International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | OPTITIME – AI Integrated Timetable Generator |
|---|---|
| ABSTRACT | The project presents a Django, Bootstrap 5, and SQLite-based web application that automates the generation, visualisation, and management of college timetables across multiple semesters. It addresses the limitations of manual, spreadsheet-based scheduling by introducing an intelligent, conflict-free timetable generation process that allocates subjects, faculty, classrooms, and time slots according to predefined institutional constraints such as teacher availability, room capacity, weekly load, and departmental structure. By centralising timetable data in a responsive web platform, the system significantly reduces administrative workload, minimises human errors, and improves overall institutional coordination. Built on Django’s Model-View-Template architecture, the system provides a secure and modular backend supporting user authentication, role-based access (admin, faculty, student), and structured database management through SQLite. Administrators can create and modify semesters, enter subjects, teachers, and rooms, and generate or regenerate timetables automatically, while still retaining the flexibility to manually edit special cases like substitutions or extra sessions. Faculty and students access personalised, semester-wise schedules through an intuitive interface, with real-time updates ensuring that any change in allocation is instantly reflected for all stakeholders. Bootstrap 5 ensures a modern, mobile-responsive UI, enabling seamless access from desktops, tablets, and smartphones, and improving usability even for non-technical users. Additional features include timetable visualisation in clear, colour-coded grids, export to PDF or Excel for offline use and notice-board display, and reporting on faculty workload and classroom utilisation to support data-driven decision making. The system is designed to be scalable, providing a foundation for future integration of AI-based optimisation, attendance tracking, and linkage with Learning Management Systems, thereby aligning timetable management with the broader vision of digital transformation in educational institutions. |
| AUTHOR | BHURKE YASH RAJENDRA, DESAI SAISH MAHESH, DHURI VEDANG VIDDESH, DICHOLKAR UTKARSH SHAILENDRA, PROF.KATE P. D. Diploma Student, Department of Computer Engineering, Yashwantrao Bhonsale Institute of Technology, Sawantwadi, Maharashtra, India HOD, Department of Computer Engineering, Yashwantrao Bhonsale Institute of Technology, Sawantwadi, Maharashtra, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401050 |
| pdf/50_OPTITIME – AI Integrated Timetable Generator.pdf | |
| KEYWORDS | |
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