PFI:BIC: Enhanced Situational Awareness Using Unmanned Autonomous Systems for Disaster Remediation

这种创新伙伴关系：内华达大学里诺分校的建设创新能力（PFI：BIC）项目的目标是通过采用具有高分辨率传感和成像能力的无人驾驶自主系统（UAS）来增强执法机构和第一响应者的态势感知能力。执法机构和第一响应者在紧急事件期间面临重大挑战，例如自然或人为灾害（地震、海啸、火灾、飓风、龙卷风、洪水、电力或核事故、战争行为或恐怖）。主要挑战之一是根据现有信息并考虑到人为因素采取果断行动，使高质量的实时态势感知对于有效管理和保护平民和实地人员至关重要。该项目的重点是使用无人机系统（空中和地面系统）创建智能应急响应服务系统，配备最先进的成像，传感和通信系统，为第一响应团队提供高质量的实时信息，以便通过人机交互采取果断有效的行动。这样的智能服务系统将引导/护送人类到安全地带，指导救援人员接近被困人员，并提供现场通信、药物、水和食物以及电力。该计划将开发机械工程，计算机科学与工程，电气工程和社会心理学研究生的必要人力基础设施。在跨学科团队中一起工作，学生将接触到各自学科之外的研究，并获得创业的创新机会。一个成功的智能服务系统将影响公共安全部门的运作，它可以被类似的组织所适应。该项目的目标包括：（1）开发和集成UAS平台，传感器，成像和通信系统，以及控制和路径规划算法，以创建基于UAS的智能服务系统，用于第一响应;（2）模拟灾难期间人类和基础设施的状态，确定现场，并创建通往安全的通道;（3）测试原型并寻求商业化机会;（4）教育公众并培训第一响应者。 创建基于UAS的智能服务系统的转化研究将侧重于传感器数据融合，场景识别，人类状态建模，基础设施及其交互，以及测试和评估补救策略，通信方案和访问路径规划的平台。对系统各方面的理解将使第一反应者和公共安全指挥人员能够通过交互式的综合数据分析和可视化来分析和理解现场的主动紧急情况;并赋予他们感知，预测，并在各种灾难现场和人类社会心理条件下采取行动。该项目的合作伙伴是里诺的内华达州大学（涉及四个部门的教师：机械工程，计算机科学与工程，电气工程和社会心理学）;行业合作伙伴：两家小型企业，无人机美国和SpecTIR，总部位于内华达州的里诺;学术合作伙伴：内华达州，拉斯维加斯的大学;和犹他州大学以及来自UNR地震实验室和瓦肖县的专家作为系统用户;更广泛的合作伙伴包括在UNR新成立的内华达州先进自主系统创新中心（NAASIC），国家支持的UAS项目管理办公室、内华达州自治系统研究所（NIAS）和内华达州工业卓越（NVIE）。

This Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) project from the University of Nevada-Reno has as its goal the enhancement of the situational awareness capabilities of law enforcement agencies and first responders by employing unmanned autonomous systems (UAS) with high-resolution sensing and imaging capabilities for disaster remediation. Law enforcement agencies and first responders face significant challenges during an emergency event, such as a natural or anthropogenic disaster (earthquake, tsunami, fire, hurricane, tornado, flood, power or nuclear accident, act of war, or terror). One of the major challenges is acting decisively based on available information and considering human factors, making high-quality real-time situational awareness critical to effectively manage and safeguard civilians and in- field personnel. This project focuses on creating a smart emergency-response service system using UAS, both air- and ground-based systems, equipped with state-of-the-art imaging, sensing, and communication systems to provide first response teams with high-quality, real-time information to act decisively and effectively via human-machine interactions. Such a smart service system will guide/escort humans to safety, direct rescue crews to access trapped humans, and provide in-situ communication, medication, water and food, and power. The program will develop the requisite human infrastructure of graduate students in mechanical engineering, computer science and engineering, electrical engineering, and social psychology. Working together in the interdisciplinary team, students will be exposed to research outside of their respective disciplines and to innovative opportunities for entrepreneurship. A successful smart service system will impact the operations of the public safety sector, and it could be adapted by similar organizations.The project's objectives include the following: (1) develop and integrate UAS platforms, sensors, imaging and communication systems, and control and path planning algorithms to create a UAS-based smart service system for first response; (2) model the state of humans and infrastructure during a disaster, identify the scene, and create access paths to safety; (3) test prototypes and pursue commercialization opportunities; and (4) educate the public and train first responders on the technology. The translational research to create the UAS-based smart service system will focus on sensor data fusion, scene identification, modeling of the state of humans, infrastructure and their interactions as well as on the platform for testing and evaluating remediation strategies, communication schemes, and access path planning. Understanding of the system aspects will enable first responders and public safety command personnel to analyze and understand on-scene, active emergency situations through interactive, integrated data analysis and visualization; and give them the ability to sense, predict, and act in a variety of disaster scenes and human socio-psychological conditions.Partners at the inception of this project are the University of Nevada at Reno (involving faculty across four departments: mechanical engineering, computer science and engineering, electrical engineering, and social psychology); industry partners: two small businesses, Drone America and SpecTIR, companies based out of Reno, Nevada; academic partners: University of Nevada, Las Vegas; and the University of Utah as well as experts from the UNR Seismology Lab and the Washoe County as System users; and broader context partners include the newly established Nevada Advanced Autonomous Systems Innovation Center (NAASIC) at UNR, the state-supported UAS program management office, Nevada Institute for Autonomous Systems (NIAS), and the Nevada Industry Excellence (NVIE).