Augmented Reality (AR) Based Virtual Lab: A Survey on Interactive AR Learning Platforms and Educational Applications Using Deep Learning Techniques

Abstract: Augmented Reality (AR) is becoming an important digital learning approach because it can convert routine laboratory instruction into an immersive, flexible, and learner-friendly experience. Conventional laboratories demand costly equipment, regular maintenance, sufficient physical space, and continuous supervision; these requirements often restrict repeated practice and equal access for students. AR-enabled virtual laboratories overcome many of these barriers by placing three-dimensional digital objects and guided simulations over the real environment through mobile or wearable devices.

This survey presents a consolidated review of AR-supported laboratory learning with particular focus on deep learning, adaptive interaction, object recognition, simulation design, and educational outcomes. It discusses the role of tools and frameworks such as Unity 3D, Blender, Vuforia SDK, Android Studio, Faster R-CNN, SSD, and YOLOv7. Existing approaches are compared with respect to accuracy, response time, scalability, and usefulness in teaching-learning practice. The paper also identifies limitations such as device dependency, processing load, tracking errors, and usability concerns, and it highlights future possibilities involving artificial intelligence, cloud-supported AR, analytics, and personalized virtual laboratories.

Keywords: Augmented Reality; Virtual Laboratories; Educational Technology; Deep Learning; YOLOv7; Interactive Learning; Computer Vision.