Tracking Context-Aware Well-Being through Intelligent Environments

Abstract

The growth of personal sensors and the ability to sensorize attributes connected with the physical beings and environments are increasing. Initiatives such as Internet of Things (IoT)) aim to connect devices and people through communication channels in order to automate and fuel interaction. Targeted approaches can be found on the Smart Cities projects which use the IoT to gather data from people and attributes related to city management. Though good for management of new cities, well-being should as well be of principal importance. It regards users higher than infrastructure and managerial data. Taking lessons from ergonomic studies, health studies and user habits it is possible to track and monitor user daily living. Moreover, the link between user living conditions and sparse events such as illness, indispositions can be tracked to well-being data through autonomous services. Such application is detailed in the approach categorized by this article and the research presented
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Author Biographies

Fábio Silva

,
University of Minho
Fábio Silva obtained an MSc in degree in Informatics Engineering in 2011 from the University of Minho in Braga, Portugal. Currently, he is working towards his Ph.D. in Informatics at the University of Minho in Portugal. Also, he is a member of the ISLab - Intelligent Systems Laboratory, a branch of the Computer Science and Technology (CST) group of ALGORITMI. His current research interests include, computational sustainability, energetic efficient systems and multi-agent support systems.

Cesar Analide

,
University of Minho
Cesar Analide is a Professor at the Department of Informatics of the School of Engineering of the University of Minho, and a researcher of the group Computer Science and Technology (CST) of Centro ALGORITMI. Also, he is founder member of the ISLab - Intelligent Systems Laboratory, a branch of the CST group of ALGORITMI.His main interests are in the areas of knowledge representation, intelligent agents and multi-agent systems, sensorization and computational sustainability.
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