The Horus WLAN location determination system
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Analysis of a device-free passive tracking system in typical wireless environments
NTMS'09 Proceedings of the 3rd international conference on New technologies, mobility and security
Kalman filter-based tracking of a device-free passive entity in wireless environments
WiNTECH '11 Proceedings of the 6th ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
AROMA: automatic generation of radio maps for localization systems
WiNTECH '11 Proceedings of the 6th ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
Analysis of WLAN's received signal strength indication for indoor location fingerprinting
Pervasive and Mobile Computing
RF-Based device-free recognition of simultaneously conducted activities
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
CoSDEO 2013: device-free radio-based recognition
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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WiFi-based device-free localization is a main indoor localization technique that has attracted much attention recently. Typically, due to the complex wireless propagation in indoor environments, WiFi-based device-free localization requires a construction of a fingerprint map that captures the signal strength characteristics when the human is standing at certain locations in the area of interest. This fingerprint requires significant overhead in construction, and thus has been one of the major drawbacks of WiFi-based device-free localization. In this paper, we leverage an automated tool for fingerprint constructions to study novel scenarios for WiFi-based device-free localization training and testing that are difficult to evaluate in a real environment. In particular, we examine the effect of changing the access points (AP) mounting location, AP technology upgrade, and outsider effect; on the accuracy of the localization system. Our analysis provides recommendations for better localization and provides insights for both researchers and practitioners.