Inspiration
University campuses often face issues like potholes, garbage, and water leaks, but there is no efficient way for students to report them. Traditional systems are slow and unstructured. This inspired us to build an AI-powered solution that makes reporting issues simple and effective.
What it does
CampusAI allows users to upload images of campus problems. The system analyzes the image and identifies the issue. It also provides a simple chatbot to assist students with basic queries.
How we built it
We built the project using Python and Streamlit. A simple AI-based logic is used to analyze images and predict the issue type. The interface is designed to be clean and easy to use.
Challenges we ran into
Acquiring a suitable dataset for training Achieving reliable prediction accuracy Integrating the AI model with the application Designing a user-friendly interface Managing time during development
Accomplishments that we're proud of
Successfully building a working AI-based application Implementing image-based issue detection Creating a simple and interactive user interface Completing the project within limited time
What we learned
Building and integrating AI models Working with real-world problem statements Improving debugging and development skills Understanding the importance of user experience
What's next for CampusAI – Smart Issue Detection & Student Assistant
Improving model accuracy with better datasets Expanding to detect more types of issues Developing a mobile application Adding an admin dashboard for monitoring Integrating with real campus systems
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