Innovative Design of Environmental Visual Art Based on Edge Cloud Computing Technology under the Background of Artificial Intelligence

Abstract

In the traditional artificial city planning, the greenway research generally takes the greenway layout or environmental effects as a single evaluation criterion. This work aims to solve the problem of weak commonality and difference of greenway landscape vision in the construction of urban style features. First, an image super-resolution reconstruction technology is proposed based on the Convolutional Neural Network to achieve precise processing of the urban greenway layout at a high level. Secondly, a one-time batch processing technology of images based on edge-cloud collaborative deep learning semantic segmentation of edge-cloud computing technology is proposed, which can quickly find out the problematic areas in greenway planning. Finally, the data set obtained by image processing is expressed by mapping software to analyze the commonness and difference of urban greenway landscape visual elements characteristics and composition diversity. The results show the spatial distribution sequence characteristics of different types of greenways and evaluate the relationship between the same type of greenway landscape visual services and their accessibility. The experimental results show that: (1) the CNN-based image super-resolution reconstruction technology designed is superior to the traditional technology in image processing and can more accurately identify the information in the image; (2) The image batch processing technology of edge-cloud collaborative deep learning semantic segmentation based on edge cloud computing technology can greatly improve the efficiency of image information processing, and has broader application prospects in image batch processing. This research aims to provide technical support for the upgrading and transformation of artificial intelligence technology in technology enterprises and reduce the adverse impact on urban construction caused by blind and one-sided urban environmental planning. Some method innovation and reference are provided for environmental visual art design innovation.