FindIT: A Smart Lost and Found Management System
Team
- E/23/431, Dulmina Weerasinghe, e23431@eng.pdn.ac.lk
- E/23/149, Livindu Jayasinghe, e23149@eng.pdn.ac.lk
- E/23/382, Lihini Silva, e23382@eng.pdn.ac.lk
- E/23/274, Thenuk Piyathilake, e23274@eng.pdn.ac.lk
Table of Contents
- Introduction
- Solution Architecture
- Core Features & Engineering
- Testing & Future Roadmap
- Conclusion
- Links
Introduction
In busy shared environments like universities, losing personal items—such as keys, electronics, or wallets—is a common and stressful occurrence. Currently, recovery relies on fragmented methods like physical notice boards, verbal inquiries, or unorganized social media posts. This lack of a central system leads to low recovery rates and high frustration.
FindIT is a digital solution designed to bridge this gap. It provides a centralized, privacy-first platform where users can report lost or found items through structured questionnaires. By using intelligent matching algorithms and a “gradual disclosure” communication model, FindIT ensures that items are returned to their rightful owners securely and efficiently, reducing the cognitive burden on both students and campus administration.
Solution Architecture
FindIT is built on a modern, decoupled Full-Stack web architecture designed for scalability, speed, and cloud efficiency.
- Frontend (Client-Side): Built with React, featuring dynamic report forms, real-time dashboard views, and client-side image compression to reduce bandwidth before data ever leaves the user’s device.
- Backend (API Layer): A robust Python FastAPI service that handles business logic, securely processes incoming reports, and manages asynchronous polling to keep the frontend updated.
- Database Layer: Hosted on Aiven MySQL cloud infrastructure. To optimize performance and prevent database bloat, the database only stores lightweight data and URL pointers, rather than heavy files.
- Cloud & Microservices:
- Cloudinary: A dedicated Content Delivery Network (CDN) used for off-site media management. High-resolution item photos are uploaded directly to the cloud, ensuring lightning-fast load times.
- Brevo API: Utilized for reliable transactional emails and automated notifications via HTTPS, bypassing traditional SMTP host limits.
Core Features & Engineering
The system is designed with a heavy focus on data privacy, user empathy, and intelligent automation. Key engineering milestones include:
- Fuzzy Logic Matching Engine: Instead of relying on unpredictable AI prompts, FindIT utilizes a precise Fuzzy Logic algorithm to pair lost and found reports. This ensures high-accuracy matches even if users make spelling mistakes or use slightly different item descriptions.
- Secure Handover Protocol: To prevent fraudulent claims, FindIT employs a “Secret Question” verification layer. A finder will only reveal the item’s location or their contact details if the claimant can correctly answer a specific question about the item (e.g., “What is the wallpaper on the phone?”).
- Privacy-First Contact Revelation: User Personally Identifiable Information (PII), such as phone numbers, is protected using Fernet Encryption. Contact details are kept strictly hidden and are only decrypted and revealed once the system mathematically verifies a successful match and handover agreement.
Testing & Future Roadmap
As the project moves into its final phases (Semester 4), testing and refinement remain our top priority:
- Unit & Integration Testing: Automated testing of FastAPI routes and React component states to ensure seamless data flow between the decoupled cloud services.
- Usability & Acceptance Testing (UAT): Gathering real customer feedback from pilot groups to refine the UI/UX, ensuring the interface remains highly responsive and intuitive for users operating under the stress of losing an item.
- Advanced Automation: Developing “7-day cleanup” logic to automatically prune the database of stale data and implementing push notifications for instant match alerts.
Conclusion
FindIT aims to transform the lost-and-found experience from a game of chance into a reliable, automated service. By leveraging cloud infrastructure, cryptographic security, and smart matching algorithms, the software creates a safer campus environment and ensures a high success rate for asset recovery.