Human Activity Recognition in Intelligent Home Environments: An Evolving Approach

Authors:
Jose Antonio Iglesias;Plamen Angelov;Agapito Ledezma;Araceli Sanchis
Affiliations:
Carlos III University, Madrid, Spain, email: jiglesia@inf.uc3m.es;InfoLab21, Lancaster University, Lancaster, United Kingdom, email: p.angelov@lancaster.ac.uk;Carlos III University, Madrid, Spain, email: ledezma@inf.uc3m.es;Carlos III University, Madrid, Spain, email: masm@inf.uc3m.es
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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Abstract

In this paper, we propose an automated approach to track and recognize daily activities. Any activity is represented in this research as a sequence of raw sensors data. These sequences are treated using statistical methods in order to discover activity patterns. However, as the way to perform an activity is usually not fixed but it changes and evolves, we propose an activity recognition method based on Evolving Systems.