Crop Recommendation and Disease Prediction System

Crop Recommendation and Disease Prediction System

Sarvesh Lele1, Nihal More2, Raj Malekar3, Rohit Londhe4

Prof Kiran Thoke (BE, ME, PhD (Pursuing)) 5

1-4Dept. of Computer Engineering, KJCOEMR, Pune

 5Professor, KJ College of Engineering and Management Research

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Abstract - India is the seventh largest country in the world speaking of land area, covering a total of 3.288 million square kilometres. The agricultural exports from India for the FY 2022 is $50.21B. The government has launched various initiatives to help the farmers and the agricultural sector. With the advent of technology and the availability of large-scale agricultural data, there is an opportunity to leverage machine learning and data analytics techniques to promote better agricultural practices. With this project we aim to leverage the offerings of Machine Learning to help the agriculture sector in India, and help the farmers choose a crop to grow based on the weather conditions. We also aim to predict and determine whether a crop has caught a disease or illness and if yes, which disease, with the help of Machine Learning and Deep Learning algorithms.

Key Words - Crop Recommendation, Crop Disease Detection, Farmers, Machine Learning, Deep Learning, Agriculture