Climate Resilient Agriculture For Crop Prediction And Management Using Deep Learning

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This Prototype has been designed by Team Heathcliff as part of the Climate Data Hackathon organized under Indo Data Week 2022 for Climate resilient Agriculture.

Stubble Burning Smoke

We wanted to give an in-depth meaning for our team name, so we thought we would combine our other interests with the project we are doing. In an Anime called Sword Art Online, Heathcliff was the development director and GM (Game Master) of the VR game, Sword Art Online which became the foundation for the creation of AI. And Heath in Heathcliff is an area of open uncultivated land in its natural state. We thought this name is perfect for our platform.

All around the World, New Technologies like Artificial Intelligence (AI), Internet of Things (IOT) and Robotics Process Automations (RPA) have been evolving every single day, even as you are reading this right now. Data driven solutions or models seem to show a higher potential when it comes to improving Crop yield Reduction.

Challenge
One of the most crucial aim all around the world is to achieve climate resilient agriculture through data driven models. The challenge is to produce a solution that can be implemented in Telangana using various new technologies like Artificial Intelligence (AI), Internet of Things (IOT) and applied data science in general. In the search for finding innovative solutions, Climate Collective and The Government of Telangana posed us with this challenge in “Hackathon for Good”.

Crop growth is directly linked to various environmental factors such as climate change, pests attack and lack of nutrients, etc. which affects the farmers greatly and causes global demand of crop supply with an increase in price hike.

Crop yield reduction is like a Craquelure in a painting. Fixing the main cause of the problem provides us with myriad of other ways to solve the relating issues hence providing with a better quality in yield.

Innovations
Crop prediction model with 94 % accuracy rate is done by implementing neural networks where the model takes in the area (District, Mandal), soil type as inputs and we get the crop and the crop type that is suitable to grow in that area as an output.

Our platform provides comprehensive resources for farmers and anyone interested in crop cultivation, offering detailed information on crop types and their categories, suitable soil types, optimal growing seasons, and the appropriate sowing and harvesting periods. It also includes insights into common pests and the pesticides used to control them, steps for effective disease management, and guidelines outlining good and bad agricultural practices. Additionally, the platform covers soil nutrient information and suggests suitable crop rotation options to enhance soil fertility. To further support farmers, we offer access to essential agricultural products such as GMO seeds, fertilizers, and other inputs that improve crop quality and yield. Monthly surveys will be conducted to identify and address farmers’ needs before, during, and after crop production. Moreover, the integration of Natural Language Processing and Speech Recognition technologies ensures easy access and overcomes language and technological barriers, empowering farmers with seamless communication and support.