@article{
 title = {Evaluation of realtime people tracking for indoor environments using ubiquitous motion sensors and limited wireless network infrastructure},
 type = {article},
 year = {2012},
 identifiers = {[object Object]},
 keywords = {evaluation,sensors,smart-home,system,tracking},
 volume = {9},
 websites = {http://dx.doi.org/10.1016/j.pmcj.2012.03.007},
 month = {4},
 id = {42fbaf07-7c00-32f8-a51d-719425ab59cb},
 created = {2018-07-12T21:31:49.297Z},
 file_attached = {false},
 profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},
 group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},
 last_modified = {2018-07-12T21:31:49.297Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {dsouza:tracking},
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 abstract = {We present the development and evaluation of a realtime indoor localisation system for tracking people. Our aim was to track a person's indoor position using dead-reckoning, while limiting position error without depending on extensive wireless network infrastructure. The Indoor People Tracker used wearable motion sensors, a floor-plan map and a limited wireless sensor network for proximity ranging. We evaluated how the position accuracy of the Indoor People Tracker was affected by floor-plan map features, wireless proximity range and motion information. The advantage of the Indoor People Tracker was found it was able to achieve accurate position resolution with minimal error, while not depending on wireless proximity.},
 bibtype = {article},
 author = {D'Souza, Matthew and Wark, Tim and Karunanithi, Mohanraj and Ros, Montserrat},
 journal = {Pervasive and Mobile Computing},
 number = {4}
}

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