Rio Nurtantyana, Ilyasa Nafan Faza, Mochammad Daffa Faqiha Fawwaz Hanjowo, Muqsit Muhammad Hanif, Wu-Yuin Hwang
In this study, we developed a system with IoT and AI-powered as an additional data acquisition module in a quadruped robot (IADAM) to address the lack of contextual authenticity data sources in EFL learning. Commonly, the EFL learning uses mobile phone devices only to explore the surroundings, however, this study is based on the robot as a physical extension of the user's companion, mediated by real-time data streams and enriched with artificial intelligence (AI). Hence, we have proposed the system architecture with four key technological aspects, such as the robot equipped with advanced onboard sensors, the IoT with a custom sensor module based on the ESP32, the communication employing WebRTC for low-latency video streaming, and the Android application that serves as a command center and interfaces with the AI. We have tested the system with user acceptance testing (UAT) in three real scenarios for EFL learning. The results found that three scenarios have passed the UAT and the future analysis was observed. © 2025 IEEE.
Telkom University, Research Center for Data and Information Sciences, National Research and Innovation Agency (BRIN), Center of Excellence of Artificial Intelligence for Learning and Optimization, Bandung, Indonesia; Indonesia University of Education, Industrial Automation Robotics Engineering Education, Bandung, Indonesia; National Dong-Hwa University & Graduate, Institute of Network Learning Technology, National Central University, Faculty of Science and Engineering, Hualien, Taiwan
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