IoT Based AI Smart Waste Classification & Segregation System
AI-powered waste classification system using TensorFlow & MobileNetV3 for real-time garbage sorting into Multiple categories. Features live camera feed integration, image upload, and instant classification results.
AI Smart Waste Classification & Segregation System – Realtime Garbage Sorting with Django & TensorFlow
Welcome to the future of smart waste management! This AI-powered waste classification system automatically identifies and sorts garbage into Multiple categories in real-time using deep learning. The system integrates seamlessly with Django for a powerful web-based dashboard, offering both live camera feed (ESP32-CAM/DroidCam) and image upload capabilities for instant classification.
Built with TensorFlow MobileNetV3, this system achieves high-precision classification, making it perfect for smart cities, recycling automation, and environmental sustainability initiatives.
🔍 How the System Works
📸 Live Camera Feed: Connects to ESP32-CAM or DroidCam for real-time video streaming and instant classification.
🧠 Deep Learning Model: TensorFlow/Keras MobileNetV3 trained on a comprehensive waste dataset.
🔄 Realtime Classification: Classifies waste into 6 categories instantly with confidence score display.
📊 Web Dashboard: Django-based interface showing live predictions, category labels, and probability percentages.
📱 Multi-Input Support: Classify waste via live camera stream OR upload images directly.
Quick Build & Interfacing Guide:
Unbox and verify all pre-tested sensors, microcontrollers, and wiring components included in your package.
Secure mechanical brackets, servos, and modules to the main frame using the provided mounting hardware.
Interface VCC, GND, and GPIO signal lines according to the verified schematic diagram provided with the kit.
Upload the tested source code via Arduino IDE, Python, or ESP-IDF and verify live sensor readings and actuation.
Key Features
Specifications
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