Energy-Saving Design of Smart City Buildings Based on Deep Learning Algorithms and Remote Sensing Image Scenes

Abstract

The building of urbanization has encouraged the ongoing expansion of the city's scale in tandem with the ongoing development of the economy and society. The disorderly and rough land acquisition and construction have brought about the problems of inefficient use of many resources, which are in line with the concept of green and smart construction. Violated. In response to these shortcomings and needs, this article introduces deep-learning algorithms and remote-sensing image scenes. Based on the business logic of smart city building energy-saving design, the data set is analyzed by category according to different types of supervision and deep learning to realize the smart city. Effective analysis of building energy efficiency, and a simulation quantitative experiment for evaluation using BIM technology to assess buildings with energy efficiency designs in order to maximize energy-saving design. The simulation experiment results show that the deep learning algorithm and remote sensing image scene are effective and can support the energy-saving design of smart city buildings.