SBIR/STTR Award attributes
Project Summary/Abstract: Sensor and Hazard Simulator for Large-Scale Field Exercises (Phase II) HAZMAT incidents can be classified as small scale and large scale. A small-scale incident involves one or more hazards whose exposure to each can be modeled as a function of distance between the worker and a point source, such as a leaky valve on a pressurized canister or small hole in a barrel. A large-scale incident involves a hazard that covers a wide area and cannot be modeled by a point source, such as a large spill or contaminated floodwaters. The number of large- scale incidents has increased by 33% in 8 years, highlighting the need for realistic large-scale incident training exercises. HAZMAT instructors and training program administrators acknowledge that field exercises are important to learning HAZMAT skills, including detecting and identifying hazards, working while wearing protective equipment (PPE), and delineating exclusion, contamination, and support safety zones. A goal of these exercises is to present learners with realistic tasks and experiences involving mock hazards, PPE, tools, and chemical and radiological sensors. However, while PPE, tools, and mock hazards are readily available to instructors, sensors that operate with large-scale mock hazards are not available. The decisions made by a HAZMAT worker, e.g., identifying hazards, establishing safety zones, and selecting command and decon sites, require exposure readings from sensors. Consequently, making and interpreting sensor readings are critical skills, and the ability of a HAZMAT trainers to teach these skills is significant. Cell Podium proposes an SBIR Phase II effort for the development and evaluation of a low-cost simulation system that enables trainers to conduct HAZMAT field exercises with multiple realistic mock sensors and small and large scale chemical and radiological hazards without the need of installing software or hardware. The system exploits recent developments in sub-meter geolocation and browser-based mobile computing, uses CAMEO physics modeling, and is one of the first HAZMAT training applications of the new multi-band GNSS receiver chips with lt 1 feet accuracy appearing in cell phones. Phase I efforts focused on assessing the field exercise requirements of instructors of HAZMAT workers and responders, and empirically verifying that GNSS can satisfy the spatiotemporal resolution requirements of realistic sensor simulation. Phase II efforts will yield several iterations of a minimum viable product (MVP) of the system, each based on feedback from six HAZMAT training organizations that will use the MVP in their HAZMAT field exercises, including schools of public health, rural and urban community organizations, and the US Air Force. The diversity in the organizations’ missions, operating styles and training requirements supports the collection of requirements and feedback representing the broader HAZMAT training community. In order to promote the research translation of the Phase II results, Cell Podium will present interim and final Phase II results at the semiannual conferences of the National Institute of Environmental Health Sciences (NIEHS) Worker Training Program (WTP), in which organizations from around the country participate to learn new HAZMAT training techniques.
