Classroom management acts as a link in creating a productive and active learning environment, especially in recent years of smart campus development. Dealing with the dynamic nature of classroom schedules and the complexity of classroom allocations presents a major challenge for classroom management especially with reservation. There have been several studies on utilizing technologies such as AI to identify attendance and room booking systems that can monitor room occupancy. This paper introduces a classroom monitoring system that aims to help manage classroom allocations and reservations through the integration of image detection utilizing a pre-trained YOLOv8-nano model to count the number of people in th eroom with frameworks such as FastAPI to develop the model's API and Laravel. The Laravel application requests the inference through the FastAPI endpoint, and the student attendance is displayed through the web page. Leveraging capabilities in YOLOv8-nano, the system identifies and analyzes the presence and movement of individuals such as students and educators using images captured by cameras in each classroom. The classroom monitoring system also consists of several other centralized features such as for reserving classrooms and managing classroom schedules and reservations. The observed results indicate a successful integration between the model and the system. Employing a pre-trained model also proves to be an effective approach as it can accurately identify the number of individuals inside a classroom, which is necessary for marking the availability of a classroom on the website. Fast inference times of the pre-trained model are also needed as the system needs to handle multiple cameras and requests simultaneously for multiple users. The centralized reservation system also helps users such as students in accessing resources from the university which is beneficial for a more organized and streamlined learning process and for administrators to aid better resource allocation and scheduling adjustments.
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Hidayat et al. (2024) studied this question.
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