FarmWise: Crop Cultivation Analysis using Image Recognition and ArcGIS Mapping

India’s agriculture industry, which employs 58% of the workforce, continues to be the foundation of the country’s society. There are various families whose daily income and livelihood are dependent on their everyday farming activities. Yet not all the farmers in the country understand what kind of crops need to be grown in the ever-changing weather conditions and locations. There is a lack of platforms that help the farmers to check the nearest freshwater resources and how that is going to affect their growth costs. Thus, there is a need for a system that considers such parameters to receive a better yield. This paper proposes a novel approach for crop selection and yield prediction for farmers using machine learning algorithms. The system makes use of image recognition to find a given crop, fetches the current weather conditions based on the location of the farmer, and makes use of regression analysis to find the ideal crop and feasibility of the crop cultivation. It makes use of ArcGIS to understand the geospatial landscape around the given area to give a gradient-based colored output of the proximity to the nearest freshwater resource. Overall, the model achieved great accuracy in prediction and was successful in providing basic yield-based financial information for a given crop and location. This in turn would help farmers to maximize their crop yields and profits while minimizing the risks associated with crop failure.