「英中对照」Willow如何以数字孪生平台加速AI赋能机场未来发展

Airports are entering one of the most transformative decades in their history. Passenger volumes are rising, operational complexity is increasing, and the pressure to deliver seamless, safe, and efficient travel experiences has never been higher. At the same time, Artificial Intelligence is rapidly reshaping how airports think about operations, infrastructure, and decision making. 机场正进入其历史上最具变革性的十年之一。客运量不断上升，运营复杂性日益增加，提供无缝、安全且高效的出行体验的压力也前所未有。与此同时， 人工 智能正在迅速重塑机场对运营、基础设施和决策的思考方式。 

In response to this shift, the Airports AI Alliance has emerged as a global coalition of airport executives, innovators, and technology partners committed to advancing responsible, effective, and scalable AI adoption across the aviation ecosystem. The Alliance brings together leaders from major hubs such as Dallas-Fort Worth, alongside technology partners building next generation airport platforms.  为应对这一转变， Airports AI Alliance 已 应运而生，成为一个由机场高管、创新者和技术合作伙伴组成的全球联盟，致力于在整个航空生态系统中推动负责任、有效且可扩展的人工智能应用。该联盟将 达拉斯-沃斯堡等主要枢纽的领导者与打造下一代机场平台的技术 合作伙伴汇聚在一起。  

As airports explore AI-driven transformation, one challenge consistently rises to the surface: solutions and experiences are only as powerful as the underlying data foundation. A unified, contextualized, and trustworthy operational data layer is critical in delivering meaningful impact. This is where Willow plays a pivotal role. 随着 机场探索人工智能驱动的转型，一个挑战不断凸显： 解决方案和体验的强大能力，仅取决于 其 底层 数据基础。 一 个统一、情境化且值得信赖的运营数据 层，对于 取得切实 成效至关重要。 Willow 正是在这方面发挥着 关键作用。 

Willow’s digital twin platform is built on semantic modeling, real-time data integration, and governance-first architecture. As a result, it is uniquely positioned to help airports unlock the full potential of AI. By creating a unified operational layer that connects systems, assets, workflows, and insights, Willow helps accelerate the AI journey and enables airports to operate with greater resilience and efficiency. Willow 的数字孪生平台基于语义建模、实时数据集成和治理优先的架构构建。因此，它在帮助机场释放人工智能的全部潜力方面具有独特优势。通过创建一个连接系统、资产、工作流和洞察的统一运营层，Willow 有助于加快人工智能之旅，并使得 机场能够 运营 得更具韧性、更加高效。 

In this blog, we’ll explore how Willow can support Airports in their AI journey across five strategic dimensions: data unification, AI governance, predictive insights, cross-system interoperability with a rich Airport ontology, and decision intelligence for capital planning.在本博客中， 我们将 探讨 Willow 如何支持 机场推进其人工智能之旅 ，涉及 五 个战略维度：数据统一、人工智能治理、预测性 洞察、跨系统互操作性 （基于丰富的机场本体）， 以及面向资本规划的决策智能。

1. Building a Foundational Data Layer1. 构建基础数据层

Airports are among the most complex operational environments in the world. A single airport relies on a variety of systems including building management, industrial controls, and access control. Runways and airfields rely on lighting systems. Gates utilize passenger boarding bridges and apron management platforms, baggage handling systems ingest data from IoT sensors. Maintenance and asset management systems keep operations running, balancing efficiency with and energy and sustainability goals. Each of these systems generates data. If siloed, a fragmented operational landscape can make it challenging for AI models to have the context needed for autonomous Agentic workflows and generating recommendations. 机场是世界上最复杂的运营环境之一。单座机场依赖各类系统，包括楼宇管理、工业控制和出入口控制。跑道和机场场地依赖照明系统。登机口使用旅客登机桥和机坪管理平台，行李处理系统从物联网传感器采集数据。维护与资产管理系统保障运营持续运行，同时兼顾效率与能源及可持续发展目标。上述每个系统都会生成数据。如果这些数据彼此孤立，碎片化的运营环境会使 AI 模型难以获得自主智能体工作流和生成建议所需的上下文。 

Willow solves this by creating a unified semantic layer that normalizes data across systems, assets, and workflows.Willow 通过创建统一语义层，对跨系统、资产和工作流的数据进行标准化，从而解决这一问题。

This unified data foundation becomes the backbone for AI-driven decision-making, relating assets to spaces with geo-spatial visualization, real time data streams, unlocking content buried in documents and bringing it all together in a Knowledge Graph. As a result, airports gain a real‑time, contextualized view of their entire operational ecosystem. 这一统一数据基础成为 AI 驱动决策的支柱，通过地理空间可视化和实时数据流将资产与空间关联起来，发掘埋藏在文档中的内容，并将所有内容整合到知识图谱中。 因此，机场可获得 实‑时、情境化的整个运营生态系统视图。 

2. Delivering AI Governance and Safety Frameworks2. 提供 AI 治理与安全框架

Airports operate under intense regulatory scrutiny. Safety, security, and compliance are non‑negotiable. As AI becomes deeply embedded in airport operations, leaders must ensure that solutions are transparent, secure, and compliant.机场在严格的监管审查下运营。安全、安保与合规绝无‑商量余地。随着 AI 深度融入机场运营，领导层必须确保解决方案透明、安全且合规。

This is one of the core priorities of the Airports AI Alliance and an area where Willow can provide value. Willow’s platform is built with governance at its core. It provides data lineage and traceability, access controls and role-based permissions, and audit trails. As an example, granular feature-level permissions support fine grained access control.这是 Airports AI Alliance 的核心优先事项之一，也是 Willow 能够创造价值的领域。Willow 的平台在构建时即以治理为核心。它提供数据血缘与可追溯性、访问控制和基于角色的权限，以及审计轨迹。 例如，细粒度的功能级权限可支持精细的访问控制。

By embedding governance into the digital twin, Willow ensures that AI systems operate safely and responsibly. This gives airport leadership and stakeholders confidence that AI-driven decisions across maintenance, energy optimization, and gate operations, are grounded in trustworthy data and transparent logic.通过将治理嵌入数字孪生，Willow 确保 AI 系统 安全且负责任地运行。这让机场领导层和利益相关方相信，维护、能源优化和登机口运营中由 AI 驱动的决策均基于可信数据和透明逻辑。

3. Enabling Predictive Operations with Insights3. 借助洞察实现预测性运营

Airports are under constant pressure to reduce delays, improve passenger flow, and optimize resource allocation. AI offers powerful tools to achieve these goals, when supported by high-quality, contextualized data that is processed in real-time to generate actionable insights. 机场一直面临减少延误、改善旅客流线和优化资源配置的压力。若有高质量、情境化的数据提供支持，并对这些数据进行实时处理以生成可执行洞察，AI 就能提供实现这些目标的强大工具。 

With Willow as the operational backbone, Skills run continuously to unlock insights. By alerting facility teams early, Skills enable proactive intervention, reducing downtime and optimizing performance. As an example, Spike in Water Consumption – Potential Water Leak continuously analyzes water consumption data to flag unexpected spikes that often precede the discovery of leaks. This enables corrective action before property damage or excessive utility usage ensues.以 Willow 作为运营支柱，Skills 会持续运行以发掘洞察。通过及早向设施团队发出警报，Skills 可实现主动干预，从而减少停机时间并优化绩效。例如，用水量飙升——潜在漏水 会持续分析用水量数据，以标记出通常在漏水被发现前出现的意外飙升。这使得相关方能够在财产损失或公用事业资源过量消耗发生之前采取纠正措施。

Tickets can be generated and updated conversationally with AI, and predictive maintenance can be tracked to systems like plumbing, electrical, HVAC, and critical assets such as chillers, baggage conveyors, and airfield lighting. AI-driven analytics help teams understand the ratio of Preventive Maintenance to Corrective Maintenance.  可借助 AI 以对话方式生成和更新工单，并可针对管道、电气、HVAC 等系统以及冷水机组、行李输送机、机场助航灯光等关键资产跟踪预测性维护。AI 驱动的分析可帮助团队了解预防性维护与纠正性维护的比率。  

Insights with the same root cause are combined and provide detailed recommendations on workflows that guide facility teams through optimal actions with real-time anomaly detection across building systems and operational equipment. Energy consumption is optimized based on occupancy, weather, and operational schedules. As a result, airports can evolve from reacting to anticipating issues, hence reducing downtime, improving safety, and enhancing the passenger experience. 具有相同根本原因的洞察会被合并，并提供工作流方面的详细建议，借助跨建筑系统和运营设备的实时异常检测，指导设施团队采取最佳行动。能源消耗根据占用情况、天气和运营计划进行优化。 因此，机场能够从被动响应问题转向主动预判问题，从而减少停机时间、提升安全性并改善旅客体验。 

4. Solving Interop with Airport Ontology4. 利用机场本体解决互操作性问题

Interoperability is one of the most persistent challenges in airport technology. With dozens of vendors, hundreds of subsystems, and decades of legacy equipment, airports can face a challenge in integrating new technologies for scaled AI solutions. 互操作性是机场技术领域最长期存在的挑战之一。机场拥有数十家供应商、数百个子系统以及使用了数十年的遗留设备，因此在集成新技术以实现规模化 AI 解决方案方面可能面临挑战。 

Most technology providers focus on a specific sub-system like apron operations, baggage systems, or passenger analytics. This leaves an open challenge around managing the entire ecosystem. 大多数技术提供商专注于特定子系统，例如机坪运营、行李系统或旅客分析。这给整个生态系统的管理留下了一个尚未解决的挑战。 

Willow takes a system-driven approach. By leveraging semantic modeling and DTDL-based ontology, Willow creates a shared data model that standardizes how assets, systems, and relationships are represented. Willow’s ontology for airports (GitHub – WillowInc/opendigitaltwins-airport: WillowTwin open digital twin definition language (DTDL) ontology for airports) models key sub-systems and equipment across Passenger Boarding Bridges, Baggage Handling, Airfield Lighting and more. Willow 采用系统驱动的方法。通过利用语义建模和基于 DTDL 的本体，Willow 创建了一个共享数据模型，用以标准化资产、系统和关系的表示方式。Willow 的机场本体（GitHub – WillowInc/opendigitaltwins-airport: WillowTwin 机场开放数字孪生定义语言 (DTDL) 本体）建模的关键子系统和设备涵盖旅客登机桥、行李处理、机场助航灯光等。 

This allows airports to digitally describe multiple systems within the airport in a single Knowledge Graph. Assets can be described in the graph with relationships to their locations and other equipment. The Map Viewer feature in Willow allows for visualization of assets nearby that have active insights. Workflow coordinators on facility teams can then combine these and assign them to a single technician, hence saving multiple trips.这使机场能够在单个知识图谱中以数字化方式描述机场内的多个系统。资产可在图谱中通过其与位置及其他设备的关系进行描述。Willow 的 Map Viewer 功能可将附近存在活动洞察的资产可视化。随后，设施团队中的工作流协调员可以将这些工作合并，并分派给同一名技术人员，从而省去多次往返。

When real-time data flows through this digital layer, it breaks down silos across all sub-systems. This enables airports to integrate legacy and modern systems and map complex operational relationships. Cross-system reasoning allows for scalable AI solutions that work across the entire airport.  当实时数据流过该数字层时，它会打破所有子系统之间的孤岛。这使机场能够整合遗留系统与现代系统，并映射复杂的运营关系。跨系统推理可支持在整个机场范围内运行的可扩展 AI 解决方案。 

5. Providing Decision Intelligence for Capital Planning5. 为资本规划提供决策智能

Airport leaders and stakeholders expect real-time visibility into operations to understand where bottlenecks exist, and which assets are at risk of failure. A complete picture can illustrate how energy consumption is trending, where safety or compliance gaps exist, and how operational decisions impact cost, sustainability, and passenger experience. 机场领导者 和利益相关方 期望 实时掌握运营情况， 以了解 瓶颈 存在于何处， 以及 哪些资产存在故障风险。全面视图 可 展示能耗趋势、安全或合规差距所在， 以及 运营决策 如何影响 成本、可持续性和乘客体验。 

Willow enables this through a single pane of glass and AI-drive Willow Copilot, a companion experience that makes it easy to conversationally understand how buildings are performing against operational efficiency goals, and what the ‘bad actor’ assets are across the entire portfolio to inform Capital Planning decisions.Willow 通过单一管理平台 和 AI 驱动的 Willow Copilot 这一配套 体验，让用户能够轻松以对话方式 了解楼宇 相对于运营效率目标的表现，以及整个资产组合中哪些是“问题”资产，从而为资本规划决策提供依据。

Willow paves the way for a dynamically generated Facility Condition Index (FCI) score by continuously integrating real‑time intelligence into operations, enabling faster, context‑aware decisions that adapt as conditions change.Willow 通过持续将 实‑时 智能融入运营，为动态生成设施状况指数（FCI）评分铺平道路，从而支持更快速、 情境‑感知 的决策，这些决策会随状况变化而调整。

Closing Thoughts结语

Airports are at a crossroads, with rising operational demands, increasing passenger expectations, and growing pressure to modernize infrastructure. AI offers a path forward to overcome the challenges of data fragmentation, governance, and interoperability. By providing a unified digital twin platform, governance first architecture, and interoperable data model, Willow can help airports unlock the full potential of AI.机场正处在十字路口，面临 运营需求不断上升、乘客期望日益提高、基础设施现代化压力持续增大。AI 提供了一条前进道路 ，以克服数据碎片化、治理和互操作性方面的挑战。 通过提供统一的数字孪生平台、治理 优先的架构和可互操作的数据模型，Willow 可帮助机场充分释放 AI 的全部潜力。

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