Inspiration

I lived in a yurt in Mongolia, where planting indoors during -40°C winters was nearly impossible. With Bloom AI, we're solving this by using IoT and AI to monitor plant health, helping families like mine grow plants even in harsh conditions. Have you ever struggled to understand what your plants need to thrive? Whether you're a seasoned gardener or a newbie, ensuring your plants get optimal care can be challenging. We created Bloom AI to eliminate the guesswork in plant care by providing real-time insights using cutting-edge technology. What It Does Bloom AI is a smart plant health monitoring system that allows you to: Monitor plant health in real-time with IoT sensors tracking temperature, humidity, soil moisture, and light levels. Receive AI-powered advice on plant care, answering questions about watering schedules, light requirements, and more. Visualize plant health data in 3D, giving you an interactive understanding of your plant's status. Analyze plant images for health assessments, offering actionable insights on issues like under-watering or poor lighting. With Bloom AI, plant care becomes easier, more efficient, and data-driven. How We Built It Frontend: Developed with Next.js, React, and TypeScript for a fast, responsive user interface. Backend: Utilized Node.js and Flask. Flask handles AI integrations and analysis, while Node.js manages data exchange between sensors and the frontend. IoT Integration: Connected sensors to Arduino and ESP8266/ESP32 boards to collect real-time environmental data. Data Visualization: Employed Recharts to visualize trends in plant health data. 3D Rendering: Used Three.js to create interactive 3D models of plant health status. AI-Powered Insights: Integrated APIs like Groq for language processing and Hume for computer vision to provide personalized plant care advice. Challenges We Ran Into Hardware Integration: Ensuring accurate data collection required precise calibration and testing of IoT sensors. AI Image Analysis: Implementing reliable image recognition across different plant types was complex. 3D Visualization: Optimizing performance and usability for interactive 3D models posed technical challenges. Accomplishments That We're Proud Of Real-Time Monitoring: Successfully built a system that provides instant feedback on plant health. AI Assistance: Developed an AI assistant that makes plant care advice accessible to all users. Interactive Visualizations: Created 3D models that simplify complex data into an understandable format. Seamless Integration: Effectively combined multiple IoT sensors into a user-friendly dashboard. What We Learned IoT Development: Gained experience in setting up and integrating sensors with web applications. AI and Machine Learning: Explored advanced algorithms for image analysis and natural language processing. Full-Stack Development: Enhanced our skills in building applications from the ground up, managing both frontend and backend components. What's Next for Bloom AI Expanded Sensor Support: Adding sensors for air quality, pH levels, and more environmental factors. Community Platform: Creating features for users to share data and gardening tips. Mobile Application: Developing a mobile app for easier access and monitoring on the go. Enhanced AI Models: Improving accuracy and personalization of insights based on specific plant types and conditions.