Crowd Identification On RSSI-WIFI Based Indoor Position Tracking System
J. E. Yahya (a), N. S. Aminah (a*)

a) Instrumentation and Computational Research Group, Institut Teknologi Bandung.
Ganesha 10, Bandung 40132, Indonesia.
*nina[at]itb.ac.id

Abstract

Corona Virus Disease (COVID-19) is a disease that spreads very rapidly, especially in Indonesia. In terms of mortality rate due to COVID-19, Indonesia ranks third in Asia in terms of positive COVID-19 cases. Therefore, we needed technology that can help reducing the spread of COVID-19 by minimizing contact between individuals. In this study, we used the Received Signal Strength Indicator (RSSI) from a WiFi router. This method utilizes the existing infrastructure, namely router devices that have been
installed in various places in the building. We divided the research area into 96 points. We obtained RSSI values from 17 routers for each position and put them into the database. The real-time RSSI value will be compared with the RSSI value in the database. The webpage can track and display the position for up to 5 users along with their location information. In identifying the crowd, the distance parameter is used to determine the physical identity of the user.

Keywords: Tracking system, RSSI, Wifi

Topic: COMPUTATIONAL SCIENCES