Farmer Helper System

Inspiration

Unawareness among farmers about the type of crop they should sow for maximum yield , due to lack of information and technological resources.

What it does

It gives recommendation to the farmer of a particular region regarding which crop to grow at the current time for maximum profit and better yield.The web application is farmer friendly as it requires no input and returns a Hindi-audio output for their better understanding.

How I built it

Using the dataset that had values about district wise ,season wise crop yield for the past 15 years for training a Gaussian Process model, through machine learning. We used Flask framework along with ResponsiveVoice.js and Mozilla location Api

Accomplishments that I'm proud of

Hindi audio output

What I learned

1. Guassian Processes
2. Flask
3. Ajax ## What's next for Agriculture-Recommender Combining it with better CNN based crop yield models for refined predictions and acquiring farm level data sets for better personal recommendations.Using data sets of Cost of cultivation we can predict input,revenue and profit percentage.

Built With

• flask
• location-api
• machine-learning
• python
• responsivevoice.js