The matrix revisited: A critical assessment of virtual reality technologies for modeling, simulation, and training

A convergence of affordable hardware, current events, and decades of research have advanced virtual reality (VR) from the research lab into the commercial marketplace. Since its inception in the 1960s, and over the next three decades, the technology was portrayed as a rarely used, high-end novelty for special applications. Despite the high cost, applications have expanded into defense, education, manufacturing, and medicine. The promise of VR for entertainment arose in the early 1990\u27s and by 2016 several consumer VR platforms were released. With VR now accessible in the home and the isolationist lifestyle adopted due to the COVID-19 global pandemic, VR is now viewed as a potential tool to enhance remote education. Drawing upon over 17 years of experience across numerous VR applications, this dissertation examines the optimal use of VR technologies in the areas of visualization, simulation, training, education, art, and entertainment. It will be demonstrated that VR is well suited for education and training applications, with modest advantages in simulation. Using this context, the case is made that VR can play a pivotal role in the future of education and training in a globally connected world

Integration of multiple data types in 3-D immersive virtual reality (VR) environments

Intelligent sensors have begun to play a key part in the monitoring and maintenance of complex infrastructures. Sensors have the capability not only to provide raw data, but also provide information by indicating the reliability of the measurements. The effect of this added information is a voluminous increase in the total data that is gathered. If an operator is required to perceive the state of a complex system, novel methods must be developed for sifting through enormous data sets. Virtual reality (VR) platforms are proposed as ideal candidates for performing this task-- a virtual world will allow the user to experience a complex system that is gathering a multitude of sensor data and are referred as Integrated Awareness models. This thesis presents techniques for visualizing such multiple data sets, specifically - graphical, measurement and health data inside a 3-D VR environment. The focus of this thesis is to develop pathways to generate the required 3-D models without sacrificing visual fidelity. The tasks include creating the visual representation, integrating multi-sensor measurements, creating user-specific visualizations and a performance evaluation of the completed virtual environment