Modelling Agriculture Productivity and Spotting Diseases using Deep Learning and Image Processing

Agriculture plays a major role in economy of INDIA. Overall, 75% of population in INDIA are depended on agriculture. Agriculture in INDIA is comprised of different types of crops like rice, wheat, oilseeds. which are very important in our day-to-day lives. Not only for consuming some crops like cotton, jute is used for commercial purposes which are very important for the growth factor of the Indian economy. Now-a- days the productivity of crops is been reducing which shows a major impact on our country growth factor. The major reasons for this rise of population bywhich most of the agricultural productivity per hector is been decreasing. Natural resources are being heavily utilized, excessive use of automobiles and increase of factories, industries lead to massive pollution. As farming is the vital occupation of every country, the GDP of the country depends mostly on the agriculture sector. The agriculture products are totally relied on the final market price. We can produce healthy and good crop by taking good care of them. In order to supervise the crops, there are many techniques such as AI (Artificial intelligence). We have gone through some of the techniques of AI such as deep learning and Optimized ANN (Artificial neural networks) and knowledge on how we can enhance the crop production using AI. The Whale Optimization Algorithm (WOA) is used to choose the essential characteristics once the data has been merged for preprocessing and pertinent features have been extracted. he models currently in use for plant disease identification. The proposed model demonstrated a notable improvement in F1-measure, Precision, Recall, and Accuracy performance. So, to prevent all these consequences we are going to develop a system where a farmer can easily model the productivity and can identify the diseases for with which crops are affected