Firefighter Location and Rescue Equipment (FLARE)

消防员定位和救援设备 (FLARE)

• 批准号: 8203151
• 负责人: Hans Gregory Schantz
• 金额: $ 15万
• 依托单位: Q-TRACK CORPORATION
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2012-05-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8203151
• 关键词: Firefighter; Location; Rescue; Equipment; FLARE

DESCRIPTION (provided by applicant): In 2010, Q-Track undertook an internal R&D project to begin developing a Firefighter Location And Rescue Equipment (FLARE) system with advice and input from the Huntsville Fire Department. On August 3, we participated in a firefighter rescue exercise at the 2010 WPI PPL Workshop. The exercise required guiding rescuers to a "lost" firefighter in a multi-story building - an exercise so challenging that only three entrants fielded systems and neither of the two vendors with "commercial" firefighter location systems on the market who attended the workshop submitted systems for evaluation. Q-Track's FLARE prototype system yielded a seven minute rescue - faster than the nine and twelve minute times from the two state-of-the-art inertial systems entered for testing at WPI. Our success was featured in the Boston Globe and fire safety trade press. Lacking funds to continue development, Q-Track had to place the project on hold. Q-Track seeks funds to implement a new proof-of-concept system to overcome the weaknesses identified in our initial effort. The present opportunity defies the current paradigms of inertial tracking and high-frequency, short-wavelength wireless location in a centralized command and control architecture. We propose to apply Q-Track's innovative, low-frequency, long-wavelength NFER RTLS to the challenging problem of firefighter location awareness with a decentralized system enabling individual self-rescue and guidance even without communications. Q-Track's proposed FLARE effort begins with setting specifications. Then, we will use our existing NFER RTLS hardware to implement a prototype FLARE system. We will collect RF response data for an NFER ("FLARE") proof-of-concept traversing a building and employ the data sets to develop an "RF breadcrumb" algorithm. The RF breadcrumb algorithm collects and compares sequential RF response data from the FLARE tag to identify when one tag is following the path of another. This innovative approach enables a rescuer to be vectored to the precise location of a disabled firefighter along the same path originally taken by the firefighter in distress, thus avoiding the conventional problem of homing in on a firefighter from the wrong side of a wall. Q-Track further aims to develop a proof-of-concept audio user interface to provide firefighter guidance and location awareness. Finally, Q-Track will complete a proof-of-concept demonstration and produce a short video demonstrating system performance for submission with our final report. Our objective is to demonstrate the ability to reliably vector a blind-folded rescuer to the location of a FLARE tagged individual along the same path taken by the first individual, or to enable a blindfolded and disoriented individual to retrace their entry path out of a facility. PUBLIC HEALTH RELEVANCE: Q-Track proposes to significantly enhance firefighter situational awareness and safety by merging a breakthrough, near-field, low frequency approach to wireless location with an innovative RF breadcrumb algorithm. The proposed system will enable a rescuer to be vectored to the precise location of a disabled firefighter along the original path of the fireighter in distress, thus avoiding the problem of attempting to route rescuers through walls.

描述（由申请人提供）：2010年，Q-Track进行了一个内部研发项目，开始开发消防员的位置和救援设备（Flare）系统，并提供了亨茨维尔消防局的建议和投入。 8月3日，我们参加了2010年WPI PPL研讨会的消防员救援演习。该练习需要指导救援人员到一座多层建筑中的“丢失”消防员 - 这是一种挑战性的锻炼，以至于只有三名参与者派遣了系统，并且两个供应商都没有参加市场上的“商业”消防员地点系统，他们参加了研讨会提交的系统进行评估。 Q-Track的耀斑原型系统进行了七分钟的救援 - 比在WPI进行测试的两个最先进的惯性系统的速度要快。我们的成功在波士顿环球报和消防安全贸易出版社中亮相。缺乏继续开发的资金，Q-track必须搁置该项目。 Q-Track寻求资金来实施新的概念验证系统，以克服我们最初努力中确定的弱点。目前的机会违反了惯性跟踪和高频，短波长无线位置的当前范例。我们建议将Q-Track的创新，低频，长波长NFER RTL应用于消防员位置意识的挑战性问题，即即使没有通信，也可以实现个人自我救援和指导。 Q-Track提出的耀斑努力始于设定规格。然后，我们将使用现有的NFER RTL硬件来实现原型耀斑系统。我们将收集RF响应数据，作为概念验证的NFER（“耀斑”），并采用数据集来开发“ RF BackCrumb”算法。 RF面包屑算法收集并比较来自火炬标签的顺序RF响应数据，以识别一个标签何时遵循另一个标签的路径。这种创新的方法使救援人员能够沿着消防员最初在遇险中采取的同一条路径将残疾人消防员的确切位置进行量化，从而避免了从墙壁错误的一侧在消防员身上寄托的常规问题。 Q-Track进一步旨在开发概念验证音频用户界面，以提供消防员的指导和位置意识。最后，Q-track将完成概念验证演示，并制作一个简短的视频，展示系统性能，以提交我们的最终报告。我们的目标是证明能够可靠地向载体旋转的救援人员沿着第一个人所采取的相同路径的位置，或者使一个蒙住眼睛的且迷失方向的个体能够从设施中追回其入口路径。 公共卫生相关性：Q-Track建议通过将突破性的，近场，低频方法与创新的RF面包屑算法合并，从而显着提高消防员的情境意识和安全性。拟议的系统将使救援人员能够沿遇险的消防员的原始路径将残疾人消防员的精确位置进行量化，从而避免了试图通过墙壁将救援人员路由救援人员的问题。