Optimization design of low-carbon building thermal energy based on optical sensing and virtual reality image scene reconstruction

With the intensification of global climate change and energy crisis, the design of low-carbon buildings has gradually become a research hotspot in the field of architecture. Effective thermal optimization design not only reduces energy consumption, but also improves the comfort and sustainability of the building. This study aims to explore the optimization design of low-carbon building heat energy based on light sensing technology, combined with virtual reality image scene reconstruction, to provide an innovative design method to achieve intelligent management and optimization of building heat energy. Through the introduction of light sensing technology, the light intensity and heat distribution inside and outside the building are monitored, and the combination of data analysis and model simulation is used to evaluate the heat use of the building. On this basis, virtual reality scenes are constructed to reconstruct the heat flow and distribution of buildings, providing designers with intuitive visualization tools. The research shows that the design method based on light sensing can effectively identify the areas of heat waste in the building, and reduce the energy consumption of the building by optimizing the window layout, adding greening and improving the thermal management system. Virtual reality image scene reconstruction makes the design process more intuitive, helps the design team to quickly adjust and optimize, and improves the efficiency and accuracy of the design.