An Intelligent Crop Cultivation Prediction System

Abstract

Agriculture has a significant role to play in the economic development of India and the farmer community is the back bone of the agriculture sector. The researcher has developed an intelligent environment in the form of Agriculture Intelligence . Such environment is composed of three components i) Pre-processing and Data Storage, ii) Mathematical Model and iii) Knowledge Presentation. This environment predicts the future market price of an agriculture commodity before the time of crop cultivation. The researcher started experiments using Time Series Analysis and has been continuing towards MLR using meteorological parameters Humidity , Rainfall , Temperature and fiscal parameter Old Supply of last year. The researcher has experimentally introduced a Fitness Factor-and#945; to refer to intelligence. The performance of the model was evaluated by comparing the outputs of the model with the actual data. In spite of highly volatile environment in agribusiness, the researcher has been able to achieve more than 80% accuracy in all selected agriculture commodities. newline newlineThis intelligent system Pre-process data, available from heterogeneous data sources, utilises Mathematical Model s expertise and presents output in the form of knowledge in knowledge presentation. Agriculture Stake holders in the form of knowledge consumer, apply Crop Cultivation related query and gain generated knowledge in this segment of knowledge presentation. newlineThis Agriculture Intelligence helps the farmer community in their decision making of farm management and agribusiness activities such as i) Predicting agriculture commodity market price before cultivation, ii) Determining best choice of cultivars to plant in their farm iii) Determine optimum cultivation date iv) Investment Prioritising v) Evaluate demand and supply risk and vi) Evaluate weather risk. It also newlinehelps other agriculture stake holders such as Agriculture Broker and intermediates in i) Determine optimum purchase period and quantity of the agriculture commodity ii) Evaluate agriculture