학술논문
Data Analytics, Automations, and Micro-Moment Based Recommendations for Energy Efficiency
Document Type
Conference
Author
Source
2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService) BIGDATASERVICE Big Data Computing Service and Applications (BigDataService), 2020 IEEE Sixth International Conference on. :96-103 Aug, 2020
Subject
Language
Abstract
Energy conservation is a critical task for domestic households and office buildings, mainly because of the shortage of energy resources and the uprising contemporary environmental issues. The development of an IoT ecosystem that monitors energy consumption habits and timely recommends actions to promote energy efficiency can be beneficial for the mainstream. In this work, we present the EM3 project, which combines data collection, information abstraction, timed recommendations for saving actions and automations that promote energy saving in a household or office setup. The article focuses on the data and information processing aspects of the EM3 solution, which efficiently handles thousands of sensor events on a daily basis and provides useful analytics and recommendations to the end user to support habit change.