TY - GEN
T1 - Distance Estimation on Moving Object using BLE Beacon
AU - Lam, Ching Hong
AU - She, James
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - The development of Internet of Things technology has connected the smart things to the Internet, enabling users to interact for different applications such as indoor positioning or location-based notification service. To improve the user experience, an accurate distance estimation is required to ensure the interaction can be delivered precisely. For general beacon-based application, the objects keep moving while they are interacting with the beacons. Therefore, their mobility needs to be considered for distance estimation. In this paper, comprehensive experiments are conducted to study the relationship between distance estimation accuracy and packet received rate from two angels, the beacon advertising interval and the object moving speed. Moreover, an improved distance estimation method using Kalman filter and support vector regression is proposed, which has archived at least 40% improvement comparing to current approaches. The proposed idea is also implemented in real-world application which archive less than 100μs computation time.
AB - The development of Internet of Things technology has connected the smart things to the Internet, enabling users to interact for different applications such as indoor positioning or location-based notification service. To improve the user experience, an accurate distance estimation is required to ensure the interaction can be delivered precisely. For general beacon-based application, the objects keep moving while they are interacting with the beacons. Therefore, their mobility needs to be considered for distance estimation. In this paper, comprehensive experiments are conducted to study the relationship between distance estimation accuracy and packet received rate from two angels, the beacon advertising interval and the object moving speed. Moreover, an improved distance estimation method using Kalman filter and support vector regression is proposed, which has archived at least 40% improvement comparing to current approaches. The proposed idea is also implemented in real-world application which archive less than 100μs computation time.
KW - Advertising Interval
KW - BLE Beacon
KW - Distance Estimation
KW - Internet of Things
KW - Moving Speed
KW - Packet Receiving Rate
UR - http://www.scopus.com/inward/record.url?scp=85077620888&partnerID=8YFLogxK
U2 - 10.1109/WiMOB.2019.8923185
DO - 10.1109/WiMOB.2019.8923185
M3 - Conference contribution
AN - SCOPUS:85077620888
T3 - International Conference on Wireless and Mobile Computing, Networking and Communications
BT - 2019 International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2019
PB - IEEE Computer Society
T2 - 15th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2019
Y2 - 21 October 2019 through 23 October 2019
ER -