Abstract
The scientific and technological evolution that has taken place in the field of human activity recognition, while enormous, is possibly only the tip of the iceberg of the possibilities that we are currently facing and will continue to experience in the foreseeable future. Much of this innovation has also been driven by the rise of IoT technology at the personal device level which has enabled convenient application in the fields of assisting living, ambient intelligence, and e-health. This paper presents a proposal that is part of an ongoing project for the deployment of sensors in supervised housing, with the challenges and opportunities that this implies. At the moment, different technical possibilities are being assessed for the implementation of the schemes, both at macro and micro level, which are described in the proposed architecture detailed in the solutions presented in this paper. The special characteristics of the individuals, usually with different types of disabilities, who live in these homes make this exciting project, marked with a very high social component, a very big challenge for their inclusion in society.
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Acknowledgements
This contribution has been supported by the Spanish Institute of Health ISCIII by means of the project DTS21–00047 and by the Spanish Ministry of Science. This research has been partially funded by the BALLADEER project (PROMETEO/2021/088) from the Consellería Valenciana. Furthermore, it has been partially funded by the AETHER-UA (PID2020-112540RB-C43) project from the Spanish Ministry of Science and Innovation.
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Lloret, Á., Valera, J.C., Gil, D., Peral, J., Ferrández, A., Amador, S. (2023). Challenges and Opportunities for the Recognition of Human Activity in Supervised Flats. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_72
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