Title
E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures
Abstract
Activity monitoring in home environments has become increasingly important and has the potential to support a broad array of applications including elder care, well-being management, and latchkey child safety. Traditional approaches involve wearable sensors and specialized hardware installations. This paper presents device-free location-oriented activity identification at home through the use of existing WiFi access points and WiFi devices (e.g., desktops, thermostats, refrigerators, smartTVs, laptops). Our low-cost system takes advantage of the ever more complex web of WiFi links between such devices and the increasingly fine-grained channel state information that can be extracted from such links. It examines channel features and can uniquely identify both in-place activities and walking movements across a home by comparing them against signal profiles. Signal profiles construction can be semi-supervised and the profiles can be adaptively updated to accommodate the movement of the mobile devices and day-to-day signal calibration. Our experimental evaluation in two apartments of different size demonstrates that our approach can achieve over 96% average true positive rate and less than 1% average false positive rate to distinguish a set of in-place and walking activities with only a single WiFi access point. Our prototype also shows that our system can work with wider signal band (802.11ac) with even higher accuracy.
Year
DOI
Venue
2014
10.1145/2639108.2639143
MobiCom
Keywords
Field
DocType
channel state information,miscellaneous,location-oriented,device-free,activity recognition,wifi
False positive rate,Activity recognition,Computer science,Wearable computer,Computer network,Communication channel,Thermostat,Real-time computing,Mobile device,Elder care,Channel state information,Embedded system
Conference
Citations 
PageRank 
References 
185
5.12
34
Authors
6
Search Limit
100185
Name
Order
Citations
PageRank
Yan Wang181140.19
Jian Liu22567.53
Yingying Chen32495193.14
Marco Gruteser44631309.81
Jie Yang5160583.06
Hongbo Liu61865.47