deepaksaipendyala/crop-prediction-machine-learning-model

Crop Prediction

Problem Statement

50% of Indian population is dependent on agriculture for livelihood. One of the major factors that affect agriculture is the quality of soil. Soil supplies essential nutrients for the crop to grow and flourish. Choosing a crop that doesn't fit with the soil type not only degrades the quality and quantity of the crop , but also deteriorates the soil of its nutrients. Unhealthy crop patterns will also damage the quality of soil which in turn again affects the yield.

Our Solution

To tackle this problem, our team has come up with a project that could help people check the soil condition and also gives crop recommendations depending on the soil parameters like nutrients in the soil, moisture in soil and rainfall. This project is based on a highly trained ML model to keep the recommendation as accurate as possible. The solution can be easily implemented and accessed by people. The user have to enter the soil parameters to check his soil compatibility and it is absolutely cost effective.

Technical Stack Description

We obtained a dataset from Kaggle and then we took LightGBM classifying machine learning model and trained it using the dataset, later we created a website using HTML, CSS and JavaScript for front end and python flask for the backend, then we hosted our ML model on the website. The user should enter the soil parameters and a recommended crop will be displayed with given soil parameters on the website. User and Admin will get an email with same crop info only when name and email id is given.

Demonstration is live on Youtube

Input:

Output:

SO,

Head to ppt folder for more info!

Team members:

1. Pendyala Deepak Sai - Team Lead
2. Prem sundar B
3. Chekuri Rohan Karthikeya
4. Tadikamalla Gowtham Krishna

Mentor

1. Dr. Oruganti Venkata Ramana Murthy

Source and reference from Kaggle