TY - GEN
T1 - ALPS
T2 - 13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015
AU - Lazik, Patrick
AU - Rajagopal, Niranjini
AU - Shih, Oliver
AU - Sinopoli, Bruno
AU - Rowe, Anthony
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - The proliferation of Bluetooth Low-Energy (BLE) chipsets on mobile devices has lead to a wide variety of userinstallable tags and beacons designed for location-aware applications. In this paper, we present the Acoustic Location Processing System (ALPS), a platform that augments BLE transmitters with ultrasound in a manner that improves ranging accuracy and can help users configure indoor localization systems with minimal effort. A user places three or more beacons in an environment and then walks through a calibration sequence with their mobile device where they touch key points in the environment like the floor and the corners of the room. This process automatically computes the room geometry as well as the precise beacon locations without needing auxiliary measurements. Once configured, the system can track a user's location referenced to a map. The platform consists of time-synchronized ultrasonic transmitters that utilize the bandwidth just above the human hearing limit, where mobile devices are still sensitive and can detect ranging signals. To aid in the mapping process, the beacons perform inter-beacon ranging during setup. Each beacon includes a BLE radio that can identify and trigger the ultrasonic signals. By using differences in propagation characteristics between ultrasound and radio, the system can classify if beacons are within Line-Of-Sight (LOS) to the mobile phone. In cases where beacons are blocked, we show how the phone's inertial measurement sensors can be used to supplement localization data. We experimentally evaluate that our system can estimate three-dimensional beacon location with a Euclidean distance error of 16.1cm, and can generate maps with room measurements with a two-dimensional Euclidean distance error of 19.8cm. When tested in six different environments, we saw that the system can identify Non-Line-Of-Sight (NLOS) signals with over 80% accuracy and track a user's location to within less than 100cm.
AB - The proliferation of Bluetooth Low-Energy (BLE) chipsets on mobile devices has lead to a wide variety of userinstallable tags and beacons designed for location-aware applications. In this paper, we present the Acoustic Location Processing System (ALPS), a platform that augments BLE transmitters with ultrasound in a manner that improves ranging accuracy and can help users configure indoor localization systems with minimal effort. A user places three or more beacons in an environment and then walks through a calibration sequence with their mobile device where they touch key points in the environment like the floor and the corners of the room. This process automatically computes the room geometry as well as the precise beacon locations without needing auxiliary measurements. Once configured, the system can track a user's location referenced to a map. The platform consists of time-synchronized ultrasonic transmitters that utilize the bandwidth just above the human hearing limit, where mobile devices are still sensitive and can detect ranging signals. To aid in the mapping process, the beacons perform inter-beacon ranging during setup. Each beacon includes a BLE radio that can identify and trigger the ultrasonic signals. By using differences in propagation characteristics between ultrasound and radio, the system can classify if beacons are within Line-Of-Sight (LOS) to the mobile phone. In cases where beacons are blocked, we show how the phone's inertial measurement sensors can be used to supplement localization data. We experimentally evaluate that our system can estimate three-dimensional beacon location with a Euclidean distance error of 16.1cm, and can generate maps with room measurements with a two-dimensional Euclidean distance error of 19.8cm. When tested in six different environments, we saw that the system can identify Non-Line-Of-Sight (NLOS) signals with over 80% accuracy and track a user's location to within less than 100cm.
UR - https://www.scopus.com/pages/publications/84962875864
U2 - 10.1145/2809695.2809727
DO - 10.1145/2809695.2809727
M3 - Conference contribution
AN - SCOPUS:84962875864
T3 - SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
SP - 73
EP - 84
BT - SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
PB - Association for Computing Machinery, Inc
Y2 - 1 November 2015 through 4 November 2015
ER -