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  Confusion-Matrix

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  Precision-Confidence Curve

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  Training Metrics

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  Sample Test

EtechCycle: Solving E-Waste Recycling problems with AI!

Project Description

EtechCycle was inspired by the growing issue of e-waste and the need for smart recycling solutions especially in the use of Artificial Intelligence. Our project makes use of YOLO object detection in order to effectively sort and categorize electronic waste.

How We Did It

1. Collected and tagged an e-waste dataset
2. Fine-tuned a YOLO model for object detection
3. Integrated a live USB webcam feed for real-time labeling

Challenges We Overcame

• Dataset constraints and model accuracy increase
• Faster real-time processing
• Environment compatibility

What We Learned

Sustainability can be made real by AI!

We learned a lot about computer vision and applied AI.

The Future of E-Waste Management

• Improve model accuracy with more data and training
• Partner with recycling plants for tangible contributions

EtechCycle: Recycling powered by AI for a sustainable future!

Built With

• cv2
• pytorch
• yolo