用机器人+传感器自动检测农田干湿，省时省力。
Automated Robotic Moisture Monitoring in Agricultural Fields
- 机器人根据传感器信号，用最短路径算法定位缺水区域
- 通过图像处理计算地块整体含水量，精度达标
- 适合大规模农场，降低人工巡检成本
在大规模种植园中监测土壤湿度是一项繁琐的工作。本项目旨在利用机器人套件与田间土壤湿度传感器协同工作，构建一个高效且经济的湿度监测系统。大田被划分为若干小网格，每个网格部署一个湿度传感器。当传感器检测到土壤干燥时，机器人会前往对应区域进行检查。通过在田地航拍图像上应用Dijkstra最短路径算法，确定前往目标区域的最优路径。随后，机器人使用合适的图像处理算法计算该区域的总含水量，并进行报告。为开发和测试本系统，搭建了一个小型试验田，在其上方安装了适当高度的摄像头以获取航拍视图。由此，成功实现了一种自动化农业田块湿度监测原型系统。
原文摘要 · Abstract (English)
Monitoring moisture level of land in a large-scale plantation is tedious. The main objective of this project is to use a robotic kit in collaboration with the on-field moisture sensor circuits, thereby creating an efficient and economical moisture monitoring system. A large agriculture field is divided into smaller grids. Each grid is placed with a moisture sensor. Whenever a sensor reports the soil to be dry, the robot goes to the concerned field for inspection. The path to the concerned field is found by applying Dijkstra's shortest path algorithm on the aerial image of the field. Then the total moisture content of the field is calculated by the robot using suitable image processing algorithms and reported accordingly. For developing and testing this work, a small study field was set up above which a camera was mounted at an appropriate height to capture its aerial view. Thus a prototype for an automated system of monitoring agricultural fields' moisture has been developed through this work.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。