{"title":"利用区块链技术实现高效农业交易的分散式预测系统","authors":"Remegius Praveen Sahayaraj, Muthurajkumar Sannasy","doi":"10.24846/v31i3y202212","DOIUrl":null,"url":null,"abstract":": Agriculture is an art, a craftsmanship and a scientific way of cultivation, growth and maintenance of edible crops and livestock. Majority of the current farming communities do not have prior knowledge of predicting the suitable crop for their soil and climatic conditions. Difficulty in raising the initial investment for crop cultivation is also one of the serious concerns of these communities. The difficulties faced by the civic agriculture, the insecure monetary transactions, along with the concerns related to the financial process have been identified and listed. The paper proposes a feasible solution by predicting the appropriate crops that could be grown in a specific scenario or environmental conditions using the machine-learning model of Support Vector Classifier and provides data related to quality yields using Fuzzy Decision Merkle Tree (FDMT) Regressor. Additionally, a transparent and secure fund transfer mechanism is provided using Ethereum blockchain-based technology. The proposed model implements a secured, translucent and tamper-resistant digital platform for the farming communities to host their products. A fortified consensus can be formed between the farmer and the investor bounded with a rating mechanism to build the credibility of both the farmer and the investor 7 based on the prior knowledge obtained in the Agri-market.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Decentralised and Predictive System for Efficient Agri-Transactions Through Blockchain Technology\",\"authors\":\"Remegius Praveen Sahayaraj, Muthurajkumar Sannasy\",\"doi\":\"10.24846/v31i3y202212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Agriculture is an art, a craftsmanship and a scientific way of cultivation, growth and maintenance of edible crops and livestock. Majority of the current farming communities do not have prior knowledge of predicting the suitable crop for their soil and climatic conditions. Difficulty in raising the initial investment for crop cultivation is also one of the serious concerns of these communities. The difficulties faced by the civic agriculture, the insecure monetary transactions, along with the concerns related to the financial process have been identified and listed. The paper proposes a feasible solution by predicting the appropriate crops that could be grown in a specific scenario or environmental conditions using the machine-learning model of Support Vector Classifier and provides data related to quality yields using Fuzzy Decision Merkle Tree (FDMT) Regressor. Additionally, a transparent and secure fund transfer mechanism is provided using Ethereum blockchain-based technology. The proposed model implements a secured, translucent and tamper-resistant digital platform for the farming communities to host their products. A fortified consensus can be formed between the farmer and the investor bounded with a rating mechanism to build the credibility of both the farmer and the investor 7 based on the prior knowledge obtained in the Agri-market.\",\"PeriodicalId\":49466,\"journal\":{\"name\":\"Studies in Informatics and Control\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies in Informatics and Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.24846/v31i3y202212\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in Informatics and Control","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.24846/v31i3y202212","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Decentralised and Predictive System for Efficient Agri-Transactions Through Blockchain Technology
: Agriculture is an art, a craftsmanship and a scientific way of cultivation, growth and maintenance of edible crops and livestock. Majority of the current farming communities do not have prior knowledge of predicting the suitable crop for their soil and climatic conditions. Difficulty in raising the initial investment for crop cultivation is also one of the serious concerns of these communities. The difficulties faced by the civic agriculture, the insecure monetary transactions, along with the concerns related to the financial process have been identified and listed. The paper proposes a feasible solution by predicting the appropriate crops that could be grown in a specific scenario or environmental conditions using the machine-learning model of Support Vector Classifier and provides data related to quality yields using Fuzzy Decision Merkle Tree (FDMT) Regressor. Additionally, a transparent and secure fund transfer mechanism is provided using Ethereum blockchain-based technology. The proposed model implements a secured, translucent and tamper-resistant digital platform for the farming communities to host their products. A fortified consensus can be formed between the farmer and the investor bounded with a rating mechanism to build the credibility of both the farmer and the investor 7 based on the prior knowledge obtained in the Agri-market.
期刊介绍:
Studies in Informatics and Control journal provides important perspectives on topics relevant to Information Technology, with an emphasis on useful applications in the most important areas of IT.
This journal is aimed at advanced practitioners and researchers in the field of IT and welcomes original contributions from scholars and professionals worldwide.
SIC is published both in print and online by the National Institute for R&D in Informatics, ICI Bucharest. Abstracts, full text and graphics of all articles in the online version of SIC are identical to the print version of the Journal.