Indoor location based tracking using Euclidean distance estimation (LTS-ED)

Abstract

To provide location-based services like indoor navigation systems or indoor crowd monitoring systems in an indoor environment, indoor location tracking systems are required. The implementation of an indoor location tracking system employing Wi-Fi signal strength will be the main topic of this study. However, there are several methods for tracking an indoor location, including fingerprinting, triangulation, and trilateration. The proposed system was created using a fingerprinting technique. The server, which is based on Java, and the client, which is based on Android, make up the system's two primary parts. Regarding Wi-Fi RSSI scanning, the client's application oversees removing weak received signal strength (RSSI), more specifically RSSI lower than −85dBm, while the server provides the location ID with the highest likelihood of matching based on offline training data kept in a database. The software algorithm powered by MySQL will be the only foundation for the indoor location monitoring system. The findings demonstrate that smaller-area location tracking provides more accuracy than larger-area tracking.