The problem AGRICOL solves

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.

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.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.

In future, AgriCol can various agricultural related service so that farmers can get all the agri-related services in a single application. AI has a great potential to improve agriculture sector in India and it should be used in a right way to get a complete value from it.

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.