Next Article in Journal
A Temperature Drift Compensation Method for Pulsed Eddy Current Technology
Next Article in Special Issue
A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living
Previous Article in Journal
An Optimization Routing Algorithm for Green Communication in Underground Mines
Previous Article in Special Issue
An IBeacon-Based Location System for Smart Home Control
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(6), 1951; https://doi.org/10.3390/s18061951

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)
Full-Text   |   PDF [2529 KB, uploaded 15 June 2018]   |  

Abstract

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
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

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

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top