Design of a Robot for Predicting Strawberry Growth Environments Based on AI and Visual Fusion

Abstract

In view of the fact that strawberry cultivation is prone to diseases, and when detected, the diseases are often already severe, leading to reduced production. This work aims to design an intelligent robot capable of predicting strawberry diseases 7 days in advance, helping strawberry growers respond to diseases in a timely manner and reduce losses. This paper adopts the K230 vision module, which is installed on an intelligent trolley. The trolley visually identifies strawberry pests and diseases, takes timed photographs of strawberry plants, and detects environmental information. The vision module uploads the photos to a cloud platform, which communicates with a WeChat mini-program via HTTP. An AI model system is deployed on the mini-program side, and the system analyzes and processes the photos to achieve disease prediction. After extensive experiments and testing, the prediction success rate reaches as high as 98%, enabling relatively accurate advance prediction of strawberry diseases. This intelligent robot system is practical and effective, providing a reliable means for strawberry growers to detect diseases early, effectively solving the problem of untimely disease detection, and has high value for promotion and application.