Leveraging Digital Image Processing and Machine Learning for Precision Farming and Loan Prediction

The agricultural sector is the cornerstone of the economy of any country and also makes the country largely self-sufficient in staple food production, such as rice, wheat, and pulses. The crop production has seen a decline over the previous years due to climate changes and soil degradation. The lack of access to emerging technologies that can provide insightful information for precision farming and hence, increase productivity is a need that has to be addressed. This paper aims to help the Indian farmers who face numerous challenges, including soil variability, crop selection, revenue prediction, and access to financial resources by applying digital image processing and advanced machine learning models. It makes use of Digital Image processing for soil classification and CNN Model for crop recommendation. It also provides crop recommendations based on soil nutrients and pH levels with the help of a decision tree model. The ML Model for revenue prediction and loan eligibility assessments further assist farmers in financial planning. Additionally, to make the features easy to use and accessible, a mobile application is being developed.