Open AccessDetection of multi‐occupancy using device‐free passive localisation
Author(s) -
Deak Gabriel,
Curran Kevin,
Condell Joan,
Deak Daniel
Publication year - 2014
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
ISSN - 2043-6394
DOI - 10.1049/iet-wss.2013.0031
Subject(s) - occupancy , signal (programming language) , signal strength , computer science , wireless , real time computing , received signal strength indication , telecommunications , engineering , architectural engineering , programming language
Indoor device‐free passive localisation (DfPL) technology uses a received signal strength indication (RSSI)‐based method to record variances of a measured signal where a person being tracked is not carrying any electronic device that can be used to estimate the location. The system monitors the changes in the RSSI measurements caused by the presence of a human body in an indoor environment. For example, it is known that the resonance frequency of water is 2.4 GHz and the human body contains >70% water. Thus, the human body attenuates the wireless signal reacting as an absorber. Wireless communication signal strengths between a number of nodes, using IEEE 802.11 or 802.15.4 standards, show that communication links covering distinct areas cannot be affected simultaneously by only one person. Thus, the authors have deployed a novel system that can identify multi‐occupants in an environment using patterns of motion from those monitored areas. A pattern recognition neural network was used to identify two people in the environment. No other work based on the DfPL technique has focused on multi‐occupancy.