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Sensors 2018, 18(6), 1951;

Cloud-Based Behavioral Monitoring in Smart Homes

Dipartimento di Ingegneria e Architettura, Università degli Studi di Parma, 43124 Parma, Italy
Author to whom correspondence should be addressed.
Received: 18 May 2018 / Revised: 11 June 2018 / Accepted: 13 June 2018 / Published: 15 June 2018
(This article belongs to the Special Issue Smart Homes)
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Environmental sensors are exploited in smart homes for many purposes. Sensor data inherently carries behavioral information, possibly useful to infer wellness and health-related insights in an indirect fashion. In order to exploit such features, however, powerful analytics are needed to convert raw sensor output into meaningful and accessible knowledge. In this paper, a complete monitoring architecture is presented, including home sensors and cloud-based back-end services. Unsupervised techniques for behavioral data analysis are presented, including: (i) regression and outlier detection models (also used as feature extractors for more complex models); (ii) statistical hypothesis testing frameworks for detecting changes in sensor-detected activities; and (iii) a clustering process, leveraging deep learning techniques, for extracting complex, multivariate patterns from daily sensor data. Such methods are discussed and evaluated on real-life data, collected within several EU-funded projects. Overall, the presented methods may prove very useful to build effective monitoring services, suitable for practical exploitation in caregiving activities, complementing conventional telemedicine techniques. View Full-Text
Keywords: active and assisted living (AAL); smart home; behavioral analysis; deep learning; machine learning active and assisted living (AAL); smart home; behavioral analysis; deep learning; machine learning

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Mora, N.; Matrella, G.; Ciampolini, P. Cloud-Based Behavioral Monitoring in Smart Homes. Sensors 2018, 18, 1951.

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