Journal
ENERGY EFFICIENCY
Volume 9, Issue 1, Pages 249-260Publisher
SPRINGER
DOI: 10.1007/s12053-015-9361-3
Keywords
Smart meter; Sensor network; Power consumption; Machine learning; Energy efficiency; Big data
Funding
- Ministry of Economy and Competitiveness of Spain [IPT-2011-1237-920000]
- FEDER
Ask authors/readers for more resources
A Smart Home is able to generate energy-related values such as electricity consumption, temperature, or luminosity without higher infrastructure requirements. The main aim of this research is to extract information from that raw data that could contribute to improving the energy efficiency management. This paper presents a system which, using different Machine Learning approaches to learn about the users' consumption habits, is able to generate collaborative recommendations and consumption predictions that help the user to consume better, which will in turn improve the demand curve. Moreover, from consumption values, the system learns to identify devices, enabling the demand to be anticipated. Taking into account the fact that the amount of energy data is increasing in real-time, the use of Big Data techniques will be the key to handling all the operations and one of the more innovative features of the system.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available