aspg-28-2313-1792155052 20261016125052 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Artificial Intelligence and Metaheuristics JAIM 2833-5597 2023 6 2 Ahmed Abdelmgeed Department of Communications & Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, Egypt Ahmed Mohamed Zaki Computer Science and Intelligent Systems Research Center, Blacksburg 24060, Virginia, USA Marwa Adel Soliman Department of Architecture, Delta Higher Institute of Engineering and Technology, Mansoura, Egypt Commencing with the transformative fusion of Smart Home and Internet of Things (IoT) technologies, this study scrutinizes the efficacy of predictive modeling approaches, specifically the autoregressive integrated moving average (ARIMA) and persistence algorithms. The primary focus lies in their potential for forecasting and optimizing energy consumption dynamics within the intricate framework of smart homes. The investigation reveals a nuanced comparison between the proposed ARIMA and conventional Persistence models. Smart Home, emblematic of innovative living, integrates seamlessly with IoT, promising an intelligent and interconnected domestic ecosystem. To enhance energy efficiency, this study explores the ARIMA model's capabilities alongside the persistence algorithm. Notably, the proposed ARIMA model showcases exceptional prowess in forecasting, substantiated by a significantly lower style='mso-bidi-font-style:normal'> mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:major-bidi'>RMSE coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> height:11.5pt'> o:title="" chromakey="white"/> compared to the Persistence model. The ARIMA model, with an Root Mean Square Error value of 0.03378, outshines the Persistence model with a higher Root Mean Square Error value of 0.158 when evaluated on the test dataset. This substantial reduction in style='mso-bidi-font-style:normal'> mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:major-bidi'>RMSE type="#_x0000_t75" style='width:27pt;height:11.5pt'> o:title="" chromakey="white"/> emphasizes the superior performance of the ARIMA model, making it a compelling choice for time series forecasting tasks. Beyond quantitative metrics, the precision of the ARIMA model holds transformative potential, promising cost-effective energy consumption, proactive maintenance, and an elevated quality of life within smart homes. This research establishes a robust foundation for integrating advanced predictive modeling, particularly the ARIMA model, to enhance the efficiency, sustainability, and inhabitant satisfaction of smart homes in the era of IoT. 2023 08 15 2313 https://creativecommons.org/licenses/by/4.0/ 10.54216/JAIM.060201 https://www.americaspg.com/journal/28/article/2313 https://www.americaspg.com/storage/91702811676.pdf