CampusFind AI AI-powered Campus Lost & Found Platform

Kolla Lohitha — Mon, 05 Oct 2026 07:15:31 +0000

What I Built

I built CampusFind AI, an AI-powered Lost & Found platform designed to help students recover lost belongings on campus.

The idea came from a simple problem: when a student loses something on campus, finding it again can be surprisingly difficult. They may post about it in WhatsApp groups, ask friends, check with security, or simply hope someone found it. At the same time, students who find an item often have no easy way to identify its owner.

CampusFind AI brings both sides together in one platform.

Students can report lost and found items with descriptions and images, and the system uses AI to analyze item details and find potential matches. Instead of relying only on exact keywords, the matching system considers information such as:

Item category
Name and description
Color
Material
Distinctive features
Location
Date
Image-based attributes

The goal is simple: make it easier for a student to get their lost belongings back.

I built it as a project that could actually be used by students on a college campus rather than just as a prototype.

Demo

Live Application:

campus-find-ai-frontend.vercel.app

The application is fully deployed, with the frontend hosted on Vercel and the backend deployed separately with a cloud MySQL database.

Image

Code

GitHub Repository:

KollaLohitha / CampusFind-AI-Frontend

React + Vite

This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.

Currently, two official plugins are available:

@vitejs/plugin-react uses Oxc
@vitejs/plugin-react-swc uses SWC

React Compiler

The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see this documentation.

Expanding the ESLint configuration

If you are developing a production application, we recommend using TypeScript with type-aware lint rules enabled. Check out the TS template for information on how to integrate TypeScript and typescript-eslint in your project.

View on GitHub

KollaLohitha / CampusFind-AI

The project contains both the frontend and backend components and includes the implementation of authentication, item management, AI-powered matching, image handling, and claim processing.

How I Built It

CampusFind AI is built using:

Frontend: React
Backend: Java + Spring Boot
Database: MySQL
Authentication: JWT + BCrypt
AI: Google Gemini
Image Storage: Cloudinary
Deployment: Vercel + Railway
Build Tool: Maven

The AI is used in two important parts of the application.

1. AI-powered item analysis

When an item is reported, AI can analyze its description and image to identify useful attributes such as the object type, colors, material, features, and distinctive characteristics.

These attributes are stored as structured data and can later be used during matching.

2. AI-powered matching

When a lost item needs to be matched with found items, the system compares multiple factors rather than simply checking whether the item names are identical.

The matching process considers attributes such as:

Category + Name + Color + Material + Features + Location + Date + Distinctive Features

The system then generates a match score and returns the most relevant potential matches.

I also implemented authentication and authorization so that students can manage their own reports, while administrative functionality can handle claims and returned items.

Why Does Open Innovation Matter?

Open innovation makes it possible for developers like me to experiment with AI-powered solutions without having to build every component from scratch.

For this project, the important part wasn't simply adding an AI chatbot. I wanted AI to solve a specific problem inside an application.

Using an AI model allowed me to turn unstructured information such as:

"I lost my cream and brown backpack near the library."

into useful attributes that could be compared against reported found items.

This makes the system more flexible than a basic keyword-based search.

Open innovation also makes it easier for students and independent developers to experiment, learn, modify existing ideas, and build solutions for problems in their own communities.

For a campus-specific problem like Lost & Found, that accessibility is particularly valuable. A student doesn't need a large company or expensive infrastructure to start building something useful for their own college.

My Agent Session

Prize Categories

AI / Open Innovation
Developer Tools

DEV Community: Kolla Lohitha