人工智能辅助下的远程农田监测系统的设计与研发

Design and development of remote farmland monitoring system assisted by artificial intelligence

人工智能技术对智慧农业的影响非常深远。针对传统智慧农业,人工智能的加入不仅能为使用者提供直观的作物数据,还可以对获取的数据进行深度学习,以获得更加精细的内容。文章以STM32F103为主控芯片,搭配一系列传感器和无线通信模块,首先将获取到的数据上传至云平台OneNET,其次搭配YOLOv9和MLP模型对相应的数据进行深度学习,旨在将学习结果反馈给使用者。

The impact of artificial intelligence technology on smart agriculture is very profound.For traditional smart agriculture,the addition of artificial intelligence not only provides users with intuitive crop data,but also enables deep learning of the obtained data to obtain more refined content.This article uses STM32F103 as the main control chip,paired with a series of sensors and wireless communication modules.Firstly,the obtained data is uploaded to the cloud platform OneNET.Secondly,YOLOv9 and MLP models are used to perform deep learning on the corresponding data,aiming to provide feedback to the user on the learning results.