The AI-Assisted Passenger Belongings Recovery System is a centralized digital platform designed to solve the persistent problem of passengers losing personal belongings while traveling on government buses.
Traditional recovery mechanisms in transport depots rely on manual registers, fragmented communication, and human memory, often resulting in delays, misplacement, or permanent loss of passenger items.
This project modernizes the entire workflow by introducing a secure, transparent, and AI-supported system that connects passengers, conductors, and depot administrators through a unified platform.
- Lost-item handling is manual and inefficient
- No centralized database across depots
- Poor coordination between passengers and depot staff
- High dependency on verbal communication
- Limited traceability and accountability
The system introduces a centralized web-based platform where:
- Passengers submit lost-item reports using travel details
- Depot staff upload found items with route data and images
- AI-assisted matching analyzes:
- Text descriptions
- Travel metadata
- Item images
- A confidence score supports decision-making with human verification
- Verified items can be returned physically or via secure parcel delivery
- Lost-item reporting with travel details
- SMS-based confirmation for verification
- Transparent recovery status tracking
- Depot-specific secure login
- Found-item reporting with image upload
- Controlled item release workflow
- Intelligent matching of lost and found items
- Text similarity and route-based alignment
- Confidence score generation
- Role-based depot access
- Controlled verification and release
- Centralized and traceable records
- Frontend: HTML, CSS, JavaScript
- Backend: Python Flask
- Database: Centralized relational database
- AI Module: Similarity-driven matching logic
- Notifications: SMS-based passenger alerts
| Figure | Description |
|---|---|
| Fig. 1 | Passenger Lost Item Reporting Interface |
| Fig. 2 | Depot Selection Screen |
| Fig. 3 | Depot Staff Authentication Interface |
| Fig. 4 | Found Item Reporting Dashboard |
| Fig. 5 | AI Matching & Notification Interface |
Screenshots are available in the screenshots/ folder.
srm-project/ ├── app.py ├── static/ ├── templates/ ├── requirements.txt ├── setup_venv.sh ├── .env.example ├── screenshots/ └── README.md
# Create virtual environment
python -m venv venv
# Activate environment
venv\Scripts\activate # Windows
source venv/bin/activate # Linux / macOS
# Install dependencies
pip install -r requirements.txt
# Run application
python app.py
🌍 Real-World Impact
Reduces dependency on manual registers
Improves recovery accuracy and response time
Enhances passenger trust in public transport
Supports digital governance initiatives
Demonstrates practical AI in civic systems
🚀 Future Enhancements
Aadhaar / e-ticket integration
Mobile app for depot staff and conductors
Advanced computer vision for item recognition
Blockchain-based tamper-proof records
Nationwide deployment
🏆 Why This Project Stands Out
Solves a real-world civic problem
Combines AI, system design, and governance
Focuses on practical deployment
Scalable and socially impactful