Artificial Intelligence‐Based Cloud Computing Network Security Promotes Green Interior Design: Low‐Carbon Landscape Design

With the increasing global attention to sustainable development goals, green building design has become an important issue in the construction industry. Especially in indoor environments, reducing heat load and improving energy efficiency has become an urgent task. By combining artificial intelligence with spatial thermal cycle models, this study explores low‐carbon and energy‐saving interior design methods, enhances the application of building thermal science, and provides new theoretical basis and practical guidance for building design. The study analyzed the building envelope structure and internal thermal environment construction, using thermal load calculation and indoor thermal environment evaluation models to determine the thermal characteristics of the building. Next, we will construct a thermal cycle model for architectural space, explore the principles of thermal cycle and mathematical modeling of indoor air, and conduct thermal balance and effect analysis. Finally, based on heat load optimization and energy strategy, evaluate the optimization effect of energy conservation and thermal comfort. Research has shown that a spatial thermal cycle model optimized by artificial intelligence can effectively reduce building heat load and improve indoor thermal comfort. After optimizing heat load and applying energy‐saving strategies, the energy efficiency of buildings has significantly improved, indoor temperature fluctuations have decreased, and living comfort has significantly improved.