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In recent years there has been a sharp increase in active shooter events, but there has been no introduction of new technology or tactics capable of increasing preparedness and training for active shooter events. This has raised a major concern about the lack of tools that would allow robust predictions of realistic human movements and the lack of understanding about the interaction in designated simulation environments. It is impractical to carry out live experiments where thousands of people are evacuated from buildings designed for every possible emergency condition. There has been progress in understanding human movement, human motion synthesis, crowd dynamics, indoor environments, and their relationships with active shooter events, but challenges remain. This paper presents a virtual reality (VR) experimental setup for conducting virtual evacuation drills in response to extreme events and demonstrates the behavior of agents during an active shooter environment. The behavior of agents is implemented using behavior trees in the Unity gaming engine. The VR experimental setup can simulate human behavior during an active shooter event in a campus setting. A presence questionnaire (PQ) was used in the user study to evaluate the effectiveness and engagement of our active shooter environment. The results show that majority of users agreed that the sense of presence was increased when using the emergency response training environment for a building evacuation environment. 

Visualization explores quantitative content of data with human intuition and plays an integral part in the data mining process. When the data is big there are different analysis methods and approaches used to find inherent patterns and relationships. However, sometimes there is a need to incorporate human in loop approach to find new patterns and relationships. Immersive virtual reality (VR) offers a human centric approach to visualize data by discovering new relationships that an existing algorithm cannot provide. This paper demonstrates the data visualization tool to visualize Baltimore crime data in immersive environment and non-immersive environment. This paper focuses on VR visualization tool design, development, and usability assessment. A pilot user study was conducted for the VR visualization tool based on the system usability scale. The study results show that the crime data visualization tool is relatively easy to use, and that the application can be considered as a storyteller with removing the noise from the data and highlighting the usefulness of the information. 

Active shooter events are not emergencies that can be reasonably anticipated. However, these events do occur more than we think, and there is a critical need for an effective emergency preparedness plan that can increase the likelihood of saving lives and reducing casualties in the event of an active shooting incident. There has been a major concern about the lack of tools available to allow for modeling and simulation of human behavior during emergency response training. Over the past few decades, virtual reality-based training for emergency response and decision making has been recognized as a novel alternative for disaster preparedness. This paper presents an immersive virtual reality (VR) training module for active shooter events for a building emergency response. There are two immersive active shooter modules developed: occupant’s module and Security personnel module. We have developed an immersive virtual reality training module for active shooter events using an Oculus for the course of action, visualization, and situational awareness for active shooter events. The immersive environment is implemented in Unity 3D where the user has an option to enter the environment as security personnel or as an occupant in the building. The immersive VR training module offers a unique platform for emergency response and decision making training. The platform allows for collecting data on different what-if scenarios in response to active shooter events that impact the actions of security personnel and occupants in a building. The data collected can be used to educate security personnel on how to reduce response times. Moreover, security personnel can be trained to respond to a variety of emergencies safely and securely without ever being exposed to real-world dangers. 

Emergency response, navigation, and evacuation are key essentials for effective rescue and safety management. Situational awareness is a key ingredient when fire responders or emergency response personnel responds to an emergency. They have to quickly assess the layout of a building or a campus upon entry. Moreover, the occupants of a building or campus also need situational awareness for navigation and emergency response. We have developed an integrated situational awareness mobile augmented reality (AR) application for smart campus planning, management, and emergency response. Through the visualization of integrated geographic information systems and real-time data analysis, our mobile application provides insights into operational implications and offers information to support effective decision-making. Using existing building features, the authors demonstrate how the mobile AR application provides contextualized 3D visualizations that promote and support spatial knowledge acquisition and cognitive mapping thereby enhancing situational awareness. A limited user study was conducted to test the effectiveness of the proposed mobile AR application using the mobile phone usability questionnaire (MPUQ) framework. The results show that the mobile AR application was relatively easy to use and that it can be considered a useful application for navigation and evacuation. 

Visualizing data effectively is critical for the discovery process in the age of big data. We are exploring the use of immersive virtual reality platforms for scientific data visualization for COVID-19 pandemic. We are interested in finding ways to better understand, perceive and interact with multidimensional data in the field of cognition technology and human-computer interaction. Immersive visualization leads to a better understanding and perception of relationships in the data. This paper presents a data visualization tool for immersive data visualizations based on the Unity development platform. The data visualization tool is capable of visualizing the real-time COVID pandemic data for the fifty states in the USA. Immersion provides a better understanding of the data than traditional desktop visualization tools and leads to more human-centric situational awareness insights. This research effort aims to identify how graphical objects like charts and bar graphs depicted in Virtual Reality tools, developed in accordance with an analyst’s mental model can enhance an analyst’s situation awareness. Our results also suggest that users feel more satisfied when using immersive virtual reality data visualization tools and thus demonstrate the potential of immersive data analytics. 

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. 

Data visualization gives a visual context through maps or graphs and makes it easier for the human mind to identify trends, patterns, and outliers within large data sets. The understanding of patterns and location of crime through data visualization and data mining techniques approaches is a very useful tool which can help and support police forces. Identification of crime characteristics and types are the first step for developing further analysis. This paper describes the development of data visualization tool using Unity 3D and Maptitude GIS for visualization of Baltimore COVID-19 and crime data. This effort aims to determine parameters that influence the vulnerability of African Americans to COVID-19 during the pandemic. The study has found that the factors shown to be influential in a person’s susceptibility include neighborhood and physical environment, housing, occupation, education, income, and wealth gaps. The data collected from Baltimore incident reports and findings shared by Maryland SOA office shows that crime has increased and decreased in different areas during the time of COVID pandemic.