Students’ Number Detection System Using Internet of Things (IoT) Based on Image Classification Method

Buhari Buhari, Muslimin Muslimin, Lisda Ramdhani

Abstract


This research aims to develop a system that can provide classroom security, design and implement a student facial recognition system in classrooms. The development of a student counting system using IoT-based image classification methods makes it easier for lecturers and teachers to document student numbers. This research uses a campus or school classroom as the case study location.

The devices used include a camera or webcam module as a face detection input device, a laptop to process the camera input, validate it against the class database, and perform the identification process (using the image classification library in the OpenCV application), and a laptop that functions as a web server to display the student count dashboard page. Test results show that the system can function properly when the distance between the camera and the student's face is between 30 cm and 170 cm, and cannot count at all at a distance of 180 cm.

 


Keywords


Student number detection system using internet-based image classification method Internet Of Things (IoT).

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DOI: http://dx.doi.org/10.58258/jupe.v10i3.9483

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