Abstract
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.
Highlights
Recent advances in sensing, networking and ambient intelligence technologies have resulted in a rapid emergence of smart environments
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
The main objective of this review paper is twofold: first, we propose a classification of the main activities considered in smart home scenarios targeted to the elderly’s independent living, as well as their characterization and formalized context representation; second, we advance towards a general set of guidelines that would help researchers and developers select the sensors and processing techniques best suited to the target activities to detect, focusing on older adults and indoor smart home activities
Summary
Recent advances in sensing, networking and ambient intelligence technologies have resulted in a rapid emergence of smart environments. Whereas it is possible to find a good number of research reviews related to aspects such as sensor design, monitoring techniques or machine learning algorithms and reasoning approaches, to the best of our knowledge the underlying and fundamental issues of activity context information representation, proper sensor selection and sensor raw data processing have not received enough attention yet in the concrete context of elderly people needs. The main objective of this review paper is twofold: first, we propose a classification of the main activities considered in smart home scenarios targeted to the elderly’s independent living, as well as their characterization and formalized context representation; second, we advance towards a general set of guidelines that would help researchers and developers select the sensors and processing techniques best suited to the target activities to detect, focusing on older adults and indoor smart home activities.
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