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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. 

There has been an increasing concern that African American community has been disproportionately impacted during the coronavirus pandemic. This paper analyzes why the African American community is disproportionately impacted during the coronavirus pandemic and compares the COVID-19 data with hospitalizations, real estate, school closings, and crime data. Human behavior was impacted as a result of lockdown due to COVID pandemic and it lead to a shift in crime dynamics. We analyze shifts in crime types by comparing crimes before and after the COVID pandemic in Baltimore. There was a significant decline in total crimes during the time period immediately following stay at home orders. Findings show that the disproportionality among the African American community is significantly influenced by factors such as living in more crowded housing situations, working in consumer-facing serviced industries, having higher rates of pre-existing medical conditions, and lack of insurance or a consistent care source. 

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. 

Emergency response training is needed to remember and implement emergency operation plans (EOP) and procedures over long periods until an emergency occurs. There is also a need to develop an effective mechanism of teamwork under emergency conditions such as bomb blasts and active shooter events inside a building. One way to address these needs is to create a collaborative training module to study these emergencies and perform virtual evacuation drills. This paper presents a collaborative virtual reality (VR) environment for performing emergency response training for fire and smoke as well as for active shooter training scenarios. The collaborative environment is implemented in Unity 3D and is based on run, hide, and fight mode of emergency response. Our proposed collaborative virtual environment (CVE) is set up on the cloud and the participants can enter the VR environment as a policeman or as a civilian. We have used game creation as a metaphor for developing a CVE platform for conducting training exercises for different what-if scenarios in a safe and cost-effective manner. The novelty of our work lies in modeling behaviors of two kinds of agents in the environment: user-controlled agents and computer-controlled agents. The computer controlled agents are defined with preexisting rules of behaviors whereas the user controlled agents are autonomous agents that provide controls to the user to navigate in the CVE at their own pace. Our contribution lies in our approach to combine these two approaches of behavior to perform emergency response training for building evacuation. 

There is growing concern that racial and ethnic minority communities around the United States are experiencing a disproportionate burden of infection rate and mortality from the coronavirus disease 2019 (Covid-19). While most research, media newspapers, websites, and television networks are providing statistical numbers of daily infection and death rate across US by state, these numbers fail to study the actual impact of COVID-19 to each race. Our approach has taken the top five races by population count in the US and has calculated the impact index by race for each state for COVID-19 infections and death rate. We also examine the rise in the utilization of hospitals as a result of the rise in cases of COVID-19 in the United states. We conclude that the African American race and Hispanic race is disproportionately impacted more than the white population for infection rate.