PFI:BIC: CityWarn -A Smart, Hyperlocal, Context-Aware Hazard Notification Service System.

PFI：BIC：CityWarn - 智能、超本地化、情境感知的危险通知服务系统。

• 批准号: 1632193
• 负责人: Brenda Philips
• 金额: $ 99.99万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1632193&HistoricalAwards=false
• 关键词: PFI; BIC; CityWarn; Smart; Hyperlocal

This project proposes to develop next generation warning systems that will improve how people make decisions about hazardous weather, such as thunderstorms, tornados and floods. Over the past two decades, cities have become a locus of population and economic activity. Currently, over 80% of the US population is concentrated in cities; furthermore, 80% of the Gross Domestic Product in the United States is produced in metropolitan areas. The concentration of people and economic activity makes cities even more vulnerable to extreme weather events. Given these trends, effective hazardous weather warning systems are critical. Hazard warning systems are service systems that aim to minimize deaths, injuries, property loss, infrastructure destruction, and service or business disruption. They include the sensors, forecasts, networking and communications, public safety personnel and decision-makers, warning information, and those who receive and respond to the warnings. CityWarn addresses three important issues for hazard notification service systems: 1) Coordination and sharing. Public safety agencies, private sector firms and the general public, all have their own hazard warning needs, and over the years, sector-specific, and even hazard-specific warning systems have evolved that may not share important information in efficient and useful ways. 2) Data Explosion. There's an explosion of data from all sources, from fine scale meteorological observations and traffic data, to humans reporting weather on social media. This is challenging for decision-makers who must quickly make sense of all of this information; and 3) Smart phone penetration. There is now a proliferation of smart phones, plus a trend toward hyperlocal, user-selected information. Warning systems have the potential to personalize weather warnings in a way that can make warning response more effective. CityWarn will deliver user-defined, dynamically changing alerts through a next-generation communications and networking platform. The platform is linked to a cutting edge radar system that provides high-resolution weather information on an urban scale of streets and neighborhoods. A mobile app delivers user-configured, weather information. Our integrated research will focus on Computing & Sensing, Behavioral Sciences, Engineered Systems and Testbeds. The Computing & Sensing thrust will develop new scalability, security, and functional advances within the communication and networking platform, and integrate high-resolution radar products and user-generated observations from the field. Through cognitive task analysis, usability studies, and live experiments, behavioral science researchers will learn how fieldworkers, such as utility workers, police, firefighters, stormwater personnel, use and share weather information in the context of their tasks and organizational constructs. Our engineered systems work will focus on aggregation and sharing of sensed information sources, automation of warning processes to address data overload problems, and user alert customization. By developing a common platform for use by industry and public sector players, we hope to break down silos between existing warning systems and increase inter-agency coordination and improve response time and quality. The main test bed will be a living lab in the Dallas Fort Worth metroplex where weather data will be disseminated to users during actual severe weather events. Primary partners: University of Massachusetts, Amherst (lead): Electrical & Computer Engineering, Computer Science, Resource Economics; Colorado State University: Electrical & Computer Engineering; Oncor Electric Delivery Company (Large Business, Dallas, Texas); TruWeather Solutions (Small Business, Reston, VA). Other broader context partners are the City of Fort Worth (Government, Fort Worth, Texas);CommPower (Small Business, Camarillo, CA); and IBM (Large Business, Armonk, New York).This award is partially supported by funds from the Directorate for Computer and Information Science and Engineering (CISE), Division of Information and Intelligent Systems (IIS).

该项目建议开发下一代警报系统，以改善人们对雷雨、龙卷风和洪水等危险天气做出决策的方式。在过去的二十年里，城市已经成为人口和经济活动的中心。目前，美国80%以上的人口集中在城市，而且美国80%的国内生产总值都在大都市地区生产。人口和经济活动的集中使城市更容易受到极端天气事件的影响。鉴于这些趋势，有效的危险天气预警系统至关重要。危险预警系统是旨在将死亡、受伤、财产损失、基础设施破坏以及服务或业务中断降至最低的服务系统。它们包括传感器、预报、网络和通信、公共安全人员和决策者、警告信息以及接收和响应警告的人。CityWarn解决了危险通知服务系统的三个重要问题：1)协调和共享。公共安全机构、私营部门公司和普通公众都有自己的危险警告需求，多年来，特定部门甚至特定危险的警告系统已经演变，可能无法以高效和有用的方式共享重要信息。2)数据爆炸。来自各种来源的数据都呈爆炸式增长，从精细的气象观测和交通数据，到人类在社交媒体上报告天气。这对决策者来说是一个挑战，他们必须迅速理解所有这些信息；以及3)智能手机的普及率。现在智能手机激增，加上超本地化、用户选择信息的趋势。警报系统有可能使天气警报个性化，从而使警报响应更加有效。CityWarn将通过下一代通信和网络平台提供用户定义的、动态变化的警报。该平台与一个尖端雷达系统相连，该系统提供城市范围内街道和社区的高分辨率天气信息。移动应用程序提供用户配置的天气信息。我们的综合研究将集中在计算与传感、行为科学、工程系统和试验台方面。计算和传感推力将在通信和网络平台内开发新的可扩展性、安全性和功能进步，并整合高分辨率雷达产品和来自现场的用户生成的观测。通过认知任务分析、可用性研究和现场实验，行为科学研究人员将了解现场工作人员(如公用事业人员、警察、消防员、雨水处理人员)如何在其任务和组织结构的背景下使用和共享天气信息。我们的工程系统工作将专注于感测信息源的聚合和共享、警报流程的自动化以解决数据过载问题，以及用户警报定制。通过开发一个供工业界和公共部门参与者使用的共同平台，我们希望打破现有预警系统之间的孤岛，加强机构间协调，改善反应时间和质量。主要的试验台将是达拉斯沃斯堡大都市中心的一个活实验室，在那里，天气数据将在实际恶劣天气事件期间向用户传播。主要合作伙伴：马萨诸塞大学阿默斯特分校(牵头)：电气与计算机工程、计算机科学、资源经济学；科罗拉多州立大学：电气与计算机工程；Oncor Electric Delivery Company(大企业，德克萨斯州达拉斯)；TruWeather Solutions(小企业，弗吉尼亚州雷斯顿)。其他更广泛的合作伙伴是沃斯堡(政府，得克萨斯州沃斯堡)、CommPower(小型企业，加利福尼亚州卡马里洛)和IBM(大型企业，阿蒙克，纽约)。该奖项由信息和智能系统部门(IIS)计算机和信息科学与工程局(CEISE)提供部分资金支持。