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

摘要/摘要-用于大规模野外演习的混合现实传感器和危险模拟器 危险品工作人员和应急人员现场培训演习的目标是提供涉及PPE、工具 危险传感器和模拟危险，使学习者可以提高他们的技能。然而，虽然模拟危险，PPE， 培训社区可以随时获得工具，传感器不会在模拟危险情况下运行。因为危险品处理小组 工作人员和响应人员使用传感器的读数来决定他们在现场的行动， 和解释它们是关键的技能，而危险品处理培训项目教授这些技能的能力是很重要的。 Cell Podium，与罗格斯大学公共卫生劳动力发展中心（CPHWD）合作 公共卫生部，原型的手持气体和辐射传感器的HAZMAT培训模拟器。一个手机应用 模拟手持传感器，并实时显示读数，就好像训练演习中的模拟危险是真实的一样。 在演习之前，教练在每个模拟危险处放置一个小信标。该系统生成传感器读数 根据学习者与模拟危险的接近程度和教师指定的危险的虚拟性质。 基于信标的模拟经济高效地实现了教师在本地化模拟练习中所期望的真实感 危险，如泄漏的鼓，其影响仅限于几米。然而，信标的范围有限， 将危险表示为点源，不适合模拟大面积危险，例如 大的泄漏，或环境事件，如洪水。这种大规模的数量每年稳步增加， 事件突出表明，在大规模事件培训演习中，非常需要逼真的传感器模拟。 应急响应训练演习的大规模危险和传感器模拟需要一种基于 危险区域，而不是将危险建模为具有信标的点源。为了经济有效地实现这一要求， 并降低技术风险，拟议的努力将开发和评估一个系统， 响应者社区已经在使用，新兴的地理定位技术，以及来自Cell的资源 Podium/Rutgers信标原型。 要整合的响应者资产包括应急行动的计算机辅助管理（CAMEO®） 系统拟议的努力是第一个接口CAMEO与现实的大规模多响应经验 训练演习。当教练在CAMEO中指定危害时，训练系统将虚拟化羽流 和安全区域（排除，污染和支持），跟踪学习者和区域，并显示逼真的 手持传感器模拟器应用上的读数通过建立基于信标的原型，培训人员将拥有 选择最方便和最具成本效益的组件，为他/她的具体培训练习。 根据提议的SBIR第一阶段工作，CPHWD和McGuire AFB将把原型系统纳入其 HAZMAT现场培训演习，教员和学员将评估培训价值、绩效和 系统的人机工程学。

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.