aspg-2-3270-1791421539 20261008010539 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2025 15 2 Osama Mohammed Middle Technical University, Baghdad, Iraq Marwa Ibrahim Islamic University of Lebanon, Lebanon Abdalrahman Fatikhan Ataalla Department of Computer Engineering Techniques, College of Engineering, University of Al Maarif, Al Anbar, 31001, Iraq The integration of sensing technologies with residential buildings raises the concept of a smart home, which has facilitated the life of the habitant nowadays. This technology helps us to track and understand the behavior of the client in the house to give him maximum comfort. A neighborhood area is an interconnected set of houses that exist in the same geographical region and share the same energy resources. The most important component in the process of decision-making is the energy usage in the smart building. The energy optimization problem in the smart building created a challenge for enterprises and the government for a long time. A lot of research were made to solve this energy optimization problem. One of these problems is the organization of energy usage within a neighborhood area network. The main challenges are to maintain the user comfort in each house and to not exceed the total energy offered to the network. For this, we proposed a technique that predicts, based on historical data of each house, its future behavior and created for each one a weekly schedule with hourly annotated field with: high, normal, or low, where each one represents the amount of energy user is able to use at this time. At the end, an incentive-based program is created to give the client an incentive on his bill if he used the daily high energy consumption in the annotated high in his schedule. To create the schedules, we extracted some features from the data, then we used the genetic algorithm to create schedules, then we did an improvement to the technique using dynamic programming that stores the features of a house with created schedule, later when we meet a similar house we can directly give a schedule that fits the need. 2025 17 26 3270 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.150202 https://www.americaspg.com/journal/2/article/3270 https://www.americaspg.com/storage/11736261482.pdf