Розробка модульної системи аналізу активності користувача персонального комп’ютера з використанням методів штучного інтелекту

Abstract

This study investigates the development of a modular software system for automated analysis of user activity on a personal computer. To address the limitations of manual monitoring and fragmented tracking tools, the framework collects contextual data such as active applications, screenshots, and optionally camera frames to support classification of user behavior. The architecture is modular, allowing components to be enabled or disabled without compromising stability. The system provides event logging, structured database storage, and integration of AI models for activity classification. The proposed approach offers a scalable foundation for intelligent monitoring and categorization of computer usage patterns, including work, study, entertainment, and inactivity