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CPS: Frontier: SONYC: A Cyber-Physical System for Monitoring, Analysis and Mitigation of Urban Noise Pollution

CPS: Frontier: SONYC: A Cyber-Physical System for Monitoring, Analysis and Mitigation of Urban Noise Pollution
CPS:前沿:SONYC:用于监测、分析和缓解城市噪声污染的网络物理系统
批准号:
1544753
负责人:
Juan Bello
金额:
$462.82万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-08-01 至 2022-07-31

项目摘要

项目成果

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中文摘要
翻译
这一前沿奖支持SONIC项目,这是一项智能城市倡议,专注于开发用于监测、分析和缓解城市噪音污染的网络物理系统(CPS)。噪声污染是美国城市居民最关心的生活质量问题之一,其对健康、教育、经济和环境的影响已得到证实。然而,大多数城市缺乏持续监测噪音和了解个别来源的贡献的资源,缺乏分析城市规模噪音污染模式的工具,以及授权城市机构采取有效的、以数据为导向的行动以缓解噪音的手段。SONIC项目推进了新颖的技术和社会技术解决方案,有助于满足这些需求。SONYC包括一个由传感器和人员组成的分布式网络,用于大规模噪声监测。这些传感器使用低成本、低功耗技术和尖端的机器收听技术,产生校准的声学测量结果,并实时识别单个声源。市民科学方法被用来帮助城市居民连接城市机构和彼此,了解他们的噪音足迹,并促进举报和自我监管。至关重要的是,SONIC利用大数据解决方案来分析、检索和可视化来自传感器和市民的信息,创建了一个全面的城市声学模型,可用于识别噪声污染的重要模式。这些数据反过来可以用来推动城市机构以最佳方式减少噪声污染的噪声法规执行的战略应用。整个系统整合了网络、物理和社会基础设施,形成了对环境的持续感知、分析和驱动的闭环。SONIC是纽约大学和俄亥俄州立大学的研究人员之间的跨学科合作。它为所有级别的学生提供多种教育机会,包括一项针对K-12 STEM教育的外联倡议。该项目以纽约市为中心,与纽约市环境保护局、卫生和心理卫生局、曼哈顿下城商业改善区以及环境声学领域的世界领先者之一ARUP建立了合作伙伴关系。SONIC是网络物理系统在智能城市领域的创新和高影响力的应用,并可能成为工程、数据科学和社会科学交叉领域新的CPS研究的催化剂。它为缓解噪音污染提供了一张蓝图,可以应用于美国和国外的城市,可能会影响数百万人的生活质量。
英文摘要
This Frontier award supports the SONYC project, a smart cities initiative focused on developing a cyber-physical system (CPS) for the monitoring, analysis and mitigation of urban noise pollution. Noise pollution is one of the topmost quality of life issues for urban residents in the U.S. with proven effects on health, education, the economy, and the environment. Yet, most cities lack the resources for continuously monitoring noise and understanding the contribution of individual sources, the tools to analyze patterns of noise pollution at city-scale, and the means to empower city agencies to take effective, data-driven action for noise mitigation. The SONYC project advances novel technological and socio-technical solutions that help address these needs.SONYC includes a distributed network of both sensors and people for large-scale noise monitoring. The sensors use low-cost, low-power technology, and cutting-edge machine listening techniques, to produce calibrated acoustic measurements and recognizing individual sound sources in real time. Citizen science methods are used to help urban residents connect to city agencies and each other, understand their noise footprint, and facilitate reporting and self-regulation. Crucially, SONYC utilizes big data solutions to analyze, retrieve and visualize information from sensors and citizens, creating a comprehensive acoustic model of the city that can be used to identify significant patterns of noise pollution. This data can in turn be used to drive the strategic application of noise code enforcement by city agencies, in a way that optimally reduces noise pollution. The entire system, integrating cyber, physical and social infrastructure, forms a closed loop of continuous sensing, analysis and actuation on the environment. SONYC is an interdisciplinary collaboration between researchers at New York University and Ohio State University. It provides multiple educational opportunities to students at all levels, including an outreach initiative for K-12 STEM education. The project uses New York City as its focal point, involving partnerships with the city's Department of Environmental Protection, Department of Health and Mental Hygiene, the business improvement district of Lower Manhattan, and ARUP, one of the world's leaders in environmental acoustics. SONYC is an innovative and high-impact application of cyber-physical systems to the realm of smart cities, and potentially a catalyst for new CPS research at the intersection of engineering, data science and the social sciences. It provides a blueprint for the mitigation of noise pollution that can be applied to cities in the US and abroad, potentially affecting the quality of life of millions of people.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Infrastructure-free, Deep Learned Urban Noise Monitoring at ~100mW
无需基础设施、深度学习的城市噪声监测,功率约为 100mW
DOI: 10.1109/iccps54341.2022.00012
发表时间: 2022
期刊: 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS
影响因子: --
作者: [Yun, Jihoon, Srivastava, Sangeeta, Roy, Dhrubojyoti, Stohs, Nathan, Mydlarz, Charlie, Salman, Mahin, Steers, Bea, Bello, Juan Pablo, Arora, Anish]
通讯作者: Arora, Anish
III: Medium: Spatial Sound Scene Description
  • 批准号:
    1955357
  • 项目类别:
    Standard Grant
  • 资助金额:
    $99.99万
  • 财政年份:
    2020
  • 负责人:
    Juan Bello
  • 依托单位:
PFI-TT: Acoustic Continuous Condition Monitoring of Manufacturing Machinery
  • 批准号:
    1827523
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2018
  • 负责人:
    Juan Bello
  • 依托单位:
I-Corps: Embedded Machine Listening for Smart Acoustic Monitoring
  • 批准号:
    1759592
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2017
  • 负责人:
    Juan Bello
  • 依托单位:
BIGDATA: Collaborative Research: IA: BirdVox: Automating Acoustic Monitoring of Migrating Bird Species
  • 批准号:
    1633259
  • 项目类别:
    Standard Grant
  • 资助金额:
    $61.24万
  • 财政年份:
    2016
  • 负责人:
    Juan Bello
  • 依托单位:
海外基金