Abstract
The implementation of concepts such as smart cities, ambient intelligence and internet of things enables the construction of complex systems that may follow users across environments through many devices. One potential application is the assessment and assurance of well-being of users within different environment with different configurations. This is a complex task that requires the capture of the state and context of both users and environments through sensors dispersed across environments and users. It’s the opportunities created by the emergence of technology that provide enough information to intelligent autonomous systems. Adapting expectations of a well-being assessment system to task and context is possible using the new techniques imported from different fields such as sensor networks, sensor fusion and machine learning. This article encompasses the design and implementation of a platform to evaluate well-being according to each context and translate it to sustainable indicators.
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Acknowledgments
This work was developed in the context of the project CAMCoF - Context-aware Multimodal Communication Framework funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through FCT - Fundação para a Ciência e a Tecnologia within project FCOMP-01-0124-FEDER-028980 and PEst-OE/EEI/UI0752/2014. Additionally, it is also supported by a doctoral grant, SFRH/BD/78713/2011, by FCT in the financial program POPH/FSE in Portugal.
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Silva, F., Gonçalves, C., Analide, C. (2015). Context-Aware Well-Being Assessment in Intelligent Environments. In: Mohamed, A., Novais, P., Pereira, A., Villarrubia González, G., Fernández-Caballero, A. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent Systems and Computing, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-19695-4_15
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DOI: https://doi.org/10.1007/978-3-319-19695-4_15
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