The mechanism of digitized landscape architecture design under edge computing

The purposes are to analyze the mechanism of digitized landscape architecture design and stablize the garden landscape image display in constructing garden landscape digitization platform. According to previous research and mobile edge computing, a scheme of digitized landscape architecture design is proposed based on edge computing. This scheme uses discrete elevation calculation to preserve the landscape design image's frame. It adopts the Roberts edge detection and Laplacian operator for high-level stable preservation of landscape images. Simultaneously, the displayed image is stablized using edge computing algorithms. Simulation experiments are performed to verify the effectiveness of the proposed scheme of digitized landscape architecture design based on mobile edge computing. Results demonstrate that the discrete elevation calculation algorithm can avoid low visual rendering in the 3D image generation process, optimize the seed point matching of edge correlation, and ensure image clarity and stability. The edge computing algorithm can fundamentally avoid the problem of image shaking. The impact of different algorithm models on the classification and accuracy of landscape images is analyzed through parameter optimization. Compared with some latest models, the proposed landscape design scheme based on edge computing has better accuracy. The average accuracy can reach more than 90%, and the Kappa coefficient remains at 86.93%. The designed garden landscape digitization platform can stably display 3D garden landscape images while avoiding the shaking of 3D images, which can provide a theoretical basis and practical value for designing and planning landscape architecture.

Automated summary

A scheme of digitized landscape architecture design based on edge computing is proposed, utilizing discrete elevation calculation and edge detection algorithms for stable preservation of landscape images. Simulation experiments demonstrate the effectiveness of the scheme in avoiding image shaking and improving image classification and accuracy.