eco-tree Web Application

About

eco-tree is a machine learning based web application build using Angular-14 and Flask. eco-tree is used for recommending Crop and Fertilizers based on the soil features. The application used three accuractely predciting models to make the final predictions. The link for the python notebooks containing the implementation for the models are present in the All Links section of this Readme.

An API was built using Flask and was deployed on AWS. This Flask API is used to get the recommendation made by the machine learning models in JSON format. The input data is sent as a POST request to the API to get the predicted information.

Angular-14 was used to build the frontend part of the application. MaterialUI was used for frontend part of the web application.

Deployed Web Application Link: http://ecotree-app.s3-website.ap-south-1.amazonaws.com/

Flask API End Points

Crop Recommendation End Point: http://ecotreeappfive-env.eba-hphdscvg.ap-south-1.elasticbeanstalk.com/predict_crop
Fertilizer Recommendation End Point: http://ecotreeappfive-env.eba-hphdscvg.ap-south-1.elasticbeanstalk.com/predict_fertilizer

About Data returned by Flask API

The data is returned in JSON format:

For Crop Recommendation

{
    xgb_model_prediction: "rice",
    xgb_model_probability: 99.2%,
    rf_model_prediction: "rice",
    rf_model_probability: 99.3%,
    knn_model_prediction: "rice",
    knn_model_probability: 99.5%,
    final_prediction: "rice",
}

For Fertilizer Recommendation

{
    xgb_model_prediction: "Urea",
    xgb_model_probability: 99.2%,
    rf_model_prediction: "Urea",
    rf_model_probability: 99.3%,
    svm_model_prediction: "Urea",
    svm_model_probability: 99.5%,
    final_prediction: "Urea",
}

Note: This API can be used in your Web Application or Mobile Application by just sending a POST request with the necessary input data to the above mentioned end points.