A Survey of Internet of Things based Indoor Positioning Systems based on Bluetooth Low Energy Beacon

Abstract

The global positioning systems (GPS) and cellular systems face inherent limitations when it comes to enclosed environments like shopping malls, hospitals, warehouses, as they have significant shadowing effects that cause the signals to be distorted. There have been many studies on different technologies and techniques aiming to find the optimum approach to be used for indoor positioning systems (IPS). Among all the technologies adapted by researchers all around the world, Bluetooth Low Energy (BLE) beacons have been a prevalent choice for many, due to its deploying flexibility, low cost, low power consumption and ability to provide very advanced services to users. It is arduous to obtain RSSI values with great accuracy because the signals can be easily intervened by many factors like humidity, temperature, physical barriers, and interference from decoherent signals. In this paper, we presented a comparative analysis of different, fairly recent IPS that are based on BLE beacons by classifying the different proposed approaches in a structured and systematic manner and traversing the issues and challenges that exist with each technique. The accuracy of the results can be enhanced by using the most suitable positioning algorithm, the orientation of the beacon setup, and optimization methods used. A preliminary result from a case study using BLE beacons with K-Nearest Neighbours (KNN) based fingerprinting approach for indoor positioning estimation shows 86.67% accuracy.