Making Safer Spaces: NVIDIA and Partners Bring Physical AI to Cities and Industrial Infrastructure

Physical AI is becoming the foundation of smart cities, facilities and industrial processes across the globe.

NVIDIA is working with companies including Accenture, Avathon, Belden, DeepHow, Milestone Systems and Telit Cinterion to enhance operations across the globe with physical AI-based perception and reasoning.

The continuous loop of simulating, training and deploying physical AI offers sophisticated industrial automation capabilities, making cities and infrastructure safer, smarter and more efficient.

For example, physical AI applications can automate potentially dangerous tasks for workers, such as working with heavy machinery. Physical AI can also improve transportation services and public safety, detect defective products in factories and more.

The need for this is greater than ever. The numbers tell the story:

Infrastructure that can perceive, reason and act relies on video sensors and the latest vision AI capabilities. Using the NVIDIA Metropolis platform - which simplifies the development, deployment and scaling of video analytics AI agents and services from the edge to the cloud - developers can build visual perception into their facilities faster to enhance productivity and improve safety across environments.

Below are five leading companies advancing physical AI - and five key NVIDIA Metropolis updates, announced today at the SIGGRAPH computer graphics conference, making such advancements possible.

Five Companies Advancing Physical AI Global professional services company Accenture is collaborating with Belden, a leading provider of complete connection solutions, to enhance worker safety by creating smart virtual fences that factories can place around large robots to prevent accidents with human operators.

Image courtesy of Accenture and Belden. The smart virtual fence is a physical AI safety system that uses an OpenUSD-based digital twin and physics-grounded simulation to model complex industrial environments. Using computer vision-based mapping and 3D spatial intelligence, the system is adaptive to increased variability in the dynamic human-robot interactions that occur in a modern shopfloor environment.

Accenture taps into the NVIDIA Omniverse platform and Metropolis to build and simulate these smart fences. With Omniverse, Accenture created a digital twin of a robot arm and workers moving in a space. And with Metropolis, the company trained its AI models and deployed them at the edge with video ingestion and the NVIDIA DeepStream software development kit (SDK)'s real-time inference capabilities.

Avathon, an industrial automation platform provider, uses the NVIDIA Blueprint for video search and summarization (VSS), part of NVIDIA Metropolis, to provide manufacturing and energy facilities with real-time insights that improve operational efficiency and worker safety.

Reliance British Petroleum Mobility Limited, a leader in India's fuel and mobility sector, used the Avathon video intelligence product during the construction of its gas stations to achieve higher standards of safety compliance, a reduction in safety noncompliance incidents and higher productivity by saving thousands of work hours.

DeepHow has developed a Smart Know-How Companion for employees in manufacturing and other industries. The companion uses the Metropolis VSS blueprint to transform key workflows into bite-sized, multilingual videos and digital instructions, improving onboarding, safety and floor operator efficiency.

Facing upskilling needs and retiring skilled workers, beverage company Anheuser-Busch InBev turned to the DeepHow platform to convert standard operating procedures into easy-to-understand visual guides. This has slashed onboarding time by 80%, boosted training consistency and improved long-term knowledge retention for employees.

Milestone Systems, which offers one of the world's largest platforms for managing IP video sensor data in complex industrial and city deployments, is creating the world's largest real-world computer vision data library through its platform, Project Hafnia. Among its capabilities, the platform provides physical AI developers with access to customized vision language models (VLMs).

Tapping NVIDIA NeMo Curator, Milestone Systems built a VLM fine-tuned for intelligent transportation systems for use within the VSS blueprint to help develop AI agents that better manage city roadways. Milestone Systems is also looking to use the new open, customizable NVIDIA Cosmos Reason VLM for physical AI.

Internet-of-things company Telit Cinterion has integrated NVIDIA TAO Toolkit 6 into its AI-powered visual inspection platform, which uses vision foundation models like FoundationPose, alongside other NVIDIA models, to support multimodal AI and deliver high-performance inferencing. TAO brings low-code AI capabilities to the Telit platform, enabling manufacturers to quickly develop and deploy accurate, custom AI models for defect detection and quality control.

Five NVIDIA Metropolis Updates for Physical AI Key updates to NVIDIA Metropolis are enhancing developers' capabilities to build physical AI applications more quickly and easily:

Cosmos Reason VLM

https://blogs.nvidia.com/wp-content/uploads/2025/08/turbine-cosmos-reasoning.mp4

The latest version of Cosmos Reason - NVIDIA's advanced open, customizable, 7-billion-parameter reasoning VLM for physical AI - enables contextual video understanding, temporal event reasoning for Metropolis use cases. Its compact size makes it easy to deploy from edge to cloud and ideal for automating traffic monitoring, public safety, visual inspection and intelligent decision-making.

VSS Blueprint 2.4

VSS 2.4 makes it easy to quickly augment existing vision AI applications with Cosmos Reason and deliver powerful new features to smart infrastructure. An expanded set of application programming interfaces in the b

LINK:	https://blogs.nvidia.com/blog/physical-ai-partners-metropolis-updates-...
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