Publications

論文誌 (国際) Efficient adaptive beacon deployment optimization for indoor crowd monitoring applications

Yang Zhen (Tokyo Institute of Technology), Masato Sugasaki (Tokyo Institute of Technology), Yoshihiro Kawahara (The University of Tokyo), Kota Tsubouchi, Matthew Ishige (The University of Tokyo), Masamichi Shimosaka (Tokyo Institute of Technology)

The Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)

2023.2.1

The indoor crowd density monitoring system using BLE beacons is one of the effective ways to prevent the overcrowded indoor situation during the pandemic. The indoor crowd density monitoring system consists of a mobile application at the user’s side and the beacon sensor network as the infrastructure. Since the performance of crowd density monitoring highly depends on how BLE beacons are placed, BLE beacon placement optimization is the fundamental research work. This research proposes a beacon deployment method EABeD to incrementally place the beacons adaptively to the latest signal propagation status. Also, EABeD reduces most walking and measurement labor costs by applying Bayesian optimization and the walking distance optimization algorithm.

Paper : Efficient adaptive beacon deployment optimization for indoor crowd monitoring applications 新しいタブまたはウィンドウで開く (外部サイト)