Abstract
The paper analyzes the application of thermal energy optimization scheme based on image recognition and light sensor technology in low-energy buildings, in order to improve building energy efficiency, reduce energy consumption and provide scientific basis for urban green environment planning. In this paper, image recognition technology is used to monitor the light change in the external environment of the building, and the indoor light intensity data is obtained by the light sensor in real time. Combined with big data analysis, building heat optimization model is established, intelligent control system is designed, and the heating and cooling system of the building is dynamically adjusted, so as to achieve efficient use of heat energy. The experimental results show that the thermal energy optimization method based on image recognition and light sensor has a good application prospect in low-energy buildings, which not only effectively reduces energy consumption, but also contributes to the sustainable development of urban green environment.
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