Indoor Localization Techniques Within a Home Monitoring Platform

TL;DR

This paper presents various Bluetooth-based indoor localization techniques for real-time monitoring of older adults, evaluating their accuracy in different home environments within a cost-effective, configurable system.

Contribution

It introduces a set of server-side algorithms for indoor localization using Bluetooth signal strength, evaluated in real home settings with different building characteristics.

Findings

Localization accuracy improved with proposed algorithms

Kalman filtering and neural networks outperform heuristics

Techniques are effective across different building types

Abstract

This paper details a number of indoor localization techniques developed for real-time monitoring of older adults. These were developed within the framework of the i-Light research project that was funded by the European Union. The project targeted the development and initial evaluation of a configurable and cost-effective cyber-physical system for monitoring the safety of older adults who are living in their own homes. Localization hardware consists of a number of custom-developed devices that replace existing luminaires. In addition to lighting capabilities, they measure the strength of a Bluetooth Low Energy signal emitted by a wearable device on the user. Readings are recorded in real time and sent to a software server for analysis. We present a comparative evaluation of the accuracy achieved by several server-side algorithms, including Kalman filtering, a look-back heuristic as well as a neural network-based approach. It is known that approaches based on measuring signal strength are sensitive to the placement of walls, construction materials used, the presence of doors as well as existing furniture. As such, we evaluate the proposed approaches in two separate locations having distinct building characteristics. We show that the proposed techniques improve the accuracy of localization. As the final step, we evaluate our results against comparable existing approaches.