ARTIFICIAL INTELLIGENCE EMPOWERED AUGMENTED REALITY APPLICATION FOR ELECTRICAL ENGINEERING LAB EDUCATION

With the rising popularity of online and hybrid learning, this study explores an innovative method to improve students’ learning experiences with Electrical and Computer Engineering lab equipment by employing cutting-edge technologies in augmented reality (AR) and artificial intelligence (AI). Automatic object detection component, aligned with AR application, is developed to recognize equipment, including multimeter, oscilloscope, wave generator, and power supply. The deep neural network model, namely MobileNet SSD v2, is implemented in the study for equipment recognition. We used object detection API from TensorFlow (TF) framework to build the neural network model. When a piece of equipment is detected, the corresponding augmented reality (AR) based tutorial will be displayed on the screen. In this study, a tutorial for multi-meter is implemented. In order to provide users an intuitive and easy-to-follow tutorial, we superimpose virtual models on the real multimeter. In addition, images and web links are added in the tutorial to facilitate users with a better learning experience. Unity3D game engine is used as the primary development tool to merge both framework systems and build immersive scenarios in the tutorial.