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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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Main Authors: Nnaemeka, Asogwa Emmanuel, Crisphine Macharia, Ngari, Bajpai, Ambar, Telagam, Nagarjuna
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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
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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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