{"title":"基于 OpenMV 的作物异常预警系统","authors":"Sitan Shen","doi":"10.56028/aetr.9.1.665.2024","DOIUrl":null,"url":null,"abstract":"In order to realize the early warning of abnormal crops, the photographing technology and image recognition technology of openMV and openCV are comprehensively applied to study the early warning of abnormal crops. The design take photos using openMV hardware platform and connects to the cloud through 5G module. Then it conducts in-depth processing such as gray processing, image denoising and boundary detection on the photos through the network server to obtain the location and size of abnormal areas, so as to help spray pesticides later and improve production efficiency.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"55 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Abnormal crop warning system based on OpenMV\",\"authors\":\"Sitan Shen\",\"doi\":\"10.56028/aetr.9.1.665.2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to realize the early warning of abnormal crops, the photographing technology and image recognition technology of openMV and openCV are comprehensively applied to study the early warning of abnormal crops. The design take photos using openMV hardware platform and connects to the cloud through 5G module. Then it conducts in-depth processing such as gray processing, image denoising and boundary detection on the photos through the network server to obtain the location and size of abnormal areas, so as to help spray pesticides later and improve production efficiency.\",\"PeriodicalId\":355471,\"journal\":{\"name\":\"Advances in Engineering Technology Research\",\"volume\":\"55 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Engineering Technology Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56028/aetr.9.1.665.2024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Engineering Technology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56028/aetr.9.1.665.2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In order to realize the early warning of abnormal crops, the photographing technology and image recognition technology of openMV and openCV are comprehensively applied to study the early warning of abnormal crops. The design take photos using openMV hardware platform and connects to the cloud through 5G module. Then it conducts in-depth processing such as gray processing, image denoising and boundary detection on the photos through the network server to obtain the location and size of abnormal areas, so as to help spray pesticides later and improve production efficiency.