Indoor Localization Using Multi-Bluetooth Beacon Deployment in a Sparse Edge Computing Environment  

作　　者：Soheil Saghafi Yashar Kiarashi Amy D.Rodriguez Allan I.Levey Hyeokhyen Kwon Gari D.Clifford 

机构地区：[1]Department of Biomedical Informatics,School of Medicine,Emory University,Atlanta,Georgia,USA [2]Department of Neurology,School of Medicine,Emory University,Atlanta,Georgia,USA [3]Department of Biomedical Engineering,Emory University and Georgia Institute of Technology,Atlanta,Georgia,USA

出　　处：《Digital Twins and Applications》2025年第1期49-56,共8页数字孪生及应用(英文)

基　　金：supported by James M.Cox Foundation,National Institute on Deafness and Other Communication Disorders(grant no.1R21DC021029-01A1);Cox Enterprises Inc.,National Institute of Child Health and Human Development(grant no.AWD-006196-G1);Thrasher Research Fund Early Career Award Program.

摘　　要：Bluetooth low energy(BLE)-based indoor localization has been extensively researched due to its cost-effectiveness,low power consumption,and ubiquity.Despite these advantages,the variability of received signal strength indicator(RSSI)measurements,influenced by physical obstacles,human presence,and electronic interference,poses a significant challenge to accurate localization.In this work,we present an optimised method to enhance indoor localization accuracy by utilising multiple BLE beacons in a radio frequency(RF)-dense modern building environment.Through a proof-of-concept study,we demonstrate that using three BLE beacons reduces localization error from a worst-case distance of 9.09-2.94 m,whereas additional beacons offer minimal incremental benefit in such settings.Furthermore,our framework for BLE-based localization,implemented on an edge network of Raspberry Pies,has been released under an open-source license,enabling broader application and further research.

关 键 词：ambient health monitoring bluetooth low energy cloud computing edge computing indoor localization 

分 类 号：TN9[电子电信—信息与通信工程]