@inproceedings{36d49294ff494e49955deface9d05b36,
title = "MobileRF: A robust device-free tracking system based on ahybrid neural network HMM classifier",
abstract = "We present a device-free indoor tracking system that uses received signal strength (RSS) from radio frequency (RF) transceivers to estimate the location of a person. While many RSS-based tracking systems use a body-worn device or tag, this approach requires no such tag. The approach is based on the key principle that RF signals between wall-mounted transceivers reflect and absorb differently depending on a person's movement within their home. A hierarchical neural network hidden Markov model (NN-HMM) classifier estimates both movement patterns and stand vs. walk conditions to perform tracking accurately. The algorithm and features used are specifically robust to changes in RSS mean shifts in the environment over time allowing for greater than 90% region level classification accuracy over an extended testing period. In addition to tracking, the system also estimates the number of people in different regions. It is currently being developed to support independent living and long-term monitoring of seniors.",
keywords = "Device-free passive localization, Health care, Indoor localization, Indoor tracking, Machine learning, Mobility, Neural network, Tag-free tracking",
author = "Paul, {Anindya S.} and Wan, {Eric A.} and Fatema Adenwala and Erich Schafermeyer and Nick Preiser and Jeffrey Kaye and Jacobs, {Peter G.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 by the Association for Computing Machinery, Inc. (ACM).; 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 ; Conference date: 13-09-2014 Through 17-09-2014",
year = "2014",
doi = "10.1145/2632048.2632097",
language = "English (US)",
series = "UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing",
publisher = "Association for Computing Machinery, Inc",
pages = "159--170",
booktitle = "UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing",
}