Using Wi-Fi signals is an attractive and reasonably affordable solution to the currently unsolved problem of widespread tracking in an indoor environment. However, this approach is hampered due to the underlying characteristics of radio waves (i.e. multipath effects) and due to infrastructural requirements. HABITS (History Aware Based Indoor Tracking System) overcomes these difficulties by modeling the historical movement habits of people in a workplace environment. It then learns from these habits and intelligently predicts the next location using a discrete Bayesian filter. This knowledge not only improves on currently available systems in terms of accuracy, yield and latency but can also be used as an input to building automation (heating, lighting) systems as an energy saving feature.
|Title of host publication||Unknown Host Publication|
|Editors||M Hofmann, J Morrison, P Doyle|
|Place of Publication||Letterkenny Institute of Technology (LYIT), Letterkenny, Ireland|
|Publisher||Letterkenny Institute of Technology|
|Number of pages||8|
|Publication status||Published - Oct 2010|
|Event||Proc. of the 10th International Conference on Information Technology & Telecommunication (IT&T 2010) - Letterkenny Institute of Technology (LYIT), Letterkenny, Ireland|
Duration: 1 Oct 2010 → …
|Conference||Proc. of the 10th International Conference on Information Technology & Telecommunication (IT&T 2010)|
|Period||1/10/10 → …|
Furey, E., Curran, K., & McKevitt, P. (2010). Incorporating past human movement into indoor location positioning systems for accurate updates. In M. Hofmann, J. Morrison, & P. Doyle (Eds.), Unknown Host Publication (pp. 85-92). Letterkenny Institute of Technology (LYIT), Letterkenny, Ireland: Letterkenny Institute of Technology.