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作 者:秦琳琳[1] 黄云梦 吴刚[1] 石春[1] QIN Linlin;HUANG Yunmeng;WU Gang;SHI Chun(Department of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China)
机构地区:[1]中国科学技术大学信息科学技术学院,合肥230027
出 处:《农业机械学报》2021年第1期303-311,共9页Transactions of the Chinese Society for Agricultural Machinery
基 金:国家重点研发计划项目(2017YFB0602704-2)。
摘 要:根据现代温室监控和管理的需求,基于Android系统开发了温室设备的状态监控模块,采用CAN总线测控系统对温室内外环境数据进行实时采集并对温室环境设备进行控制。基于Android开发的系统软件具有远程监控的功能。根据摄像头提供的实时视频数据,对图帧间差分法和自相关函数法应用于温室风机停转状态的监测以及背景差分法和Canny边缘检测算法应用于温室天窗开度状态的监测进行研究,比较不同算法的实时性和准确性,实现了温室通风设备风机和天窗状态的异常监测。试验表明,系统数据传输稳定、环境调控可靠、视频图像清晰流畅,能够实时可靠地监测设备的运行状态,且操作简单、界面友好,保证了温室通风设备自动控制的安全性,能够满足远程智能监控现代温室的需求。According to the requirements of modern greenhouse monitoring and management,the status monitoring module of greenhouse devices was developed based on Android system.CAN bus system was used for the real-time environmental data acquisition and environmental devices control in greenhouse.The system software was developed based on Android operating system and it had the function of remote monitoring.Based on the real-time video data provided by the camera,different image recognition technologies were studied in the status detection of greenhouse devices to implement abnormal monitoring of fan and vent status of greenhouse ventilation devices.The frame subtraction method and autocorrelation function were used in the detection of fan switch.The background subtraction method and Canny edge detection were studied to detect the opening status of ventilation window.The real-time and accuracy of different algorithms were compared.Test results showed that the system data transmission was stable,the environmental regulation was reliable,the video image was clear and smooth,and the devices status can be detected in real time and reliably.The operation of the status monitoring module of greenhouse ventilation devices was simple and the interface was friendly,which guaranteed the safety of automatic control of greenhouse ventilation devices and realized the requirements of remote intelligent monitoring in modern greenhouses.
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