Agriculture Monitoring Using AI and IoT

AGROCARE for smart Agriculture

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Inspiration

Seeing the farmers struggle to grow crops and facing loss in today's scenario, we thought to help the agriculture sector with the amazing technology!

What it does

Our project takes in some input from the farmer like Nitrogen value, Pottasium value, Phosphorus value, pH value, rainfall level, and user's location to give him the best tip to plant the crop that'll help him to maximize his yield and profit as well. Not only this, but we also built a section, where farmers can get improvement tips on the basis of these factors, using which they can improve the yield of already planted crops. In addition to these features, the farmer can also get to know any disease that his crops are suffering from by just uploading an image on the website!

Also, to reduce the manual work, we also developed a prototype of an IoT device, that can measure these parameters for the farmer and just suggest him for the same, no need of manual input

How we built it

We used Machine Learning and Flask to build the webpage. Some models were used as it is and the rest were written and trained during the hackathon and the dataset was taken from Kaggle. IoT part was done on an online simulator and a block diagram was made for the same. Now the website runs on the local host when the user executes the script in the Jupyter notebook.

Challenges we ran into

We ran into many challenges during this hackathon like getting used to git/GitHub, working on different tech stacks, making the video, combining all the models, finding the content, solving the errors, etc. We proudly handled them as a team and got out of all the bugs and got a final product at the END.

Accomplishments that we're proud of

We are proud of working as a team in our first hackathon, we got to learn about frameworks, Git/GitHub. Again, combining all the stuff was not that simple and we handled that part very strongly. We all teammates were strangers to each other before the hack, but now we are a team, thanks to the #teambuilding section of the Power To Fly Discord channel!

What we learned

We learned how to implement ML and IoT into one and how to make something small yet powerful enough to help the farmers. We got knowledge of the Flask framework, by working on it, and it was definitely a very good hack period for us!

What's next for Agriculture Monitoring Using AI and IoT

As we mentioned, we are going to automate the data input process for the website, so implementing the device will not only make things smarter, it'll also reduce the need to train a farmer to use the device, as no technical knowledge is required at that time!

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