Smart Garden AI 🌿: An Open-Source AI Plant Care Assistant

Smart Garden AI: Your Full-Stack Open-Source Plant Care Assistant 🌿

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

What I Built

Gardening can be challenging for beginners. People often struggle to identify plants, understand plant health, and decide how to care for them.

Smart Garden AI is a full-stack, beginner-friendly web application designed to make plant care easier and encourage people to connect with nature.

Our project aims to bring together four useful gardening tools:

• Plant Identification: Identify plants using uploaded plant or leaf photos.
• Leaf Disease and Health Detection: Help users explore possible leaf health issues and understand recommended next steps, while communicating uncertainty.
• AI Care Chatbot: Explore gardening questions about watering, soil, sunlight, and plant care using a local open-weight AI model.
• Smart Care Reminders and Timers: Help users organize plant-care schedules and keep track of gardening tasks.

We want to make gardening knowledge more accessible to beginners by combining technology with practical, real-world plant care.

Demo

Here are some screenshots of our Smart Garden AI project.

Code

GitHub Repository: Smart Garden AI

How I Built It

We are building Smart Garden AI using HTML, CSS, JavaScript, Node.js, Express.js, and MongoDB Atlas.

• Frontend: Responsive HTML and CSS with JavaScript for interactive features and form submissions.
• Backend: Node.js and Express.js, organized using the Model-View-Controller (MVC) architecture.
• Database: MongoDB Atlas for storing application data.
• AI Integration: Ollama with the Llama model to explore locally run, open-weight AI assistance for gardening-related questions.

We are developing the project collaboratively and aim to improve its functionality, usability, and reliability through testing and feedback.

Why Does Open Innovation Matter?

Open innovation allows developers to learn from existing technologies, collaborate with others, and build solutions that can continue to improve through community contributions.

For Smart Garden AI, open-source tools and open-weight AI models give us an opportunity to experiment, learn, and explore more flexible approaches to AI-powered gardening assistance. We hope our project will make plant-care knowledge easier for beginners to access while encouraging other developers to contribute ideas and improvements.

The Touch Grass theme reminds us that technology can do more than keep us on screens. It can also encourage us to engage with the natural world.

Prize Categories

• Best Use of MongoDB Atlas

Team Members

• Mahak: @mahak_df3f16062dee3d361da
• Sanchi: @sanchi_bareja_ea7f4891aad
• Khushi: @khushi_jangra_70ed76e19fa
• Prachi: @prachimanchandapm_20_c76a

devchallenge #hf26challenge