AI-Based Mobile Usage Analysis for Productivity Improvement (AI Mobile Usage for Productivity)

Abstract

In the digital era, excessive smartphone usage has become a major source of productivity loss among students and professionals. This paper proposes an Artificial Intelligence-based system that detects time-wasting activities on mobile devices by analyzing user behavior patterns such as application usage, screen time, and interaction frequency. The system utilizes machine learning algorithms to classify activities into productive and non-productive categories and generates a personalized productivity score. Additionally, it provides real-time recommendations to reduce distraction and improve focus. Experimental results show that the proposed model can accurately identify time-wasting patterns and assist users in managing their time effectively. This system can be applied in educational environments, workplaces, and personal productivity management.

With the rapid growth of smartphone usage, excessive engagement in non-productive activities has become a major concern affecting individual productivity and mental well-being. This paper proposes an AI-based mobile usage behavior analysis system that monitors user activity patterns, identifies time-wasting behaviors, and provides intelligent recommendations to improve productivity. Using machine learning algorithms, the system classifies applications into productive and non-productive categories, analyzes usage trends, and generates actionable insights. Experimental results demonstrate that the proposed system can significantly reduce unproductive screen time and enhance user efficiency.