Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems

协作研究：CPS：中：使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散

• 批准号: 2038741
• 负责人: Eric Rowell
• 金额: $ 15万
• 依托单位: Nevada System of Higher Education, Desert Research Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038741&HistoricalAwards=false
• 关键词: Collaborative; Research; CPS; Medium; Wildland

Increasing wildfire costs---a reflection of climate variability and development within wildlands---drive calls for new national capabilities to manage wildfires. The great potential of unmanned aerial systems (UAS) has not yet been fully utilized in this domain due to the lack of holistic, resilient, flexible, and cost-effective monitoring protocols. This project will develop UAS-based fire management strategies to use autonomous unmanned aerial vehicles (UAVs) in an optimal, efficient, and safe way to assist the first responders during the fire detection, management, and evacuation stages. The project is a collaborative effort between Northern Arizona University (NAU), Georgia Institute of Technology (GaTech), Desert Research Institute (DRI), and the National Center for Atmospheric Research (NCAR). The team has established ongoing collaborations with the U.S. Forest Service (USFS) in Pacific Northwest Research Station, Kaibab National Forest (NF), and Arizona Department of Forestry and Fire Management to perform multiple field tests during the prescribed and managed fires. This proposal's objective is to develop an integrated framework satisfying unmet wildland fire management needs, with key advances in scientific and engineering methods by using a network of low-cost and small autonomous UAVs along with ground vehicles during different stages of fire management operations including: (i) early detection in remote and forest areas using autonomous UAVs; (ii) fast active geo-mapping of the fire heat map on flying drones; (iii) real-time video streaming of the fire spread; and (iv) finding optimal evacuation paths using autonomous UAVs to guide the ground vehicles and firefighters for fast and safe evacuation. This project will advance the frontier of disaster management by developing: (i) an innovative drone-based forest fire detection and monitoring technology for rapid intervention in hard-to-access areas with minimal human intervention to protect firefighter lives; (ii) multi-level fire modeling to offer strategic, event-scale, and new on-board, low-computation tactics using fast fire mapping from UAVs; and (iii) a bounded reasoning-based planning mechanism where the UAVs identify the fastest and safest evacuation roads for firefighters and fire-trucks in highly dynamic and uncertain dangerous zones. The developed technologies will be translational to a broad range of applications such as disaster (flooding, fire, mud slides, terrorism) management, where quick search, surveillance, and responses are required with limited human interventions. This project will also contribute to future engineering curricula and pursue a substantial integration of research and education while also engaging female and underrepresented minority students, developing hands-on research experiments for K-12 students. This project is in response to the NSF Cyber-Physical Systems 20-563 solicitation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

增加野火成本---反映了野外气候变化和发展的反映 - - 驱动呼吁新的国家管理野火的能力。由于缺乏整体，弹性，灵活和具有成本效益的监控协议，无人驾驶系统（UAS）的巨大潜力尚未在该领域充分利用。该项目将制定基于UAS的消防策略，以最佳，高效和安全的方式使用自动无人驾驶汽车（UAV），以在火灾探测，管理和撤离阶段为第一响应者提供帮助。该项目是北亚利桑那大学（NAU），佐治亚理工学院（GATECH），沙漠研究所（DRI）和国家大气研究中心（NCAR）之间的合作努力。该小组已与美国西北部研究站，Kaibab国家森林（NF）和亚利桑那州林业和消防管理部的美国森林服务局（USFS）建立了持续的合作，以在处方和托管大火期间进行多次现场测试。该提议的目标是开发一个满足未满足Wildland Fire Management需求的综合框架，通过使用低成本和小型自动无人机的网络以及地面车辆以及在不同的火灾管理操作阶段，在科学和工程方法方面取得了重要的进步，包括：（i）使用自动无人机在偏远和森林地区的早期发现； （ii）飞行无人机上火热图快速积极的地理图； （iii）火灾的实时视频流传播； （iv）使用自动无人机找到最佳撤离路径，以引导地面车辆和消防员快速安全地撤离。该项目将通过开发：（i）创新的基于无人机的森林火灾检测和监测技术，以快速干预以最少的人为干预来保护消防员的生命； （ii）使用来自无人机的快速射击映射，提供战略性，事件级和新的板载，低竞争策略； （iii）基于推理的计划机制，无人机在高度动态和不确定的危险区域中为消防员和消防员确定最快，最安全的撤离道路。开发的技术将转化为广泛的应用，例如灾难（洪水，火灾，泥泞滑坡，恐怖主义）管理，在有限的人力干预措施下，需要快速搜索，监视和反应。该项目还将为未来的工程课程做出贡献，并在研究和教育上进行实质性的整合，同时还吸引女性和代表性不足的少数民族学生，并为K-12学生开发动手研究实验。该项目是对NSF网络物理系统20-563征集的回应。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估标准来通过评估来支持的。