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ITH RISING PROSPERITY AND THE TRANS-formation of societies around the globe, the largest wave of urbanization ever is taking place. This migration of people from rural to urban areas is creating pressure on cities

worldwide. In 1950, there were 83 cities with more than 1 mil-lion residents. That year, the urban population of the world was 751 million, according to the United Nations. As of 2018, there were 512 such cities, and the urban population was 4.2 billion. The IEEE predicts that the urban population will reach 5 billion (about 60% of the world population) by 2030.

This surge is creating many challenges for cities as they attempt to deliver services. These challenges strain

efforts to maintain an adequate infrastructure, preserve good air and water quality, provide security, ensure mobil-ity, and keep citizens safe. Meanwhile, city dwellers expect and are becoming accustomed to higher levels of service from their cities.

Deploying Smart ApplicationsUrbanization has created urgency for a deep transforma-tion of the ways cities solve problems and for tighter inte-gration of the public and private sectors in a way that simplifies and improves people’s lives. In the end, building a smart city is about making a city better equipped to manage all of its resources and, more critically, anticipate and prevent or minimize the risks of dangerous or disas-trous events before they occur. It’s also about making that city a more comfortable and desirable place to live.

WWW

Planning the Second Generation of Smart

CitiesTechnology to handle

the pressures of urbanization.

By Itai Dadon

IMAGE LICENSED BY INGRAM PUBLISHING

Digital Object Identifier 10.1109/MELE.2019.2925729Date of publication: 4 September 2019

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Much of the infrastructure required to create a smart city is in place in a fast-growing number of cities around the world, and leading cities have deployed what they consider to be applications with the highest returns on investment (ROIs) in terms of efficiencies and safety (Figure 1). Other cities are moving ahead from this incip-ient stage, with growth paths charted by the numbers and types of applications they plan to deploy. Now, inno-vators are shaping new plans for what smart cities can become as they evolve and mature.

The Second-Generation Smart CityThe smart city industry is projected to constitute a US$400 billion market by 2020, according to TechRepub-lic. The U.K.’s Economic and Social Research Council

predicts that smart city revenue will reach US$88.7 bil-lion by 2025.

Technology adoption has driven the pace of smart city development. Now, two forces—a surge in data from net-worked devices and the proliferation of the Internet of Things (IoT)—is ushering in a second generation of smart cities. The monumental growth in data over just a few years is powering a wave of new applications.

The IoT enables ubiquitous sensing and new net-work infrastructures. The growth of the smart city is a macrolevel move to manage every aspect of cities and to do so in real time. This transition means shedding manual, disconnected systems in favor of automated, connected systems in virtually every industry and municipal environment.

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“It started with ‘every company is a technology compa-ny,’ moved to ‘every business is a digital business,’ and now I think we’re at ‘every industry is an Internet of Things industry,’” said Leon Hounshell, a member of the Forbes Technology Council, in a recent article in Forbes.

The ChallengeThere’s growing recognition that the technology cities implement must be based on cost-effective and field-proven standards. City planners agree that the tech-nology must be future-proofed to the extent it can be, with the awareness that what lies ahead is uncer-tain and that municipal populations may grow faster than projected.

PlatformsThe network platform and the connectivity it provides form the foundation for any smart city. Cities have mul-tiple options, making the task of choosing the appropri-ate platform a challenge. Cities can deploy multiple, single-use platforms, as they already do for voice and data. But building and managing multiple networks also multiply costs. That approach can add complexity to network operations, in part because interoperability of the networks is almost always a concern. However, with the IoT, a single network platform can support multiple applications, which can lower the cost of connecting and speed integration.

A safe option for cities is to choose a flexible network architecture, one that can incorporate multiple transports and technologies. This means not just a wireless smart utility network or a cellular network or a Bluetooth Low Energy network, but any of these in combination.

Sensors and ConnectivityAs technology matures, cities are laying the groundwork for the first phase of the transformation, the infrastruc-ture. Advanced sensors can be deployed everywhere using multiple technologies and connecting via innovative net-works reliably and securely. Different types of applications require different types of sensors for collecting data from the environment, and those sensors are connected directly or indirectly to IoT networks.

Types of SensorsSensors are essentially data collectors, and their type, breadth, and precision will play important roles in deter-mining just how valuable the data they collect will be to city planners (Figure 2). Today’s sensors fall into the follow-ing broad categories:

xx temperature sensors: for measuring heat generated by an object or from the surrounding areaxx humidity sensors: for measuring the amount of water vapor in the airxx motion sensors: for detecting motion in the surround-ing area (typically used for security)

Figure 1. Much of the infrastructure for smart cities is already in place.

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xx gas sensors: for detecting gas leaksxx air-quality sensors: for detecting and measuring the amount of smoke or particulate matter in the sur-rounding areaxx pressure sensors: for detecting and measuring pressure in systems and devicesxx image sensors: for capturing images xx accelerometer sensors: for detecting the motion, orien-tation, or positioning of an object and also for detect-ing shocks and vibrationsxx infrared sensors: for measuring heat emitted by objectsxx proximity sensors: for detecting the presence or absence of a nearby object without making any physi-cal contact.

Smart City SolutionsThe creation a new generation of smart cities will require the coordination of these elements: a resilient infrastruc-ture served by a reliable supply of energy, technologies that ensure fast and efficient mobility, networks that enhance safety and security, and a range of convenient and useful digital services (Figure 3).

Resilient Infrastructure and Reliable EnergyThese following applications will help cities reach opera-tional and environmental goals (Figure 4).

Smart StreetlightsSmart streetlights are often the first smart technology to be deployed in urban areas. That’s because they save a sig-nificant amount of energy and enhance safety for city dwellers. Streetlight intensity can be adjusted automati-cally as sunset and dawn approach, and on/off patterns can change dynamically when an emergency vehicle approaches to give that vehicle priority.

Smart Energy MeteringSmart meters are designed to monitor energy usage in small increments. This capability enables utilities to price consumption differently according to the season or at different times of the day. Customers are thus motivated to reduce energy consumption and lower energy costs. For example, some utilities lower costs for electricity or gas consumed after midnight, which encourages customers to schedule washing dishes or clothes during those hours. Utilities benefit by reducing loads on the power grid during peak energy consump-tion times.

Water-Quality SensingWater-quality sensing, often applied to ground water, typ-ically uses a network of sensors placed at ground level, a mechanism for measuring water quality, and communi-cations to alert personnel of an impending risk or current

Figure 2. Sensors are driving data collection. They automate the management of light intensity, on/off state, and other conditions, helping cit-ies safeguard citizens and reduce their own carbon footprint.

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danger. Water-quality sensing can detect the presence of oil, waste, or fuel spillage, which may spread through sur-face-water runoff. If surface water is polluted, real-time alerts can minimize environmental damage.

Air-Quality SensingTechnology for sensing air quality is used to detect air pol-lution over large areas or in specific locations. Distributed sensors measure such gases as ozone, carbon dioxide, and nitrogen. Some sensors measure particulates in the air.

Today, with this technology, cities can even collect data that show how air pollution has changed over time. Cities can also send out alerts when, for example, there is a high concentration of pollutants in a certain area.

Electric Vehicle ChargingAs urban areas grow and electric vehicles (EVs) become more popular, cities will need to put in place a well-planned grid of EV charging stations throughout the urban area. The distance between any two charging stations must be less than the range of popular EVs. Today’s level-2 EV charging stations are an improvement over their predecessors and offer methods for accepting cashless payments.

Smart Waste ManagementSmart waste collection is helping municipalities mon-itor levels of waste and optimize collection routes, enabling cities to reach sustainability objectives, improve services for residents, and reduce operational costs. Systems for waste collection can monitor fill levels, temperature, and tilt within waste containers. Such systems also transmit the resulting data and incorporate data analysis.

Intelligent TransportationUsing intelligent transportation systems, city planners can apply technologies for sensing, analyzing, controlling, and communicating to ease congestion, enhance road safety, and save lives. These systems monitor traffic and apply

Smart StreetLights

SmartMeters

SmartParking

WeatherSensors

SolarInverters

DigitalSignage

Waterand GasMetering

ITSSystems

EVCharging

IPCameras

WasteManagement

AcousticSensors

Figure 3. The variety and scope of smart city applications. As cities evolve, many deploy applications in phases, focusing first on those with the greatest urgency or those that will deliver the highest value for citizens and visitors. ITS: intelligent transportation system; IP: Internet Protocol.

Figure 4. A representation of smart city applications related to streetlights, EVs, and waste management.

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measures to ease traffic congestion, while also improving the efficiency of such activities as collecting tolls and dis-patching information to travelers. Intelligent transportation can also help reduce the number traffic accidents, lower levels of pollution, and moderate traffic jams (Figure 5).

Smart ParkingParking in dense urban areas is a challenge. One study found that approximately 30% of traffic congestion in the United States comes from drivers searching for a parking space. Today, smart parking solutions are designed to use a sensor in each parking space to detect the presence or absence of a vehicle in the space. Systems can use those data to direct drivers to the nearest parking space and provide information on parking prices.

Smart parking also benefits from the use of intelligence to manage traffic at intersections. These intersections consist of interconnected traffic lights that are also connected to a cen-tral network. Information can be gathered at the intersection on types of vehicles on the road and current traffic patterns.

Smart Traffic SignalingCities benefit by capturing real-time data on the flow of traf-fic. Sensors on roads, together with in-vehicle sensors, can adjust traffic signals to reduce congestion. Smart signaling is also used to give priority to emergency vehicles and to find and suggest the best routes. In addition, smart signaling can extend green signals for cyclists or pedestrians to ensure that they can cross a street safely (Figure 6).

Artificial intelligence (AI) is now being tested for its ability to predict traffic flow and patterns. It is also being developed to provide alerts, such as information about traffic or safety during large city events or when harsh weather conditions are expected.

Public Safety and SecurityFor most applications related to public safety and security, a quick response is essential.

Gunshot DetectionA gunshot detection system or gunfire locator uses acoustic or optical sensors to detect and convey the location of shots from guns or other weapons. This same acoustic sensing technology can identify the sounds of incidents such as a car accident. Sensors can also detect location in real time, alerting law enforcement agencies, which can then send nearby police officers to that location rapidly (Figure 7).

If a city has a gunshot detection system, it must also be able to automatically alert people. This alert could be programmed to run on all roadway displays within a five-mile radius of the location of the gunshot, directing citi-zens to stay indoors or avoid the area.

Pollution DetectionDetecting the many contributors to pollution involves measuring such factors as emissions, pollen levels,

weather conditions, humidity, water quality, and tem-perature. The IoT and AI are making it possible to combine such measurements with historical data to spot trends.

Figure 5. A representation of smart city applications related to park-ing and traffic signaling.

Figure 6. Sensors placed in high-traffic areas smooth traffic flow and provide additional safety for pedestrians.

Figure 7. A representation of sensors on streetlights. Such sensors can be used to detect and identify the origin of gunshots.

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Radiation DetectionRadiation monitors detect and alert a city to nuclear radia-tion in real time. Some monitors, often called radiation por-tal monitors (RPMs), can detect radiation on moving sources, such as people and vehicles. RPMs are especially valuable at ports of entry and private facilities where the detection of radiation could minimize or eliminate the risk of injury or loss.

Gas-Leak DetectionGas-leak detection systems are used to detect the presence of noxious gases. As with other smart city systems or appli-cations, gas-leak detection technology relies on sensors, often connected wirelessly, to pinpoint the source of leaks.

Intrusion DetectionAn intrusion-detection system (IDS) is a security system that works in tandem with IoT devices or applications mainly in the network layer of an IoT system. An IDS can analyze packets of data and respond in real time.

To guard against distributed denial of service and bot-net attacks, city IT departments should also deploy net-work-monitoring and intrusion-detection measures that can determine when botnets are attempting to connect with known command-and-control servers. An IDS can detect whether compromised workstations are scanning the network for vulnerabilities, for example.

Digital ServicesDigital services are those that connect, inform, and alert citizens about available city services as well as explain how they can take advantage of them (Figure 8). Applica-tions include digital kiosks and public Wi-Fi.

Digital KiosksA digital kiosk is essentially a computer system with a dis-play and specialized hardware and software that provides access to information and applications related to shop-ping, entertainment, education, public services, personal safety, and emergency services.

Digital kiosks, typically placed in city centers or any location where crowds gather, give passersby easy access

to information (Figure 9). A kiosk can also serve as a con-cierge and a gathering place.

Public Wi-FiPublic Wi-Fi refers to the availability of wireless service made freely available within a specific location. Many cit-ies provide free Wi-Fi in specific sites within the city to anyone within range of a Wi-Fi hub.

The Contribution of AIA hallmark of the second-generation smart city is tech-nology that enables urban planners, administrators, and incident-response teams to see or anticipate events or spot patterns that presage events, thereby leaving time to mitigate issues or prevent situations that could be dan-gerous or disastrous. AI is already on the cusp of shaping decisions related to what-if scenarios. That’s because today’s planners are more adept than ever at gathering real-time data and combining those data with the capa-bilities of AI. They can gain rich insights into what they can do to improve the city—whether to choose from potential options or to make a “go, no-go” decision before expending capital budgets and work on options that would likely prove in the end to be unwise or impractical.

Many technologies used in the smart city ecosystem, such as networks, sensors, and the IoT itself, are maturing fast. But AI and its counterpart, machine learning, are just now being adopted to improve the sophistication of ser-vices that create smart cities.

As an example, AI can be applied to predict, based on what happened today, what is likely to happen in a simi-lar circumstance later on if, for example, people drive or take rapid transit from the suburbs to attend a sporting event. City planners can then use that foresight to better channel traffic, set speed limits, manage parking, create additional temporary parking, or find another solution. But, today, we are just touching the surface of what AI will bring in the second generation of the smart city.

Many industry watchers are signaling caution in the deployment of AI as it matures. Panelists at a Brookings Institution event in February 2019 agreed that planners must roll out AI in “a secure and responsible manner” rather than striving to create “the first tech adopters on the block.” Hence, adopters of AI must take a studied approach to AI rollouts, due in part to the evolutionary state of AI. The same cannot be said about the infrastructures or applications in which to deploy AI; those are plentiful, and they can only gain and deliver a huge ROI once they become “AI-infused.”

The first phases—building networks, developing sen-sors, determining where to place those sensors, and generating data from them—are complete. In that sense, nothing is holding back AI. It’s ready for prime time. The second phase is to collect data to feed AI algorithms.

The many potential applications across the smart city underscore the need to accelerate the adoption of AI. For exam-ple, consider the use of cameras. According to research by

Figure 8. An illustration symbolizing digital services offered in smart cities.

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Nvidia, 1 billion cameras will be deployed on infrastructure, commercial buildings, and government property by 2020. Those cameras will collect massive amounts of data, far more than humans can analyze without the support of AI (Figure 10).

AI in Traffic Management and PlanningOne AI-based application is built around a neural network that runs on an IoT edge router. Using information from cameras and traffic lights at the intersection, it’s possible to predict in real time when the traffic lights will change from green to red or from red to green. Traffic data can also be used to improve light timing and predict “exit routes” to move people out of or through the city faster.

Today, with smart cameras and radar in place, plan-ners can learn not only how many vehicles are on the road but also the types of vehicles and the specific lanes they occupy. They can then push that information and offer alternative routes to, for example, emergency responders, delivery trucks, and ride-sharing vehicles.

Planners can add an AI layer to the application to cre-ate various simulation engines and can then develop sim-ulations. They could, for example, study how traffic would be affected if a car lane were converted into a lane for cyclists or how rerouting some traffic to the new bike lane would relieve overall traffic congestion.

AI in Air QualityToday air-quality sensors, guided by AI, are already deployed in smart cities. As soon as sensors detect

pollution, the AI engine reverse-engineers the data from multiple sensors and, after taking into consideration such factors as wind, temperature, and humidity, identifies the source of the pollution. That source, perhaps a manufac-turing plant, can then be quickly shut down, heading off the need for an evacuation alert.

AI can also be used to predict how fast and where pol-lution spreads. Authorities can push alerts to people in the city who are most at risk: senior citizens, families with children, or people with respiratory conditions.

Smart City Profiles

CopenhagenCopenhagen is in the vanguard of smart cities, having ini-tially adopted a high-ROI application, smart streetlights,

Figure 9. A digital kiosk is an example of smart city technology delivering information in public spaces.

Figure 10. AI will be essential for interpreting the vast amount of data collected in smart cities.

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to make travel safer for drivers and cyclists (Figure 11). Copenhagen’s smart lighting system enables remote lighting management and control, and city officials are projecting that the system will ultimately encompass 20,000 networked streetlights, leading to improved energy efficiency, lower operational costs, and enhanced public safety. Nearly half of commutes in Copenhagen are by bicycle, making smart lighting a critical element of the city’s efforts to guarantee the well-being of all its citizens.

Today, planners dim the lights 20–30% at night and, in real time, increase illumination as soon as sensors detect an approaching cyclist. The city has achieved energy savings of 76% with the new lighting system, which instantly alerts lighting administrators to outag-es. The network also fuses intersection-based occupan-cy sensors with light controls to provide additional illumination at intersections when a cyclist or pedestri-an is approaching.

One of the city’s current projects is to deploy road-con-dition sensors to determine when or if it’s necessary to sand or salt roads. Planners are acutely aware that sand-ing and salting increase the carbon footprint, and they are dedicated to minimizing or eliminating sanding or salting if such measures are not required.

GlasgowGlasgow is one of the world’s top sporting cities and a major destination for conferences and concerts. Many thousands of people visit the city throughout the year to

take part in its various events. However, this influx brings significant challenges in terms of getting people safely to their destination. The influx also affects the lives of resi-dents and the business community by putting pressure on the public transport system and its ability to connect to retail destinations.

To strengthen its position as a top international desti-nation, Glasgow is looking at how it can best manage large-scale events and the safety of large numbers of visitors and ensure that their experience and those of the city’s residents and businesses will remain positive.

To achieve this goal, Glasgow is participating in the Itron Smart City Challenge and has invited IoT develop-ers to create services and products that help improve the experience for residents and visitors during high-traffic events (Figure 12). Leveraging the city’s Itron IoT network, developers could offer, for example, transport services to reduce congestion and streamline travel to and from major events and venues. Winners will be announced this summer.

SustainabilityFor cities to be sustainable, an infrastructure must be in place to ensure connectedness among devices and systems. Technology is also needed—via designers, planners, agencies, and citizens—to make the city “self-aware.” To become self-aware, a city needs actionable data to promote growth, provide smart services, and improve operations.

Figure 11. Copenhagen is among the world’s leading smart cities.

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According to an April 2018 study by the Economic and Social Research Council, technology transformation is driving business-friendly environments and citizen-cen-tric service delivery. The potential for using what the council calls “urban data” for increasing sustainability remains untapped.

Let’s look at two initiatives and what those initiatives are striving to achieve, and have already achieved, in pur-suit of sustainability.

Panasonic InitiativeIn collaboration with Japanese entities, Panasonic chose neighboring cities outside Tokyo and transformed them with the latest smart city technology. They then measured how the improvements have affected the quality of life of the citizens.

Many cities have a range of data-based metrics and current data. These might be related to, for example, air quality, commute times, education needs, and health-care needs. According to Panasonic, the chief question now is “Do measures we have taken translate into greater happi-ness and improved quality of life?”

A critical component of Panasonic’s Town Development Concept is a set of targets for this smart city, including numerical goals, for example, a 40% reduction of CO2 emissions (in comparison with levels in the fiscal year ended 31 March 2006) and usage rates of 30% or higher for new sources of energy. Notably, the Town Development Concept also stipulates rules for managing the town’s landscapes and design.

C40 CitiesC40 Cities is a global coalition that measures the sus-tainability of the top 40 cities in the world. The coali-tion, whose members are representatives of those cities, is committed to reducing greenhouse gas emissions and climate risk through the implementation of mea-surable, replicable, and sustainable climate-related poli-cies and programs.

C40 Cities has developed the Deadline 2020 Program to support all its members in developing and delivering ambitious plans aligned with the 1.5 ˚C “pathway” (i.e., limiting the increase in global average temperature to 1.5 ˚C) established by the Paris Agreement. The program also monitors member cities to ensure that they develop inte-grated climate action plans detailing both ambitious miti-gation and adaptation commitments.

In September 2018, C40 Cities reported that “27 cities across the globe, home to 54 million people, have already reached their peak greenhouse gas levels and are now seeing emissions fall an average 2% per year.”

C40 also reported that 27 cities in its analysis, including Barcelona, Berlin, Paris, New York City, and Sydney, have seen their emissions fall from a peak in 2012. C40 Cities reports that, if cities take a step forward in sustainability, it will have a tremendous impact on the “global picture” of

climate change. Program officials noted that “the world’s leading scientists have calculated that global greenhouse gas emissions should peak at the latest by 2020 and sub-sequently sharply drop.”

ConclusionsThe grand vision of smart cities is a self-awareness that will enable people to move with a high degree of efficiency and safety, while enjoying the benefits of AI acting on unprecedented amounts of data (the defining characteris-tics of the second-generation smart city) to promote per-sonal safety and security, better health, and the greater economic growth that come with progress and innovation.

The good news is that, by and large, vital technologies are maturing and will usher in improvements needed to help make life in cities something to be cherished. AI is ready to be tapped. Devices that produce data, the sensors that col-lect and measure those data, and the IoT network itself will make the second generation of the smart city a reality.

For Further ReadingU. Sengupta et al., “Sustainable smart cities: Applying com-plexity science to achieve urban sustainability,” United Nations University, Tokyo, 2017. [Online]. Available: http://col lections.unu.edu/view/UNU:6393

Itron, “Itron resourcefulness report: An analysis of inter-national energy and water trends,” Liberty Lake, Washington, 2018. [Online]. Available: https://itron.com/de/resources-page/resourcefulness-report

Economic & Social Research Council, “Smart cities and sustainability,” Swindon, U.K., 2018. [Online]. Available: https://esrc.ukri.org/files/news-events-and-publications/evidence-briefings/smart-cities-and-sustainability/

GuideStar, “C40 Cities Climate Leadership Group,” [Online]. Available: https://www.guidestar.org/profile/ 90-0634376

New China, “27 world biggest cities reach peak of green-house gas emissions,” 2018. [Online]. Available: http://www .xinhuanet.com/english/2018-09/15/c_137468474.htm

Smartcity Press, “Artificial intelligence: The evolving brain of smart cities,” 2017. [Online]. Available: https://www.smart city.press/artificial-intelligence-in-smart-cities/

BiographyItai Dadon (Itai.Dadon@itron.com) is with Itron, Liberty Lake, Washington.

Figure 12. Glasgow is participating in the Itron Smart City Challenge.

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