plantpulse.

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Inspiration

The inspiration behind "PlantPulse" came from our own struggles and curiosity as plant owners. Many of us have had plants that seem to thrive for a while, only to slowly wither away without clear reasons why. It’s frustrating for both seasoned gardeners and beginners alike, sometimes it’s not just about knowing when to water, but understanding the specific health needs of a plant.

What it does

PlantPulse is a comprehensive plant health tracking service assists both seasoned gardeners and beginners alike. By leveraging Gemini's cutting-edge AI API, our app allows users to upload photos of their plants, where the AI analyzes the image to provide a health score and specific feedback on the plant's condition. This empowers users to understand exactly what's happening with their plants and what they can do to improve their health.

The app doesn't just focus on the individual plant but also helps users track the overall health of their garden.

How we built it

We built a web application using HTML, CSS, JavaScript, Python Flask, NodeJS, and Google Firebase for user authentication and storing data in our back end. To interpret the plant/crop images, we engineered a prompt into Gemini API to generate a concise and detailed summary about the plant's health, condition, and how the user/farmer can improve the plant's health.

Challenges we ran into

Since we were all new to hackathons, we only somewhat knew how to collaborate on GitHub, causing a setback in time and merge conflicts.

Unfortunately, since we did not use JavaScript libraries (React) / frameworks, it made it difficult and time consuming to manage our code and multiple HTML/CSS/JavaScript files.

Accomplishments that we're proud of

We are really proud of our frontend UI/UX design. It took us a really long time to make it aesthetically pleasing to us and the user.

We are really proud of our teamwork and how we were able to get this done with not too much knowledge of web applications.

Also, we are proud of getting our backend running and parsing the data with Gemini API generated responses

What we learned

We learned how to effectively work as a team in a programming environment and learned how to collaborate together with GitHub better.

What's next for plantpulse.

Implementation of data analysis based on generated AI information Implementation of visualized data, displaying the progress of plant growth Implementing automated notifications, reminding users to upload updated images