Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
127 University of North Texas (142015)
Principal Investigator: Sharma,Sharad
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 180,000
Exceeds $250,000 (Is it flagged?): No
Start and End Dates: 12/15/22 - 9/30/23
Restricted Research: YES
Academic Discipline: Information Science
Department, Center, School, or Institute: College of Information
Title of Contract, Award, or Gift: Collaborative Research: CISE-MSI: RCBP-RF: CPS, CNS: Emergency Response and Evacuation Training for Active Shooter Events
Name of Granting or Contracting Agency/Entity:
National Science Foundation
CFDA Link: NSF
47.070
Program Title:
none
CFDA Linked: Computer and Information Science and Engineering
Note:
In recent years, we witnessed a sharp increase in active shooter events; however, unfortunately, there has been no introduction of new technology or tactics capable of increasing preparedness and training for active shooter events. The goal of this effort is to conduct data collection, preliminary experiments, and a prototype development for the two campuses for improving emergency preparedness for an active shooter event using collaborative immersive virtual reality (VR) environment. We have already developed an occupants training virtual reality instructional (VRI) module of active shooter response for a BSU building using run, hide and fight mode. The simulation environment will be further expanded for the active shooter scenarios on two campuses for civilian training and security personnel training. This project develops algorithms, implements software and demonstrates proof-of-concept using building systems as a challenge application area. In particular, the research involves devising novel conceptual methods for new theoretical and empirical guidance needed to have an environment for human and machine decision making for highly uncertain, complex, time urgent, and dynamically changing missions. The research objectives of this proposal include: 1. Develop an immersive Collaborative Virtual Environment (CVE) using Oculus for course of action, visualization, and situational awareness for active shooter events. 2. Develop a unique immersive graphical user interface (GUI) for communicating between PCs (Player characters) and NPCs (Non-Player Characters) for user interaction. 3. Implementing algorithms for human behavior for NPCs in active shooter events. (e.g. Hostile, Non-Hostile, Selfish, Leader-Following, Panic). 4. Deep learning-based (data-driven) behavioral modeling for realistic NPCs.
Discussion: No discussion notes