HostelMate

Project Inspiration: Living in hostels, students often face delays in reporting and resolving complaints like maintenance issues, cleanliness, or food problems. We wanted to create a system that makes complaint management fast, transparent, and intelligent, benefiting both students and wardens. What It Does: HostelMate allows students to submit complaints easily. The AI categorizes each complaint, prioritizes urgent issues, suggests actions for the warden, and keeps track of resolution status. Wardens get a dashboard view to manage complaints efficiently. Features include: AI-powered complaint categorization Urgent issue detection Suggested actions for quicker resolution Dashboard with statistics (total, pending, resolved) Delete and mark-resolved options for better management How We Built It: We used Python with Streamlit for the frontend and interactive UI. Pandas helped manage the complaint data in CSV files. AI features were implemented using Google’s GenAI API to analyze complaints and provide recommendations. We also added dark mode/light mode, search functionality, and a responsive design for ease of use. Challenges We Ran Into: Integrating AI analysis while keeping the interface simple Handling dynamic updates for resolved or deleted complaints Managing UI consistency across dark and light modes Ensuring the system works smoothly without needing a separate backend Accomplishments We Are Proud Of: A fully functional AI-driven complaint manager Clean, intuitive, and responsive UI with themes Ability to prioritize urgent complaints automatically Added student and warden interactions on the same platform What We Learned: How to integrate AI models in real-world applications UI/UX design principles for accessibility and readability Streamlit session management and dynamic data handling Best practices in deploying Python applications online What’s Next for HostelMate: Adding separate student and warden logins for privacy Supporting multi-hostel management in one platform Real-time notifications for urgent complaints Moving to a cloud database for scalability Enhancing AI suggestions using machine learning feedback loops