Crop Prediction System based on Soil and Weather Characteristics

India is mostly a farming country. Agriculture is vital to the Indian economy and humanity’s destiny. Agriculture also employs a sizable portion of the workforce. 70% of India’s rural population relies on agricultural activity for their livelihood. Crop output forecasting is one of the most sought-after and difficult tasks that any government can do. Any farmer wants to know how much crop production they might expect in the near future. Traditionally, while calculating yields, the farmer’s expertise of the crop and land was taken into account. Machine Learning algorithms can be used to extract accuracy as well as previously unknown patterns or information from massive datasets. As a result, crop output projections will help farmers choose the best crop for their farms. They could also generate a larger profit as a result of this. Multiple attribute selection techniques for crop prediction, as well as the Machine Learning methodology, are discussed in this work. This research study will discuss about the future path of agricultural output prediction systems near the end of the programme.