{"title":"提高泰国清莱小型养牛场主的智能农业能力","authors":"Bunyarat Umsura, Kamonlak Chaidee, Kingkan Puansurin, Dueanpen Manoruang, Pornthipat Wimooktayone, Kanjana Boontasri, Wisoot Kaenmueng","doi":"10.37936/ecti-cit.2024181.253823","DOIUrl":null,"url":null,"abstract":"This research aims to develop an IoT-driven smart farming system for beef cattle management in Chiang Rai Province, Thailand. The system empowers small-scale farmers by enabling precise criteria for cattle care, optimized feeding, growth monitoring, breeding analysis, and cost estimation through WSN and cloud-based platforms. The sensors gather raw data on consumption from the feeding troughs and then transmit it to the cloud-based platform. Consumption data is then analyzed using Linear Regression Analysis. Key findings indicate a substantial correlation (0.995) between feed quantity and cattle weight gain, with a predictive capability of 99%. This system enhances precision and decision-making in cattle farming, offering significant benefits to small-scale farmers in the region.","PeriodicalId":507234,"journal":{"name":"ECTI Transactions on Computer and Information Technology (ECTI-CIT)","volume":" 29","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing Smart Farming Capabilities for Small-Scale Cattle Farmers in Chiang Rai, Thailand\",\"authors\":\"Bunyarat Umsura, Kamonlak Chaidee, Kingkan Puansurin, Dueanpen Manoruang, Pornthipat Wimooktayone, Kanjana Boontasri, Wisoot Kaenmueng\",\"doi\":\"10.37936/ecti-cit.2024181.253823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research aims to develop an IoT-driven smart farming system for beef cattle management in Chiang Rai Province, Thailand. The system empowers small-scale farmers by enabling precise criteria for cattle care, optimized feeding, growth monitoring, breeding analysis, and cost estimation through WSN and cloud-based platforms. The sensors gather raw data on consumption from the feeding troughs and then transmit it to the cloud-based platform. Consumption data is then analyzed using Linear Regression Analysis. Key findings indicate a substantial correlation (0.995) between feed quantity and cattle weight gain, with a predictive capability of 99%. This system enhances precision and decision-making in cattle farming, offering significant benefits to small-scale farmers in the region.\",\"PeriodicalId\":507234,\"journal\":{\"name\":\"ECTI Transactions on Computer and Information Technology (ECTI-CIT)\",\"volume\":\" 29\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ECTI Transactions on Computer and Information Technology (ECTI-CIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37936/ecti-cit.2024181.253823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ECTI Transactions on Computer and Information Technology (ECTI-CIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37936/ecti-cit.2024181.253823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing Smart Farming Capabilities for Small-Scale Cattle Farmers in Chiang Rai, Thailand
This research aims to develop an IoT-driven smart farming system for beef cattle management in Chiang Rai Province, Thailand. The system empowers small-scale farmers by enabling precise criteria for cattle care, optimized feeding, growth monitoring, breeding analysis, and cost estimation through WSN and cloud-based platforms. The sensors gather raw data on consumption from the feeding troughs and then transmit it to the cloud-based platform. Consumption data is then analyzed using Linear Regression Analysis. Key findings indicate a substantial correlation (0.995) between feed quantity and cattle weight gain, with a predictive capability of 99%. This system enhances precision and decision-making in cattle farming, offering significant benefits to small-scale farmers in the region.
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