In today's academic environment, students face significant challenges in managing their time effectively due to multiple responsibilities such as attending classes, completing assignments, preparing for examinations, working on projects, and developing technical as well as soft skills. Poor time management often leads to stress, reduced productivity, and poor academic performance. This paper proposes a Smart Student Time Management System, which helps students efficiently organize their daily academic and personal tasks. The system integrates task scheduling, priority management, and intelligent reminders to optimize time utilization. It allows users to input their tasks, assign priorities, and receive automated suggestions for scheduling based on urgency and importance. The proposed system uses rule-based logic and optional machine learning techniques to analyze user behavior and recommend optimized study schedules. The system also tracks progress and provides feedback to improve productivity over time. Experimental evaluation shows that the system significantly enhances task completion rate and reduces procrastination among students.
Kumar et al. (2026) studied this question.