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Sensors 2017, 17(8), 1749; doi:10.3390/s17081749

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

University of Salamanca, BISITE Research Group, Edificio I+D+I, 37007 Salamanca, Spain
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Received: 12 June 2017 / Revised: 22 July 2017 / Accepted: 25 July 2017 / Published: 31 July 2017
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Abstract

Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated. View Full-Text
Keywords: real-time localization system; wireless sensor networks; energy behaviour; energy savings; social computing; recommendation system; virtual organization of agents real-time localization system; wireless sensor networks; energy behaviour; energy savings; social computing; recommendation system; virtual organization of agents
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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).

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MDPI and ACS Style

García, Ó.; Prieto, J.; Alonso, R.S.; Corchado, J.M. A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring. Sensors 2017, 17, 1749.

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