中国农业机械化科学研究院集团有限公司 主管

北京卓众出版有限公司 主办

面向智慧农业的多功能自主巡检系统研究与实现

Research and implementation of multifunctional autonomous inspection system for smart agriculture

  • 摘要: 随着现代农业的快速发展,传统人工巡检方式已难以满足大规模智能化农业生产的需求。针对这一问题,设计并实现一种基于Arduino单片机控制的智能巡检小车系统。该系统集成多项关键技术:通过红外传感器和舵机实现自动导航;配备OV2710型高清摄像头采集农作物生长状态;双重避障技术将红外与超声波优势互补,能更好地适应各种农业环境条件;集成温湿度等环境监测传感器,实现农田环境的全面监控。采用WiFi无线传输技术,将采集的图像和环境数据实时上传至云平台,用户可随时远程查看农田状况。为解决续航问题,配备太阳能供电模块,在光照充足条件下可持续工作8 h以上。该系统还支持GPS定位功能,确保巡检路径的准确性和可追溯性。试验结果表明,该系统能够稳定可靠地完成农田环境远程监控任务,适用于农场、果园和温室大棚等多种农业生产场景,不仅提升农业巡检的效率和精度,还为农业生产管理提供实时、准确的数据支持,是一种高效、经济的智慧农业解决方案。

     

    Abstract: With modern agriculture rapid development, traditional manual inspection method has been difficult to meet large-scale intelligent agricultural production needs.To address this problem, an intelligent inspection trolley system controlled by an Arduino microcontroller has been designed and realized.System integrated multiple key technologies.Automatic navigation was achieved through infrared sensors and servos.An OV2710 high-definition camera was equipped to collect crop growth status.Double obstacle avoidance technology combined infrared and ultrasonic advantages, so that system could better adapt to various agricultural environmental conditions.Environmental monitoring sensors for temperature and humidity sensors were integrated to achieve a comprehensive monitoring for farmland environment.System adopted WiFi wireless transmission technology to upload collected images and environmental data to cloud platform in real time, enabling users to remotely view farmland conditions anytime.To solve battery life concerns, a solar power supply module was equipped, which can work continuously for more than 8 hours under sufficient sunlight conditions.In addition, system also supported GPS localization to ensure inspection path accuracy and traceability.Experimental results showed that intelligent inspection system stably and reliably fulfilled remote monitoring tasks for farmland environment, and it was applicable to diverse agricultural production scenarios such as farms, orchards and greenhouses.System not only significantly improved agricultural inspection efficiency and accuracy, but also provided real-time and accurate data support for agricultural production management, establishing an efficient and economical solution for intelligent agriculture.

     

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