InspectAR: An Augmented Reality Inspection Framework for Industry

Ramakrishna Perla, Gaurav Gupta, Ramya Hebbalaguppe, Ehtesham Hassan

Abstract: With the advancement in camera technologies and data streaming protocols, AR based applications are proving to be an important aid for inspection, training and supervision tasks in various operations including automotive industry, education etc. We demonstrate an AR based re-configurable inspection framework that can be utilized in cross-domain applications such as maintenance and repair assistance in industrial inspection and automotive/avionics domain inspection, amongst others. A deep learning component detects parts viewed in inspector's Field-of-View (FoV) accurately and the corresponding inspection check-list can be prioritized based on detection results. The back-end of the framework is easily configurable for different applications where instructions can be directly imported and visually integrated with inspection type. Accurate recording of status of inspection is provided through evidence capturing of images, notes and videos. Our current framework supports all the Android based devices and will be demonstrated on Google Glass, Google Cardboard with smartphone, and Tablet with the help of 3D printer inspection use-case.