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Modeling user movement habits for intelligent indoor tracking

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Furey, E, Curran, K and McKevitt, P (2010) Modeling user movement habits for intelligent indoor tracking. In: Proc. of the 3rd Annual Intel European Research and Innovation Conference (ERIC-2010): Building a Smart, Sustainable and Inclusive Society through Research and Innovation partnerships, Intel Ireland Campus, Leixlip, Co. Kildare, Ireland. Intel Ireland. 1 pp. [Conference contribution]

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URL: http://newsroom.intel.com/docs/DOC-1304

Abstract

Using Wi-Fi signals is an attractive and reasonably affordable option to deal with the currently unsolved problem of widespread tracking in an indoor environment. These systems however suffer 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 by modeling the historical movement habits of people in a workplace environment and then learns from these and intelligently predicts next location using a discrete Bayesian filter. This knowledge not only improves on currently available systems in terms of accuracy, yield and latency but also can be used as an input to building automation (heating, lighting) systems as an energy saving feature.

Item Type:Conference contribution (Poster)
Faculties and Schools:Faculty of Arts
Faculty of Computing & Engineering
Faculty of Arts > School of Creative Arts and Technologies
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:21354
Deposited By:Professor Paul McKevitt
Deposited On:08 May 2012 16:19
Last Modified:08 May 2012 16:19

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