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INTERNATIONAL JOURNAL OF RECENT TRENDS IN TECHNOLOGY AND ENGINEERING (IJRTTE)

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Smart Multi-Sensor Fusion Framework for Robust Indoor Localization

Shikha Tewari
Assistant Professor, Graphic Era Hill University India.
S Suresh Kumar
Assistant Professor, Artificial Intelligence & Data Science, J.J.College of Engineering and Technology, India.

Keywords: Indoor Localization, Sensor Fusion, UWB, IMU, Wi-Fi Positioning, Real-Time Tracking, Smart Environments, Adaptive Localization, Multi-Sensor Integration, Indoor Navigation

Abstract

Inaccurate and unreliable indoor positioning remains a persistent challenge in environments where GPS signals are unavailable or degraded. Traditional localization systems relying on a single sensor modality such as Wi-Fi, UWB, or IMU often suffer from signal noise, non-line-of-sight (NLOS) errors, and limited adaptability in dynamic environments. This paper proposes a Smart Multi-Sensor Fusion Framework that integrates heterogeneous sensor data using intelligent fusion strategies to achieve robust, real-time, and high-precision indoor localization. The proposed framework dynamically adjusts sensor contributions based on environmental conditions, signal quality, and motion context, thereby overcoming the limitations of individual sensors and delivering enhanced localization performance. By leveraging modular architecture, the system is scalable across a wide range of platforms including smartphones, wearables, and autonomous robots. Extensive experimental comparisons show the superiority of the framework in terms of accuracy and reliability of localization over the traditional single-sensor and static fusion methods. This paper fills a crucial gap in the state of research and offers a robust and flexible solution applicable to challenging indoor contexts, like smart buildings, industrial facilities and healthcare systems.
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Published
2022-09-28
Pages
1-10
Issue
Vol. 1 No. 3 (2022): IJRTTE - 01 - 03
Section
Articles

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