PHS 2019-02 Omnibus Solicitation of the NIH, CDC, and FDA for Small Business Innovation Research Gra

Summary/Abstract - Mixed-Reality Sensor and Hazard Simulator for Large-Scale Field Exercises A goal of HAZMAT worker and responder field training exercises is to present realistic experiences involving PPE, tools, hazard sensors, and mock hazards so that learners can improve their skills. However, while mock hazards, PPE, and tools are readily available to the training community, sensors do not operate with mock hazards. Because HAZMAT workers and responders use the readings from sensors to decide on their actions in the field, making sensor readings and interpreting them are critical skills, and the ability of a HAZMAT training program to teach these skills is significant. Cell Podium, in collaboration with the Center for Public Health Workforce Development (CPHWD) at the Rutgers School of Public Health, prototyped a simulator of handheld gas and radiation sensors for HAZMAT training. A cell phone app simulates a handheld sensor, and displays readings in real-time as if mock hazards in the training exercise were real. Prior to the exercise, the instructor places a small beacon on each mock hazard. The system generates sensor readings based on the learner’s proximity to the mock hazards and the virtual nature of the hazards specified by the instructor. Beacon-based simulation cost-effectively achieves the realism desired by instructors in exercises with localized mock hazards, such as a leaky drum whose effect is limited to a few meters. However, the limited range of beacons, and their representation of hazards as point sources, do not lend themselves to the simulation of a large area hazard such as a large spill, or an environmental incident such as a flood. The steady annual increase in the number of such large-scale incidents highlights the significant need for realistic sensor simulation in large-scale incident training exercises. Large-scale hazard and sensor simulation for emergency response training exercises requires a technology based on hazard area and not on modeling hazards as point sources with beacons. To achieve this requirement cost-effectively and mitigate technological risk, the proposed effort will develop and assess a system that innovatively combines assets already in use by the responder community, emerging geo-location technologies, and resources from the Cell Podium/Rutgers beacon-based prototype. Responder assets to be integrated include the Computer-Aided Management of Emergency Operations (CAMEO®) system. The proposed effort is the first to interface CAMEO with realistic large-scale multi-responder experiential training exercises. When the instructor specifies the hazards in CAMEO, the training system will virtualize the plumes and the safety zones (exclusion, contamination, and support), track the learners and the zones, and display realistic readings on their handheld sensor simulator apps. By building upon the beacon-based prototype, trainers will have the option to choose the most convenient and cost-effective components for his/her specific training exercises. Under the proposed SBIR Phase I effort, CPHWD and McGuire AFB will incorporate the prototype system into their HAZMAT field training exercises, where instructors and learners will evaluate the training value, performance and ergonomics of the system.Narrative - Mixed-Reality Sensor and Hazard Simulator for Large-Scale Field Exercises The actions selected by a HAZMAT worker are often dictated in real-time by the readings from chemical and radiological sensors; consequently, knowing how to make and interpret such sensor readings are critical life-saving skills in man- made, environmental, and weather-related incidents. Using advanced low-cost assets, this project will cost-effectively introduce the realism of mixed reality to experiential HAZMAT training that supports the development and evaluation of these skills. In particular, the project prototypes and deploys to operational training programs a smartphone app for large-scale HAZMAT training exercises that simulates different handheld sensors and displays realistic exposure levels taking into account the presence of all the mock hazards deployed in the exercise, and their type, leakage, and safety zones.