NSF Engineering Research Center for Smart Streetscapes (CS3)

超过80%的美国人和超过一半的世界人口生活在城市地区。高密度城市正在改变人们的生活、工作、出行和管理城市基础设施的方式。随着美国城市地区面临威胁宜居性、安全性和包容性的新挑战，街景-社区街道、人行道和公共空间-标志着公共和商业活动的纽带，在那里可以利用丰富的、空间上和暂时密集的数据来造福于公共利益。由哥伦比亚大学领导的NSF智能街景工程研究中心(CS3)与佛罗里达大西洋大学、罗格斯大学、中佛罗里达大学和雷曼学院一起，将开发一个丰富的街景应用生态系统，建立在实时、超本地智能的基础上，以推进宜居、安全和包容的社区。CS3将采用一种全新的工程研究方法，利用不同的非学术利益相关者--行业合作伙伴、社区组织、市政当局和K-12学校--作为知识的协作性联合生产者和技术研发的审核者，建立在包容文化的基础上，弥合明显划分利益相关者的“数字鸿沟”。通过广泛的合作伙伴网络，CS3将探索五个应用主题：道路安全和交通效率、公共安全、残疾人辅助技术、户外工作的未来以及超本地传感和建模。CS3的S工程流程将从研究社区特定的应用要求、限制和敏感性开始。由此产生的以社区为灵感的应用程序将在纽约市(NY)、西棕榈滩(FL)和新泽西州新不伦瑞克(New Brunswick)这三个不同的城市试验床进行试点，利用之前的联邦和市政投资。这些试点的成果将催生一个新颖的创新生态系统，利用CS3的S由有抱负的企业家、新兴初创企业和老牌公司组成的广泛网络。实现和维持这一愿景需要一支贯穿工程、数据科学、社会科学和政策的下一代劳动力队伍；CS3将利用共享的日常街景体验来吸引来自不同学科和背景的学生参与智能城市这一新兴学科。基于美国国家科学基金会ERC计划的四个紧密结合的基本要素--研究、工程劳动力发展、包容的多样性和文化以及创新生态系统--CS3的S工作有可能重新定义美国的街道景观，方法是在有形的城市基础设施上应用数字层，确保美国城市满足当地社区的需求，并确保所采用的技术考虑到安全、公平、隐私和安保等关键问题。美国国家科学基金会智能街道景观工程研究中心(CS3)将通过基于边缘云技术、无线光学工程、视觉分析、计算机安全和社会科学。CS3将通过一种汇聚的研究模式将不同的研究团体团结在一起，该模型在五个工程和科学领域提供创新：(1)Wi-Edge--集成了高速无线-光网络、高性能边缘-云计算和软件定义的无线电和网络；(2)情境感知--在街景尺度的不同时间范围内对人类行为的精细、实时观察、建模和预测；(3)安全、隐私和放大；公平-解决当地智能街道景观内隐私和安全的社会技术障碍，为街道景观应用程序产生软件管道，提供社区可配置的隐私、公平和透明度保证；(4)公共利益技术-了解CS3技术、应用程序和安全/隐私政策如何影响社会景观和促进区域经济发展；以及(5)街景应用程序-将个别社区在设计过程中阅读、解释和响应地方情报的独特方式纳入设计过程，以优化社区特有的利益。CS3将推进土木工程和城市系统工程、电气和网络工程、视觉分析和传感器融合、计算机隐私和安全以及公共信任和技术方面的基础知识-催化和融合智能城市这一新兴学科。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

More than 80% of Americans and over half the world’s population live in urban areas. High-density cities are transforming how people live, work, travel, and manage urban infrastructure. With the nation’s urban areas facing emerging challenges threatening livability, safety, and inclusion, it is the streetscape –neighborhood streets, sidewalks, and public spaces– that marks the nexus of public and commercial activities, where rich, spatially and temporarily dense data can be harnessed for the public good. The NSF Engineering Research Center for Smart Streetscapes (CS3), led by Columbia University, together with Florida Atlantic University, Rutgers University, University of Central Florida, and Lehman College, will develop a rich ecosystem of streetscape applications built upon real-time, hyper-local intelligence to advance livable, safe, and inclusive communities. CS3 will adopt a fundamentally new approach to engineering research, leveraging a diverse cohort of non-academic stakeholders –industry partners, community organizations, municipalities, and K-12 schools– as collaborative co-producers of knowledge and auditors of technology research and development, built on a culture of inclusion that bridges the “digital divide” that starkly demarcates stakeholdership. With an extensive network of partners, CS3 will explore five application themes: road safety and traffic efficiency, public safety, assistive technologies for people with disabilities, the future of outdoor work, and hyper-local sensing and modeling. CS3’s engineering process will begin with the study of community-specific application requirements, constraints, and sensitivities. The resulting community-inspired applications will be piloted within three distinct urban testbeds –in New York City (NY), West Palm Beach (FL), and New Brunswick (NJ)– leveraging prior federal and municipal investments. Outcomes from these pilots will catalyze a novel innovation ecosystem, drawing upon CS3’s broad network of aspiring entrepreneurs, emerging start-ups, and established companies. Realizing and sustaining this vision requires a next-generation workforce that cross-cuts engineering, data science, social science, and policy; CS3 will leverage shared, day-to-day streetscape experiences to attract students from diverse disciplines and backgrounds to engage in the emerging discipline of smart cities. Built on the four closely integrated foundational elements of NSF’s ERC program –Research, Engineering Workforce Development, Diversity and Culture of Inclusion, and Innovation Ecosystem– CS3’s work has the potential to redefine America’s streetscapes by applying a digital layer over physical urban infrastructure, ensuring that America’s cities meet the needs of local communities and that the technologies being adopted take into account critical questions regarding safety, equity, privacy, and security.The NSF Engineering Research Center for Smart Streetscapes (CS3) will advance livable, safe, and inclusive communities through real-time, hyper-local streetscape applications built on advancements in edge-cloud technology, wireless-optical engineering, visual analytics, computer security, and social science. CS3 will unite diverse research communities through a convergent research model that delivers innovations across five engineering and scientific areas: (1) Wi-Edge – the integration of high-speed wireless-optical networking, high-performance edge-cloud computing, and software-defined radios and networking; (2) Situational Awareness – fine-scale, real-time observation, modeling, and forecasting of human behavior over variable time horizons at streetscape scales; (3) Security, Privacy & Fairness – addressing socio-technical barriers of privacy and security within locally intelligent streetscapes, yielding a software pipeline for streetscape applications that gives community-configurable guarantees of privacy, fairness, and transparency; (4) Public Interest Technology – understanding how CS3 technologies, applications, and security/privacy policies impact the social landscape and promote regional economic development; and (5) Streetscape Applications – incorporating the distinct ways in which individual communities read, interpret, and respond to local intelligence within the design process in order to optimize community-specific benefits. CS3 will advance fundamental knowledge in civil and urban systems engineering, electrical and network engineering, visual analytics and sensor fusion, computer privacy and security, and public trust and technology – catalyzing and coalescing the emerging discipline of smart cities.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.