Simulation of dynamic heat dissipation energy optimization based on IoT and image recognition in low carbon building VR design process

With the global emphasis on low-carbon buildings, how to effectively optimize the thermal management of buildings has become a research hotspot. This article constructs a three-dimensional model of low-carbon buildings and implements real-time heat dissipation detection of buildings through image recognition to evaluate their heat dissipation performance. Then a heat load prediction model was proposed, which obtained the heat load prediction results of buildings under different environmental conditions through data analysis. Thus, it lays the foundation for the subsequent optimization of dynamic heat dissipation energy. The core of the research is to establish a dynamic heat dissipation optimization strategy. This article provides a detailed introduction to the principle of dynamic heat dissipation synergy, combined with the thermal network temperature compensation model and dynamic adjustment model, to achieve the expected energy efficiency improvement. Finally, the construction of a dynamic heat dissipation energy optimization control system based on the Internet of Things has strengthened the collection and analysis of real-time temperature data, and its effectiveness and reliability in practical applications have been verified through system testing.