TY - GEN
T1 - BLoc
T2 - 14th International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2018
AU - Ayyalasomayajula, Roshan
AU - Vasisht, Deepak
AU - Bharadia, Dinesh
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - Bluetooth Low Energy (BLE) tags have become very prevalent over the last decade for tracking applications in homes as well as businesses. These tags are used to track objects, navigate people, and deliver contextual advertisements. However, in spite of the wide interest in tracking BLE tags, the primary methods of tracking them are based on signal strength (RSSI) measurements. Past work has shown that such methods are inaccurate, and prone to multipath and dynamic environments. As a result, localization using Wi-Fi has moved to Channel State Information (CSI, includes both signal strength and signal phase) based localization methods. In this paper, we seek to investigate what are the challenges that prevent BLE from adopting CSI based localization methods. We identify fundamental differences at the PHY layer between BLE and Wi-Fi, that make it challenging to extend CSI based localization to BLE. We present our system, BLoc, that incorporates novel, BLE-compatible algorithms to overcome these challenges and enable an accurate, multipath-resistant localization system. Our empirical evaluation shows that BLoc can achieve a localization accuracy of 86 cm with BLE tags, a 3X improvement over a state-of-the-art baseline.
AB - Bluetooth Low Energy (BLE) tags have become very prevalent over the last decade for tracking applications in homes as well as businesses. These tags are used to track objects, navigate people, and deliver contextual advertisements. However, in spite of the wide interest in tracking BLE tags, the primary methods of tracking them are based on signal strength (RSSI) measurements. Past work has shown that such methods are inaccurate, and prone to multipath and dynamic environments. As a result, localization using Wi-Fi has moved to Channel State Information (CSI, includes both signal strength and signal phase) based localization methods. In this paper, we seek to investigate what are the challenges that prevent BLE from adopting CSI based localization methods. We identify fundamental differences at the PHY layer between BLE and Wi-Fi, that make it challenging to extend CSI based localization to BLE. We present our system, BLoc, that incorporates novel, BLE-compatible algorithms to overcome these challenges and enable an accurate, multipath-resistant localization system. Our empirical evaluation shows that BLoc can achieve a localization accuracy of 86 cm with BLE tags, a 3X improvement over a state-of-the-art baseline.
KW - Bluetooth Low Energy
KW - Indoor Localization
KW - RF-based indoor positioning
UR - http://www.scopus.com/inward/record.url?scp=85060373642&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060373642&partnerID=8YFLogxK
U2 - 10.1145/3281411.3281428
DO - 10.1145/3281411.3281428
M3 - Conference contribution
AN - SCOPUS:85060373642
T3 - CoNEXT 2018 - Proceedings of the 14th International Conference on Emerging Networking EXperiments and Technologies
SP - 126
EP - 138
BT - CoNEXT 2018 - Proceedings of the 14th International Conference on Emerging Networking EXperiments and Technologies
PB - Association for Computing Machinery
Y2 - 4 December 2018 through 7 December 2018
ER -