Fujitsu Ltd.

01/22/2025 | Press release | Distributed by Public on 01/21/2025 18:35

Sustainable AI – Creating Tomorrows Urban Living

As urbanization accelerates, urban populations grow, and infrastructure and operational complexity increase, cities face growing sustainability challenges.

Today, smart city initiatives are harnessing the power of AI to help plan, improve, and operate our cities' infrastructure. These initiatives provide the foundation for establishing Sustainable AI as a practice for urban development. By learning from the best approaches and integrating effective solutions, the development of Sustainable AI is helping to make our cities smarter, more innovative, and more sustainable.

Mitigating the urbanization challenge with sustainable AI

Today, more than half of the world's population already lives in urban areas, and by 2050, this is expected to increase to almost 70%. With this urbanization comes a host of sustainability challenges: higher energy demands, strained transportation systems, increased waste production, and water scarcity. Urban centers already contribute over 70% of global carbon emissions and account for the bulk of resource consumption.

However, while these challenges are substantial, they are not insurmountable. AI is emerging as a pivotal tool in creating sustainable solutions for cities, providing data-driven approaches to everything from energy and waste management to urban planning and climate resilience.

So far, most of these initiatives are based on different AI approaches, models and algorithms. However, our whitepaper "Sustainable AI for Enterprise Transformation, Innovation and Growth" shows how the development and implementation of Sustainable AI platforms can become a driving in integrating and orchestrating sustainable development initiatives. It shows how AI, especially generative AI, can integrate existing management systems to improve prediction, optimization, and planning across diverse management functions.

In cities, Sustainable AI can enable data-driven decision-making and streamlining of complex sustainability initiatives across infrastructures and value chains. This integration is critical for implementing effective environmental, social, and governance (ESG) strategies.

Sustainable AI and the Potential of Digital Twins for Urbanization

An important development is that cities, universities, and technology companies are increasingly working together to solve social issues. An example is the cooperation between Fujitsu and Carnegie Mellon University for the development of a Social Digital Twin.

It digitally reproduces the relationships between people, goods, the economy and society to offer a simulation, prediction and decision-making environment. It also extends capabilities in 3D modeling to monitor activity on streets and determine where issues or accidents may be taking place. Fujitsu's Social Digital Twin can now be used for a growing range of applications, from traffic planning to CO2 reductions and disaster resilience preparation.

Fujitsu Social Digital Twin Technology

Source: https://www.youtube.com/watch?v=UZnWku3kECY

As urbanization continues to reshape the global landscape, cities must adapt their initiatives to ensure a sustainable future. Those that harness the power of AI responsibly will be better positioned to meet the environmental and logistical challenges of rapid urban growth, creating urban environments that not only support a high quality of life, but also minimize their environmental footprint. On the path to sustainable urbanization, Sustainable AI is not just a tool, but a catalyst and a practice for reimagining the cities of tomorrow.

Optimizing Energy Use and Integrating Renewables with AI

Urban energy consumption is a major contributor to greenhouse gas emissions, given the intense demand for heating, cooling, and lighting across residential, commercial, and industrial sectors. However, AI offers cities the ability to optimize energy usage, integrate renewable sources into the grid, and predict peak demands.

One example comes from New York City, where AI is helping reduce the energy use of one of its most iconic buildings: the Empire State Building. Using an AI-powered energy management platform, the building's heating, ventilation, and air conditioning (HVAC) systems adjust in real time to factors such as weather and occupancy levels. This data-driven approach has enabled the building to cut its energy consumption by nearly 40%, showcasing how AI can make existing infrastructure more efficient and environmentally friendly.

Similarly, Tokyo's Electric Power Company (TEPCO) has implemented AI to manage the energy needs of several residential neighborhoods. With a network of sensors and data points throughout the grid, TEPCO's AI system predicts demand surges and distributes energy accordingly. It can also determine the best times to draw on renewable energy sources like solar and wind, whose supply fluctuates. The AI system allows for both greater energy efficiency and a substantial increase in renewable integration, reducing Tokyo's reliance on fossil fuels and lowering carbon emissions across the city.

Singapore's Building and Construction Authority has also introduced a program encouraging building owners to install AI-based energy management systems. Through adaptive controls on lighting, HVAC, and other energy-intensive functions, these AI platforms have helped buildings achieve energy savings of up to 30%. By incentivizing the adoption of AI in energy management, Singapore is setting an example for other cities striving to reduce their energy footprint.

Reducing Congestion and Pollution through AI in Transportation

Transportation is one of the most resource intensive aspects of urban living, and AI has the potential to make urban transportation networks more efficient and sustainable. AI systems can optimize traffic management, improve the efficiency of public transit, and facilitate the use of electric and autonomous vehicles (EVs and AVs).

In Beijing, where congestion and pollution are significant challenges, the city has deployed an AI-powered traffic management system. Data from thousands of traffic cameras, sensors, and GPS signals is analyzed in real time, allowing the system to manage traffic flow, adjust signal timings, and even suggest alternate routes for drivers. This dynamic approach has reduced commuter travel time by as much as 20%, leading to a corresponding reduction in vehicle emissions and fuel consumption.

On the public transit side, Dubai's Metro system has integrated AI to optimize train schedules based on demand patterns. By analyzing passenger data, the AI system can increase train frequency during peak hours, reducing wait times and enhancing energy efficiency by limiting unnecessary trips. As a result, Dubai has seen a 15% increase in ridership and reduced energy consumption per trip, demonstrating the dual benefits of AI in promoting sustainable public transit.

In Europe, Stockholm has piloted autonomous electric buses that rely on AI-powered navigation systems. These shuttles not only provide an energy-efficient alternative to private cars but also reduce the need for drivers and fuel-intensive operations. Stockholm's autonomous buses are programmed to operate along specific routes, further optimizing energy use and lowering emissions. If successful, this pilot could set a precedent for autonomous and AI-enabled transit systems that prioritize both convenience and sustainability.

AI and the Circular Economy: Transforming Waste Management

Waste management is one of the most pressing issues in densely populated urban centers. Traditional waste collection methods are often inefficient, and cities struggle to keep up with waste generation. AI driven solutions are helping cities tackle waste collection and promote recycling, enabling a more sustainable approach to managing resources.

Seoul, South Korea, has integrated AI into its waste management system by equipping smart waste bins with sensors that monitor fill levels. This data enables city waste collection teams to optimize their routes, making fewer trips to bins that are not yet full and reducing fuel consumption in the process. Seoul's AI powered waste system has improved collection efficiency by 25% and decreased the city's dependency on landfills.

Barcelona has also deployed a similar system, using Internet of Things (IoT) sensors connected to an AI platform that determines optimal routes for waste collection. This approach reduces unnecessary trips, lowers emissions from waste collection trucks, and has made Barcelona's waste management 10% more efficient. Additionally, the system's data helps the city identify patterns in waste production, enabling policymakers to design targeted waste reduction initiatives.

In San Francisco, the Recology recycling facility has introduced AI enhanced robots to sort waste. These robots, powered by machine vision, can identify and separate various materials such as plastics, metals, and paper. With higher accuracy and speed than human workers, these robots have helped San Francisco increase its recycling rate by 30%, reducing the volume of waste sent to landfills and supporting the city's goal of achieving zero waste.

Water Management: AI for Conservation and Leak Detection

Water scarcity is becoming a critical issue as climate change and urban population growth strain resources. AI can significantly improve urban water management by enhancing leak detection, optimizing distribution, and enabling predictive maintenance.

Cape Town, South Africa, deployed an AI driven water management system during its recent severe drought. The system monitors water usage across the city, identifying leaks and irregular patterns that could indicate potential issues. This data-driven approach allowed the city to reduce water wastage by 15%, ensuring a more efficient use of limited resources.

In Las Vegas, AI is used to forecast water demand based on historical consumption data and seasonal patterns. This predictive capability enables the city to optimize water distribution, meeting demand without overusing the resource. Las Vegas has saved approximately 10% of its annual water supply, a notable achievement for a city in an arid region.

Tokyo has also implemented a similar system to detect leaks in its water network, utilizing sensors and AI to pinpoint issues early. The program has allowed Tokyo to save millions of liters of water each year, showcasing how AI can help manage and conserve urban water resources.

Urban Planning and Climate Resilience with AI-Driven Insights

With the impacts of climate change increasingly affecting urban areas, cities need to adopt flexible and resilient approaches to urban planning. AI powered models are helping cities simulate potential outcomes, enabling data driven decision making for sustainable development and climate resilience.

Singapore, for example, has developed a "digital twin" of the city a virtual model that mirrors the real world and allows urban planners to test the impact of proposed infrastructure and policies. This AI powered simulation incorporates data from traffic flows, energy usage, and weather patterns to help planners make informed decisions on land use and resource allocation. Singapore's use of AI for urban planning has enabled it to balance population growth with green space preservation, setting a benchmark for sustainable development.

New York City is also using AI based climate models to prepare for extreme weather events like hurricanes. By analyzing historical climate data and environmental factors, these models help city officials predict and mitigate potential impacts from storms. This proactive approach has improved New York's resilience to climate related risks, reducing disruptions and property damage from severe weather events.

Amsterdam's AI system addresses flood risk management, a critical need in a low-lying city susceptible to rising sea levels. By analyzing data from weather forecasts and water levels, Amsterdam's AI program helps officials decide when to activate flood barriers or evacuate vulnerable areas, protecting residents and critical infrastructure from climate-induced hazards.

Addressing Ethical and Privacy Concerns in AI-Driven Urban Sustainability

While AI offers substantial benefits in driving urban sustainability, it also raises ethical and privacy concerns. Cities implementing AI must address data privacy issues and avoid algorithmic biases that could exacerbate inequities. For example, data collected from traffic cameras or smart waste bins must be protected to maintain public trust, and algorithms must be designed to ensure that all communities benefit equally from these technologies.

In addition, cities should promote transparency in how AI systems are developed and used in urban management. Responsible AI practices are critical to fostering a fair and inclusive approach to sustainable urbanization, ensuring that the benefits of AI reach all segments of society.

Conclusion

The use of AI has the potential to help us transform positively nearly every aspect of urban living including the fundamentals of energy, transportation, water, and waste management as well as the sustainability of urban living. AI powered solutions can help cities address some of their most pressing sustainability challenges. As urbanization continues, the importance of sustainable, AI powered city management will only increase. Cities that embrace AI responsibly, balancing technological innovation with ethical considerations, will be better positioned to meet the demands of rapid population growth while minimizing their environmental impact.

Cities like New York, Tokyo, Singapore, and Amsterdam are already pioneering the use of AI to create more efficient, resilient, and sustainable urban environments.

So, why not talk to Fujitsu and find out how we can help you harness the power of Sustainable AI? You can also find out more about the transformative potential of Sustainable AI in our white paper "Sustainable AI for Enterprise Transformation, Innovation and Growth."

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