By Chip Hathaway, TerraGo; Mike Mullen, Deep Water Point; and John Torres, Guidepost Solutions

As the GEOINT Community expands beyond traditional defense and intelligence arenas, so do innovations that marry geospatial intelligence (GEOINT) technology with the Internet of Things (IoT) and cybersecurity to create smart cities and smart military bases.

A National League of Cities report, “Trends in Smart City Development,” defined a smart city as “one that has developed technological infrastructure that enables it to collect, aggregate, and analyze real-time data to improve the lives of its residents.”

Today’s smart cities embrace fully connected networks of IoT sensors and sensor nodes, smart devices, mobile applications, and social networks that generate location-based data to optimize energy efficiency, security, traffic, infrastructure, public safety, emergency response, and more. The underpinning of the network is geospatial technology that provides a framework for data collection, language for analysis and decision-making, a method for decision implementation, and a means for communication with a public that increasingly drives smart cities.

Smart cities are the next big thing in a technological continuum that has stretched more than a quarter century and looks ahead to transformation. But what makes a city smart? What does a smart city look like? Ask several practitioners and each will have a different answer, depending on personal involvement. Often the response is, “I don’t know, but I recognize it when I see it.” 

Some point to applications to find available parking spaces. Others to streetlights that vary in intensity in response to public safety needs, and snowplows strategically placed to cope with storms. Still others note the power grid. Or busses and trains that run on time, or traffic signals timed strategically with rush hours. Some stakeholders will add elements of “economic development.” Others want to include “resiliency” and “sustainability.” Still others mention automation, machine learning, or artificial intelligence (AI). More enlightened respondents point to public interaction that drives decisions and their implementation.

More properly, smart cities are about the art of the possible, limited by the budget of the practical but not by the imagination of the creative. They’re about an industry generating solutions to problems some cities didn’t know they had, and other cities believed were insoluble as merely the high price of growth. They’re about quality of life, but also increasingly about concerns of threatened privacy and fears of cybersecurity breaches that could shut down critical infrastructure and cause chaos.

Smart cities technology is being used to cope with a population migration to urban areas. The infusion of people brings increased public and private resource and amenity requirements and quality-of-life demands, as well as potential effects on climate and weather.

The United Nations reported in 2018 that 55 percent of the world’s population lives in cities, and that the percentage would rise to 68 percent by 2050. In the United States, 82.7 percent of the population lives in urban areas, and that number is expected to grow to 87.4 percent by 2050.

An estimated $80 billion was spent on smart cities in 2018, largely driven by priorities in transportation, public safety, and energy, according to International Data Corporation, which predicts expenditures will rise to $158 billion in 2022.

While the U.S. military talks of moving toward smart cities technology for bases, budgets remain focused on personnel and weaponry, with less emphasis on funding facility updates. Still, the Army uses smart energy to reduce costs up to $160 million a year. A 250-acre solar farm at Fort Stewart, Ga., provides 30 percent of the facility’s needs. Cameras and other sensors are being more closely integrated in some facilities to tighten security.

The Army plans to launch a series of pilot programs over the next 12 to 18 months to see how smart cities concepts can improve facility services, according to Lt. Gen. Gwen Bingham, assistant chief of staff for installation management. Public-private partnerships have been suggested to overcome budget issues.

The U.S., which lagged behind Europe and Asia in embracing smart city concepts, led the world in 2018 with $22 billion spent on smart cities technology, followed closely by China’s $21 billion. But the countries are spending differently. The U.S. is retrofitting mature cities with tools aimed at infrastructure and quality-of-life issues such as transportation, health, education, and safety. China is building cities with smart cities technology, addressing some of the same issues, but also with facial recognition and movement monitoring technology as part of the security apparatus. Many Americans would find those measures intrusive.

But smart cities and bases are about more than money and investment. They’re about geospatial analytics that shape the future. 

  • This article is part of USGIF’s 2019 State & Future of GEOINT Report. Download the PDF to view the report in its entirety. 

GEOINT for the Internet of Cyber Assets

When you speak with many smart cities advocates, their emphasis is on building the network “now” to enable a future in which connected devices will proliferate, bringing new data sources online that enable new services, real-time analytics, and infrastructure optimization.

Security demands will increase with the growth of smart cities networks, devices, and sensors, as well as a future that includes fleets of automatic vehicles (AVs). There were 2.1 billion machine-to-machine (M2M) connections added to an already crowded cybersphere last year, according to Cisco CEO Chuck Robbins. He also said another 27 billion M2M connections will be added in the next five years. Put simply, that’s 27 billion networked cyber assets. 

This is where geospatial intelligence (GEOINT) technology has another unique, enabling role to play. IoT cyber assets need vigilant chain of custody and location tracking during installation, commissioning, and maintenance, and, ultimately, a secure disposition. Like traditional corporate networks, smart cities networks need robust access controls and threat intelligence. Unlike traditional networks, IoT sensors represent a geographically dispersed population of network devices that can’t be housed in secure data centers. A GEOINT-enabled security framework tracks the location of all network devices to prevent the risk of physical exfiltration along with illicit network penetration. 

GEOINT, including spatial analytics, enables many of the economic benefits of today’s smart cities networks. New and broader GEOINT technology will be required to help secure those networks, and GIS practitioners with smart cities skillsets will be needed to apply that technology as part of the security process to meet the needs of the cities of tomorrow.

Beginning at the End

The path to smartness begins at its end, according to the National League of Cities: “[Before buying smart cities technology] cities should consider the outcomes they want to achieve. The most successful Smart City initiatives will be those with clear objectives that solve public problems unique to each city.”

More succinctly, said Deloitte CEO Cathy Engelbert, “Cities … have to think big but start small.”

This approach has taken time to develop. When smart cities took root in the 1990s, their champions were IBM, Cisco, and other companies that developed products sold as solutions. Smart cities scientist Boyd Cohen calls this technology-driven period “Smart Cities 1.0.” What followed was a generation of mayors and city officials who identified future issues and how technology addressed them in Smart Cities 2.0. Citizen involvement created a Smart Cities 3.0 model that is ongoing, according to Cohen.

The art of the possible became reality in the minds of an educated public eager for and demanding change. Quality of life became the product of an ecosystem built to generate solutions to questions such as:

  • Does the city want more effective public safety?
  • More efficient transit?
  • Better access to health services?
  • More reliable disaster response?
  • More efficient utilities?
  • Better schools?
  • More greenspace? Recreational facilities? An arena? A ballpark? All of the above?

With input from citizens, city administrators and urban planners learned that answers were in data that was available—at a price. Smart cities technology can be expensive, and cost often drives the scope of its implementation, making it incremental.

At their core, smart cities use a data-gathering network of IoT sensors, nodes, and software to generate data for research, and analytics to interpret the story the data tells. That data includes citizen input that often drives decision-making and implementation. Smart cities are built on government-citizen dialogue, fostered by ease of public access to the process. That dialogue runs the gamut of inputs, ranging from digital access to smart cities websites, to town halls and open council meetings, to committees that work hand-in-hand with officials.

“The way forward today is a community-driven, bottom-up approach where citizens are an integral part of designing and developing smart cities, and not a top-down policy with city leaders focusing on technology platforms alone,” said Bettina Tratz-Ryan, Research Vice President at Gartner, at a 2018 “Development of Smart Cities” symposium in Dubai.   

Smart cities data is foundationally geospatial. Both providers and consumers can foster smart growth based on geographic characteristics as part of the value of smart city investments.

For example, the citizens of Vancouver and Surrey, British Columbia, answered the call for input on the region’s application for part of a $300 million Canadian Smart Cities Challenge award for innovation. They came up with a corridor for autonomous vehicles that would eliminate crashes with cars driven by humans. The bid received $250,000 from the Canadian government for research and was short-listed for a $50 million award.

Other dialogue is fostered, for example, when a city official tells a town-hall-style audience that smart cities data will be used to bring commerce and industry to a community, then assures questioners that personally identifiable information won’t be used to create customer mailing lists.

Turning On (and Off) the Smart City Lights

Because of costs, some cities made purchases in piecemeal, believing smart cities technology to be a solution to an existing problem rather than part of a whole.

For example, New York was one of several cities to buy acoustic sensors, which detect and track gunshots. Other cities used parking technology to help drivers find available spaces. Still others used technology to plan public transit. But most technologies weren’t integrated with each other to offer a broader picture. Now cities are turning to streetlights as a step toward broader adoption of smart cities technology. Lighting is ubiquitous and generates high energy costs, and savings from smart cities technology significantly improve the bottom line.

Cities are deploying light-emitting diode (LED) bulbs and fixtures to replace more expensive sodium and mercury vapor bulbs. Even greater savings and possibilities come from networking lights for advanced controls. Using GEOINT principles, the system can be mapped to determine where maintenance is needed and to plan for future smart cities technology expansion and security. The map also becomes part of the foundation for dialogue with the public.

The lights themselves can be manipulated to be dimmer in safer neighborhoods, brighter in commercial and high-crime areas, and can be controlled seasonally to adjust to weather conditions.

Cities have saved money and lowered CO2 emissions with smart streetlight programs. Chicago, for example, expects to save $10 million annually in energy costs with a 270,000-light, four-year retrofit and the addition of intelligent controls.

Using a smaller example, the town of Richmond Hill, part of Greater Toronto, expects to save nearly $1 million annually from its implementation of 13,000 networked streetlights using Itron’s SLV smart city management platform. Kansas City, Washington, D.C., Pittsburgh, and other cities are making comparable investments.

Lighting fixtures can also host acoustic and air quality sensor nodes, and those that monitor pedestrian sidewalk use, traffic congestion, parking availability, school zone activity, weather, and other public safety and quality-of-life issues. Cities are also considering streetlight infrastructure for adding cameras, emergency response aids, smart traffic lights that can adjust timing to align with demand, and public Wi-Fi. 

Autonomous Vehicles

While surveys show public opinion of autonomous vehicles (AVs) remains mixed, investment in research accelerates. In an October 2017 report, the Brookings Institution determined 160 projects spent $80 billion on AVs from 2014 to 2017, and that as much would be spent in 2018 alone. Still, a 2018 report from Deloitte showed only a small percentage of U.S. respondents consider driverless vehicles safe, though the report also indicated a trend toward more trust when compared to earlier surveys.

In March 2018, a pedestrian was killed in a crosswalk by an Uber Volvo driving in automatic mode, and five days later the safety driver of a Tesla operating in automatic mode died when the car struck a barricade in Silicon Valley. In each case, the safety drivers were determined to be at least partly at fault.

Though many manufacturers are aiming at AV or driver-assisted AV rollouts in the next decade, there are more than 270 million manned automobiles on the road in the U.S. and weaning drivers off them is going to take time. It’s also going to mean that the human element continues to be part of traffic and autonomous vehicle research.

As AVs grow in scope and capability, smart cities can contribute to AI that can drive vehicle development. Driverless cars with sensors and algorithms that interact with smart city IoT sensors, as well as with sensors and geo-fencing, can help with autonomous navigation, updating dynamic maps that are downloaded into the vehicles. Traffic light sensors, sensors in school and construction zones, traffic flow sensors, parking availability sensors, and weather and road condition monitors offer the potential to build a “halo of safety” around autonomous vehicles.

Threat Risk Grows with Networked Devices

Even when the IoT was considered a personal amalgamation of baby monitors, garage-door openers, light switches, television remote controls, and other conveniences, there was concern about hacking. That concern has been heightened by smart city technology in which every sensor and step along the data value chain is considered a potential portal for cyberattack.

To name just a few concerns—Could a hacker take over electronic traffic control boards and light systems to create chaos? How would that that impact AVs? Could someone override sensors monitoring the water level in a reservoir to create a flood?

Could a hacker-created snarl impede first responders in an emergency? Alter the power grid? Exacerbate the impact of a weather emergency or other natural disaster?

An accidental missile alert in Hawaii on January 13, 2018, and hackers setting off 156 outdoor tornado sirens in Dallas on April 7, 2017, highlighted potential security issues. So too did the Intelligence Community’s finding that Russian-sponsored actors invaded U.S. election infrastructure in 2016, in addition to reports of foreign attempts to impact the nation’s power grid.

Those questions and actions drove researchers from IBM Security, dubbed IBM X-Force Red, and Threatcare, along with others, to probe smart cities infrastructure for vulnerabilities. Many were found, and companies that built data-gathering and processing platforms responded with patches for existing vulnerabilities and more security-conscious software development.

The result is more secure—and costly—smart cities technology and, likely, a budding related security industry to address future fears. And need for more and better geospatial technology and applications—and GIS-trained people to run them. 

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Posted by USGIF