2024-03-29T04:42:59Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1370272024-03-13T09:53:02Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
00925njm 22002777a 4500
dc
García Pérez, Óscar
author
Prieto Tejedor, Javier
author
Alonso Rincón, Ricardo Serafín
author
Corchado Rodríguez, Juan Manuel
author
2017
[EN]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.
García, Ó., Prieto, J., Alonso, R.S., Corchado, J.M. (2017). A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring. Sensors, 17 (8), pp. 1-21
1424-8220
http://hdl.handle.net/10366/137027
10.3390/s17081749
Real-time localization system
Electric power engineering
Wireless sensor networks
Computer science
Energy behaviour
Energy savings
Social computing
Recommendation system
Virtual organization of agents
A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring