Hybrid Exam Planning System for Room and Invigilator Management Using AI

Abstract

Examination management in educational institutions involves scheduling examinations, allocating classrooms, and assigning invigilators, all of which are often performed manually. These activities require considerable time and are susceptible to errors such as timetable conflicts, inefficient resource utilization, and last-minute changes. This project presents a Hybrid Exam Planning System for Room and Invigilator Management Using AI to automate examination planning and improve administrative efficiency. The system maintains a centralized database containing student, faculty, and room information to support automatic timetable generation, room allocation, and invigilator assignment. AI-based scheduling is used to produce balanced and conflict-free allocations while providing mechanisms for conflict detection and resource reallocation when faculty or room availability changes. A webbased dashboard enables administrators to monitor examination activities, manage resources, and generate seating plans and invigilation schedules. The proposed system reduces manual effort, improves scheduling accuracy, enhances resource utilization, and provides a transparent approach to examination management. Its scalable design allows deployment across institutions with different examination requirements, offering a practical solution for efficient and reliable exam administration. Keywords— Artificial Intelligence, Examination Management, Exam Scheduling, Room Allocation, Invigilator Assignment, Resource Management.