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Mobile Apps · Major Project

TrashPoint: Reward-Based Waste Management

Photograph waste, get its bin category and earn points for disposal

3-4 weeks build

Overview

A Flutter app that classifies a photo of waste into categories such as plastic, paper, glass, metal and organic using an on-device TensorFlow Lite model trained on the public TrashNet dataset. Disposing at a verified drop point by scanning its QR code earns points, which feed a leaderboard and can be redeemed for rewards.

What makes it stand up

  • 01On-device waste classification with TensorFlow Lite
  • 02Disposal guidance for each predicted category
  • 03QR-verified drop points to stop point farming
  • 04Points ledger, leaderboard and reward redemption
  • 05Admin view of drop points and category trends

Module breakdown

  1. 01

    Classifier

    MobileNet transfer learning, exported to TensorFlow Lite.

  2. 02

    Camera flow

    Capture, classify and show disposal instructions.

  3. 03

    Drop points

    Map of bins with QR check-in verification.

  4. 04

    Rewards

    Firebase points ledger, leaderboard and redemptions.

  5. 05

    Admin

    Drop-point management and disposal statistics.

After this, you will be able to

  • Explain model quantisation for on-device inference
  • Defend how QR check-in prevents gaming the points
  • Demo classifying items and earning points live

Technology stack

  • Flutter
  • TensorFlow
  • Firebase
  • Python

Complete kit

₹7,199₹12,199
-41%

Delivered in under 48 hours

Level
Major Project
Domain
Mobile Apps
Build time
3-4 weeks
Difficulty

You receive

  • Complete, commented source code
  • 60-90 page project report (IEEE format)
  • Editable presentation deck
  • Architecture, ER and UML diagrams
  • Local setup and deployment guide
  • Sample dataset or seed data
  • Viva question bank with answers
  • One 45-minute walkthrough call
  • 30 days of doubt-clearing support
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