Modern educational institutions require intelligent and automated systems to improve classroom management, enhance safety, and optimize energy usage. Traditional methods of attendance recording, classroom monitoring, and resource management often involve manual effort and lack real-time automation. This paper presents an Artificial Intelligence (AI) and Internet of Things (IoT)-enabled Smart Classroom Monitoring System using Raspberry Pi to provide a contactless, efficient, and intelligent learning environment. The proposed system integrates face recognition technology through a camera module for automatic attendance marking, a Passive Infrared (PIR) sensor for detecting human presence and controlling electrical appliances such as lights and fans, a microphone for recording classroom lectures, and an automated lecture summarization process for generating digital notes. The Raspberry Pi serves as the central processing unit that manages data acquisition, decision-making, and communication processes, including sending attendance and notification emails to teachers and parents. Experimental implementation of the proposed system demonstrates reliable real-time student identification, automated appliance control based on occupancy, and efficient generation of lecture summaries, reducing manual workload and unnecessary energy consumption. The developed system contributes to Smart Campus and digital learning ecosystems by combining Artificial Intelligence and Internet of Things technologies to create a more efficient, sustainable, and technology-driven educational infrastructure.

The proposed Artificial Intelligence (AI) and Internet of Things (IoT)-Enabled Smart Classroom Monitoring System using Raspberry Pi provides an intelligent and cost-effective solution for modern educational environments. The system successfully integrates face recognition-based automated attendance, occupancy-based control of classroom appliances, email notification services, and lecture audio summarization within a single platform. The implementation reduces manual effort, improves attendance accuracy, enhances communication between educational institutions and parents, and promotes efficient energy utilization. The integration of Artificial Intelligence, IoT technologies, and embedded computing enables the development of a smart classroom infrastructure that supports digital learning and sustainable resource management. The experimental results demonstrate the feasibility and effectiveness of the proposed system in providing real-time monitoring and automation.

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