AI-Powered College Complaint Analyzer

Abstract

Efficient and transparent grievance redressal is essential for maintaining student satisfaction and administrative accountability in educational institutions. However, many colleges still rely on manual complaint handling methods such as paper forms, emails, or verbal communication, which often result in delays, misrouting, and lack of proper tracking. This paper presents an AI-Powered College Complaint Analyzer, an intelligent system designed to automate complaint classification, routing, and monitoring. The proposed solution integrates an Android application for students, a web-based dashboard for department managers, and a machine learning model that automatically categorizes complaints into relevant departments such as academics, hostel, examinations, IT, administration, and maintenance. Built using Java/XML, Firebase Realtime Database, Python-based machine learning, and a Bootstrap web interface, the system ensures real-time synchronization, transparent status updates, and centralized data management. Experimental evaluation shows reduced response time, improved complaint resolution efficiency, and enhanced accountability, making the system suitable for modern smart campus environments.