SCC-IRG Track 1: Enabling Smart Cities in Coastal Regions of Environmental and Industrial Change: Building Adaptive Capacity through Sociotechnical Networks on the Texas Gulf Coast

SCC-IRG 第 1 轨道：在环境和工业变化的沿海地区实现智慧城市：通过德克萨斯州墨西哥湾沿岸的社会技术网络建设适应能力

• 批准号: 2231557
• 负责人: Michelle Hummel
• 金额: $ 239.98万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231557&HistoricalAwards=false
• 关键词: SCC; IRG; Track; Enabling; Smart

The Coastal Bend Region (CBR) of Texas is vulnerable to acute and chronic environmental stressors stemming from natural and industrial sources, including flooding and erosion from high tides, storm surge events, and ship traffic, as well as higher levels of air and water pollution due to expansion of nearby industrial operations. Despite the multitude of environmental hazards facing the region, formal monitoring systems are limited and provide an incomplete view of local-level conditions. In addition, networks for communication and decision-making are often localized and/or fragmented. As a result, CBR communities lack the comprehensive data and decision-making structures needed to plan for, respond to, and mitigate the impacts of potential hazards. This project will advance the understanding of how smart and connected technologies can be integrated into and support regional communication networks to build adaptive capacity in the face of cumulative impacts from climate change and industrial expansion, using the CBR as an exemplar. Research activities will be co-developed and coordinated with residents, community-based organizations, elected officials, and city/county staff to strengthen multidisciplinary, cross-sector partnerships, enhance public engagement with science and technology, and broaden participation by underrepresented groups and frontline communities in the scientific process.This project will apply a mixed-methods approach to assess how sociotechnical networks can be leveraged to increase knowledge and awareness of environmental and industrial hazards and to build community adaptive capacity equitably among diverse residents of the CBR. This project's main objectives are to (1) evaluate the structure and evolution of regional communication, information-sharing, and policy-making networks focused on environmental change and industrial expansion using grounded theory, (2) develop and leverage real-time sensing technologies, machine learning models, and data dissemination tools to monitor, predict, and communicate local-level environmental conditions, and (3) integrate the social and technical components through usability testing, tabletop exercises, and longitudinal questionnaires to assess how the generated data can be effectively interpreted and presented to various stakeholders to increase knowledge of environmental hazards, strengthen regional decision-making processes, and build adaptive capacity. Community workshops and symposia will provide opportunities to refine the study needs and objectives, obtain feedback on the sensor network and data products, share project results, co-develop a vision for long-term sustainability of the project, and discuss opportunities for integration with other regional efforts.This project is in response to the Smart & Connected Communities program. It is co-funded by the Advancing Informal STEM Learning program which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments.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.

德克萨斯州的沿海弯曲地区（CBR）容易受到来自自然和工业来源的急性和慢性环境压力的影响，包括由涨潮、风暴潮事件和船舶交通造成的洪水和侵蚀，以及由于附近工业运营扩张造成的更高水平的空气和水污染。尽管该地区面临着大量的环境危害，但正式的监测系统是有限的，并且对地方一级的情况提供了不完整的看法。此外，通讯和决策网络往往是局部的和（或）分散的。因此，CBR社区缺乏规划、响应和减轻潜在危害影响所需的全面数据和决策结构。本项目将以CBR为例，推动理解如何将智能和互联技术融入并支持区域通信网络，以建立适应能力，应对气候变化和工业扩张带来的累积影响。研究活动将与居民、社区组织、民选官员和市/县工作人员共同开发和协调，以加强多学科、跨部门的伙伴关系，增强公众对科学技术的参与，并扩大代表性不足的群体和一线社区对科学进程的参与。该项目将采用混合方法来评估如何利用社会技术网络来提高对环境和工业危害的认识和认识，并在CBR的不同居民中公平地建立社区适应能力。该项目的主要目标是：(1)利用扎根理论评估以环境变化和产业扩张为重点的区域通信、信息共享和决策网络的结构和演变；(2)开发和利用实时传感技术、机器学习模型和数据传播工具来监测、预测和交流地方层面的环境状况；(3)通过可用性测试、桌面练习和纵向问卷调查，整合社会和技术成分，评估如何有效地解释生成的数据并将其呈现给各利益相关者，以增加对环境危害的认识，加强区域决策过程，建立适应能力。社区讲习班和专题讨论会将提供机会，以完善研究需求和目标，获得对传感器网络和数据产品的反馈，分享项目结果，共同制定项目的长期可持续性愿景，并讨论与其他区域努力整合的机会。该项目是对智能互联社区计划的回应。它由推进非正式STEM学习计划共同资助，该计划旨在推进非正式环境中STEM学习的设计和开发的新方法和基于证据的理解。该奖项反映了美国国家科学基金会的法定使命，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。