudpmc-viewer/production/a2b04810/var/data/static/assets/vendor-Co8Vdmw2.js" type="text/javascript" crossorigin="anonymous" rel="modulepreload" as="script" />
</body>
</html>