An information-based decision support framework for eAgriculture
International Association for the Scientific Knowleldge
Faculty of Computing, Health and Science
School of Computer and Security Science
The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. An inconsistency in information delivery and standards for the integration of information also limits the decision making process. Knowledge Discovery in Databases (KDD) methodology described for the data mining is an example of how frameworks can be used to facilitate such data integration. This research will examine how such a ICT based framework can be used to facilitate the acquisition of knowledge for the farmer decision making process. The Farmer Knowledge and Decision Support Framework (FKDSF) takes information provided to farmers and utilizes processes that deliver this critical information for knowledge acquisition. This framework describes steps for data capture, analysis and data processing which precede the delivery of the integrated information for the farmer. Information is collected from disparate sources, captured and validated according to defined rules. Data mining tools then process and integrate the data into a format that contributes to the knowledge base that can be readily used by the farmer. This research paper will show how the proposed framework may be used for farmer knowledge acquisition using simulated data and discusses how it can be used in an agricultural industry context.