• Aimaan Khan
• Mariyum Siddique
• Siddharth Pallar
• Shiburaj Pappu
• Dr. Anupam Choudhary

In today’s educational landscape, managing academic schedules has become a significant challenge due to the increasing number of students, expanding course offerings, and limited infrastructure. Manual creation of timetables is both time-consuming and prone to errors, leading to conflicts in scheduling and inefficient use of resources. To address these issues, this project aims to develop an AI-powered timetable scheduling system that automates the creation of academic schedules. The system will use advanced AI algorithms to optimize resource allocation, including teacher availability, room assignments, and lab scheduling, based on predefined constraints. Built on Node.js and MongoDB for a scalable and flexible backend, this system will not only generate conflict free timetables but will also allow dynamic adjustments to accommodate last-minute changes. By eliminating manual intervention and leveraging AI, the project seeks to significantly reduce administrative workload while improving the accuracy and efficiency of academic scheduling in institutions of varying sizes

Automation, Conflict-Free Timetables, Resource Optimization, Scalability, Efficiency

"AI powered timetable scheduler and management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.f322-f325, October-2024, Available :http://www.jetir.org/papers/JETIR2410528.pdf

"AI powered timetable scheduler and management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. ppf322-f325, October-2024, Available at : http://www.jetir.org/papers/JETIR2410528.pdf