The problem FarmAid Application solves

The track for our chosen problem is Sustainable Development. Agriculture plays a vital role in the Indian economy with over 70% of rural households depending on it. It contributes about 18% of the total GDP and provides employment to over 60% of the population. Crop monitoring can improve food security and help prevent famines and tackle climate change in India.
However, there is no proper agriculture-based and crop yield management software for admin officials of various Indian states. Hence, coming up with a proper procurement plan after harvesting is a problem. Farmers don’t have an all-inclusive platform for suggesting soil-wise crops, government schemes, pest control, and other vital agricultural information.

We propose to build two Applications - FarmAid and Krishi Sahayta App catering to Government officials and Farmers respectively.

FarmAid - A platform that helps govt. officials to get insights over the future yields for particular crops in their district to help them with better procurement plans and deploy logistics with detailed statistics. Resource management, transport of goods is hence more efficient.

Krishi Sahayta - A platform that helps farmers understand their crops choice and improve financial growth with simple, to the point observations.
It has various insights about govt. schemes, best crops for a particular crop, how to cure crop diseases, and best selling strategies to maximize profit.
It also has a multilingual chatbot that answers user queries regarding best farming practices, current government schemes, MSP of a crop, nearest markets etc.

Challenges we ran into

Collection of the required Dataset and Structuring of Dataset along with Data Engineering for all the states was a huge task. Even dealing with missing values of NDVI required some thought processes.
All our Models were finished on time within the span of the hackathon.
Writing API calls and functions for these Models was a bit tricky as we had to learn Flask and we had not used it before. Faced delayed responses from API and RAM usage was more so deployed Flask API on Azure Platform instead of Heroku for better computation power. Had to perform research for content in Hindi and English for ChatBot and Krishi Sahayta App with agri information.