TY - GEN
T1 - Smart watch RSSI localization and refinement for behavioral classification using laser-SLAM for mapping and fingerprinting
AU - Carlson, Jay D.
AU - Mittek, Mateusz
AU - Parkison, Steven A.
AU - Sathler, Pedro
AU - Bayne, David
AU - Psota, Eric T.
AU - Pérez, Lance C.
AU - Bonasera, Stephen J.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - As a first step toward building a smart home behavioral monitoring system capable of classifying a wide variety of human behavior, a wireless sensor network (WSN) system is presented for RSSI localization. The low-cost, non-intrusive system uses a smart watch worn by the user to broadcast data to the WSN, where the strength of the radio signal is evaluated at each WSN node to localize the user. A method is presented that uses simultaneous localization and mapping (SLAM) for system calibration, providing automated fingerprinting associating the radio signal strength patterns to the user's location within the living space. To improve the accuracy of localization, a novel refinement technique is introduced that takes into account typical movement patterns of people within their homes. Experimental results demonstrate that the system is capable of providing accurate localization results in a typical living space.
AB - As a first step toward building a smart home behavioral monitoring system capable of classifying a wide variety of human behavior, a wireless sensor network (WSN) system is presented for RSSI localization. The low-cost, non-intrusive system uses a smart watch worn by the user to broadcast data to the WSN, where the strength of the radio signal is evaluated at each WSN node to localize the user. A method is presented that uses simultaneous localization and mapping (SLAM) for system calibration, providing automated fingerprinting associating the radio signal strength patterns to the user's location within the living space. To improve the accuracy of localization, a novel refinement technique is introduced that takes into account typical movement patterns of people within their homes. Experimental results demonstrate that the system is capable of providing accurate localization results in a typical living space.
UR - http://www.scopus.com/inward/record.url?scp=84929501086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84929501086&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2014.6944048
DO - 10.1109/EMBC.2014.6944048
M3 - Conference contribution
C2 - 25570416
AN - SCOPUS:84929501086
T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
SP - 2173
EP - 2176
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Y2 - 26 August 2014 through 30 August 2014
ER -