Abstract
In this work, we present an approach for the recognition of hygiene activities by means of fusion sensors. On the one hand, hygiene habits are related to the correct behavior and functional status of people. Therefore, the monitoring of these activities represent a research outcome with immediate practicality, such as guaranteeing the correct functional status of people while Covid-19 confinement. In the proposed approach, multi sensorial devices are integrated in the toilet to recognize hygiene activities. First, an architecture of non-invasive sensors and data processing methods, which is a key element to guarantee the privacy of inhabitants specifically in the space of toilets, is proposed. The type of sensor proposed in this work are audio, ambient and inertial sensors. A fog computing approach to recognize patterns in real-time close to the sensor which are collected is introduced. The case studies presented here are: i) audio recognition to provide water and human event detection, ii) inertial sensors determine hand washing movements by wristband devices, iii) methane and hydrogen sensors to detect defecation, and iv) humidity sensor to detect showering.
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Acknowledgements
This contribution has been supported by the Andalusian Health Service by means of the project PI-0387-2018. Funding for this research is provided by EU Horizon 2020 Pharaon Project ‘Pilots for Healthy and Active Ageing’, Grant agreement no. 857188. Moreover, this research has received funding under the REMIND project Marie Sklodowska-Curie EU Framework for Research and Innovation Horizon 2020, under grant agreement no. 734355.
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Polo-Rodriguez, A., Cruciani, F., Nugent, C., Medina-Quero, J. (2021). Recognition of Hygiene Activities by Means of Multimodal Sensors. In: Visvizi, A., Troisi, O., Saeedi, K. (eds) Research and Innovation Forum 2021. RIIFORUM 2021. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-84311-3_9
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