Simulating Energy Savings Impact of Daylight HarvestingSystems in Buildings Using Cognitive Agents in Unreal Engine

Daylight harvesting systems are a critical component of adaptive lighting technologies, designed toadjust artificial lighting based on the availability of natural daylight to optimize energy efficiency andoccupant comfort. This research paper explores the development, implementation, and performanceevaluation of a daylight harvesting system within a virtual architectural environment using UnrealEngine. By integrating real-time environmental data and cognitive agents, the system dynamicallyadjusts lighting conditions to maintain consistent illumination levels. A series of simulations wereconducted to assess the system's performance under various conditions, including different natural lightscenarios, occupancy levels, and weather conditions. The study provides a comparative analysis ofenergy consumption and occupant comfort between traditional static lighting systems and the proposedadaptive system. Results demonstrate significant energy savings and enhanced occupant satisfactionwith the adaptive system, highlighting its potential for wide-scale application in commercial andresidential buildings. The findings of this research contribute to the growing body of knowledge onadaptive lighting technologies and offer practical insights for the design and implementation of effectivedaylight harvesting systems. This paper concludes with recommendations for future research andpotential improvements to further optimize system performance and integration.

کلیدواژه ها:

Cognitive Agents ، Unreal Engine ، Lighting Simulation ، Behavior Trees ، AdaptiveLighting Systems ، Daylight Harvesting Systems