Spatial Models for Human Motion-Induced Signal Strength Variance on Static Links
IEEE Transactions on Information Forensics and Security - Part 1
Passive detection of situations from ambient FM-radio signals
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
SCPL: indoor device-free multi-subject counting and localization using radio signal strength
Proceedings of the 12th international conference on Information processing in sensor networks
New insights into wifi-based device-free localization
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Device-free indoor localization using ambient radio signals
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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We investigate the use of received RF-signals for activity recognition in scenarios with multiple receive nodes and multiple simultaneously active individuals. Our system features a short 0.5 second window over which features are calculated and we report on experiences in the choice of the neighbourhood size of the k-nearest neighbour (k-NN) classifier utilised. In a case study with software defined radio nodes utilised in an active, device-free activity recognition (DFAR) system, we observe a good recognition accuracy for the recognition of multiple simultaneously conducted activities with two and more receive devices. This is the first study to distinguish this particular set of activities from users conducting them simultaneously. For a single individual, we repeat the experiment and report the recognition accuracy in scenarios where the recognition area per receive node is larger than 8sqm