Smart Classroom Monitoring System Using IoT and AI to Improve Space Utilization in Higher Education

Abstract

The rapid advancement of digital technology has encouraged higher education institutions to implement intelligent systems for improving facility management efficiency. This study focuses on the development and evaluation of a Smart Monitoring Class system that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies to optimize classroom utilization. The system employs multiple sensors to monitor environmental parameters such as temperature, humidity, and illumination, as well as to detect occupancy in real time. The collected data are processed using AI algorithms to analyze room usage patterns and provide recommendations for scheduling and energy management. The research follows the System Development Life Cycle (SDLC) approach, including stages of requirement analysis, system design, implementation, and evaluation. Experimental results show that the proposed system achieves high performance in terms of sensor accuracy, data transmission delay, and overall system reliability. The AI module successfully identifies classroom usage patterns with an accuracy rate of over 90%, enabling adaptive control of environmental conditions and energy-saving mechanisms. These findings indicate that the integration of IoT and AI technologies significantly enhances the efficiency, transparency, and sustainability of classroom management in higher education institutions.