Dynamic Occupant Adaptive Energy Management System(DOAEM) for Smart Building

The increasing global energy demands highlight the need for improved energy management systems in smart buildings. Traditional systems are inadequate in resolving the dynamic interplay between energy consumption and occupant comfort due to their inability to adapt to the dynamic nature of occupancy. The main goal of this research is to use dynamic occupancy data to optimize energy consumption. This research introduces a solution that is African Vulture Optimization Algorithm (AVOA) based Dynamic Occupant Adaptive Energy Management System. The adoption of AVOA resulted in a significant reduction in energy consumption, with a median consumption drop of 329.39 kWhr from a baseline of non-optimized 938.08 kWhr. More specifically, the implementation of AVOA showed an average improvement in energy gain to 0.9940, demonstrating the effectiveness of the system in improving energy efficiency while maintaining occupant comfort. This research proposes an integrated approach that balances energy efficiency with the well-being of its occupants, so contributing to the broader targets of sustainable urban development