AI and GenAI can boost smart city goals like efficiency, sustainability, and quality of life, but cities must leverage existing IT investments and heterogenous devices to scale innovations.
A tale of two cities
When Robert Howard built his home in 1680, he couldn’t have known that it would eventually become one of the oldest buildings in the United States. The house still sits on a bumpy cobblestone road in Boston’s North End, wedged between a gift shop and an Italian restaurant. Visitors may be forgiven for getting lost trying to find it; after all, Boston is known for a confusing street layout, said to be the result of paving over cow paths. Considering when a city has been around for hundreds of years, its current state is a result of millions of decisions made by hundreds of people over the course of centuries.
So, when you envision a smart city, you might not immediately think of Boston, or Pittsburgh or even New York City with their rich pasts and resulting mix of historical and modern buildings, roadways and city infrastructure. You’d more likely think of Toyota Woven City in Japan, a planned city that connects people, buildings and vehicles through pervasive sensors to test connected AI technologies on a citywide level.1) This next generation of preplanned cities provides visionaries with a blank canvas and the opportunity to integrate AI-driven smart city technologies from the start. Having a clean slate, city master planners can preempt existing city challenges and architect technology and infrastructure from the onset, creating a foundation through implementation, designing for commerce, merchants, citizens and services prior to beginning construction.
While these cities serve as innovative showcases and incubators, most city planners of the world operate in environments with existing infrastructure built on decades and centuries of refinement like Boston, or Pittsburgh or New York City — cities that have grown organically over hundreds of years. The key here is to envision both scenarios leveraging technological advancements to provide a mechanism that addresses both situations, streamlining function and form to meet the needs of ever-evolving cities.
When AI and GenAI are a new portrait on an existing canvas
When you consider the ramifications of paving over cow paths, you can start to see some of the challenges cities face when adopting new technologies. A perfect example of this is the explosion of AI and GenAI. These technologies have the potential to revolutionize city planning and civil engineering for physical infrastructure from bridges, roads and sewers to trenching fiber lines. AI and GenAI can help to optimize orchestration of city systems and services to harmonize a series of vibrant data flows, reducing drive times, congestion and greenhouse gas emissions. Further optimizing energy consumption behaviors while implementing sustainable design and building practices, AI and GenAI help cities achieve sustainability goals. Delivering public services faster and more effectively through the usage of AI and GenAI brings efficient access to information and resources.
However, cities face significant challenges simply maintaining existing essential IT infrastructure. Ripping and replacing is simply not an option, not to mention the costly investments previously applied. When considering layering new technologies over legacy investments, cities need to ensure they’re choosing solutions that provide the flexibility to keep pace with rapid technological advancements, including the latest innovations in AI and GenAI.
One approach is to use software to connect a series of edge devices into a central nervous system for your entire IT landscape, with a single console that securely manages the entire asset estate and application management. In such an environment, city administrators can explore new AI or GenAI use cases; they can find, pilot and create a blueprint that contains infrastructure, applications and their associated configurations. The blueprint methodology automates every step, leveraging predefined configurations for consistency and reliability. A single console can be used to push consistent blueprints out to all of your end points. You also have the ability to deploy a blueprint multiple times with minor alterations applied to variant scenarios. For example, you could have a blueprint for AI-driven smart parking that you test on a limited basis, using AI feedback loops to optimize it at scale and then expand it into other departments and other use cases — all while still using a single pane of glass to define the blueprint and deploy it. Once this centralized nervous system is in place, testing, evolving and deploying multiple solutions throughout the city using the same mechanism becomes seamless.
By selecting an edge operations software platform with an open, vendor-agnostic design that works with a variety of applications, models, Internet of Things (IoT) frameworks, multi-vendor operational technology (OT) solutions and multicloud environments, you can maximize legacy IT investments by centrally and consistently deploying innovations that work across citywide heterogenous environments.
Overcome AI and GenAI challenges
As Smart Cities adopt AI, GenAI and other innovative technologies, solutions like Dell NativeEdge provide a unified platform that enables administrators to deploy blueprinted models and orchestrate heterogeneous systems, keeping IT manageable, secure and ready for future expansion. Learn more about digital cities.
1)Sustainability Magazine, Toyota’s smart, sustainable concept city of the future, July 2023.
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Autor(en)/Author(s): John Lockhart
Quelle/Source: Forbes, 11.09.2024
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