{"title":"KrishiMantra: agricultural recommendation system","authors":"Vikas Kumar, V. Dave, R. Bhadauriya, S. Chaudhary","doi":"10.1145/2442882.2442933","DOIUrl":null,"url":null,"abstract":"With the evolution of Web 2.0, ICT has become the primary need of human beings. There is a gap between the farmers and the knowledge of agricultural experts. ICT can fill the gap between farmers and the experts. In this paper, we have proposed a semantic web based architecture to generate agricultural recommendations, using spatial data and agricultural knowledge bases. Our knowledge base acts as a domain expert and will send recommendations to the farmers based on climate conditions and geographic data. We have shown experimental results as a part of implementation of our proposed architecture. A farmer sends a query to the query engine, in order to get information for a specific crop. Query may be related to GIS data, crop knowledge base or both. The result of the query is displayed on a mobile device.","PeriodicalId":240004,"journal":{"name":"ACM DEV '13","volume":"133 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM DEV '13","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2442882.2442933","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
With the evolution of Web 2.0, ICT has become the primary need of human beings. There is a gap between the farmers and the knowledge of agricultural experts. ICT can fill the gap between farmers and the experts. In this paper, we have proposed a semantic web based architecture to generate agricultural recommendations, using spatial data and agricultural knowledge bases. Our knowledge base acts as a domain expert and will send recommendations to the farmers based on climate conditions and geographic data. We have shown experimental results as a part of implementation of our proposed architecture. A farmer sends a query to the query engine, in order to get information for a specific crop. Query may be related to GIS data, crop knowledge base or both. The result of the query is displayed on a mobile device.