Using the Big Data generated by the Smart Home to improve energy efficiency management

被引:10
|
作者
Rodriguez Fernandez, Maria [1 ]
Cortes Garcia, Adolfo [2 ]
Gonzalez Alonso, Ignacio [3 ]
Zalama Casanova, Eduardo [1 ]
机构
[1] Univ Valladolid, Valladolid, Spain
[2] Ingn Integrac Avanzadas Ingenia SA, Malaga, Spain
[3] Univ Oviedo, Oviedo, Asturias, Spain
关键词
Smart meter; Sensor network; Power consumption; Machine learning; Energy efficiency; Big data; TECHNOLOGIES; CONSUMPTION; PREDICTION; FEEDBACK;
D O I
10.1007/s12053-015-9361-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:249 / 260
页数:12
相关论文
共 50 条
  • [1] Using the Big Data generated by the Smart Home to improve energy efficiency management
    María Rodríguez Fernández
    Adolfo Cortés García
    Ignacio González Alonso
    Eduardo Zalama Casanova
    [J]. Energy Efficiency, 2016, 9 : 249 - 260
  • [2] A Smart Home Energy Management System Using IoT and Big Data Analytics Approach
    Al-Ali, A. R.
    Zualkernan, Imran A.
    Rashid, Mohammed
    Gupta, Ragini
    AliKarar, Mazin
    [J]. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2017, 63 (04) : 426 - 434
  • [3] Smart Building Energy Management using Big Data Analytic Approach
    Hashim, Naufal Hajjaj Noor
    Ramli, Nor Azuana
    [J]. 2019 13TH INTERNATIONAL CONFERENCE ON MATHEMATICS, ACTUARIAL SCIENCE, COMPUTER SCIENCE AND STATISTICS (MACS-13), 2019,
  • [4] Big data: the key to energy efficiency in smart buildings
    Moreno, M. Victoria
    Dufour, Luc
    Skarmeta, Antonio F.
    Jara, Antonio J.
    Genoud, Dominique
    Ladevie, Bruno
    Bezian, Jean-Jacques
    [J]. SOFT COMPUTING, 2016, 20 (05) : 1749 - 1762
  • [5] Big data: the key to energy efficiency in smart buildings
    M. Victoria Moreno
    Luc Dufour
    Antonio F. Skarmeta
    Antonio J. Jara
    Dominique Genoud
    Bruno Ladevie
    Jean-Jacques Bezian
    [J]. Soft Computing, 2016, 20 : 1749 - 1762
  • [6] Smart Homes, Smart Choices: Using Big Data to Boost Energy Efficiency and Environmental Sustainability
    Choubey, Anurag
    Mishra, Shivendu
    Behera, Sourajit
    Misra, Rajiv
    Pandey, Amit Kumar
    Pandey, Digvijay
    [J]. ELECTRIC POWER COMPONENTS AND SYSTEMS, 2024,
  • [7] Big data driven smart energy management: From big data to big insights
    Zhou, Kaile
    Fu, Chao
    Yang, Shanlin
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 56 : 215 - 225
  • [8] Smart Home Control and Management Based on Big Data Analysis
    Chi, Hao
    Chi, Yuyan
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [9] Smart Home Control and Management Based on Big Data Analysis
    Chi, Hao
    Chi, Yuyan
    [J]. Computational Intelligence and Neuroscience, 2022, 2022
  • [10] A Smart Home Energy Management System using Smart Plugs
    Mtshali, Progress
    Khubia, Freedom
    [J]. 2019 CONFERENCE ON INFORMATION COMMUNICATIONS TECHNOLOGY AND SOCIETY (ICTAS), 2019,