Yigit Tuncel, T. Basaklar, Mackenzie M Smithyman, J. Dórea, Vinícius Nunes De Gouvêa, Younghyun Kim, Ümit Y. Ogras
{"title":"迈向智能养牛场:利用真实数据自动检查牛的健康状况","authors":"Yigit Tuncel, T. Basaklar, Mackenzie M Smithyman, J. Dórea, Vinícius Nunes De Gouvêa, Younghyun Kim, Ümit Y. Ogras","doi":"10.23919/DATE56975.2023.10137281","DOIUrl":null,"url":null,"abstract":"Cattle diseases have a significant negative impact not only on the animals' welfare but also on the economic performance of the cattle industry [1], [2]. For example, Bovine Respiratory Disease is responsible for approximately 75% of the morbidity and 57% of the mortality in US feedlots, which is estimated to cost the agriculture industry about $1B annually [1], [2]. The current management practice to diagnose and select cattle for treatment is a widespread clinical scoring system called DART (Depression, Appetite, Respiration, and Temperature). DART requires manual labor and skilled personnel, which is a limiting factor due to labor-shortage in several industry sectors, including agriculture [3]. Therefore, a continuous and automated IoT solution to predict the health state of a cow is a critical tool for the cattle industry.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards Smart Cattle Farms: Automated Inspection of Cattle Health with Real-Life Data\",\"authors\":\"Yigit Tuncel, T. Basaklar, Mackenzie M Smithyman, J. Dórea, Vinícius Nunes De Gouvêa, Younghyun Kim, Ümit Y. Ogras\",\"doi\":\"10.23919/DATE56975.2023.10137281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cattle diseases have a significant negative impact not only on the animals' welfare but also on the economic performance of the cattle industry [1], [2]. For example, Bovine Respiratory Disease is responsible for approximately 75% of the morbidity and 57% of the mortality in US feedlots, which is estimated to cost the agriculture industry about $1B annually [1], [2]. The current management practice to diagnose and select cattle for treatment is a widespread clinical scoring system called DART (Depression, Appetite, Respiration, and Temperature). DART requires manual labor and skilled personnel, which is a limiting factor due to labor-shortage in several industry sectors, including agriculture [3]. Therefore, a continuous and automated IoT solution to predict the health state of a cow is a critical tool for the cattle industry.\",\"PeriodicalId\":340349,\"journal\":{\"name\":\"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/DATE56975.2023.10137281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/DATE56975.2023.10137281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Smart Cattle Farms: Automated Inspection of Cattle Health with Real-Life Data
Cattle diseases have a significant negative impact not only on the animals' welfare but also on the economic performance of the cattle industry [1], [2]. For example, Bovine Respiratory Disease is responsible for approximately 75% of the morbidity and 57% of the mortality in US feedlots, which is estimated to cost the agriculture industry about $1B annually [1], [2]. The current management practice to diagnose and select cattle for treatment is a widespread clinical scoring system called DART (Depression, Appetite, Respiration, and Temperature). DART requires manual labor and skilled personnel, which is a limiting factor due to labor-shortage in several industry sectors, including agriculture [3]. Therefore, a continuous and automated IoT solution to predict the health state of a cow is a critical tool for the cattle industry.