AI-Based Smart Scheduling System for Students
College students frequently struggle to manage multiple academic responsibilities such as assignments, exams, projects, and extracurricular activities. Existing planner applications provide static timetables that require manual updates and fail to adapt to changing workloads. This paper presents an AI-Based Smart Scheduling System designed to generate personalized and dynamic schedules for students based on their study habits, productivity patterns, and academic deadlines. The system uses behavior analysis, workload prediction, and adaptive scheduling algorithms to create flexible plans that automatically reorganize when priorities change. Experimental observations show that students using this system experience improved time management and reduced academic stress. The proposed work demonstrates the potential of AI-driven scheduling tools to support effective learning and personal organization in academic environments.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-11-24
- DOI
- https://doi.org/10.5281/zenodo.17702071
- Primary Topic
- Scheduling and Timetabling Solutions
- Type
- article
- Field-Weighted Citation Impact
- 0.00