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