{"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}
引用次数: 0
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.