Evaluating the Use of Augmented Reality and 2D Interfaces for Diagnosing IoT-based Habitable Smart Spaces by Non-Expert Users EICS022
Ioannis Kanellopoulos, Ioulia Simou, Andreas KomninosSmart space automation has, for decades, proposed a vision for enhancing the quality of human life. The Internet of Things (IoT) is one of the technologies addressing challenges and automating tasks that were once solely dependent on human intervention. However, what happens if an IoT system goes into a fault state? How can field-service technicians and even moderately tech-literate end-users without prior system knowledge diagnose and fix problems? In this paper, we investigate how different interface paradigms support diagnostic tasks in such scenarios, by presenting an Augmented Reality-based diagnostic tool and comparing it against a traditional 2D diagnostic desktop interface in a controlled user evaluation (n=25). We find that participants using the situated and embodied AR system complete tasks faster, task accuracy remains similar across interfaces and that the AR-based system is associated with higher physical demand. We interpret these findings as reflecting trade-offs between situated and embodied AR interfaces and symbolic 2D interfaces, and discuss implications for the design of diagnostic tools in smart space environments.