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《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:

期数:

2025年02期

页码:

48-53

栏目:

出版日期:

2025-04-15

文章信息/Info

Title:

Design and application of a remote greenhouse monitoring system based on LoRa and NB-IoT

文章编号:

1000-0682（2025）02-0048-06

作者:

顾志强; 朱武; 王光东

（1.上海电力大学 电子与信息工程学院，上海 200090；2.国网上海电力崇明供电公司，上海 201250）

Author(s):

GU Zhiqiang;  ZHU Wu;  WANG Guangdong

(1.School of Electronic and Information Engineering,Shanghai University of Electric Power,Shanghai 200090,China；2.State Grid Shanghai Electric Power Chongming Supply Company, Shanghai 201250,China)

关键词:

温室; 远程监控; 图像采集; YOLOv8; 叶片病虫害

Keywords:

greenhouse; remote monitoring; image capture; YOLOv8; leaf pests and diseases

分类号:

TP277TP399

DOI:

10.19950/j.cnki.CN61-1121/TH.2025.02.009

文献标志码:

A

摘要:

为了提升农业远程监控系统的数据可视化与信息化水平，该文设计了一种集成环境因子采集、图像采集、无线通信和远程监控的温室监控系统。该系统利用嵌入式微处理器采集环境因子数据，采用ESP32CAM搭载OV2640摄像头采集叶片病虫害图像，通过LoRa和NB-IOT进行组网，将数据上传至云服务器，并通过基于B/S架构的监控平台实现温室数据上传与控制命令下发。系统结合YOLOv8目标检测算法，对采集的病虫害图片进行识别，以预防病虫害对温室作物产生的不利影响。测试结果显示，在3000米范围内，LoRa通信成功率达到98%。经过验证，系统运行稳定可靠，能够实现温室的远程监控与应用。

Abstract:

To enhance the data visualization and informatization levels of agricultural remote monitoring systems, this paper designs an integrated greenhouse monitoring system. The system combines environmental factor collection, image acquisition, wireless communication, and remote monitoring. An embedded microprocessor is used to collect environmental data, while an ESP32CAM with an OV2640 camera captures images of leaf pests and diseases. LoRa and NB-IoT technologies are employed for networking, enabling data upload to a cloud server. A B/S architecture-based monitoring platform facilitates data upload and control command issuance for the greenhouse. The system incorporates the YOLOv8 object detection algorithm to identify pests and diseases in the collected images, preventing potential adverse effects on greenhouse crops. Test results demonstrate that within a range of 3000 meters, the LoRa communication success rate reaches 98%. Validation tests confirm the system’s stable and reliable operation, making it effective for remote greenhouse monitoring and applications.

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备注/Memo

备注/Memo:

收稿日期：2024-07-11第一作者：顾志强（1998—），男，安徽阜阳人，硕士，主要研究方向为物联网与计算机视觉。E-mail：1241692955@qq.com通信作者：朱武（1969—），男，湖北随州人，博士，教授，主要研究方向为信号处理、检测技术、电器设备故障诊断。E-mail：zjmzwsy@126.com

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更新日期/Last Update: 1900-01-01