Development of Monitoring System for Early Childhood Education Learning Progress
Muhammad Sufi Aulia, Ary Setijadi Prihatmanto ,Rahadian Yusuf,Agus sukoco

School of Electrical Engineering and Informatics, Bandung Institute of Technology
Jalan Ganesha 10, Bandung 40132, Indonesia

Abstract

ECE (Early Childhood Education ) is important for children learning since it sets a benchmark of learning for children when they begin schooling. However, identification of child development in the context of ECE has been found to be a huge challenge. The objective of this study is to design a highly effective monitoring system based on deep learning, object detection, and YOLO to improve the correctness and speed of monitoring ECE learning progress. Through the use of this technology, the system is designed to be able to analyses and categorise different activities of children in realtime with the feedback to the teachers and parents being immediate. It makes the process of monitoring much easier apart from enhancing communication between the teachers and the parents, not forgetting the progressive growth of the children. This capability was tested based on data captured by cameras placed in the classrooms then passed through yav8 to improve its accuracy as well as real-time monitoring abilities. The study shows how technology application in monitoring ECE improves the system^s ability to meet the need of the children.

Keywords: Early Childhood Education (ECE), Deep Learning, Object Detection, YOLO (You Only Look Once), Real-time Monitoring

Topic: Artificial Intelligence (AI)