面向智慧城市的边缘 AI：从洞察到认知行动

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This white paper explains how edge AI and physical AI help cities move beyond passive monitoring. It shows how urban infrastructure can sense, reason, and act on real-time conditions across public safety, mobility, and infrastructure management.

What you will learn about:  

• How the shift from smart cities to cognitive cities depends on infrastructure that reasons and acts, rather than infrastructure that only monitors.
• Why edge AI supports low-latency decisions, keeps sensitive data within city boundaries, and reduces dependency on centralized cloud infrastructure.
• How computer vision, multimodal sensing, and generative and agentic systems work together to support public safety, mobility, and infrastructure applications.
• How a tiered edge architecture assigns monitoring, planning, and action tasks across the far edge, regional, and cloud layers, and what durability, security, and interoperability requirements this places on hardware and software.

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IEEE Spectrum and Wiley are proud to bring you this white paper, sponsored by Intel.

More Information

Smart city deployments have historically relied on cameras, sensors, and dashboards that capture data without delivering timely insight. Edge AI changes this by letting inference happen close to where data is generated. This supports faster decisions, stronger data sovereignty, and lower operating costs than cloud-only designs. This guide traces the progression from automation and perception to prediction, agentic coordination, and physical AI, where urban systems continuously perceive conditions, reason about them, and act within a tiered edge architecture spanning far-edge sensors, regional infrastructure, and the cloud. It also outlines the durability, security, and interoperability requirements that production-grade edge hardware and software must meet to support public safety, mobility, and infrastructure use cases at city scale.