PFI:AIR - TT: Situational Awareness during Fire and Emergency (SAFE)

该PFI：AIR技术翻译项目的重点是翻译无人机（UAV）技术，以满足在野火和结构火灾等紧急情况下生成实时，准确的态势感知的需求。 该项目将开发一个原型系统，该系统由一架无人机和一个地面站组成，并配有相关软件，可在野火和结构性火灾情况下为消防“事件管理小组”提供先进的态势感知能力。这种基于无人机的系统具有以下独特的功能：i）消防专业人员在管理无人机操作时易于使用; ii）快速部署;以及iii）实时获取和处理无人机收集的信息，以便不仅提供当前的情况图片，而且在野火的情况下还具有预测能力。这些特征提供的优点包括与当前的方法（例如基于有人驾驶飞机的监视、卫星图像和人工瞭望实践）相比降低的操作成本和提高的生命和财产安全。 该项目解决了从研究发现到商业应用的一些技术差距。例如，将从无人机以遥测和流视频形式收集的数据转换为消防员易于理解的直观形式，需要在实时视频处理、时空估计、多源信息的系统组合以及信息呈现和可视化方面进行创新。同样，消防专业人员的预期用途（他们不是训练有素的飞行员）以及其他实际限制要求无人机操作是自主的，算法是计算效率高的。该项目的合作伙伴来自托莱多大学技术转让办公室，Kayos Enterprise，Inc.，西弗吉尼亚州林业部门和辛辛那提消防部门指导商业化进程，增强研究能力，提供测试环境，并在这项从研究发现到商业现实的技术转化工作中提供对用户需求和观点的理解。所提出的基于无人机的技术很重要，因为它将工具放在野火和结构火灾事故指挥官手中，获得更好的态势感知，以便及时做出明智的决策。预计这将节省大量费用，提高安全水平，减少生命和财产损失，并加强环境保护。随着无人机即将进入国家领空，这项研究开发的技术在执法、边境巡逻和周边监视等许多其他民用应用中具有广泛的潜力。该项目为未来的工程师、事故指挥官、无人机操作员和企业家提供培训，他们将在未来几年引领这一技术领域。此外，该项目将有助于美国在民用无人机应用领域的竞争力，并在五到十年内产生潜在的经济影响。

This PFI: AIR Technology Translation project focuses on translating Unmanned Aerial Vehicle (UAV) technology to fill the need of generating real-time, accurate situational awareness during emergency situations, such as wildfires and structural fires. The project will result in the development of a prototype system consisting of a UAV and a ground station with associated software that can provide the firefighting "Incident Management Teams" with advanced situational awareness capabilities during wildfire and structural fire scenarios. This UAV based system has the following unique features: i) ease-of-use by firefighting professionals in managing UAV operations; ii) quick deployment; and iii) real-time acquisition and processing of information gathered by UAV in order to provide not only a current situational picture but also predictive ability in case of wildfires. These features provide advantages including reduced cost of operation and improved safety of lives and properties as compared with current methodologies such as manned aircraft based surveillance, satellite imageries, and manual lookout practices. This project addresses a number of technology gaps as it translates from research discovery toward commercial application. For example, the conversion of data gathered from UAVs in the form of telemetry and streaming video into an intuitive form easily understandable by firefighters requires innovations in real-time video processing, spatio-temporal estimation, systematic combination of information from multiple sources, and information presentation and visualization. Similarly, intended use by firefighting professionals, who are not trained pilots, and other practical constraints require the UAV operations to be autonomous and algorithms to be computationally efficient.The project engages partners from the University of Toledo Technology Transfer Office, Kayos Enterprise, Inc., West Virginia Division of Forestry, and the Cincinnati Fire Department to guide the commercialization process, augment the research capability, provide a testing environment, and offer an understanding of users' needs and perspectives in this technology translation effort from research discovery toward commercial reality.The proposed UAV based technology is important because it puts tools in hands of wildfire and structural fire incident commanders so they can obtain improved situational awareness for making timely and informed decisions. This is expected to result in substantial cost savings, improved levels of safety, lower loss of life and property, and augmented preservation of the environment. With the imminent inclusion of UAVs in the national airspace, the technologies developed in this research have wide potential in a number of other civilian applications such as law enforcement, border patrol, and perimeter surveillance. This project provides training to future engineers, incident commanders, UAV operators and entrepreneurs who would lead this field of technology in years to come. In addition, the project will contribute to the U.S. competitiveness in the area of civilian UAV applications with potential economic impact within five to ten years.