"Green Health Monitor ☘️- A Plant Disease Detection System "

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Inspiration ✍️

Our inspiration for creating our detection system arose from seeing how quickly our plants would die off. One day our plants would be fruitful and filled with life, and the next day our plants were decaying. This eventually begged the question as to how we can tell if our plants were in good condition or if they were suffering a serious illness. This would not only help us raise our house plants better, but on a larger scale, could also aid the farming industry detect if their crops are still in excellent condition.

What it does

By uploading an image of your plants onto our website, our detection system will use a multitude of data gathered from our machine & eventually provide you with the result of how healthy your plant truly is.

How we built it ☘️

We built our machine in Google Colab and used various images of diseases found in plants & trained our machine to recognize these diseases in the average houseplant. Also , we made the UI of our model through python library Streamlit

Challenges we ran into ☠️

We ran into a lot of troubleshooting regarding our machine because it did take us a while to test our machine and see if it was fully functional

Accomplishments that we're proud of ☘️

Since both of us are relatively new to hackathons, we are really proud of our progress, going from little to no experience to eventually figuring out our way through hackathons.

What we learned 📚

We mainly learned how to collaborate with one another and communicate whenever we had issues regarding our project. Since our group lived in different time zones, it was crucial for us to communicate effectively and to properly divide the work among our group to ensure a smooth ride on our hackathon journey.

What's next for "Green Health Monitor 🌱- A Plant Disease Detection System"

For starters, we would like to work on keeping a very user-friendly interface and may rely more on the usage of images and articles. To be more specific, the usage of articles can help our audience learn more about certain plant diseases and what one can do to prevent these diseases in the future.