Data Analytics, Automations, and Micro-Moment Based Recommendations for Energy Efficiency
Date
2020Author
Sardianos, ChristosVarlamis, Iraklis
Chronis, Christos
Dimitrakopoulos, George
Himeur, Yassine
Alsalemi, Abdullah
Bensaali, Faycal
Amira, Abbes
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Metadata
Show full item recordAbstract
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. 2020 IEEE.
DOI/handle
http://dx.doi.org/10.1109/BigDataService49289.2020.00022http://hdl.handle.net/10576/37804
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- Electrical Engineering [2649 items ]