The Role of Object Detection, Tracking and Augmentation in Guiding the Remote Assistance Systems

Abstract

Establishing a remote assistance system which will guide the user in repair or maintenance works of any manufacturer machine is quite challenging. The present paper proposes a solution where the user will train a deep learning models to detect different devices and devices parts. The paper discusses different solutions used in training the models and compares these models in detecting the objects of devices with respect to accuracy and time. The tracking and real-time detection of the objects help the user to perform any remote task with the help of an expert. The solution is ported in all types of mobile devices where users can see the devices and devices parts with augmented information on top of that. This solution will help the user to take remote tasks with the help of expert where expert cannot reach the field for repair or maintenance of devices. The entire solution is deployed for dialysis machine use case for performing multiple repair or maintenance activities of the dialysis machine. The accuracy of these models and model performance in real-time also play a key role as part of our remote assistance tasks.