EEMCS EPrints Service
Muthukrishnan, K. and van der Zwaag, B.J. and Havinga, P.J.M. (2009) Inferring motion and location using WLAN RSSI. In: The Second International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, 30 Sep - 03 Oct 2009, Orlando, Florida, U.S.A.. pp. 163-182. Lecture Notes in Computer Science 5801. Springer Verlag. ISBN 978-3-642-04378-9
Full text available as:
Official URL: http://dx.doi.org/10.1007/978-3-642-04385-7_12
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.
Export this item as:
To correct this item please ask your editor
Repository Staff Only: edit this item