Toward a mixed reality domain model for time-Sensitive applications using IoE infrastructure and edge computing...

Area of Science:

• Computer Science
• Human-Computer Interaction
• Ubiquitous Computing

Background:

• Mixed Reality (MR) applications face significant design and implementation challenges, particularly concerning time-sensitive operations.
• Existing MR systems often struggle with latency and limited interactivity, impacting user experience.
• Integration with advanced networking models is crucial for overcoming these limitations.

Purpose of the Study:

• To propose a novel conceptual model for Mixed Reality applications.
• To enhance MR interactivity and user experience through the integration of Internet of Things (IoT) and Internet of Everything (IoE) models.
• To address latency issues in time-sensitive MR applications by incorporating cloud and fog computing.

Main Methods:

• Development of a conceptual model for MR applications.
• Integration of Internet of Things/Internet of Everything (IoT/IoE) principles.
• Incorporation of cloud and fog computing layers for enhanced processing and reduced latency.
• Validation through a prototype demonstration and a real-time case study.

Main Results:

• The proposed model offers a new layer of interactivity for MR applications.
• Cloud and fog compute layers provide necessary processing power and reduce latency for time-sensitive tasks.
• The model demonstrates applicability, ease of role definition, and data/process coherence in common MR scenarios.

Conclusions:

• The conceptual model effectively enhances MR application interactivity and quality of experience.
• The integration of IoT/IoE and cloud/fog computing is a viable approach to address MR challenges.
• The model's validation confirms its practical applicability and potential for diverse MR applications.