基于人工智能的虫情监测系统设计

Design of Bug Situation Monitoring System Based on Artificial Intelligence

人工智能在农业领域的广泛应用,促进了智慧农业的高速发展。我国是一个农业大国,虫害造成了产量减少和质量下降,导致农民的收入减少,从而虫情监测显得尤为重要。传统虫情监测需要依靠专业技术人员,导致耗费大量人力、物力,无法满足及时虫情监测的需求。本文设计的基于人工智能的虫情监测系统为智慧农业提供精准预测和智能决策。本设计以STM32F103核心板为核心,结合图像采集模块、图像处理模块、图像分类模块,采用深度学习模型对捕获的虫体进行学习形成训练模型,通过对虫体图像进行识别,让机器具有对虫体不同类别进行识别和判定的能力,将结果传输到STM32单片机,进行计数处理操作,进而分析虫体种类和数量,对害虫的综合治理具有重要的指导意义。

The wide application of Artificial intelligence is widely applied in the agricultural field to promote the rapid development of intelligent agriculture.China is a large agricultural country,the pest causes the reduction of production and quality,resulting in the reduction of farmers'income,so the pest monitoring is particularly important.Traditional pest monitoring needs to rely on professional and technical personnel,resulting in a large amount of manpower and material resources,and can not meet the needs of timely pest monitoring.However,the AI-based bug situation monitoring system designed in this paper provides accurate prediction and intelligent decision-making for smart agriculture.The design takes the STM32F103 core board as the core,combines the image acquisition module,image processing module and image classification module,and adopts deep learning model to learn the captured insect body and form a training model.By recognizing the image of the insect body,the machine has the ability to recognize and judge different categories of the insect body.The results are transmitted to STM32 microcontroller for counting and processing operation,and then the species and quantity of insect are analyzed,and it has an important guiding significance for the comprehensive control of insect pestsand.