The Global Positioning System (GPS) is widely used in navigation purposes while Indoor Positioning System (IPS) can be considered like a GPS for indoor environments. IPS is focused on indoor tracking as GPS is only good for outdoor settings. IPS is needed by industries organization to track events happening as the indoor environment activities are expanding especially on working conditions. A company needs guards to protect the people and objects from damages. The guard’s performance is the key factor to secure the safety. An IPS can help to ensure the guards performance in an organized method to avoid any kind of accidents issues. As the IoT based Indoor Guard Touring System (GTS) help to give guards on duty information through the Bluetooth Low Energy beacons and handheld device, the management level can track the real-time condition of the security team. The received signal strength indicator (RSSI) on BLE beacons is used as the method to collect position data. This RSSI based trilateration method is studied and the accuracy was not at maximum. Meanwhile, Machine Learning approach was introduced to train from the data and giving predictions on the position information. The data obtained from the previous research are trained to observe any significant improvement. This application is showed to have a better accuracy from the estimation done previously using trilateration method.

Rozeha A. Rashid

Department of Communication Engineering
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
Johor Bahru, Malaysia.
rozeha@fke.utm.my

Keywords—Indoor Positioning System, BLE beacon, Node-RED

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