Revolutionising Educational Management with AI and Wireless Networks: A Framework for Smart Resource Allocation and Decision-Making - Christos Koukaras; Euripides Hatzikraniotis; Maria Mitsiaki; Paraskevas Koukaras; Christos Tjortjis; Stavros G. Stavrinides (Applied Sciences)
Educational institutions face growing challenges. Rising enrolment, limited budgets, and sustainability goals demand more efficient resource management and administrative decision-making. To address challenges like these, this work proposes a conceptual framework for smart campus management which integrates Artificial Intelligence (AI) and advanced wireless networks based on 5G. The framework’s design outlines layers for campus data collection (via sensors and connected devices), high-speed communication, and AI-driven analytics for decision support. By leveraging data-driven insights enabled by reliable wireless connectivity, institutions can make more informed decisions, use resources more effectively, and automate routine tasks. Envisioned AI capabilities include forecasting (for predictive maintenance and demand planning), anomaly detection (for fault or irregularity identification), and optimisation (for resource scheduling). Rather than reporting empirical results, the framework is illustrated through hypothetical scenarios (e.g., anticipating equipment maintenance, dynamically scheduling classrooms, or reallocating resources) to present potential benefits and tools for researchers. The discussion also highlights how the framework incorporates data privacy, security, and accessibility considerations to ensure inclusive adoption. Eventually, this conceptual proposal provides a roadmap for administrators and planners, guiding the adoption of AI and wireless innovations in educational management to enable more responsive, efficient governance and, ultimately, improve outcomes for students and staff.