ARIoT: Scalable Augmented Reality Framework for Interacting with Internet of Things Appliances Everywhere

Abstract

This paper proposes a scalable Augmented Reality (AR) framework enabled by a simple extension to the Internet of Things (IoT) infrastructure, called the "ARIoT." Through ARIoT (1) potential user-proximal target objects are dynamically identified in any IoT-enabled space, (2) tracking feature information is directly obtained from the IoT objects enabling fast recognition and tracking (independent of the number of the total IoT objects everywhere), and (3) generic interactive contents are augmented as an IoT service to the AR client. To further improve the AR tracking performance, which often depends on feature appearances, this paper introduces a method in which the preferred tracking method is determined by the very IoT object in hand. The proposed concept of ARIoT is demonstrated, and its performance is evaluated and compared with the conventional single serveror client-based AR implementation. In addition, a pilot usability test is conducted between a spatially registered visual in-situ AR interface using ARIoT and a conventional interface based only on an online connection, and the results are then compared. This study shows how AR and IoT can be complementary to each other: AR as an attractive visual insitu interface for IoT objects and IoT as a basis for scalable AR(1).