Context Awareness by Analyzing Accelerometer Data
ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
Composcan: adaptive scanning for efficient concurrent communications and positioning with 802.11
Proceedings of the 6th international conference on Mobile systems, applications, and services
Sensing motion using spectral and spatial analysis of WLAN RSSI
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
Self-mapping in 802.11 location systems
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Mobility detection using everyday GSM traces
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Information Sciences: an International Journal
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We present novel algorithms to infer movement by making use of inherent fluctuations in the received signal strengths from existing WLAN infrastructure. We evaluate the performance of the presented algorithms based on classification metrics such as recall and precision using annotated traces obtained over twelve hours effectively from different types of environment and with different access point densities. We show how common deterministic localisation algorithms such as centroid and weighted centroid can improve when a motion model is included. To our knowledge, motion models are normally used only in probabilistic algorithms and such simple deterministic algorithms have not used a motion model in a principled manner. We evaluate the performance of these algorithms also against traces of RSSI data, with and without adding inferred mobility information.