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

德克萨斯州的沿海弯曲地区（CBR）容易受到自然和工业来源的急性和慢性环境压力，包括洪水和涨潮侵蚀，风暴潮事件和船舶交通，以及由于附近工业活动的扩张而导致的更高水平的空气和水污染。尽管该区域面临着众多的环境危害，但正式的监测系统有限，无法全面了解地方一级的情况。此外，通信和决策网络往往是地方性的和/或分散的。因此，社区康复社区缺乏计划、应对和减轻潜在灾害影响所需的全面数据和决策结构。该项目将以CBR为范例，促进理解如何将智能和互联技术融入并支持区域通信网络，以建设适应气候变化和工业扩张累积影响的能力。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，加强公众对科学和技术的参与，并扩大代表性不足的群体和前线社区在科学过程中的参与。该项目将采用混合-评估如何利用社会技术网络来增加对环境和工业危害的知识和认识，并在社区康复的不同居民中公平地建立社区适应能力的方法。该项目的主要目标是：（1）使用扎根理论评估区域交流、信息共享和政策制定网络的结构和演变，重点关注环境变化和工业扩张;（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，以监测、预测和交流地方环境状况;以及（3）通过可用性测试、桌面练习和纵向调查问卷整合社会和技术组成部分，以评估如何有效地解释生成的数据并将其呈现给各利益攸关方，从而增加对环境危害的了解，加强区域决策过程，并建立适应能力。社区研讨会和座谈会将提供机会来完善研究需求和目标，获取传感器网络和数据产品的反馈，分享项目成果，共同制定项目长期可持续性的愿景，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。该奖项由推进非正式STEM学习项目共同资助，该项目旨在推进非正式环境中STEM学习设计和开发的新方法和基于证据的理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.