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Home Automation and Machine Learning Models for Health Monitoring

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Proceedings of the 5th International Conference on Big Data and Internet of Things (BDIoT 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 489))

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Abstract

Medical surveillance has been constantly linked to hospitals and infirmaries. However, the recent increase in demand for health assistance, especially with the current covid-19 pandemic, has made it clear that relying on placing patients on hospitals for surveillance is deprecated. In the same context, this paper strives to illuminate the significance of using trending paradigms such as home automation and artificial intelligence to better advance and modernize healthcare systems. Accordingly, the main contribution of this study is a demonstration of a novel smart home architecture and an evaluation of machine-learning algorithms aimed at predicting a health condition severity based on the patient data gathered from several sensors and wearables. In respect to the need of providing a real time alerting system, several classification algorithms are highlighted with their advantages in mitigating the remote health monitoring problematic. The results assessment of the machine learning algorithms emphasizes the convenience of using artificial intelligence for health monitoring regardless of time and place constraints.

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Author information

Authors and Affiliations

  1. Laboratory of Informatics Systems and Telecommunications (LIST), Department of Computer Engineering, Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Route Ziaten, B.P. 416, Tangier, Morocco

    Lamiae Eloutouate, Fatiha Elouaai & Mohammed Bouhorma

  2. Laboratory of Advanced Sciences and Technologies (STA), Department of Computer Science, Multidisciplinary Faculty of Larache, Abdelmalek Essaadi University, Tetouan, Morocco

    Hicham Gibet Tani

Authors
  1. Lamiae Eloutouate
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  2. Fatiha Elouaai
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  3. Hicham Gibet Tani
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  4. Mohammed Bouhorma
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Corresponding author

Correspondence to Lamiae Eloutouate .

Editor information

Editors and Affiliations

  1. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  2. UNILEHAVRE, UNIROUEN, Normandie Université, Le Havre, France

    Claude Duvallet

  3. Vrije Universiteit Brussel, Brussels, Belgium

    Abdellah Touhafi

  4. ENSA, Abdelmalek Essaâdi University, Tetuan, Morocco

    Mohammed Al Achhab

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Eloutouate, L., Elouaai, F., Gibet Tani, H., Bouhorma, M. (2022). Home Automation and Machine Learning Models for Health Monitoring. In: Lazaar, M., Duvallet, C., Touhafi, A., Al Achhab, M. (eds) Proceedings of the 5th International Conference on Big Data and Internet of Things. BDIoT 2021. Lecture Notes in Networks and Systems, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-07969-6_27

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