Forget moving sidewalks and robot police. The biggest technology change in our cities will involve data, and lots of it.
By harnessing massive, often diverse information flowing from routine municipal activities (think traffic), services (such as utility grids), and reports (like police statistics), cities across the world are already running more efficiently and cost-effectively.
“(This year and next) is where we start really seeing the value of cloud in government and cities,” said Dr. Katharine Frase, CTO, IBM Public Sector. What’s more, this will be “an engine for innovation and citizen services, not just cost savings,” she said.
The latest report on smart cities from Navigant Research forecasts that annual smart city technology investment will reach $27.5 billion by 2023, with total cumulative investment over the next decade reaching almost $175 billion.
But an ongoing problem for government use of advanced analytics is a skills gap, the Navigant report noted.
“Above all, managing and analyzing large data sets and developing insights for effective policymaking or operational improvements require skills that are in short supply, particularly in the public sector,” wrote company research director Eric Woods. “Meeting the skills gap for data analytics will be a significant barrier to city innovation.”
Technology vendors have been talking about smart cities for years. But the concept seems to be taking off now, thanks to a few relatively recent developments.
IBM’s Frase believes the emergence of cloud computing has made cross-departmental IT much easier. Rather than previous attempts to build a unified “city database,” departments share their data repositories via a shared cloud service.
Just as important, government agencies are loosening their traditionally territorial grip on data.
“They are getting out of the notion that everybody should have their own data locked down in their own agency,” Frase said. Overcoming this organizational mindset makes possible cross-agency cooperation and a single view of city- or state-wide data. To allay the fears of department heads that proprietary data could slip out, software tooling can be added to extract only the “time and space” information of the record necessary for the shared scheduling application, Frase said.
A simple example of cross-agency cooperation at work is street repairs. By sharing schedules about new construction, scheduled utility maintenance, homeowner association block parties and real-time pothole reports, city planners can start doing collaborative planning. The result is that the street isn’t ripped by three different city agencies on three separate dates. This kind of efficiency saves money while pleasing residents.
Another important driver behind smart city initiatives is the Great Recession, which continues to put tremendous pressure on city, state, and federal budgets. Out of necessity, government at all levels has had to become more efficient and nimble.
At the start of this year, the City of Minneapolis began using IBM’s Smarter Cities analytics solution for a growing list of functions, including law enforcement, city code enforcement, and traffic safety.
Now, Minneapolis administrators identify landlords who are violating city codes by pulling data from multiple, formerly unlinked databases, and combining that data with citizen complaint reports.
The key to the approach is gaining insight by combining multiple data sources. For example, a study of 2013 vehicle collisions with pedestrians in the city revealed the fact that July saw a particularly high number of such incidents. Further analysis found the collision spots were popular with visitors unfamiliar with the roads and intersections.
The most ambitious example of IBM’s work in this arena is with the California Department of Technology. CalCloud is the first of its kind cloud computing model to be implemented at the state level in the United States.
Instead of separate IT systems for each department, the CalCloud service model allows government entities to share a common pool of computing resources. The five year, $37 million project, announced this summer, is being built and managed by IBM, and will start with more than 20 of the state’s 400 governmental departments.
The march toward smarter cities will be especially important for the “mega cities in Brazil, China and India,” said Enterra Solutions CEO Stephen DeAngelis. These cities, which are home to 20 to 30 million people, will need these technologies to support their quality of life, he said.
DeAngelis, whose company specializes in AI-based analytics, said energy monitoring/allocation, security, and traffic optimization are the likely first applications of these systems.
DeAngelis also sees an intersection between the goals of smarter cities and the Internet of Things (IoT), which together will spur the need for increasingly automated solutions.
“Smart cities will dwarf the volume of data that’s on the Internet today,” he said. “How do you technically process all the data? Who is going to process it, fast enough, to make decisions in minutes, not weeks or months?”
DeAngelis suggested the need for cognitive computing platforms that can, within milliseconds, optimize something, like traffic, as well as “learn from patterns to predict actions of people and things.”
But not everyone thinks real-time analytics is essential to the success of smarter cities.
“Real-time is an interesting phrase that means different things to different people,” said IBM’s Frase. In the case of smart cities, she said much can be made of human scale events, those on the order of minutes to a quarter hour. She said that a problem with real-time feeds are events that happen in fractions of a second.
“One of the technical challenges (in real-time data) is that it is also very noisy,” she said. “If you react to the noise, you may make wrong choices.”
Nor is there just one approach that fits all cities, Frase said.
“Traffic is often a place people start, in part because it is honestly predictable,” she said. However, the methods of getting the necessary data into the system can vary.
“In London, there are sensors in the road. Other places will rely on GPS. But in a place like Nairobi, with no sensors or GPS, we had a pilot project using public webcam information and a road map.” When the algorithm predicts a coming bottleneck, Nairobi traffic police are advised via their cell phones.
Smart Cities Council Guide
An early version of The Readiness Guide was introduced and beta-tested in the summer of 2013. In addition to input from more than 100 experts, the first draft was evaluated by a number of U.S. cities, including Baltimore, Dallas, Green Bay, Hartford, and Orlando.
A collection of guidelines, best practices, and more than 50 case studies, the guide also includes vendor-neutral technology recommendations on all eight of a city’s most important responsibilities: the built environment, energy, telecommunications, transportation, water and waste water, health and human services, public safety, and payments.
The guide is available for free download at www.smartcitiescouncil.com/readinessguide.
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