The Elderly's Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development

Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of "activity" as the building block with which to construct applications such as healthcare monit...

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Bibliographic Details
Published inSensors Vol. 15; no. 5; pp. 11312 - 11362
Main Authors Ni, Qin, García Hernando, Ana Belén, de la Cruz, Iván Pau
Format Journal Article Book Review
LanguageEnglish
Published Switzerland MDPI AG 14.05.2015
MDPI
Subjects
activity characterization
activity monitoring
Classification
Data processing
e-health services development
Failure
independent living
Infrastructure
Monitoring
Preprocessing
Review
Sensors
Smart buildings
smart home
independent living
sensors
data processing
activity monitoring
smart home
activity characterization
e-health services development
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Summary:Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of "activity" as the building block with which to construct applications such as healthcare monitoring or ambient assisted living. The process of identifying a specific activity encompasses the selection of the appropriate set of sensors, the correct preprocessing of their provided raw data and the learning/reasoning using this information. If the selection of the sensors and the data processing methods are wrongly performed, the whole activity detection process may fail, leading to the consequent failure of the whole application. Related to this, the main contributions of this review are the following: first, we propose a classification of the main activities considered in smart home scenarios which are targeted to older people's independent living, as well as their characterization and formalized context representation; second, we perform a classification of sensors and data processing methods that are suitable for the detection of the aforementioned activities. Our aim is to help researchers and developers in these lower-level technical aspects that are nevertheless fundamental for the success of the complete application.
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These authors contributed equally to this work.
ISSN:1424-8220
1424-8220
DOI:10.3390/s150511312