Novelty Detection in User Behavioural Models within Ambient Assisted Living Applications: An Experimental Evaluation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Current approaches to networked robot systems(or ecology of robots and sensors) in ambient assisted livingapplications (AAL) rely on pre-programmed models of theenvironment and do not evolve to address novel states of theenvironment. Envisaged as part of a robotic ecology in an AALenvironment to provide different services based on the eventsand user activities, a Markov based approach to establishing auser behavioural model through the use of a cognitive memorymodule is presented in this paper. Upon detecting changes inthe normal user behavioural pattern, the ecology tries to adaptits response to these changes in an intelligent manner. Theapproach is evaluated with physical robots and anexperimental evaluation is presented in this paper. A majorchallenge associated with data storage in a sensor richenvironment is the expanding memory requirements. In orderto address this, a bio-inspired data retention strategy is alsoproposed. These contributions can enable a robotic ecology toadapt to evolving environmental states while efficientlymanaging the memory footprint.
Original languageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusPublished - 5 Dec 2014
EventIEEE International Conference on Robotics and Biometrics - Bali, Indonesia
Duration: 5 Dec 2014 → …


ConferenceIEEE International Conference on Robotics and Biometrics
Period5/12/14 → …


Cite this