Intelligent Decision Support System for Smart Agriculture

Indian economy is mainly dependant on agriculture. Thus development in this field will highly contribute to the economic welfare. A large amount of uncertainty exists in agriculture during prediction of fertilizer, pesticide, watering requirement of every individual crop during various stages of its growth. Thus there is need to develop a system which will help farmer in producing quality and quantity crop production. Fuzzy inference based controller integrated with IOT can be implemented for better precision. The designed decision support system integrates various environmental factors such as moisture, temperature, soil nutrition level, pest sound frequency and soil PH to formulate and estimate individual crop watering requirement. System is smart enough to start and stop irrigation automatically considering human expert opinion learning through feedback provided. System will also provide alert and recommendation on water soluble fertilizer and pesticide requirement for individual crop. Soil condition can be analyzed for pre processing before prediction to determine water retention ratio, soil nutrition ratio so that the accuracy of the system can be increased. Geographic location based customized fertilizer, pesticide and watering need prediction can be used to make suitable predict for specific region and weather.