AI-Enabled Facial Recognition Architecture for Real-Time School Monitoring and Operational Analytics

Public school systems often rely on fragmented enrollment, access, and attendance records, limiting timely identification of absenteeism patterns and weakening operational decision-making. This study proposes an ICT-oriented architecture that integrates facial recognition, real-time attendance automation, and analytical dashboards to support more reliable, data-driven school monitoring. Using an applied and exploratory conceptual-design approach, the modeling yielded a seven-module architecture comprising a digital enrollment database, biometric authentication and access control, a real-time attendance engine, early-warning analytics, a family communication interface, managerial dashboards, and intervention logging. The model positions facial recognition not only as an authentication layer but also as a source of auditable events for operational intelligence. By connecting attendance events with analytical rules and historical patterns, the architecture is designed to support earlier identification of recurrent absences, improve data consistency, reduce manual procedures, strengthen access monitoring, support communication with families, and provide planning inputs for services such as school meals. Because biometric data are sensitive personal data, the architecture incorporates privacy-by-design principles, including LGPD-aligned data governance, data minimization, access controls, secure storage and transmission, retention rules, human oversight, and parental or guardian consent procedures where legally applicable. Raw video footage is not intended for permanent storage; facial images are processed for biometric matching, while only protected biometric templates required for authentication are retained. The architecture has not yet been empirically implemented or piloted and remains a conceptual model intended for future technical and institutional validation in public school systems. Its main contribution is the integration of biometric sensing, real-time data flows, and AI-enabled analytics into a unified framework for operational school management and early intervention.