FindingHuMo: Real-Time Tracking of Motion Trajectories from Anonymous Binary Sensing in Smart Environments

Abstract—In this paper we have proposed and designed FindingHuMo (Finding Human Motion), a real-time user tracking system for Smart Environments. FindingHuMo can perform device-free tracking of multiple (unknown and variable number of) users in the Hallway Environments, just from non-invasive and anonymous (not user specific) binary motion sensor data stream. The significance of our designed system are as follows: (a) fast tracking of individual targets from binary motion datastream from a static wireless sensor network in the infrastructure. This needs to resolve unreliable node sequences, system noise and path ambiguity; (b) Scaling for multi-user tracking where user motion trajectories may crossover with each other in all possible ways. This needs to resolve path ambiguity to isolate overlapping trajectories; FindingHumo applies the following techniques on the collected motion datastream: (i) a proposed motion data driven adaptive order Hidden Markov Model with Viterbi decoding ...

• Type: Journal
• Year: 2012
• Where: ICDCS
• Authors: Debraj De, Wen-Zhan Song, Mingsen Xu, Cheng-Liang Wang, Diane Cook, Xiaoming Huo
• Keywords: Distributed And Parallel Computing, ICDCS 2012, Real Time System, Wireless Sensor Network, Wireless Sensor Networks