SmartGate ACC: A Proposed QR-Based Attendance and Entry Management Framework for PSU - ACC

Institutional management is undergoing an extensive digital shift driven by Industry 4.0, making real-time data acquisition essential for administrative accountability. For educational institutions like Pangasinan State University – Alaminos City Campus (PSU-ACC), maintaining precise attendance logs for its 88 personnel (60 faculty and 28 non-teaching staff) is critical, since minor tracking delays carry direct institutional sanctions. While Quick Response (QR) code tracking systems offer an affordable, contactless mechanism for automated logs, standard configurations remain heavily dependent on continuous internet connectivity. Network disruptions frequently break automated workflows, forcing security personnel to revert to manual paper sign-in sheets, introducing administrative redundancies, reporting delays, and vulnerability to proxy attendance. To address these gaps, this study aims to design and develop SmartGate ACC, a proposed IoT-integrated entry management system featuring dual-layer authentication—combining QR code scanning and biometric facial recognition—alongside an engineered offline-first synchronization architecture. Following an Agile Software Development Life Cycle (SDLC) framework structured across seven phases (Plan, Design, Develop, Test, Deploy, Review, and Launch), the system will integrate a Flutter mobile application, Google ML Kit for localized biometric matching, an embedded SQLite local cache database, a Laravel back-end web dashboard, and a central MySQL database. System usability and quality will be evaluated by 50 purposively sampled respondents using a modified questionnaire based on the ISO/IEC 25010 standard, covering functional suitability, reliability, performance efficiency, usability, and security. The proposed system framework aims to establish a secure, network-resilient blueprint capable of executing identity verification locally on the edge terminal during network outages and triggering an automated Store-and-Forward background process to synchronize data with the cloud server upon reconnection. By eliminating manual logbook redundancies and preventing credential fraud, this study aims to demonstrate how localized edge computing and automated cloud synchronization can secure administrative workflows in resource-constrained academic environments.

Quick Response (QR) technology, Biometric Face Recognition, Edge Computing, Offline-First Architecture

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