Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/1849 2019 2019 Department of Computer Techniques Engineering, Al Mustaqbal University College , Babylon 51001, Iraq Mohammed Hasan Aldulaimi Department of Computer Techniques Engineering, Al-turath University College, Baghdad 10021, Ira; MEU Research Unit, Middle East University, Amman 11831, Jordan Ibrahim Najem Department of Accounting, College of Administrative and Financial Sciences, Imam Ja'afar Al-Sadiq University, Baghdad, Iraq Tabarak Ali Abdulhussein Department of Medical device technology Engineering, National University of Science and Technology, Thi Qar, Iraq M. H. Ali Performance Quality Department, Mazaya University College, Thi-Qar, Iraq Asaad Shakir Hameed Department of Medical device technology Engineering, Alfarahidi University, Baghdad, Iraq M. Altaee Department of Mathematics, Faculty of Education, Kafkas University, Kars, Hatira Gà Günerhan The DTA-LI system's fusion data method is crucial in the monitoring of appliance loads for the purposes of improving energy efficiency and management. Common home electrical devices are identified and classified from smart meter data through the analysis of voltage and current variations, allowing for the measurement of energy usage in residential buildings. A load identification system based on a decision tree algorithm may infer information about the residents of a building based on their energy usage habits. Better power savings rates, load shedding management, and overall electrical system performance are the results of the clusters' ability to capture families' purchasing patterns and geo-Demographic segmentation. The DTA-LI system's fusion data method presents a promising avenue for improving residential buildings' energy performance and lowering their carbon footprint, especially in light of the widespread use of smart meters in recent years. 2023 2023 24 35 10.54216/JISIoT.090102 https://www.americaspg.com/articleinfo/18/show/1849