Smart cities and the infrastructure metaverse: can data markets and securitization help close the financing gap?

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

The increasing integration of sensors and digital infrastructure in city assets to enable climate resilience, infrastructure health monitoring or venue flow of people and goods is fueling the growth of a wide range of data types differing in latency, scope, reliability and frequency. While data-driven business models in this new metaverse of cities have received attention in engineering design, policy, and legislation, the connection between this information supply chain and the capital markets that finance infrastructure remains largely unexplored. This paper addresses three research questions: how do smart city data value chains connect to infrastructure financing models; how can data securitization leverage market mechanisms to support new structured finance instruments; and what conditions enable transactional data markets to move beyond bilateral agreements toward liquid price discovery? By leveraging the literature on asset-backed securities (ABS) and data markets, a multi-layer securitization framework is proposed to structure contracted revenues from smart cities data and services to raise capital for next-generation infrastructure delivery. The framework maps the full digital infrastructure stack onto a structured capital raise: physical sensing and digital twin (Layers 1–2) data that are productized into contracted revenue streams (Layer 3), pooled in a special purpose vehicle and issued as rated debt tranches (Layer 4), under data stewardship and credit enhancement governance (Layer 5). A use case of the framework is illustrated using digital transportation infrastructure (smart pavements) design and financing. Although no rated data contract securitization for infrastructure has yet closed, individual elements of the framework are operational across public and private contracting contexts. Policy implications address data stewardship governance, regulatory frameworks for digital twin-based finance, and the structural preconditions. These include standardized data quality scoring and independent measurement, reporting and verification (MRV), required for capital markets to treat infrastructure data as a creditworthy asset class. Key limitations include the absence of a recognized rating agency methodology for data-backed ABS, legal ambiguity over data ownership on public rights-of-way, and government counterparty appropriations risk.

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