AGRICOL

Cover image
Dashboard page
crop plan with success rates
Data flow diagram

Inspiration

The knowledge and infrastructural gaps, particularly in rural regions, are the major problems affecting Indian agriculture today. Infrastructure issues with regard to markets, transportation, and irrigation all significantly increase the cost of farming. The absence of delivery systems is another problem. There are several programmes designed to advance agriculture. In terms of boosting productivity, cutting costs, or improving price realisation on the ground, we lack efficient delivery systems that may convert into efficient facilitation. Crop planning is also an other important problem in agriculture sector. That is, to select proper set of crops to be cultivated at particular season for maximization of yield and minimization of crop wastage.A crop plan is complete only when it contains the following factors,such as pH of soil,temperature,humidity,climatic details,etc..The existing crop planning application does not met the desired accuracy level.AgriCol comes here with a solution.

What it does

AgriCol is an AI based guiding application that provides a complete crop plan for farmers(from sowing to harvesting) thereby enhancing the life of farmers.The crop plan includes the success rate of crops at particular season, information about irrigation,crop and pest management.We also provide 24/7 customer support to farmers.Chatbot feature is also available and it is trained for agricultural related activities.Overall, it improves the life of farmers and brings up a reform in agricultural sector.

How we built it

AgriCol uses Random forest classification algorithm where the accuracy of crop selection is more than 85%.We have developed AgriCol as an MERN stack application to provide better user experience to farmers.

Challenges we ran into

Agricol is an AI based application. So we faced a challenge to select the correct data and dataset to train a model.This should be done right to achieve proper crop planning.Another task is to select the correct classification algorithms.Mostly Decision tree algorithm is used for crop selection and recommendation system.The accuracy for these applications is very less.So we have used RANDOM FOREST algorithm to improve the accuracy of crop selection.

Accomplishments that we're proud of

We are proud of bringing out something useful for the Indian Farming Community with available technology to enhance their life.

What we learned

Building a MERN stack application is overall a nice experience and also we have learnt lot about how to integrate frontend and backend.We also experienced the machine learning art.