Systematic Review of Radio Wave Techniques for Indoor Positioning Systems

Abstract

Indoor human positioning has become crucial for applications such as health monitoring, security surveillance, human pose identification and rescue operations. However, achieving reliable indoor human positioning is challenging due to numerous constraints.This paper aims to compare and analyze radio waves techniques and approaches for indoor positioning,providing a comprehensive review for human detection, positioning and activity recognition. A systematic review of the scientific literature and datasets was conducted. Four digital libraries, ACM Library Digital, IEEE Xplore, ScienceDirect and Spring Link were searched to identify results that met the selection criteria. A data extraction process was performed on the selected articles and datasets. The Parsifal platform was utilized to extract relevant information. After completing the systematic review, It was identified 26 eligible articles and extracted 11 methods for radio wave detection. The overview of indoor positioning system with radio waves was introduced. The most frequently mentioned tools in the articles for the capture stage were Radar Sensors, Wireless Sensor, and Antennas. For the processing stage, DNN Techniques, Processing Algorithms followed by Filtering, Fingerprint, Trilateration, and other machine learning algorithms formed the majority.