Inspiration
Smart Solar Tracking Cooker
Idea: Automatically adjust the cooker to face the sun for maximum heat.
How AI helps:
Use computer vision (camera + model) to detect sun position Or use light sensors + ML model to predict optimal angle
Tech Stack:
Frontend: React (dashboard for angle + temp) Backend: Node.js / Python Hardware: Arduino/Raspberry Pi
What it does
Uses solar energy to cook food efficiently without electricity or gas. Automatically tracks the sun’s position to maximize heat absorption. Monitors real-time temperature and adjusts cooking conditions using AI. Predicts cooking time based on weather, sunlight intensity, and food type.
How I built it
Developed an AI/ML model to predict optimal cooking time and adjust conditions based on sunlight intensity, weather data, and food type. Implemented sun-tracking logic using sensors/algorithms to automatically adjust the cooker’s angle for maximum efficiency. Built a backend system (Node.js/Python) to process sensor data, run predictions, and manage cooking sessions. Created a frontend dashboard (React.js) to display live temperature, cooking status, and predictions. Integrated weather APIs to enhance accuracy in cooking time and performance.
Challenges I ran into
Inconsistent sunlight Weather changes (clouds, rain) made it difficult to maintain stable cooking temperatures. Accurate sun tracking Ensuring the cooker always faced the sun required precise sensor calibration and alignment. Temperature control issues Maintaining optimal cooking temperature without overheating or heat loss was challenging
What I learned
Gained practical experience in building real-world IoT systems by integrating sensors, microcontrollers, and software. Learned how to apply AI/ML concepts to solve real-life problems like predicting cooking time and optimizing performance. Improved my skills in full-stack development by building a React dashboard and backend APIs for real-time monitoring.
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