@inproceedings{e03cfd08321a40f1bc96e52f90bdde4e,
title = "Machine learning prediction based integrated smart energy management system to improve home energy efficiency",
abstract = "This paper proposes an integrated smart energy management system that applies different machine learning regression techniques to gather, enhance, and prepare various relevant data taken from the surrounding environment to predict and schedule the running periods of one of the schedulable appliances in the household. The system was applied to a case study with encouraging results showing energy consumption reduction rates up to 36\%.",
keywords = "Computer science and informatics",
author = "Souheil Khaddaj and Ahmed Al-Adaileh",
note = "Organising Body: IEEE; 2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) ; Conference date: 14-10-2022 Through 18-10-2022",
year = "2023",
month = feb,
day = "9",
doi = "10.1109/DCABES57229.2022.00042",
language = "English",
isbn = "9781665454636",
series = "International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "119--122",
booktitle = "2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science",
address = "United States",
}