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AuthorSardianos, Christos
AuthorVarlamis, Iraklis
AuthorChronis, Christos
AuthorDimitrakopoulos, George
AuthorHimeur, Yassine
AuthorAlsalemi, Abdullah
AuthorBensaali, Faycal
AuthorAmira, Abbes
Available date2022-12-29T07:34:42Z
Publication Date2020
Publication NameProceedings - 2020 IEEE 6th International Conference on Big Data Computing Service and Applications, BigDataService 2020
AbstractEnergy 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.
SponsorThis paper was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectbig data collection
habit change
information abstraction
information processing
timed recommendations
TitleData Analytics, Automations, and Micro-Moment Based Recommendations for Energy Efficiency
TypeConference Paper

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