NVIDIA Partners Bring Physical AI, New Smart City Technologies to Dublin, Ho Chi Minh City, Raleigh and More – NVIDIA Blog

Report on AI-Driven Urban Development and its Contribution to Sustainable Development Goals

A United Nations projection indicates that by 2050, an additional 2.5 billion people will reside in urban areas, escalating the urgency for urban planning and public services that align with the Sustainable Development Goals (SDGs). The integration of Artificial Intelligence (AI) presents a transformative approach to addressing these challenges, particularly in advancing SDG 11: Sustainable Cities and Communities.

NVIDIA’s Technological Framework for Sustainable Cities

NVIDIA has introduced a comprehensive framework, the NVIDIA Blueprint for smart city AI, designed to help municipalities build resilient and sustainable infrastructure, directly supporting SDG 9 (Industry, Innovation, and Infrastructure). This blueprint facilitates the development of intelligent urban environments through a streamlined workflow that integrates several key technologies.

• Digital Twins: Utilizing NVIDIA Omniverse, cities can create large-scale simulations of urban environments to model, plan, and manage infrastructure and services, enhancing progress towards SDG 11.3 on sustainable urbanization.
• Synthetic Data Generation: NVIDIA Cosmos world foundation models generate photorealistic, physically accurate data, enabling the training of robust AI models without compromising citizen privacy.
• AI-Powered Video Analytics: Vision Language Models (VLMs) and AI agents, part of the NVIDIA Metropolis platform, analyze real-time video feeds to improve traffic management, public safety, and operational efficiency.

Partner Innovations Advancing the SDGs

A global ecosystem of partners is leveraging NVIDIA’s technologies to deploy city-scale AI solutions that address specific SDG targets. The following case studies, highlighted at the Smart City Expo World Congress, demonstrate practical applications of physical AI in urban settings.

Esri: Enhancing Urban Mobility and Environmental Sustainability (SDG 11.2, 11.6)

In collaboration with the City of Raleigh, North Carolina, mapping and analytics firm Esri is developing an AI agent to process vast amounts of sensor data. This initiative aims to:

1. Generate real-time insights on an interactive geospatial map for city operators.
2. Optimize traffic flows and automate streetlight timing to reduce road delays.
3. Decrease carbon emissions from vehicular congestion, contributing directly to SDG 11.6 (reducing the environmental impact of cities) and SDG 13 (Climate Action).

Milestone Systems: Improving Urban Safety with Generative AI (SDG 11)

Milestone Systems is integrating generative AI into its XProtect video management platform. By post-training NVIDIA Cosmos Reason VLMs on extensive traffic video data, the system can automatically analyze video streams, generate reports, and filter false alarms. This enhances urban safety and operational efficiency, aligning with the goal of creating safer and more resilient cities under SDG 11.

Linker Vision: Accelerating Incident Response for Safer Communities (SDG 3.6, 11.2)

Linker Vision is deploying the end-to-end NVIDIA Blueprint in Ho Chi Minh City and Danang, Vietnam. Building on a successful implementation in Taiwan that reduced incident response times by up to 80%, this project utilizes digital twins and vision AI to:

• Monitor traffic and construction activities in real-time.
• Improve urban mobility and operational efficiency.
• Significantly enhance road safety, contributing to SDG 3.6 (halve deaths and injuries from road traffic accidents).

Bentley Systems and VivaCity: Promoting Sustainable Transport in Dublin (SDG 11.2)

The Smart Dublin organization is leveraging technology from Bentley Systems and VivaCity to support SDG 11.2 (access to safe and sustainable transport systems). The project involves:

1. Using a Cesium-powered digital twin with NVIDIA Omniverse for real-time data visualization of micromobility, including cycling and walking.
2. Deploying VivaCity’s AI-powered sensors on the NVIDIA Jetson platform to gather multimodal data on traffic patterns and identify dangerous sites.
3. Integrating data into the digital twin to analyze route utilization and improve safety for vulnerable road users.

Deloitte: Automating Infrastructure Maintenance for Pedestrian Safety (SDG 11.2)

Deloitte is applying AI to automate the inspection of street crosswalks, a critical task for protecting vulnerable road users. Using NVIDIA Cosmos, Deloitte can:

• Convert static images into photorealistic videos to simulate various real-world conditions like rain, fog, and low light.
• Utilize AI to evaluate these scenarios and identify areas for infrastructure improvement.
• Enhance the safety of pedestrians and cyclists, directly supporting the objectives of SDG 11.2.

Conclusion: A Collaborative Ecosystem for Sustainable Urban Futures

The deployment of physical AI in urban environments represents a significant step towards achieving the Sustainable Development Goals, particularly SDG 11. The collaborative efforts of technology providers like NVIDIA and its diverse ecosystem of partners are crucial for developing and scaling innovative solutions. By integrating digital twins, advanced AI models, and real-time data analytics, cities can better manage the complexities of rapid urbanization, building more sustainable, resilient, and inclusive communities for the future.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 11: Sustainable Cities and Communities: This is the most central SDG addressed. The article begins by highlighting the rapid urbanization projected by the UN and the “urgent need for more sustainable urban planning and public services.” It focuses on solutions like smart traffic management, improving urban mobility, and enhancing city processes to accommodate growing populations, which are core components of SDG 11.
• SDG 9: Industry, Innovation and Infrastructure: The article is fundamentally about leveraging innovation and technology (AI, digital twins, IoT sensors) to build resilient and sustainable infrastructure. It describes how companies are developing “city-scale AI solutions” and upgrading systems for traffic management, road maintenance, and public safety, directly aligning with the goal of building resilient infrastructure and fostering innovation.
• SDG 3: Good Health and Well-being: The article explicitly mentions improving “road safety” and protecting “vulnerable roadway users such as pedestrians and bikers.” Initiatives like identifying “dangerous sites” using near-miss detection in Dublin and automating street inspections for crosswalks directly contribute to reducing traffic-related injuries and fatalities, a key aspect of public health.
• SDG 13: Climate Action: The article connects smart city technology to climate change mitigation. For example, it states that the City of Raleigh aims to “decrease carbon emissions from cars sitting in traffic” by automating streetlight timing. This demonstrates how urban planning and technology can be used to address climate change.

2. What specific targets under those SDGs can be identified based on the article’s content?

• Target 11.2: Provide access to safe, affordable, accessible and sustainable transport systems for all. The article’s focus on “optimizing traffic flows,” improving “urban mobility,” and analyzing micromobility (walking, cycling) in Dublin directly supports this target. The efforts to make roadways safer for pedestrians and cyclists also align with providing special attention to vulnerable users.
• Target 9.1: Develop quality, reliable, sustainable and resilient infrastructure. The deployment of AI-powered computer vision sensors, digital twins for simulating urban conditions, and intelligent video analytics platforms are all examples of developing technologically advanced, sustainable, and resilient infrastructure to manage modern cities effectively.
• Target 3.6: Halve the number of global deaths and injuries from road traffic accidents. The use of AI by VivaCity in Dublin to “identify dangerous sites” and understand road user behavior to improve “road safety” is a direct action toward this target. Similarly, Deloitte’s work on automating crosswalk inspections aims to protect vulnerable users and prevent accidents.
• Target 13.2: Integrate climate change measures into national policies, strategies and planning. The City of Raleigh’s plan to use AI to manage traffic and “decrease carbon emissions” is a clear example of integrating climate mitigation measures into city-level operational planning and strategy.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• Incident Response Time: The article provides a specific metric from Kaohsiung City, where the vision AI platform “cut incident response times by up to 80%.” This is a direct indicator of improved operational efficiency and public safety (relevant to Target 11.2).
• Carbon Emissions Reduction: The goal to “decrease carbon emissions from cars sitting in traffic” is a direct, measurable indicator of progress towards climate action (Target 13.2).
• Road Safety Metrics: The use of VivaCity’s “near-miss feature” to detect “road accidents hotspots” serves as a proactive indicator for measuring and improving road safety, contributing to the reduction of accidents (Target 3.6).
• Micromobility Utilization: The analysis of “bike route utilization” in Dublin is an indicator used to understand and promote sustainable transport modes like cycling (Target 11.2).
• Operational Efficiency: Milestone Systems’ technology aims to “reduce up to 30% of operator alarm fatigue.” This is a quantifiable indicator of improved efficiency in managing city infrastructure and security systems (relevant to Target 9.1).

4. Summary Table of SDGs, Targets, and Indicators

Source: blogs.nvidia.com