Volume 44, Issue 1, November 2024, Pages 1–10
Moe Moe Zaw1 and Hla Hla Myint2
1 Faculty of Information and Communication Technology, University of Technology (Yatanarpon Cyber City), Myanmar
2 Department of Information Technology Supporting and Maintenance, University of Computer Studies (Magway), Magway, Myanmar
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The Smart Learning Tool for Kids with Real-time Image Classification is an AI-powered educational tool designed to assist young learners in recognizing and identifying objects through real-time image classification. The system captures images using a webcam, processes them through a Convolutional Neural Network (CNN) model and outputs the corresponding class label. It provides immediate audio feedback by pronouncing the class name in four languages: English, Myanmar, Thai and Chinese. The system aims to enhance kids’ learning experience by engaging multiple senses—visual and auditory—that makes learning interactive and multilingual. The CNN model is trained with custom training data, enabling accurate classification of 12 object classes. This system serves as a smart and user-friendly tool for early childhood education.
Author Keywords: Real-time Image Classification, Convolutional Neural Network (CNN), Multilingual Audio Feedback, Early Childhood Education, Interactive Learning, AI in Education.
Moe Moe Zaw1 and Hla Hla Myint2
1 Faculty of Information and Communication Technology, University of Technology (Yatanarpon Cyber City), Myanmar
2 Department of Information Technology Supporting and Maintenance, University of Computer Studies (Magway), Magway, Myanmar
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The Smart Learning Tool for Kids with Real-time Image Classification is an AI-powered educational tool designed to assist young learners in recognizing and identifying objects through real-time image classification. The system captures images using a webcam, processes them through a Convolutional Neural Network (CNN) model and outputs the corresponding class label. It provides immediate audio feedback by pronouncing the class name in four languages: English, Myanmar, Thai and Chinese. The system aims to enhance kids’ learning experience by engaging multiple senses—visual and auditory—that makes learning interactive and multilingual. The CNN model is trained with custom training data, enabling accurate classification of 12 object classes. This system serves as a smart and user-friendly tool for early childhood education.
Author Keywords: Real-time Image Classification, Convolutional Neural Network (CNN), Multilingual Audio Feedback, Early Childhood Education, Interactive Learning, AI in Education.
How to Cite this Article
Moe Moe Zaw and Hla Hla Myint, “Smart Learning Tool for Kids with Real-Time Image Classification,” International Journal of Innovation and Applied Studies, vol. 44, no. 1, pp. 1–10, November 2024.
