VIO: Visualize Interactive Objects

Abstract

The rapid advancement of eXtended Reality (XR) technologies has coincided with a growing demand for innovative applications that integrate seamlessly with the Internet of Things (IoT). However, the multidisciplinary nature of XR applications often makes data integration a resource-intensive and time-consuming task. Additionally, current XR data visualization techniques frequently overlook the representation and interaction with IoT devices within virtual environments, neglecting the spatial representation and interactive capabilities required to effectively engage with IoT devices in the virtual world. To address these challenges, this thesis presents VIO, a data transformation framework designed to simplify the integration of IoT devices and data into XR applications.

VIO consists of two main components: a runtime library (VRT) integrated into game engines and a JSON-based syntax for defining VIO Descriptions (VDs). The VRT interprets VDs to facilitate the visualization and interaction of IoT data within the XR environment. By raising the level of abstraction, VIO enables developers to integrate IoT data with minimal coding effort.

The framework was evaluated through both quantitative and qualitative methods. The quantitative evaluation demonstrated that VIO implementations are lightweight and incur negligible overhead at runtime compared to native implementations. The qualitative evaluation, conducted with 12 participants, revealed that VDs are intuitive, easy to use, and extensible to other types of data.