SCC-IRG Track 2: Toxic-Free Footprints to Improve Community Health against Respiratory Hazards

在美国通过《清洁空气法》50年后，据估计，到2020年，全国近一半的人口将生活在污染的空气中，并呼吸着污染的空气。气候变化及毁灭性的COVID-19大流行导致近期野火的数量和强度加快，令空气污染对公众健康的影响更加令人担忧。这个智能互联社区项目在脆弱社区建立和加强技术，经济，政治和社会基础设施，以更好地感知和监测空气质量，防止暴露于呼吸道危害，提高对空气质量的认识和打击错误信息。该研究旨在建立智能和连接无毒社区，这与NSF的使命“促进国家健康，繁荣和福利”产生共鸣。研究小组与当地基层组织，社区，研究中心和规划机构在两个社区，罗克斯伯里，波士顿，MA和圣约翰浸信会教区，洛杉矶。该项目所产生的新技术方法和空气质量数据沿着着社区的深入参与，将潜在地影响和加强政策，并使服务不足的社区受益，使其更公平地获得健康的环境。在该研究项目中，研究团队（1）开发数据驱动的方法，将人类流动性（即，（2）设计实时人工智能技术，将信息与社区连接起来，支持基于网络的干预措施;（3）在两个具有代表性的当地社区部署该方法，其特点是少数民族和多样性都受到空气污染的影响。研究重点是挥发性有机化合物（VOCs）和颗粒物（例如，PM2.5），因为它们已知会导致肺癌、心血管和呼吸系统疾病。工作的主要交付成果包括：（1）数据驱动和基于实时AI的框架，该框架将多模型数据流（例如，地理位置、空气质量、社交网络等）量化和预测与人类足迹相关的空气污染暴露;（2）基于社会网络的干预策略，与两个受空气污染影响的社区互动开发并进行测试（Roxbury，Boston，MA and St. John教区区，New Orleans，LA）;以及（3）实时AI驱动的移动的应用程序（App），Toxic-Free Life，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Fifty years after the passing of the Clean Air Act in the U.S., nearly half of the nation’s population is estimated to live with and breathe polluted air in 2020. The recent acceleration in the number and intensity of wildfires driven by climate change and the devastating COVID-19 pandemic have made air pollution effects on public health an even more heightened concern. This Smart and Connected Communities project builds and enhances technological, economic, political, and social infrastructures in vulnerable communities to better sense and monitor air quality, prevent exposure to respiratory hazards, and raise awareness of and battle misinformation on air quality. The research aims to build smart and connected toxic-free communities, which resonates with NSF’s mission “to advance the national health, prosperity, and welfare.” The research team collaborates with local grass-root organizations, communities, research centers, and planning agencies in two communities, Roxbury, Boston, MA and St. John the Baptist Parish, LA. The new technological approaches and air quality data generated by the project along with the deep community engagement will potentially influence and enhance policies and benefit underserved communities with more equitable access to a healthy environment.In this research project, the research team (1) develops data-driven approaches to seamlessly link human mobility (i.e., a person’s footprints within and beyond the residential place) and respiratory hazards measured by air quality monitors; (2) designs real-time AI technologies to connect information and communities that support both network-based interventions; and (3) deploys the methodology in two representative local communities characterized with minority and diversity both burdened by air pollution. The research focuses on volatile organic compounds (VOCs) and particulate matter (e.g., PM2.5) for their known health impacts of causing lung cancers and cardiovascular and respiratory diseases. The key deliverables of work include: (1) a data-driven and real-time AI-based framework that links multi-model data streams (e.g., geolocations, air quality, social networks, etc.) to quantify and predict air pollution exposures associated with human footprints; (2) social network-based interventions strategies developed interactively with and tested by two communities burdened by air pollution (Roxbury, Boston, MA and St. John Parish, New Orleans, LA); and (3) real-time AI-powered mobile application (App), Toxic-Free Life, for mainstream smartphones that allows real-time estimations of air exposure and supports network-based interventions.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.