Design and Development of Smart AI-Powered Desktop Assistant for Productivity Enhancement
Rahul S Santhosh P Rajvignesh B S Dr. R S Ponmagal
AbstractThis 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) for retrieving text from images, task reminders integrated with Google and Microsoft calendars, sticky notes, a to-do list, and a QR scanner for decoding embedded information. A unique clipboard manager securely tracks and stores up to 20 copied items persistently, with encrypted storage for enhanced security. Additionally, the assistant features a specialized Developer Mode, 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 multi-screen 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 architecture, implementation, and performance, demonstrating its effectiveness in streamlining user workflows and improving overall efficiency.