Istituto di Scienza e Tecnologie dell'Informazione     
Palumbo F., La Rosa D., Ferro E. Stigmergy-based Long-Term Monitoring of Indoor Users Mobility in Ambient Assisted Living Environments: the DOREMI Project Approach. In: AI*AAL2016 - Artificial Intelligence for Ambient Assisted Living 2016 co-located with 15th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2016) (Genova, Italy, 28 November 2016). Atti, pp. 18 - 32. Stefania Bandini, Gabriella Cortellessa, Filippo Palumbo (eds.). (CEUR Workshop Proceedings AI*IA series, vol. 1803). CEUR-WS.org, 2016.
Aging trends in Europe motivate the need for technological solutions aimed at preventing the main causes of morbidity and premature mortality. In this framework, the DOREMI project addresses three important causes of morbidity and mortality in the elderly by devising an ICT-based home care services for aging people to contrast cognitive decline, sedentariness and unhealthy dietary habits. In DOREMI, the house itself is transformed in an unobtrusive monitoring environment able to keep track of the daily activities of older users. In this paper, we present a system able to detect behavioral deviations of the routine indoor activities, in terms of indoor movements, on the basis of indoor localization information coming from the deployed environmental sensor network and a swarm intelligence method, namely stigmergy. Similarity evaluation is performed between stigmergic maps over different weeks in order to assess deviations. These deviations can be related to an effective application of the DOREMI protocol as well as to malfunctioning devices, thus representing a useful tool to detect changes in the DOREMI environment and in the user's life-style. The proposed solution has been validated in a pilot study lasted six months and carried out in UK and in Italy.
URL: http://ceur-ws.org/Vol-1803/paper2.pdf
Subject Stigmergy
Long-term Monitoring
Ambient Assisted Living

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