AI-Based Child Behaviour and Mental Health Monitoring System

Children increasingly use smartphones for communication, entertainment, and learning. Although digital devices provide useful opportunities, excessive or unsuitable use may affect daily routines and expose children to inappropriate content. Parents may find it difficult to understand these patterns through occasional observation alone. This paper presents an Android-based prototype, Safeguard, designed to support parental awareness of children's smartphone behaviour. The system focuses on application-use monitoring, content-safety screening, behavioural indicators, and parent notifications. App activity is organized to provide a view of usage patterns, while text-related safety signals are screened using a rule-based approach. The system is intended to highlight potentially concerning patterns for review rather than make a clinical diagnosis. Prior research has explored mobile mental-health applications, emotion-aware typing analysis, social-media text classification, and child mental-health surveillance. These studies inform the design of the proposed system, particularly the need for continuous observation, accessible reporting, and careful interpretation of automated indicators. The prototype's current functionality is described, together with its limitations and a proposed evaluation plan. No clinical validation or measured predictive accuracy is claimed. The system is intended as an assistive tool for caregivers, with further work required to assess usability, reliability, privacy, and effectiveness.