Crop recommendation AI

The has an AI that predicts the most recommended crop based on factors such temperature, soil minerals, etc.

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Inspiration

We wanted to create a solution to combat global warming and maximize crop yield in various areas and decided to work on it

What it does

We are using an AI based on machine learning algorithms and neural networks to predict the best crop to be used based on the level of potassium, phosphorus, temperature , humidity, pH and rainfall.

How we built it

We Trained neural networks on Tensorflow, and created front end with flask web application software, HTML and CSS

Challenges we ran into

We had very limited time, and the conversion of hdf5 file was really troublesome and tedious. Developing the full stack was a challenge we were faced with in the process, though our front-end and backend were fully functional independently.

Accomplishments that we're proud of

We got our AI to be trained at more than 98% accuracy. In a 36 hour hackathon we slept 4 hours :)

What we learned

We learnt how to create web application using Flask and we learnt how to create machine learning algorithms as well.

What's next for Crop recommendation AI

Accept more variables and make more accurate predictions. Also, designing the webpage more properly.

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