Prototype for a real-time crop recommendation algorithm in Python using Machine Learning and Data Analytics. This work presents a system, in form of a website. The business logic in Python uses Machine Learning techniques in order to predict the most profitable crop in the forecasted weather and soil conditions at a specified location. The proposed system will integrate the data obtained from soil, crop repository, weather department and by applying machine learning algorithm: Multiple Linear Regression, a prediction of most suitable crops according to current environmental conditions is made. This provides a farmer with variety of options of crops that can be cultivated.
The business logic can be located in /code/mlr_algo.py directory. The server is programmed using node.js. To execute the project you just need to run the node.js- 'server.js' script and navigate to the displayed ip address on the prompt to access the system.
Python package Stack: scikit-learn, pandas. Web development technologies: HTML, CSS, JavaScript. All the necessary datasets are included in the repository itself.
Project Walkthrough: https://www.youtube.com/watch?v=7zR-3olbr9E&t=186s
Contributors, Omkar Buchade, Nilesh Mehta, Shubham Ghodekar.
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