Improving Accuracy and Reliability of Bluetooth Low-Energy-Based Localization Systems Using Proximity Sensors

Abstract

One of the functionalities which are desired in Ambient and Assisted Living systems is accurate user localization at their living place. One of the best-suited solutions for this purpose from the cost and energy efficiency points of view are Bluetooth Low Energy (BLE)-based localization systems. Unfortunately, their localization accuracy is typically around several meters and might not be sufficient for detection of abnormal situations in elderly persons behavior. In this paper, a concept of a hybrid positioning system combining typical BLE-based infrastructure and proximity sensors is presented. The proximity sensors act a supporting role by additionally covering vital places, where higher localization accuracy is needed. The results from both parts are fused using two types of hybrid algorithms. The paper contains results of simulation and experimental studies. During the experiment, an exemplary proximity sensor VL53L1X has been tested and its basic properties modeled for use in the proposed algorithms. The results of the study have shown that employing proximity sensors can significantly improve localization accuracy in places of interest.

Keywords

• localization
• hybrid localization
• bluetooth low energy
• extended kalman filter
• internet of things
• proximity sensors