Overview

The Smart Waste Segregation System is an automated waste management solution designed to classify and separate dry, wet, and metal waste using sensor-based detection and microcontroller-controlled automation.

The system utilizes moisture sensing, metal detection, and infrared sensing technologies to identify different types of waste and automatically direct them into the appropriate bins. An integrated alert system monitors bin fill levels and notifies users when bins approach full capacity.

Objectives

• Automate waste segregation at the source.
• Improve recycling efficiency.
• Reduce manual handling of waste.
• Minimize environmental pollution.
• Support sustainable waste management practices.

Components Used

• Arduino UNO
• Rain Drop Sensor (Moisture Sensor)
• IR Sensor
• Inductive Proximity Sensor
• Ultrasonic Sensor (HC-SR04)
• Stepper Motor
• Servo Motor
• ULN2003 Stepper Driver
• HC-05 Bluetooth Module
• 16x2 LCD Display
• Buzzer

Working Principle

1. The moisture sensor detects wet waste.
2. The IR sensor identifies dry waste.
3. The inductive proximity sensor detects metallic objects.
4. The Arduino UNO processes sensor inputs.
5. The stepper motor and servo motor direct waste into the correct bin.
6. The ultrasonic sensor monitors bin fill levels.
7. The Bluetooth module sends alerts when a bin reaches capacity.

Features

• Automatic dry, wet, and metal waste segregation
• Real-time waste classification
• Bin fill-level monitoring
• Bluetooth alert system
• LCD status display
• Low-cost and eco-friendly design

Results

• Dry Waste Detection Accuracy: 95%
• Wet Waste Detection Accuracy: 97%
• Metal Waste Detection Accuracy: 98%
• Average Sorting Time: 2.5 seconds per item
• Bin Fill-Level Monitoring Accuracy: 92%

Applications

• Household waste management
• Smart cities
• Municipal waste collection systems
• Recycling facilities
• Educational and research projects

Future Scope

• GSM-based alert notifications
• Machine learning-based waste recognition
• Solar-powered operation
• Industrial-scale waste segregation
• IoT-enabled remote monitoring

Technologies Used

• Arduino IDE
• Embedded C
• Sensor Integration
• Automation Systems
• Embedded Systems