Transforming Plastic Waste Collection Through Smart Reverse Vending, Computer Vision & Cashless Incentive Systems

Industry: Waste Management, Sustainability, Circular Economy

Region: India, Middle East & Southeast Asia

Engagement: Complete engineering of an AI-powered Reverse Vending Machine (RVM) including computer vision detection, shredding automation, IoT communication, and digital payments for waste pickers.

Technology Stack Overview

Hardware:Custom PCB, Industrial-grade shredding motor, Load sensors, 360° RGB camera module, Stepper motors for bin segregation

AI & Computer Vision:Python + OpenCV, TensorFlow Lite, Object classification (color, material type), Image preprocessing pipeline

IoT Backend:AWS IoT Core, MQTT, Lambda, API Gateway

Telemetry: Fill level, cycle count, motor health, bin status

Cloud & App Layer:

• Mobile App: Flutter

• Dashboard: ReactJS + FastAPI

• Payments: UPI, Paytm Wallet, RazorpayX APIs

Challenge

Plastic waste collection requires speed, accuracy, and reliable incentives to maintain participation. Traditional collection points faced several problems:

• Bottles were not sorted, lowering recycling value

• Waste pickers had no real-time payout, leading to delays and friction

• Manual collection verification created trust issues

• Facilities lacked data visibility into volumes, machine health, or segregation efficiency

• Opportunity to create a gamified, automated recycling ecosystem was missing

The client needed a fully automated, digitally connected RVM that could:

1. Accept bottles

2. Detect & classify plastic in real time

3. Shred and segregate based on color categories

4. Pay the waste picker instantly

5. Report all activity to a cloud dashboard

Solution

EC Infosolutions built an end-to-end Reversible Vending Machine Platform integrating computer vision, IoT, electromechanical control, and mobile wallet payments.

Key Functional Modules

1. Smart Bottle Detection (360° Camera + AI)

• A 360-degree camera scans every inserted bottle

• AI model detects:

  • PET vs non-PET

  • Bottle color classification (e.g., clear, green, blue)

  • Presence of contaminants

• Real-time inference done on edge hardware for speed

  
  

2. Automated Shredding & Segregation

• Industrial shredding system activates upon classification

• Shredded output directed into correct bin using:

  • Motor-controlled chute

  • Servo-guided bin selection

• Sensors monitor:

  • Shredder motor load

  • Bin fill-level

  • Door status

  • Jam alerts

    
    

3. AWS IoT Cloud Platform

All machines connected via secure MQTT channels:

• Telemetry tracking: cycle count, bin status, machine health

• Remote commands to restart shredders, adjust classification parameters

• OTA firmware updates for ML model improvements

  
  

4. Mobile App for Waste Pickers

Built in Flutter (Android-first):

• Login via OTP

• QR code scan to identify machine

• View earnings in real time

• Track number of bottles deposited

• Withdraw money anytime to UPI/mobile wallet

  
  

5. Instant Digital Payments Engine

Automatic payout processed per bottle:

• AI classifies & confirms bottle

• Backend logs the transaction

• Payment gateway triggers wallet payout

• User receives instant confirmation

Results

• Accurate Plastic Segregation: ML-driven color & material detection improved recycling efficiency by ~35%.

• Operational Transparency: Every bottle’s journey was tracked, logged, and audit-ready.

• Instant Incentive Model: Waste picker payouts increased participation and collection rates.

• Reduced Manual Labor: Automated shredding & sorting eliminated the need for manual segregation.

• Scalable Deployment: The cloud-managed design enabled deployment across multiple urban locations.

• Maintenance Efficiency: IoT alerts allowed predictive maintenance and reduced machine downtime.

Key Takeaways

• Combining AI + IoT + electromechanical engineering can revolutionize waste collection.

• Real-time payments drive user adoption and trust.

• Automated classification adds economic value by improving recycling quality.

• Cloud dashboards allow operators to track environmental impact and machine performance.

• This model can scale to cities, universities, malls, airports, and corporates to support sustainability goals.

Get Connect

Looking to build smart recycling systems or IoT-based sustainability solutions?

EC Infosolutions develops end-to-end IoT, AI, and embedded tech platforms that transform waste management operations.

Book a consultation to explore how automation and real-time incentives can power your next green initiative.