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@article{196145,
        author = {Nisha D Pande and Prof. Rajashree S. Mathane and Vaishnavi D. Dange and Khushi M. Gohar and Kaushal N. Dhepe and Rohan K. Rathod},
        title = {Smart Classroom and Timetable Scheduler},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {2326-2329},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196145},
        abstract = {In modern educational environments, managing classrooms and generating efficient timetables is a complex and time-consuming task. Traditional scheduling methods often result in conflicts, inefficient resource utilization, and lack of flexibility. This research proposes a Smart Classroom and Timetable Scheduler using Machine Learning (ML) techniques to automate and optimize scheduling processes. The system integrates intelligent algorithms to analyze historical data, faculty availability, classroom capacity, and student preferences to generate conflict-free and adaptive timetables. The proposed model improves decision-making, enhances resource utilization, and supports dynamic rescheduling in real-time. The study demonstrates how ML-based scheduling can transform conventional academic management systems into smart, efficient, and scalable solutions.},
        keywords = {},
        month = {April},
        }