期刊文献+

山地花椒智能监控系统的研究与设计

Research and Design of Intelligent Monitoring System for Zanthoxylum bungeanum
下载PDF
导出
摘要 针对花椒种植过程中信息监控及智能分析不足的问题,论文设计开发了一套智能监控及分析系统。系统设计总体包括数据采集层、网络传输层、分析应用层。数据采集层中的各种传感器设备负责采集花椒的环境参数与图像数据,在网络传输层实现了有线及无线数据远距离传输,并对应用层进行分析,设计了系统6个模块。该系统在贵州晴隆花椒生产基地进行了安装、调试和部署。通过实地验证,该系统符合设计需求和各项指标,采用智能监控及分析系统使得花椒种植产量和质量得到了有效提升,节省了企业管理成本。 To address the issue of inadequate information monitoring and intelligent analysis during the cultivation of Zanthoxylum bungeanum,a comprehensive intelligent monitoring and analysis system was designed and developed in this study.The system design consisted of a data acquisition layer,a network transmission layer,and an analysis application layer.Different sensor devices within the data acquisition layer were tasked with gathering environmental parameters and image data of Z.bungeanum.These sensors facilitated the long-distance transmission of wired and wireless data in the network transmission layer,which was then analyzed in the application layer to design six modules of the system.The system was installed,commissioned,and then deployed at the Qinglong pepper production base in Guizhou.After conducting field verification,it was confirmed that the system successfully met the design requirements and various indicators.The intelligent monitoring and analysis system has significantly enhanced the yield and quality of Z.bungeanum cultivation,resulting in cost savings for the enterprise in terms of management expenses.
作者 徐杨 黄易仟 李论 蒋林 Xu Yang;Huang Yiqian;Li Lun;Jiang Lin(School of Big Data and Information Engineering,Guizhou University,Guiyang 550025,Guizhou,China;Guizhou Xuande Zanthoxylum Industry Development Co.,Ltd.,Guiyang 550018,Guizhou,China)
出处 《山地农业生物学报》 2024年第3期33-40,共8页 Journal of Mountain Agriculture and Biology
基金 贵州省科技计划项目(黔科合支撑[2021]一般176)。
关键词 山地花椒 深度学习 智能监控 Zanthoxylum bungeanum deep learning intelligent surveillance
  • 相关文献

参考文献10

二级参考文献99

  • 1王卓,王健,王枭雄,时佳,白晓平,赵泳嘉.基于改进YOLO v4的自然环境苹果轻量级检测方法[J].农业机械学报,2022,53(8):294-302. 被引量:36
  • 2成芳,应义斌.基于Matlab平台的稻种图像分析系统[J].浙江大学学报(农业与生命科学版),2004,30(5):572-576. 被引量:9
  • 3凌云,王一鸣,孙明,孙红,张小超.基于机器视觉的大米外观品质检测装置[J].农业机械学报,2005,36(9):89-92. 被引量:42
  • 4赵玉霞,王克如,白中英,李少昆,谢瑞芝,高世菊.贝叶斯方法在玉米叶部病害图像识别中的应用[J].计算机工程与应用,2007,43(5):193-195. 被引量:27
  • 5Hou Z J, Wei G W. A new approach to edge detection[J]. Pattern Recognition, 2002, 35: 1559-1570.
  • 6Shahin Mulaammad A, Symons Stephen J, Poysa Vaino W. Determining soya bean seed size uniformity with image analysis[J]. Biosystems Engineering, 2006, 94(2): 191-198.
  • 7中华人民共和国林业行业标准-花椒等级质量(LY/T1652-2005).
  • 8Yud-Ren Chen, Kuanglin Chao, Kim Moon S. Machine vision technology for agricultural applications[J]. Computers and Electronics in Agriculture, 2002, 36:173-191.
  • 9Liao K, Paulsen M R, Reid J F, et al. Corn kernel breakage classification by machine vision using a neural network classifier[J]. Transactions oftheASAE, 1994, 36(6): 1949-1953.
  • 10Bennedsen B S, Peterson D L. Performance of a System for Apple Surface Defect Identification in Near-infrared Images[J]. Biosystems Engineering, 2005, 90(4): 419-431.

共引文献44

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部