Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 7, Issue 4, Pages 3160-3169Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.2965583
Keywords
Bayesian filter; Bluetooth low energy (BLE) beacon; iBeacons; Kalman filter (KF); nonparametric information (NI) filter; particle filter; proximity accuracy; proximity estimation
Categories
Funding
- Natural Sciences and Engineering Research Council of Canada
Ask authors/readers for more resources
The interconnectedness of all things is continuously expanding which has allowed every individual to increase their level of interaction with their surroundings. Internet of Things (IoT) devices are used in a plethora of context-aware application, such as proximity-based services (PBSs), and location-based services (LBSs). For these systems to perform, it is essential to have reliable hardware and predict a user's position in the area with high accuracy in order to differentiate between individuals in a small area. A variety of wireless solutions that utilize received signal strength indicators (RSSIs) have been proposed to provide PBS and LBS for indoor environments, though each solution presents its own drawbacks. In this article, Bluetooth low energy (BLE) beacons are examined in terms of their accuracy in proximity estimation. Specifically, a mobile application is developed along with three Bayesian filtering techniques to improve the BLE beacon proximity estimation accuracy. This includes a Kalman filter, a particle filter, and a nonparametric information (NI) filter. Since the RSSI is heavily influenced by the environment, experiments were conducted to examine the performance of beacons from three popular vendors in two different environments. The error is compared in terms of mean absolute error (MAE) and root mean squared error (RMSE). According to the experimental results, Bayesian filters can improve proximity estimation accuracy up to 30% in comparison with traditional filtering, when the beacon and the receiver are within 3 m.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available