Development of an intelligent time management application with context-aware optimisation

Abstract

This study develops an intelligent time management application using machine learning and context-aware optimisation. The system automates task prioritisation by integrating learning analytics with passive mobile sensing while balancing productivity and well-being. Controlled trials demonstrated a 41% reduction in time management effort and 29% higher task completion rates than conventional tools. The results advance adaptive personal productivity systems through demonstrated cross-context portability and automated behavioral adaptation.​