Smart Classroom & Timetable Scheduler by Team Hack Smack | SIH2025
The current scheduling mechanism in most higher education institutes/colleges relies on manual input via spreadsheets or basic tools. These fail to account for real-time availability of faculty, room capacity, teaching load norms, subject combinations, and student preferences. A solution is required that will accommodate the various parameters required for scheduling classes for UG and PG students and return an optimized timetable ensuring:
• Maximized utilization of classrooms and laboratories
• Minimized workload on faculty members and students
• Achievement of required learning outcomes
what is the solution?
The AI-powered Smart Timetable Scheduling System is an advanced web-based platform designed to automate and optimize class scheduling for higher education institutions. Traditional manual timetable creation is time-consuming, error-prone, and often fails to consider multiple complex constraints such as faculty availability, classroom capacity, and elective subject choices. To overcome these challenges, the proposed system leverages Google OR-Tools, a powerful combinatorial optimization library, to generate intelligent, clash-free timetables that meet institutional requirements efficiently.
Developed with a Flask (Python) backend and an intuitive HTML, CSS, and JavaScript frontend, the platform enables administrators to seamlessly manage core data such as faculties, subjects, classrooms, and elective courses. It ensures:
• Clash-free scheduling across subjects, faculties, and classrooms.
• Faculty availability and workload balance are strictly respected.
• Classroom capacities and resource constraints are met.
• Elective subjects are flexibly assigned to students without overlap.
A unique feature of the system is its collaborative voting mechanism, where stakeholders (such as faculty coordinators or students) can review and vote for the most efficient or preferred timetable among multiple generated options. This participatory approach introduces transparency and inclusivity in academic scheduling, ensuring that the final timetable reflects both institutional constraints and user preferences.
By integrating automation with human-centered feedback, this system not only reduces administrative workload but also enhances decision-making, fairness, and satisfaction in the scheduling process. It represents a significant leap toward AI-driven academic management, aligning with the vision of modern, flexible, and data-informed educational ecosystems.