AI-Based Smart Scheduling System for Students
Year: 2025
Type: article
Abstract: 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.
Author: Bontha, Sanjaynath
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7106507294
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