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A Framework for Real-Time Localization in Constrained Devices Connected to the IoT
The primary objective of this work is to enhance the spatial intelligence of connected devices, which is becoming increasingly vital in various applications, including asset tracking, indoor navigation, and context-aware services. In an ever-expanding world of the Internet of Things, the ability to...
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creator | Nnaemeka, Asogwa Emmanuel Crisphine Macharia, Ngari Bajpai, Ambar Telagam, Nagarjuna |
description | The primary objective of this work is to enhance the spatial intelligence of connected devices, which is becoming increasingly vital in various applications, including asset tracking, indoor navigation, and context-aware services. In an ever-expanding world of the Internet of Things, the ability to self-localize and determine the location of other nodes has significant implications for automation, security, and resource optimization. The proposed localization framework enables accurate and efficient location awareness in mobile devices and connected nodes. This can address the need for location awareness in such nodes. The presented technique achieves a real-time localization accuracy of 99% in real-time localization with an average system response time of 3 seconds. |
doi_str_mv | 10.1109/CONECCT62155.2024.10677241 |
format | conference_proceeding |
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The presented technique achieves a real-time localization accuracy of 99% in real-time localization with an average system response time of 3 seconds.</description><subject>Accuracy</subject><subject>ESP32</subject><subject>indoor localization</subject><subject>Internet of Things</subject><subject>Internet of Things (IoT)</subject><subject>KNN</subject><subject>Location awareness</subject><subject>location fingerprinting</subject><subject>Mobile handsets</subject><subject>Real-time systems</subject><subject>Robot sensing systems</subject><subject>Scalability</subject><subject>Wi-Fi</subject><issn>2766-2101</issn><isbn>9798350385922</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kM1Kw0AURkdBsNS8gYvBfeKdO5m_ZYmtFoqFEtdlktzB0TYjSVD06a2oqwNncfj4GLsRUAgB7rbaPi6rqtYolCoQsCwEaGOwFGcsc8ZZqUBa5RDP2QyN1jkKEJcsG8cXAJAI0lmcsd2CrwZ_pI80vPKQBr4jf8jreCS-Sa0_xC8_xdTz2PMq9eM0-NhTx-_oPbY0_rie2ulkpsSnZ-LrVF-xi-API2V_nLOn1bKuHvLN9n5dLTZ5PE2dcuUaB74jtKZstVGNNaozTRdc0BYaLC15gaUKnTSobIuagCAEEdBZjY2cs-vfbiSi_dsQj3743P_fIL8B1O9R2A</recordid><startdate>20240712</startdate><enddate>20240712</enddate><creator>Nnaemeka, Asogwa Emmanuel</creator><creator>Crisphine Macharia, Ngari</creator><creator>Bajpai, Ambar</creator><creator>Telagam, Nagarjuna</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20240712</creationdate><title>A Framework for Real-Time Localization in Constrained Devices Connected to the IoT</title><author>Nnaemeka, Asogwa Emmanuel ; Crisphine Macharia, Ngari ; Bajpai, Ambar ; Telagam, Nagarjuna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i106t-59b90ade2874c675b875d7bdf9f680b248ea1245fd37258c26e0e0ff1f29862b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>ESP32</topic><topic>indoor localization</topic><topic>Internet of Things</topic><topic>Internet of Things (IoT)</topic><topic>KNN</topic><topic>Location awareness</topic><topic>location fingerprinting</topic><topic>Mobile handsets</topic><topic>Real-time systems</topic><topic>Robot sensing systems</topic><topic>Scalability</topic><topic>Wi-Fi</topic><toplevel>online_resources</toplevel><creatorcontrib>Nnaemeka, Asogwa Emmanuel</creatorcontrib><creatorcontrib>Crisphine Macharia, Ngari</creatorcontrib><creatorcontrib>Bajpai, Ambar</creatorcontrib><creatorcontrib>Telagam, Nagarjuna</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Nnaemeka, Asogwa Emmanuel</au><au>Crisphine Macharia, Ngari</au><au>Bajpai, Ambar</au><au>Telagam, Nagarjuna</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Framework for Real-Time Localization in Constrained Devices Connected to the IoT</atitle><btitle>2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)</btitle><stitle>CONECCT</stitle><date>2024-07-12</date><risdate>2024</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><eissn>2766-2101</eissn><eisbn>9798350385922</eisbn><abstract>The primary objective of this work is to enhance the spatial intelligence of connected devices, which is becoming increasingly vital in various applications, including asset tracking, indoor navigation, and context-aware services. In an ever-expanding world of the Internet of Things, the ability to self-localize and determine the location of other nodes has significant implications for automation, security, and resource optimization. The proposed localization framework enables accurate and efficient location awareness in mobile devices and connected nodes. This can address the need for location awareness in such nodes. The presented technique achieves a real-time localization accuracy of 99% in real-time localization with an average system response time of 3 seconds.</abstract><pub>IEEE</pub><doi>10.1109/CONECCT62155.2024.10677241</doi><tpages>5</tpages></addata></record> |
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ispartof | 2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2024, p.1-5 |
issn | 2766-2101 |
language | eng |
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source | IEEE Xplore All Conference Series |
subjects | Accuracy ESP32 indoor localization Internet of Things Internet of Things (IoT) KNN Location awareness location fingerprinting Mobile handsets Real-time systems Robot sensing systems Scalability Wi-Fi |
title | A Framework for Real-Time Localization in Constrained Devices Connected to the IoT |
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