A Consumer Product of Wi-Fi Tracker System using RSSI-based Distance for Indoor Crowd Monitoring

This study aims to design and develop Wi-Fi tracker system that utilizes RSSI-based distance parameters for crowd-monitoring applications in indoor settings. The consists of three main components, namely 1) an embedded node runs on Raspberry-pi Zero W, 2) a real-time localization algorithm, 3) server with online dashboard. scans collects relevant information from Wi-Fi-connected smartphones, such as MAC data, RSSI, timestamps, etc. These data are then transmitted the system, where algorithm passively determines location devices long is enabled. mentioned tablets, laptops, while used Non-Linear System Lavenberg–Marquart Unscented Kalman Filter (UKF). dashboard (web-based application) have functions, including displaying recording device results, setting parameters, visualizing analyzed data. hardware was designed minimum size portability, resulting consumer electronics product outlook. demonstration this conducted validate its functionality performance.