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Situational awareness provides the decision making capability to identify, process, and comprehend big data. In our approach, situational awareness is achieved by integrating and analyzing multiple aspects of data using stacked bar graphs and geographic representations of the data. We provide a data visualization tool to represent COVID pandemic data on top of the geographical information. The combination of geospatial and temporal data provides the information needed to conduct situational analysis for the COVID-19 pandemic. By providing interactivity, geographical maps can be viewed from different perspectives and offer insight into the dynamical aspects of the COVID-19 pandemic for the fifty states in the USA. We have overlaid dynamic information on top of a geographical representation in an intuitive way for decision making. We describe how modeling and simulation of data increase situational awareness, especially when coupled with immersive virtual reality interaction. This paper presents an immersive virtual reality (VR) environment and mobile environment for data visualization using Oculus Rift head-mounted display and smartphones. This work combines neural network predictions with human-centric situational awareness and data analytics to provide accurate, timely, and scientific strategies in combatting and mitigating the spread of the coronavirus pandemic. Testing and evaluation of the data visualization tool have been done with real-time feed of COVID pandemic data set for immersive environment, non-immersive environment, and mobile environment. 

Healthcare practitioners, social workers, and care coordinators must work together seamlessly, safely and efficiently. Within the context of the COVID-19 pandemic, understanding relevant evidence-based and best practices as well as identification of barriers and facilitators of care for vulnerable populations are of crucial importance. A current gap exists in the lack of specific training for these specialized personnel to facilitate care for socially vulnerable populations, particularly racial and ethnic minorities. With continuing advancements in technology, VR based training incorporates real-life experience and creates a “sense of presence” in the environment. Furthermore, immersive virtual environments offer considerable advantages over traditional training exercises such as reduction in the time and cost for different what-if scenarios and opportunities for more frequent practice. This paper proposes the development of Virtual Reality Instructional (VRI) training modules geared for COVID-19 testing. The VRI modules are developed for immersive, non-immersive, and mobile environment. This paper describes the development and testing of the VRI module using the Unity gaming engine. These VRI modules are developed to help increase safety preparedness and mitigate the social distancing related risks for safety management. 

Real-time data visualization can enhance decision making and empower teams with human-centric situational awareness insights. Decision making relies on data which comes in overwhelming velocity and volume, that one cannot comprehend it without some layer of abstraction. This research effort aims to demonstrate the data visualization of the COVID pandemic in real-time for the fifty states in the USA. Our proposed data visualization tool includes both conceptual and data-driven information. The data visualization includes stacked bar graphs, geographic representations of the data, and offers situational awareness of the COVID-19 pandemic. This paper describes the development and testing of the data visualization tool using the Unity gaming engine. Testing has been done with a real-time feed of the COVID-19 data set for immersive environment, non-immersive environment, and mobile environment. 

During emergencies communicating in multi-level built environment becomes challenging because architectural complexity can create problems with visual and mental representation of 3D space. Our Hololens application gives a visual representation of a building on campus in 3D space, allowing people to see where exits are in the building as well as creating alerts for anomalous behavior for emergency response such as active shooter, fire, and smoke. It also gives path to the various exits; shortest path to the exits as well as directions to a safe zone from their current position. The augmented reality (AR) application was developed in Unity 3D for Microsoft HoloLens and also is deployed on tablets and smartphones. It is a fast and robust marker detection technique inspired by the use of Vuforia AR library. Our aim is to enhance the evacuation process by ensuring that all building patrons know all of the building exits and how to get to them, which improves evacuation time and eradicates the injuries and fatalities occurring during indoor crises such as building fires and active shooter events. We have incorporated existing permanent features in the building as markers for the AR application to trigger the floor plan and subsequent location of the person in the building. This work also describes the system architecture as well as the design and implementation of this AR application to leverage HoloLens for building evacuation purposes. We believe that AR technologies like HoloLens could be adopted for all building evacuating strategies during emergencies as it offers a more 

During active shooter events or emergencies, the ability of security personnel to respond appropriately to the situation is driven by pre-existing knowledge and skills, but also depends upon their state of mind and familiarity with similar scenarios. Human behavior becomes unpredictable when it comes to making a decision in emergency situations. The cost and risk of determining these human behavior characteristics in emergency situations is very high. This paper presents an immersive collaborative virtual reality (VR) environment for performing virtual building evacuation drills and active shooter training scenarios using Oculus Rift head mounted displays. The collaborative immersive environment is implemented in Unity 3D and is based on run, hide, and fight mode for emergency response. The immersive collaborative VR environment also offers a unique method for training in emergencies for campus safety. The participant can enter the collaborative VR environment setup on the cloud and participate in the active shooter response training environment, which leads to considerable cost advantages over large-scale real-life exercises. A presence questionnaire in the user study was used to evaluate the effectiveness of our immersive training module. The results show that a majority of users agreed that their sense of presence was increased when using the immersive emergency 

Emergency response in indoor building evacuation is essential for effective rescue and safety management. First responders often lack the situational awareness capability to quickly assess the layout of a building upon initial entry. For occupants of the building, situational awareness becomes more important in cases of active shooter events or circumstances of fire and smoke. One of the challenges is to provide user-specific personalized evacuation routes in real-time. In multilevel building environments, the complexity of the architecture creates problems for both visual and mental representation of the 3D spaces. This paper presents three cutting edge Augmented Reality Instructional (ARI) modules that overcome the visual limitations associated with the traditional, static 2D methods of communicating evacuation plans for multilevel buildings. Using existing building features, the authors demonstrate how the three modules provide contextualized 3D visualizations that promote and support spatial knowledge acquisition and cognitive mapping thereby enhancing situational awareness. These ARI visualizations are developed for first responders and building occupants to help increase emergency preparedness and mitigate the evacuation related risks in multilevel building rescues and safety management. Specifically, the paper describes the design and implementation of the ARI modules and reports the results of the pilot studies conducted to evaluate their perceived usefulness, ease-of-use, and usability. The results suggest the desirability of further heuristic examination of three-dimensional situational awareness-based ARI application effectiveness in multilevel building evacuations. 

Collaborative virtual assembly environment is a vital computer-aided design tool in product design and can be used as a learning and training tool. It helps in supporting complex product design by enabling designers to collaborate and communicate with other designers involved in the product design. This paper proposes a collaborative virtual assembly environment built in two phases for the immersive and non-immersive environments. Phase one was developed in Unity 3D using Virtual Reality Toolkit (VRTK) and Steam VR. Whereas, phase two was built using Vizard and Vizible. This work aims to allow scientists and engineers to discuss the concept design in a real-time VR environment so that they can interact with the objects and review their work before it is deployed. This paper proposes the system architecture and describes the design and implementation of a collaborative virtual assembly environment. The outcome of this work is to be able to resolve communication and interaction problems that arise during the concept-design phase. 

Human-centric situational awareness and visualization are needed for analyzing the big data in an efficient way. One of the challenges is to create an algorithm to analyze the given data without any help of other data analyzing tools. This research effort aims to identify how graphical objects (such as data-shapes) developed in accordance with an analyst's mental model can enhance analyst's situation awareness. Our approach for improved big data visualization is two-fold, focusing on both visualization and interaction. This paper presents the developed data and graph technique based on forcedirected model graph in 3D. It is developed using Unity 3D gaming engine. Pilot testing was done with different data sets for checking the efficiency of the system in immersive environment and non-immersive environment. The application is able to handle the data successfully for the given data sets in data visualization. The currently graph can render around 200 to 300 linked nodes in real-time.