Journal of Artificial Intelligence and Metaheuristics JAIM 2833-5597 10.54216/JAIM https://www.americaspg.com/journals/show/3350 2022 2022 School of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic, PO Box 33349, Isa Town, Bahrain; Jadara University Research Center, Jadara University, Jordan; Applied Science Research Center, Applied Science Private University, Amman, Jordan admin admin Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 11152, Egypt Marwa M. Eid School of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic, PO Box 33349, Isa Town, Bahrain Abdelhameed Ibrahim School of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic, PO Box 33349, Isa Town, Bahrain Osama Alabedallat This study pursues machine learning models for the task of smart homes' energy management with the use of a dataset that combines smart meter readings and weather conditions at the same time. The assessment of the Baseline Qualification and ARIMA models is done using various criteria, such as MSE, RMSE, and others. Most telling, the best performance is shown by ARIMA, which gets the lowest MSE score, 0.0693, in this instance. They show that such a model is optimal in forecasting energy consumption dynamics, and while they could be better, weather information helps improve the accuracy of the forecasts. The conduct helps uncover priceless information, allowing for the development of new smart home operating systems with a prospect of energy efficiency enhancement as well as a sustainable environment. 2024 2024 10 18 10.54216/JAIM.080202 https://www.americaspg.com/articleinfo/28/show/3350