Waste Segregation and Collection Automation using CV

Waste Segregation and Collection Automation using Computer Vision

Project Overview

This project automates waste segregation using Computer Vision (CV) and AI. A camera captures waste images, and a trained deep learning model identifies waste types such as plastic, paper, glass, and metal. The waste is then automatically directed into the appropriate bin.

Objectives

  • Reduce manual waste sorting.
  • Improve recycling efficiency.
  • Minimize environmental pollution.
  • Enable smart waste collection.
Waste Management

Technologies Used

  • Python
  • OpenCV
  • TensorFlow / YOLO
  • Raspberry Pi
  • Servo Motors
  • Smart Dustbin Sensors

Benefits

  • Fast waste classification.
  • Higher recycling accuracy.
  • Reduced operational costs.
  • Supports smart city initiatives.

Waste Segregation Automation Project | Computer Vision

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