Planning Grant: Engineering Research Center for Infrastructure Finance through Intelligent Design and Operations (InFinIDO)

工程研究中心规划拨款竞赛是ERC项目的试点征集。规划补助金不需要作为ERC竞赛的一部分，但它旨在在团队之间建立能力，以规划聚合的、中心规模的工程研究。美国的公共基础设施投资严重不足，不仅无法维持现有需求，更重要的是，无法满足日益由数据驱动的经济的需求。向数据驱动型经济的转变取决于所谓的？智能城市?它监控城市公用事业和运营的信息，并能对不断变化的情况做出反应。智能基础设施系统处于早期发展阶段，在水、能源、交通和建筑领域的应用正在迅速发展。越来越多地，工程智能城市所需的数据分析技能与许多金融模型和交易所需的技能相同。有证据表明，智慧城市收集的数据可以催生新的融资模式，为其发展提供资金。规划拨款小组将汇集这些领域以及政策和法律方面的专家。目标是将工程设计和财务模型集成到一个决策框架中，该框架旨在克服部署智能基础设施的技术和法律障碍。这种转变的社会效益包括确定新的金融工具和资源，从而影响GDP和就业，并提高生活质量。与公共政策专家的合作将探讨智能基础设施如何在富裕和贫困社区提供公平的接入。与法学院同事的合作将解决隐私和安全问题，以及数据货币化对金融体系的影响。智能基础设施金融工程硕士等新的教育项目将旨在培养人工智能时代的新工程师。培训将帮助工程师与企业和关键的公民利益相关者接触。上述这些学科之间的相互作用将产生新的技术，刺激充满活力的创新生态系统，并促进这些技术的获取和使用。规划资助团队将探索传感器（智能）数据网络如何为设计高效融资机制提供智能，以构建和运营智能（适应性、弹性）基础设施系统。包括两个研讨会在内的规划赠款活动将使该团队能够与潜在的学术、商业和政府合作伙伴接触。尽管令人兴奋，但智能城市基础设施的可扩展性受到有限的运营基准，缺乏可靠的信息估值经济模型以及可能吸引公共或私人投资的定价机制的阻碍。该研究验证了一个假设，即智能基础设施产生的数据具有足够的范围、规模、频率和准确性，可以与新兴数据市场的金融模型和规范保持一致，并通过这些模型和规范进行测试。通过这些规划研讨会，将进一步确定中心与工业界、投资者和公众合作的研究活动和战略。目标是了解智能系统的物理或操作性能测量如何不仅能够实现性能优化或设计迭代，还能带来可在数据交换中使用或交易的衍生价值。如何安全地设计智能基础设施，并测试物联网数据，以实现金融或拍卖模型的价值优化？数据驱动的高效资本，如保险和衍生品（期货、期权），以及可变利率履约债券和智能合约，越来越依赖于实时物联网（IoT）信息。在与工业和公共合作伙伴的合作下，ERC计划拨款团队将在模拟环境中使用传感器和金融数据模型，以及基于部署的试点智能基础设施系统，开发、测试和验证工程模型、计量经济学和金融理论原理。这些包括智慧城市的组成部分，如：（风暴）供水设施、智能交通（道路和桥梁）、能源系统和绿色建筑。拟议的ERC设想构建反映互补学科的三个信任领域：(i)基础设施系统数据的风险量化和动态特征；（ii）隐私和网络安全受限数据市场中的金融风险建模、定价和信息估值；（三）基础设施设计、弹性管理和新投资范例的决策反馈模型。工程设计与信息评估、定价和政策的整合是一个新兴的研究和实践领域，对未来的智能基础设施设计具有重要意义。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。

The Planning Grants for Engineering Research Centers competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.Public infrastructure investment in the US is woefully inadequate, not only to maintain existing demands, but more importantly to meet the needs of an increasingly data-driven economy. The transition to a data-driven economy depends on so-called ?smart cities? which monitor information on city utilities and operations and can respond to changing situations. Smart infrastructure systems are in an early development stage with rapidly developing applications across water, energy, transportation and buildings. Increasingly, the data analysis skills needed for engineering smart cities, are the same skills needed for many financial models and transactions. Evidence suggests that the very data smart cities collect can lead to new financing models that help fund their development. The planning grant team will bring together experts in these areas, as well as policy and law. The goal is to integrate engineering design and financial models in a decision framework that seeks to overcome technical and legal barriers for deployment of intelligent infrastructures. The societal benefits of this transition include identifying new financial instruments and resources that impacts GDP and jobs, and improves quality of life. Collaboration with public policy experts will explore how smart infrastructures can provide equitable access across rich and poor communities. Engagement with law school colleagues will address privacy and security concerns, and the impact of data monetization on the financial system. New educational programs such as a Masters in Engineering in Smart Infrastructure Finance will be aimed at training new engineers in the era of artificial intelligence. Training will help engineers engage with business and key civic stakeholders. The described interactions between these disciplines will result in new technologies that stimulate a vibrant innovation ecosystem and facilitate access and use of these technologies. The planning grant team will explore how sensor-enabled (smart) data networks provide intelligence for the design of efficient financing mechanisms to build and operationalize smart (adaptive, resilient) infrastructure systems. The planning grant activities, including two workshops, will allow the team to engage with potential academic, business and government partners. Despite the excitement, the scalability of smart city infrastructure is hampered by limited operational benchmarking, lack of robust economic models for valuation of information, and pricing mechanisms that may attract public or private investment. The research tests the hypothesis that intelligent infrastructures generate data of sufficient scope, scale, frequency and accuracy that can be aligned with, and tested against, financial models and specifications of emerging data markets. Through these planning workshops, the proposed Center research activities and strategies to collaborate with industry, investors and the public will be further defined. The objective is to understand how physical or operational performance measurements of smart systems not only enable performance optimization or design iterations, but bring derivative value that can be used or traded in data exchanges. How can intelligent infrastructures be safely designed - and the IoT data tested - against financial or auction models for value optimization? Data-driven efficient capital such as insurance and derivatives (futures, options), as well as variable rate performance bonds and smart contracts, increasingly depend on real-time IoT (Internet of Things) information. In cooperation with industry and public partners, the ERC planning grant team will develop, test and validate engineering models, econometric and financial theory principles using sensor and financial data models in a simulation environmental, and well as based on deployed pilot smart infrastructure systems. These include smart city components such as: (storm)water utilities, intelligent transportation (roads and bridges), energy systems, and green buildings. The proposed ERC envisions structuring three trust areas reflecting complementary disciplines: (i) Risk quantification and dynamic characterization of infrastructure system data; (ii) Financial risk modeling, pricing, and information valuation in privacy- and cyber security-constrained data markets; (iii) Decision feedback models for infrastructure design, resilience management, and new investment paradigms. The integration of engineering design with information valuation and pricing, and policy is an emerging field of inquiry and practice with implications for future designs of smart infrastructures.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.