Smart Cities and Quality of Life: Urbanization Underscores the Value of Internet of Things Applications

Chung-Sheng Li
January 13, 2015


More people live in cities today than at any time in human history, and the urbanization of the global population appears set to continue as the 21st century unfolds.

The multi-faceted pressures of urbanization will force cities to develop efficiencies and strategies in order to remain viable. Smarter ways of doing everything better, with fewer resources, will be required. So will the ability to forecast disruptive events such as natural disasters and their effect on urban dwellers and the infrastructure that supports them.

Cities that that succeed in improving their sustainability and adaptability in the face of disruptive events will attract people and enterprises that improve the local economy and create a desirable quality of life. “Smart cities” is the new tag for this goal.

How can the “smart cities” vision be made real?

Enter: Internet of Things (IoT)

Set aside, for a moment, the notion of IoT as a network of innumerable devices that 'talk' to each other, perhaps in the service of energy efficiency or machine-to-machine functional coordination. Certainly a day may come when every object has an Internet address and definable attributes that aid interconnectivity with other objects for various purposes.

For this article, however, let’s reimagine IoT as a set of applications that are the outcome of behavioral models that reflect the real world and anticipate its behavior. These applications will be made possible by a proliferation of sensors, data and timely data analysis that takes place either centrally or closer to the system’s edge. Some smart, IoT-enabled systems may become fully automated and run in the background to support urban infrastructure, for instance, while other applications will be designed to provide insights to people making everyday decisions on how they interact with their environment.

The infrastructure and daily processes of urban life may well benefit from such IoT-related applications to support and improve economic growth, public safety and security, transportation, buildings, work, food, healthcare and arts and culture – in short, all the elements of a vibrant, sustainable city.

Thus, let’s consider at a high level how IoT might aid urban infrastructure-related functions and provide insight into how to manage infrastructure and mitigate damage in the event of a natural disaster or other similarly disruptive event.

[For more technical detail on likely IoT components, processes, behaviors, applications and challenges, readers can replay an IEEE IoT webinar held Oct. 29, “Orchestrating a Smarter Planet in the World of IoT.”]

The urban foundation

One of the obvious challenges to urban centers is ensuring that the fundamental needs of city-dwellers are met. Water, food, power, transportation and healthcare must be consistently available to all. Moreover, these services – and many others – are linked by complex inter-dependencies. Optimizing each system must be accompanied by the optimization of an inter-dependent system of systems, both for ordinary blue sky days as well as under the duress of disruptive events.

Given the vast, often subterranean nature of a city’s infrastructure, the dynamics and demands of a so-called blue sky day are challenging enough. Simply maintaining operations in an optimal manner is a challenge, as anyone who reads a major metropolitan newspaper will attest. Power to traffic signals can be lost without warning. Water mains suddenly break. Natural gas lines may spring a leak. Construction mishaps can block streets.

IoT comes into play by integrating the widest possible, relevant data sets and models to identify normal operating metrics, asset conditions and vulnerabilities, as well as providing notice of conditions that indicate incipient failures.

Apply this IoT-supported methodology to power, water, natural gas or other critical supply lines such as food, transportation, medical care – you name it – and one can see how system optimization and proactively addressing predictable failures in infrastructure would aid efficient, cost-effective operations that underpin a city’s quality of life.

Fortunately, asset management techniques are shifting from time-based to condition-based assessments that will aid optimal operations. In the past, an infrastructure component designed for 10 years of service might be prioritized for replacement – or monitored for failure – after 10 years. In condition-based or context-based monitoring, sensors record various parameters so that asset managers can understand current conditions and forecast impending failures. “Smart grid” and “smart water” are two areas where IoT-like applications are being used today.

It’s difficult to imagine, let along articulate, the many permutations of IoT-related outcomes possible in the interdependent world of urban infrastructure. But sit down with a traffic engineer sometime and ask what’s involved in programming a city’s traffic lights. It’s complicated. IoT-related applications may offer the best tools for managing these complexities.

Disaster preparedness and response

Natural disasters will always occur on a dynamic planet, but their destructive impacts on infrastructure and people – particularly those concentrated in urban centers – can be mitigated. IoT-related systems can provide practical insights into how a storm will behave and, coupled with knowledge of infrastructure vulnerabilities, how a storm may impact essential services. With data-driven insights into probable impacts, improved preparation can lessen the blow. Even an advantage measured in seconds could save lives in an evacuation.

If maintaining infrastructure in an urban environment presents a challenge, imagine the disruptions caused when a hurricane hits a coastal city and roads are washed away, a water main breaks, a gas line leaks or an underground power substation is flooded. Suddenly, access to a dangerous gas leak is blocked. A loss of power leads a hospital to evacuate its patients. Flooding contaminates drinking water.

New York City experienced all of these impacts simultaneously when it was struck by Hurricane Sandy in 2012. With more extreme weather forecast for the decades ahead, and sea level expected to rise as the planet warms, coastal cities will need to actively manage such risks. Recent, deadly and destructive tsunamis in Southeast Asia underscore this point. Inland cities will face their own set of challenges.

It’s not difficult to imagine IoT-related models, based on real-world data, providing an advantage in preparing for extreme weather events. For instance, power utilities typically call in out-of-state crews and marshal their resources in the face of an impending storm. If they were able to pre-position crews inside areas likely to be hardest hit, power restoration might be swifter. Or utility officials might pre-emptively take a section of the grid down to help isolate expected damage, as New York City’s Consolidated Edison did in Hurricane Sandy.

Obviously, the sensors and data and communication networks that will enable sustainability and resiliency will themselves have to be strategically designed, located and maintained so that IoT applications continue to deliver useful insights during the very emergencies they’re intended to mitigate. Smart buildings, for instance, might have motion- and/or life-detecting sensors that could aid evacuations or guide incoming public safety personnel to trouble spots or safe havens.

Thus, IoT might markedly improve familiar responses or it might yield new insights and inform entirely new ways of optimizing infrastructure and mitigate damage to a city’s foundations.


Of course, the implementation of IoT applications to our cities will require coordination and cooperation among many different entities in the public and private sectors, so inevitably it will take root differently in different societies.

In the United States the market may be the driver as cities compete to attract the most productive people and businesses. New York City may find it necessary to apply IoT-related applications to guard against catastrophic sea surges and their impact on infrastructure. In China, in contrast, a top-down centrally planned and run city and economy could rival a free market approach for effectiveness. Some cities will tackle across-the-board challenges while others might attempt to address a particularly vexing issue, such as Beijing’s air pollution challenge.

By the same token, mid-sized cities may not have acute or chronic issues, but instead must meet prosaic challenges to their very existence, as urban centers compete for high-quality workers and cutting-edge businesses. Bigger isn’t necessarily better in the quest for urban adaptability. Perhaps Peoria, Illinois, will manage to compete with Chicago because it possesses less entrenched public bureaucracies and more community-minded private enterprises.

Whatever the approach, the goal will be similar. When a city is approached as a gigantic system, its various moving parts can be optimized for efficiencies and its dwellers can be aided in adapting their lifestyles to a changing environment. A generic IoT approach will use sensors, data and analytical models to produce insights into how the world behaves and, more importantly, how it will behave, to enable people and systems to be more adaptable.

Though such an approach could work anywhere, the urban environment and its inherent challenges and mounting population pressures offer a clear opportunity and compelling use case for IoT-related innovations.



Chung-Sheng LiChung-Sheng Li is currently the director of the Commercial Systems Department. He has been with IBM T.J. Watson Research Center since May 1990.

His research interests include cloud computing, security and compliance, digital library and multimedia databases, knowledge discovery and data mining, and data center networking. He has authored or coauthored more than 130 journal and conference papers and received the best paper award from IEEE Transactions on Multimedia in 2003. He is both a member of IBM Academy of Technology Leadership Team and a Fellow of the IEEE.