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The rise in crime rates over the past few years is a major issue and is a huge source of worry for police departments and law enforcement organizations. Crime severely harms the lives of victims and the communities they live in many places throughout the world. It is an issue of public disturbance, and large cities often see criminal activity. Many studies, media, and websites include statistics on crime and it is contributing elements, such as population, unemployment, and poverty rate. This paper compares and visualizes the crime data for four different cities in the USA, namely Chicago, Baltimore, Dallas, and Denton. We assess areas that are significantly affected based on zip codes and variations in crime categories. As the crime rates have significantly changed both upward and downward throughout time, these changes are compared to their external causes such as population, unemployment, and poverty. The results show crime frequency and distribution across four different cities and supply valuable information about the complex relationship between social factors and criminal behavior. These results and outcomes will help the police department and law enforcement organizations better understand crime issues, map crime incidents onto a geographical map, and supply insight into factors affecting crime that will help them deploy resources and help in their decision-making process. 

During emergencies like fire and smoke or active shooter events, there is a need to address the vulnerability and assess plans for evacuation. With the recent improvements in technology for smartphones, there is an opportunity for geo-visual environments that offer experiential learning by providing spatial analysis and visual communication of emergency-related information to the user. This paper presents the development and evaluation of the mobile augmented reality application (MARA) designed specifically for acquiring spatial analysis, situational awareness, and visual communication. The MARA incorporates existing permanent features such as room numbers and signages in the building as markers to display the floor plan of the building and show navigational directions to the exit. Through visualization of integrated geographic information systems and real-time data analysis, MARA provides the current location of the person, the number of exits, and user-specific personalized evacuation routes. The paper also describes a limited user study that was conducted to assess the usability and effectiveness of the MARA application using the widely recognized System Usability Scale (SUS) framework. The results show the effectiveness of our situational awareness-based MARA in multilevel buildings for evacuations, educational, and navigational purposes. 

Indoor navigation in complex building environments poses significant challenges, particularly for individuals who are unfamiliar with their surroundings. Mixed reality (MR) technologies have emerged as a promising solution to enhance situational awareness and facilitate navigation within indoor spaces. However, there is a lack of spatial data for indoor environments, including outdated floor plans and limited real-time operational data. This paper presents the development of a mixed-reality application for indoor building navigation and evacuation. The application uses feature extraction for location sensing and situational awareness to provide accurate and reliable navigation in any indoor environment using Microsoft HoloLens. The application can track the user's position and orientation and give the user-specific information on how to evacuate the building. This information is then used to generate navigation instructions for the user. We demonstrate how this mixed reality HoloLens application can provide spatially contextualized 3D visualizations that promote spatial knowledge acquisition and situational awareness. These 3D visualizations are developed as an emergency evacuation and navigation tool to aid the building occupants in safe and quick evacuation. Experimental results demonstrate the effectiveness of the application, providing 3D visualizations of multilevel spaces and aiding individuals in understanding their position and evacuation path during emergencies. We believe that adopting mixed reality technologies, such as the HoloLens, can greatly enhance individuals' ability to navigate large-scale environments during emergencies by promoting spatial knowledge acquisition and supporting cognitive mapping. 

There are a wide variety of mobile phone emergency response applications exist for both indoor and outdoor environments. However, outdoor applications mostly provide accident and navigation information to users, and indoor applications are limited to the unavailability of GPS positioning and WiFi access problems. This paper describes the proposed mobile augmented reality system (MARS) that allows both outdoor and indoor users to retrieve and manage information for emergency response and navigation that is spatially registered with the real world. The proposed MARS utilizes feature extraction for location sensing in indoor environments as during emergencies GPS and WiFi systems might not work. This paper describes the implementation of this MARS deployed on tablets and smartphones for building evacuation purposes. The MARS delivers critical evacuation information to smartphone users in the indoor environment and navigation information in the outdoor environments. A limited user study was conducted to test the effectiveness of the proposed MARS using the mobile phone usability questionnaire (MPUQ) framework. The results show that AR features were well integrated into the MARS and it will help identify the nearest exit in the building during the emergency evacuation. 

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. 

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.