We are delighted to announce that our research paper, “Hybrid Learning for Mobile Ad-Hoc Distancing/Positioning Using Bluetooth Low Energy,” has been published in the IEEE Internet of Things Journal!

A heartfelt thank you goes out to my co-authors: Yik Him Ho, Caiqi Zhang, Yerkezhan Sartayeva, and Henry C.B. Chan. Working alongside these brilliant minds has been an enlightening journey.

Brief Overview of the Paper:

The rise of Bluetooth Low Energy (BLE)-enabled smartphones has sparked considerable interest in investigating BLE-based distancing/positioning methods, especially for social distancing applications. Our paper introduces a novel hybrid learning method to support mobile ad-hoc distancing/positioning using BLE-enabled smartphones. We explore a blend of unsupervised learning, supervised learning, and genetic algorithms to enhance distance estimation accuracy.

You can access the full paper at this link. We hope that our work can provide valuable insights to researchers and professionals in the field of IoT.