NVIDIA Unveils Smart City AI Blueprint to Revolutionize Urban Planning and Management

NVIDIA Brings Physical AI to European Cities With New Blueprint for Smart City AI

NVIDIA Omniverse Blueprint for smart city AI -- integrating NVIDIA Omniverse, Cosmos, NeMo and Metropolis -- adopted by leading ISV partners to improve sustainability and quality of life for residents across Europe. Urban populations are expected to double by 2050, which means around 2.5 billion people could be added to urban areas by the middle of the century, driving the need for more sustainable urban planning and public services. Cities across the globe are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions. Building a digital twin of a city and testing smart city AI agents within it, however, is a complex and resource-intensive endeavor, fraught with technical and operational challenges. To address those challenges, NVIDIA today announced the NVIDIA Omniverse Blueprint for smart city AI, a reference framework that combines the NVIDIA Omniverse, Cosmos, NeMo and Metropolis platforms to bring the benefits of physical AI to entire cities and their critical infrastructure. Using the blueprint, developers can build simulation-ready, or SimReady, photorealistic digital twins of cities to build and test AI agents that can help monitor and optimize city operations. Leading companies including XXII, AVES Reality, Akila, Blyncsy, Bentley, Cesium, K2K, Linker Vision, Milestone Systems, Nebius, SNCF Gares&Connexions, Trimble and Younite AI are among the first to use the new blueprint. The NVIDIA Omniverse Blueprint for smart city AI provides the complete software stack needed to accelerate the development and testing of AI agents in physically accurate digital twins of cities. It includes: The blueprint workflow comprises three key steps. First, developers create a SimReady digital twin of locations and facilities using aerial, satellite or map data with Omniverse and Cosmos. Second, they can train and fine-tune AI models, like computer vision models and VLMs, using NVIDIA TAO and NeMo Curator to improve accuracy for vision AI use cases. Finally, real-time AI agents powered by these customized models are deployed to alert, summarize and query camera and sensor data using the Metropolis VSS blueprint. The blueprint for smart city AI enables a large ecosystem of partners to use a single workflow to build and activate digital twins for smart city use cases, tapping into a combination of NVIDIA's technologies and their own. SNCF Gares&Connexions, which operates a network of 3,000 train stations across France and Monaco, has deployed a digital twin and AI agents to enable real-time operational monitoring, emergency response simulations and infrastructure upgrade planning. This helps each station analyze operational data such as energy and water use, and enables predictive maintenance capabilities, automated reporting and GDPR-compliant video analytics for incident detection and crowd management. Powered by Omniverse, Metropolis and solutions from ecosystem partners Akila and XXII, SNCF Gares&Connexions' physical AI deployment at the Monaco-Monte-Carlo and Marseille stations has helped SNCF Gares&Connexions achieve a 100% on-time preventive maintenance completion rate, a 50% reduction in downtime and issue response time, and a 20% reduction in energy consumption. The city of Palermo in Sicily is using AI agents and digital twins from its partner K2K to improve public health and safety by helping city operators process and analyze footage from over 1,000 public video streams at a rate of nearly 50 billion pixels per second. Tapped by Sicily, K2K's AI agents -- built with the NVIDIA AI Blueprint for VSS and cloud solutions from Nebius -- can interpret and act on video data to provide real-time alerts on public events. To accurately predict and resolve traffic incidents, K2K is generating synthetic data with Cosmos world foundation models to simulate different driving conditions. Then, K2K uses the data to fine-tune the VLMs powering the AI agents with NeMo Curator. These simulations enable K2K's AI agents to create over 100,000 predictions per second. Milestone Systems -- in collaboration with NVIDIA and European cities -- has launched Project Hafnia, an initiative to build an anonymized, ethically sourced video data platform for cities to develop and train AI models and applications while maintaining regulatory compliance. Using a combination of Cosmos and NeMo Curator on NVIDIA DGX Cloud and Nebius' sovereign European cloud infrastructure, Project Hafnia scales up and enables European-compliant training and fine-tuning of video-centric AI models, including VLMs, for a variety of smart city use cases. The project's initial rollout, taking place in Genoa, Italy, features one of the world's first VLM models for intelligent transportation systems. Linker Vision was among the first to partner with NVIDIA to deploy smart city digital twins and AI agents for Kaohsiung City, Taiwan -- powered by Omniverse, Cosmos and Metropolis. Linker Vision worked with AVES Reality, a digital twin company, to bring aerial imagery of cities and infrastructure into 3D geometry and ultimately into SimReady Omniverse digital twins. Linker Vision's AI-powered application then built, trained and tested visual AI agents in a digital twin before deployment in the physical city. Now, it's scaling to analyze 50,000 video streams in real time with generative AI to understand and narrate complex urban events like floods and traffic accidents. Linker Vision delivers timely insights to a dozen city departments through a single integrated AI-powered platform, breaking silos and reducing incident response times by up to 80%. Bentley Systems is joining the effort to bring physical AI to cities with the NVIDIA blueprint. Cesium, the open 3D geospatial platform, provides the foundation for visualizing, analyzing and managing infrastructure projects and ports digital twins to Omniverse. The company's AI platform Blyncsy uses synthetic data generation and Metropolis to analyze road conditions and improve maintenance. Trimble, a global technology company that enables essential industries including construction, geospatial and transportation, is exploring ways to integrate components of the Omniverse blueprint into its reality capture workflows and Trimble Connect digital twin platform for surveying and mapping applications for smart cities. Younite AI, a developer of AI and 3D digital twin solutions, is adopting the blueprint to accelerate its development pipeline, enabling the company to quickly move from operational digital twins to large-scale urban simulations, improve synthetic data generation, integrate real-time IoT sensor data and deploy AI agents. Learn more about the NVIDIA Omniverse Blueprint for smart city AI by attending this GTC Paris session or watching the on-demand video after the event. Sign up to be notified when the blueprint is available.

Nvidia debuts new AI models and tools for robotics, smart cities and autonomous vehicles - SiliconANGLE

Nvidia debuts new AI models and tools for robotics, smart cities and autonomous vehicles Nvidia Corp. today debuted several announcements aimed at empowering developers and industry professionals building autonomous vehicles, robot fleets and smart cities. During Nvidia GTC Paris at VivaTech, the company's technology conference, Nvidia showcased Nvidia Drive, an autonomous vehicle development platform now in production. It's enabling leading brands, including some of Europe's premier automakers, to build self-driving cars. Drive consists of several interconnected systems, including DGX systems and graphics processing units designed for training artificial intelligence models and developing artificial intelligence software. It also incorporates the Nvidia Omniverse and Cosmos platforms, which are used for simulation and synthetic data generation to facilitate the testing and validation of autonomous driving scenarios. There's also the AGX in-vehicle computer, responsible for processing real-time sensor data to ensure safe and automated driving capabilities. Nvidia said Drive is a unified software stack, using deep learning and AI foundation models trained on large datasets of human driving behavior to process sensor data to eliminate the need for predefined rules. "AV software development has traditionally been based on a modular approach, with separate components for perception, prediction, planning and control," Xinzhou Wu, Nvidia vice president of auto, said in a blog post. "While there are benefits to this approach, it also opens up potential inefficiencies and errors that can hinder development at scale." The company said safety is an important component of all autonomous vehicle development. Earlier this year, Nvidia launched Nvidia Halos, a safety system that integrates hardware, software, AI models and tools to ensure safe AV development and deployment from cloud to car. Halos includes an advanced AI Systems Inspection Lab with membership that includes Continental AG, Ficosa International S.A., OmniVision Technologies, Inc., On Semiconductor Corp. and Sony Semiconductor Solutions Corp. Newly announced automotive leaders joining to verify the safe integration of their products with Nvidia technologies to advance AV safety include Robert Bosch GmbH, Easyrain i.S.p.A. and Nuro Inc. To help accelerate the development of next-generation autonomous vehicle architectures, Nvidia released Cosmos Predict-2, a new world foundation model with improved world prediction capabilities for high-quality synthetic data generation. World foundation models are a type of generative AI model that understands the dynamics of the real world, including physical and spatial properties. They can be used to represent and predict dynamics such as motions, force and spatial relationships from sensor data. That means they can be used to assist in the training of robot and AV models by generating simulations of the real world, predicting human behavior and guiding robots, thus increasing safety and accuracy. The Nvidia Research team post-trained the Cosmos models on 20,000 hours of real-world driving data. Using the AV-specific models to generate Multiview video data, the company said, the team improved model performance when representing challenging conditions such as fog and rain. In addition to Cosmos Predict-2, Nvidia released Cosmos Transfer as an Nvidia NIM microservice, which allows easy deployment on data center GPUs. This microservice augments datasets and generates photorealistic videos using structured input or ground-truth simulations from Nvidia Omniverse, the company's 3D simulation platform. In combination with the NuRec Fixer model helps inpaint and resolve gaps in reconstructed AV data. CARLA, short for Car Learning to Act, the world's leading open-source AV simulator, has integrated Cosmos Transfer and Nvidia NuRec into its latest release. By doing so, CARLA's user base of more than 150,000 AV developers can now render generative simulation scenes and viewpoints with high fidelity and generate endless variations of lighting, weather and terrain using simple prompts. Nvidia today announced the next update to its foundation model for humanoid robots, Isaac GR00T N1.5 is now available for download on Hugging Face. The N1.5 update upgrades the previous generation and can better adapt to different environments and workspace configurations. Nvidia said it significantly improves its performance in material handling and manufacturing tasks. Nvidia also announced that Halos, the comprehensive safety system for autonomous vehicles, has been expanded to robotics. Arkansas Best Corp., Advantech Co. Ltd., Bluewhite, Boston Dynamics Inc., Fort Robotics Inc., Inxpect Electronics Co., Ltd., Kion Group AG and NexCobot Co. Ltd. were among the first robotics companies to join the Halos Inspection Lab to integrate their products with Nvidia safety and cybersecurity requirements. As cities continue to grow and planners need to address issues such as sustainable services, many are turning to digital twins and AI models to get the job done. This very scenario was addressed by IBM Corp.'s Smarter Cities initiative in 2014 and the need is only expected to expand as urban populations as set to double by 2050. Building a digital twin of a city and testing smart city AI agents can be a daunting task. The resources needed are complex and resource-intensive because of the technical and operational challenges. To help deal with these challenges, Nvidia today announced the Nvidia Omniverse Blueprint for smart city AI, a reference framework that combines Nvidia Omniverse, Cosmos, NeMo and Metropolis platforms. Using the blueprint, developers can generate simulation-ready, or SimReady, photorealistic digital twins of cities to build and test AI agents that can monitor and optimize city operations. Leading companies including 22nd Century Group, AVES Reality GmbH, Bentley Motors Ltd. and Milestone Systems Inc. are among the first to use the new blueprint. Linker Vision Corp. was among the first to partner with Nvidia to deploy smart city digital twins and AI agents for Kaohsiung City, Taiwan working with AVES Reality, a digital twin company. It uses aerial imagery of the city and infrastructure to generate 3D geometry and ultimately SimReady digital twins. It now scales up to analyze 50,000 video streams in real-time with generative AI to understand and narrate complex urban events such as floods and traffic accidents.