A Real-Time Artificial Intelligence System for Collaborative Document Editing and Workload Optimisation

Abstract

Managing and collaborating on documents has long been integral to work,
education, and communication. In the digital age, these tasks demand greater
speed, flexibility, and security. This dissertation proposes a Real-Time AI-Powered
Document Editing System for Collaborative Workflows, designed to address the
challenges of simultaneous multi-user editing, access control, and data protection.
The primary aim is to develop a platform that enables multiple users to edit the
same document in real-time with synchronized updates and intelligent conflict
resolution. The system integrates an AI-driven permission management module
that assigns and adjusts user roles dynamically, based on contextual analysis and
behavioral patterns. To safeguard document integrity and user data, the system
also includes encrypted file access, automated activity logging, and access anomaly
detection. The solution is developed using an Object-Oriented Approach, paired
with the Rapid Application Development (RAD) methodology. This ensures a
modular, user-focused design process with frequent iterations and fast
prototyping. The choice of RAD supports responsive adaptation to user feedback
and evolving requirements during the development cycle. This research
demonstrates how the combination of real-time collaboration, artificial
intelligence, and secure design principles can enhance document management
systems. The outcome is a scalable and intelligent platform that aligns with the
growing demand for collaborative, efficient, and secure digital workspaces.