Smart Classrooms: A Simplified Approach to Face Recognition Using Machine Learning

This article investigates the integration of the latest technology in educational environments, emphasizing an easy implementation of machine learning for face recognition. Leveraging the user-friendly platform Teachable Machine, the study successfully designed and implemented a face recognition system in a classroom setting. A dataset consisting of 50 facial images for each of the 12 students was utilized, resulting in a highly accurate machine-learning model. Remarkably, the machine learning that was built recognized all 12 students. The findings indicate not only the efficiency of the implemented system but also its potential for widespread application in enhancing classroom security and attendance tracking. The accessibility of Teachable Machines emerges as a key factor, standardizing the development and deployment of machine learning models in educational contexts. The study highlights how smoothly advanced technology can be used in classrooms. The Accuracy value of the developed Machine Learning model is 94.4%, and the F1 score is 95%.