In recent years, energy conservation and emission reduction have received widespread attention, but there is no more research data on energy conservation and emission reduction in smart buildings. Therefore, this article analyzed the energy conservation and emission reduction, and optimization control of smart buildings. The main focus of this article was on the optimization of cloud computing in building energy efficiency. By monitoring five aspects: environmental utilization rate, electrical energy consumption, carbon emissions, water consumption, and new energy utilization rate, the effectiveness of cloud computing in optimizing building energy efficiency can be analyzed to make further optimization measures. Firstly, this article explored the overall data processing system through the use of cloud computing, which enabled artificial intelligence of the overall data. The experimental results showed that the average environmental utilization rates of smart building energy-saving systems and traditional building energy-saving systems assisted by cloud computing were 56.5% and 43.1%, respectively, based on the data after one month of building energy-saving optimization. Based on the data from two months after optimizing building energy efficiency, the average environmental utilization rates of smart building energy efficiency systems and traditional building energy efficiency systems assisted by cloud computing were 64.3% and 45.3%, respectively. Therefore, applying cloud computing to the optimization control of smart building energy conservation and emission reduction systems is effective in increasing the environmental utilization of building energy saving systems.

Xueting Qin. Algorithm for Optimizing Control of Energy Conservation and Emission Reduction in Smart Buildings Assisted by Cloud Computing. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 7: 130-139. https://doi.org/10.25236/AJCIS.2025.080716.

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