Design and Development of Smart AI-Powered Desktop Assistant for Productivity Enhancement

This paper presents the development of a multifunctional desktop assistant designed to enhance productivity through task automation, text extraction, and developer-centric utilities. The assistant includes features such as text extraction using optical character recognition (OCR), achieving a QR scanner processing time of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1. 2}$</tex> seconds under normal conditions for retrieving text from images. It integrates task reminders with Google and Microsoft calendars, maintaining a Google Calendar sync time of approximately 1.5 seconds. Sticky notes and a todo list offer lightweight data storage, using as little as 30 KB under typical usage. A unique clipboard manager securely tracks and stores up to 20 copied items persistently, utilizing 15 KB of storage during normal operations, with encrypted storage for enhanced security. Additionally, the assistant features a specialized Developer Mode, activating in just 1.0 second, offering tools like a package installer for seamless library installations, a function finder for retrieving information on built-in functions, a system variable path editor for efficient environment variable management, and a multiple monitor setup for optimizing multiscreen workflows. The screen time manager further improves digital well-being by tracking screen usage, scheduling breaks, and activating night mode when necessary. This research discusses the system's modular architecture, implementation, and performance — demonstrating its effectiveness in streamlining user workflows while maintaining low resource consumption, such as 150 MB memory usage and a CPU load of 8.7% under normal working conditions.