Seamless Mobile Indoor Navigation With VLP-PDR
This study unveils a mobile app-based indoor positioning system (IPS) tailored for seamless museum navigation. Leveraging smartphone inertial measurement unit (IMU) sensors, it incorporates a pedestrian dead reckoning (PDR) algorithm and a visible light positioning (VLP) beacon-based angle of arriva...
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| Veröffentlicht in: | IEEE sensors journal 2024-04, Vol.24 (7), p.11504-11514 |
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| container_title | IEEE sensors journal |
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| creator | Alcazar-Fernandez, Aitor De-La-Llana-Calvo, Alvaro Lazaro-Galilea, Jose Luis Perez-Navarro, Antoni Gil-Vera, Ruben Gardel-Vicente, Alfredo |
| description | This study unveils a mobile app-based indoor positioning system (IPS) tailored for seamless museum navigation. Leveraging smartphone inertial measurement unit (IMU) sensors, it incorporates a pedestrian dead reckoning (PDR) algorithm and a visible light positioning (VLP) beacon-based angle of arrival (AoA) algorithm for precise user positioning relative to smart light sources. In standalone mode, the VLP AoA-based algorithm demonstrates reliability with a mean error of 10.64 cm, while the PDR algorithm, operating independently, exhibits mean error of 3 m influenced by environmental factors. Integration of both algorithms proves crucial in mitigating cumulative errors. By updating PDR deviations with the precision provided by the VLP AoA-based solution, the entire system minimizes its mean error to 0.85 m. The user-friendly interface not only enriches visitor experiences with contextual information but also enables intuitive navigation without continuous internet connectivity. This innovative solution caters to the critical demand for precise indoor navigation, particularly in museum environments, fostering increased user acceptance and utilization. |
| doi_str_mv | 10.1109/JSEN.2024.3368169 |
| format | Article |
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Leveraging smartphone inertial measurement unit (IMU) sensors, it incorporates a pedestrian dead reckoning (PDR) algorithm and a visible light positioning (VLP) beacon-based angle of arrival (AoA) algorithm for precise user positioning relative to smart light sources. In standalone mode, the VLP AoA-based algorithm demonstrates reliability with a mean error of 10.64 cm, while the PDR algorithm, operating independently, exhibits mean error of 3 m influenced by environmental factors. Integration of both algorithms proves crucial in mitigating cumulative errors. By updating PDR deviations with the precision provided by the VLP AoA-based solution, the entire system minimizes its mean error to 0.85 m. The user-friendly interface not only enriches visitor experiences with contextual information but also enables intuitive navigation without continuous internet connectivity. This innovative solution caters to the critical demand for precise indoor navigation, particularly in museum environments, fostering increased user acceptance and utilization.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2024.3368169</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Android ; Angle of arrival ; angle of arrival (AoA) ; Applications programs ; Cameras ; Dead reckoning ; Errors ; Indoor navigation ; inertial measurement unit (IMU) ; Inertial navigation ; Inertial platforms ; Inertial sensing devices ; Light sources ; Mobile applications ; Mobile computing ; Mobile handsets ; Museums ; Receivers ; Sensor phenomena and characterization ; Sensors ; Signal processing algorithms ; smartphone ; Smartphones ; visible light positioning (VLP)</subject><ispartof>IEEE sensors journal, 2024-04, Vol.24 (7), p.11504-11514</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c289t-ebd53663ab5e26db66897c82eaa57e9d063357ec010a4294d173fc8c69cd8f883</cites><orcidid>0000-0002-5579-6718 ; 0000-0001-5048-7134 ; 0000-0002-1297-8343 ; 0000-0002-8889-0452 ; 0000-0001-7887-4689 ; 0000-0002-7037-0635</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10452268$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids></links><search><creatorcontrib>Alcazar-Fernandez, Aitor</creatorcontrib><creatorcontrib>De-La-Llana-Calvo, Alvaro</creatorcontrib><creatorcontrib>Lazaro-Galilea, Jose Luis</creatorcontrib><creatorcontrib>Perez-Navarro, Antoni</creatorcontrib><creatorcontrib>Gil-Vera, Ruben</creatorcontrib><creatorcontrib>Gardel-Vicente, Alfredo</creatorcontrib><title>Seamless Mobile Indoor Navigation With VLP-PDR</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description>This study unveils a mobile app-based indoor positioning system (IPS) tailored for seamless museum navigation. Leveraging smartphone inertial measurement unit (IMU) sensors, it incorporates a pedestrian dead reckoning (PDR) algorithm and a visible light positioning (VLP) beacon-based angle of arrival (AoA) algorithm for precise user positioning relative to smart light sources. In standalone mode, the VLP AoA-based algorithm demonstrates reliability with a mean error of 10.64 cm, while the PDR algorithm, operating independently, exhibits mean error of 3 m influenced by environmental factors. Integration of both algorithms proves crucial in mitigating cumulative errors. By updating PDR deviations with the precision provided by the VLP AoA-based solution, the entire system minimizes its mean error to 0.85 m. The user-friendly interface not only enriches visitor experiences with contextual information but also enables intuitive navigation without continuous internet connectivity. This innovative solution caters to the critical demand for precise indoor navigation, particularly in museum environments, fostering increased user acceptance and utilization.</description><subject>Algorithms</subject><subject>Android</subject><subject>Angle of arrival</subject><subject>angle of arrival (AoA)</subject><subject>Applications programs</subject><subject>Cameras</subject><subject>Dead reckoning</subject><subject>Errors</subject><subject>Indoor navigation</subject><subject>inertial measurement unit (IMU)</subject><subject>Inertial navigation</subject><subject>Inertial platforms</subject><subject>Inertial sensing devices</subject><subject>Light sources</subject><subject>Mobile applications</subject><subject>Mobile computing</subject><subject>Mobile handsets</subject><subject>Museums</subject><subject>Receivers</subject><subject>Sensor phenomena and characterization</subject><subject>Sensors</subject><subject>Signal processing algorithms</subject><subject>smartphone</subject><subject>Smartphones</subject><subject>visible light positioning (VLP)</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNpNkMtOwzAQRS0EEqXwAUgsIrFOsD3xa4lKgaJQKsprZzmOA6nautgpEn9PonbBau7i3DvSQeic4IwQrK4e5uNpRjHNMwAuCVcHaEAYkykRuTzsM-A0B_FxjE5iXGBMlGBigLK5M6ulizF59GWzdMlkXXkfkqn5aT5N2_h18t60X8lbMUtnN8-n6Kg2y-jO9neIXm_HL6P7tHi6m4yui9RSqdrUlRUDzsGUzFFelZxLJaykzhgmnKowB-iCxQSbnKq8IgJqKy1XtpK1lDBEl7vdTfDfWxdbvfDbsO5easBAQCkseUeRHWWDjzG4Wm9CszLhVxOsey2616J7LXqvpetc7DqNc-4fnzNKuYQ_C8hcRg</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Alcazar-Fernandez, Aitor</creator><creator>De-La-Llana-Calvo, Alvaro</creator><creator>Lazaro-Galilea, Jose Luis</creator><creator>Perez-Navarro, Antoni</creator><creator>Gil-Vera, Ruben</creator><creator>Gardel-Vicente, Alfredo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-5579-6718</orcidid><orcidid>https://orcid.org/0000-0001-5048-7134</orcidid><orcidid>https://orcid.org/0000-0002-1297-8343</orcidid><orcidid>https://orcid.org/0000-0002-8889-0452</orcidid><orcidid>https://orcid.org/0000-0001-7887-4689</orcidid><orcidid>https://orcid.org/0000-0002-7037-0635</orcidid></search><sort><creationdate>20240401</creationdate><title>Seamless Mobile Indoor Navigation With VLP-PDR</title><author>Alcazar-Fernandez, Aitor ; De-La-Llana-Calvo, Alvaro ; Lazaro-Galilea, Jose Luis ; Perez-Navarro, Antoni ; Gil-Vera, Ruben ; Gardel-Vicente, Alfredo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c289t-ebd53663ab5e26db66897c82eaa57e9d063357ec010a4294d173fc8c69cd8f883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Android</topic><topic>Angle of arrival</topic><topic>angle of arrival (AoA)</topic><topic>Applications programs</topic><topic>Cameras</topic><topic>Dead reckoning</topic><topic>Errors</topic><topic>Indoor navigation</topic><topic>inertial measurement unit (IMU)</topic><topic>Inertial navigation</topic><topic>Inertial platforms</topic><topic>Inertial sensing devices</topic><topic>Light sources</topic><topic>Mobile applications</topic><topic>Mobile computing</topic><topic>Mobile handsets</topic><topic>Museums</topic><topic>Receivers</topic><topic>Sensor phenomena and characterization</topic><topic>Sensors</topic><topic>Signal processing algorithms</topic><topic>smartphone</topic><topic>Smartphones</topic><topic>visible light positioning (VLP)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alcazar-Fernandez, Aitor</creatorcontrib><creatorcontrib>De-La-Llana-Calvo, Alvaro</creatorcontrib><creatorcontrib>Lazaro-Galilea, Jose Luis</creatorcontrib><creatorcontrib>Perez-Navarro, Antoni</creatorcontrib><creatorcontrib>Gil-Vera, Ruben</creatorcontrib><creatorcontrib>Gardel-Vicente, Alfredo</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE sensors journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alcazar-Fernandez, Aitor</au><au>De-La-Llana-Calvo, Alvaro</au><au>Lazaro-Galilea, Jose Luis</au><au>Perez-Navarro, Antoni</au><au>Gil-Vera, Ruben</au><au>Gardel-Vicente, Alfredo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Seamless Mobile Indoor Navigation With VLP-PDR</atitle><jtitle>IEEE sensors journal</jtitle><stitle>JSEN</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>24</volume><issue>7</issue><spage>11504</spage><epage>11514</epage><pages>11504-11514</pages><issn>1530-437X</issn><eissn>1558-1748</eissn><coden>ISJEAZ</coden><abstract>This study unveils a mobile app-based indoor positioning system (IPS) tailored for seamless museum navigation. Leveraging smartphone inertial measurement unit (IMU) sensors, it incorporates a pedestrian dead reckoning (PDR) algorithm and a visible light positioning (VLP) beacon-based angle of arrival (AoA) algorithm for precise user positioning relative to smart light sources. In standalone mode, the VLP AoA-based algorithm demonstrates reliability with a mean error of 10.64 cm, while the PDR algorithm, operating independently, exhibits mean error of 3 m influenced by environmental factors. Integration of both algorithms proves crucial in mitigating cumulative errors. By updating PDR deviations with the precision provided by the VLP AoA-based solution, the entire system minimizes its mean error to 0.85 m. The user-friendly interface not only enriches visitor experiences with contextual information but also enables intuitive navigation without continuous internet connectivity. 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| subjects | Algorithms Android Angle of arrival angle of arrival (AoA) Applications programs Cameras Dead reckoning Errors Indoor navigation inertial measurement unit (IMU) Inertial navigation Inertial platforms Inertial sensing devices Light sources Mobile applications Mobile computing Mobile handsets Museums Receivers Sensor phenomena and characterization Sensors Signal processing algorithms smartphone Smartphones visible light positioning (VLP) |
| title | Seamless Mobile Indoor Navigation With VLP-PDR |
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