IoT-Enhanced Smart Campus Management System

Abstract

The emergence of smart campus technologies has transformed educational environments by integrating biometrics, the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML). This paper reviews key advancements in automatic attendance systems, intelligent learning environments, and campus infrastructure optimization. Biometric approaches such as fingerprint, facial recognition, RFID, and NFC enhance the accuracy of real-time attendance monitoring, reducing proxy incidents and administrative workload. IoT frameworks further enable wireless connectivity, real-time analytics, and cloud-based storage, improving system reliability and responsiveness. Concurrently, AI-driven Learning Management Systems (LMS) and Campus Management Systems (CMS) provide personalized learning recommendations, student performance predictions, and risk assessment models with predictive accuracy exceeding 90%. Based on these insights, an IoT-based Smart Campus Management System is proposed that integrates RFID check-in, AI-powered facial verification, and teacher-in-the-loop supervision for robust, privacy-preserving attendance monitoring. This multi-sensor, human-assisted framework enhances accuracy, scalability, and decision-making, contributing to the development of adaptive, secure, and data-driven smart campus ecosystems for future-ready education.