The rapid development of the economy brings the problem of environmental pollution. The ecological design of housing products is a response to the concept of sustainable development. It is an important means to build an environmentally friendly society. This paper proposes an intelligent control strategy based on deep reinforcement learning for ecological energy-saving control of housing products, and carries out energy-saving and energy-consumption verification simulation for its effectiveness. In order to further analyze the effect of ecological design of housing products, a comprehensive evaluation of ecological design of housing products is carried out through the evaluation index system combined with gray clustering model. The overshoot and static difference were 0.52°C and 0.14°C, respectively, when the intelligent control strategy for housing products was performed for indoor temperature control, and the average monthly energy consumption of housing products was reduced from 52,346 kWh to 36,222 kWh after applying the intelligent control strategy for 2 months. In the ecological design of housing products, the weight of ecological sustainability had the highest proportion of 0.2585, and the gray clustering composite evaluation score of 4.484 points. The integration of intelligent technology and ecological design of housing products can significantly improve the energy-saving efficiency of housing products and provide a new research direction for the sustainable development of ecological environment.
