Data-Use Lessons from Smart Cities
By Dante Ricci, Lauren Gibbons Paul | 10 min read
In the United States during the COVID-19 pandemic, there were numerous reports of urbanites moving to the country. The reason was straightforward: Fewer neighbors made social distancing and, by extension, healthy living easier. Many people also learned that they could work from anywhere because their jobs did not require commuting to an office.
But the truth is that cities were never going away. More than half of the world’s people – about 55% – live in urban centers, and this majority is expected to reach close to 70% by 2050, according to the United Nations. Even during the pandemic, cities demonstrated their vitality by providing critical services at a time when officials raced to address both a healthcare crisis and resource constraints.
Cities remain economic engines, even as people in many regions have shifted to at-home and then hybrid work arrangements. Indeed, cities still provide critical infrastructure for business, says Anders Lisdorf, a Copenhagen-based consultant and author of Demystifying Smart Cities: Practical Perspectives on How Cities Can Leverage The Potential of New Technologies.
“The city is and will continue to be the space where the vast majority of business will be done,” says Lisdorf. “Cities will provide the backdrop for future business. Understanding where smart cities are going impacts the future of most businesses.”
This article highlights the work of three regional governments – Newcastle upon Tyne, UK; Heidelberg, Germany; and Chattanooga, Tennessee – to illustrate the ways in which government, academic, and business collaborations have used data to serve the needs of their constituencies on a shoestring while managing multiple stakeholders. They are role models for business leaders who are looking to do more with – and get more out of – their data. They offer lessons, including how combining existing and new data sources can derive fresh sources of value, how the use of sensor data can predict demand for services, how harvesting and analyzing location data can isolate safety hazards and mitigate public safety risks – and how data that is properly prepared for sharing and analysis can make for an ever-growing set of valuable applications.
Understanding quality-of-life measures with real-time data
The project: Newcastle upon Tyne, a city of 268,000 in the UK, developed an urban data dashboard powered by advanced analytics that helps city officials and residents understand metrics that affect residents’ health and safety, including compliance with social distancing measures.
Major benefits: The dashboard provides an accurate assessment of the population’s performance on COVID-19 safety measures along with a host of other measures, including vehicle and pedestrian movement, air quality, and wind speed measures in real time.
During the pandemic, it was crucial for cities to understand how well their citizens were complying with safety guidelines such as social distancing. But other than conventional observation, for example, reviewing CCTV footage, it was difficult to systematically gauge compliance levels. The city of Newcastle upon Tyne completed a pilot project to test if it could do just that, working with Newcastle University to provide an online data portal that shows pedestrian congestion in the city center, among other highlights.
Using a traffic light indicator system with red, green, and yellow lights, the Newcastle Urban Observatory uses advanced analytics to measure pedestrian density and to determine the pedestrians’ proximity to each other. The system strips out personally identifiable details, anonymously identifying people who maintain safe distances while flagging (in red) instances where social distancing measures are violated. During the height of the pandemic, the project team hypothesized that this insight could help public officials make evidence-based decisions, such as understanding what messages would best promote public health.
We can imagine a city where we manage traffic flows or charges for private vehicles based on things like air quality. You can start to tie those things together.
Phil James, director of the National Urban Observatory Facility, Newcastle upon Tyne, UK
Funded by several research grants from Newcastle University and in partnership with the City Council, the Urban Observatory, which is now in production, was established long before COVID-19. Its purpose was to provide city managers with a dashboard that tracked key safety performance measures through analysis of thousands of sensors and other data sources with artificial intelligence (AI) algorithms. The managers also use the dashboard to monitor movement around the city such as traffic and pedestrian flow and congestion, car park occupancy, and bus GPS trackers. It also tracks energy consumption, air quality, and noise levels.
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The Proximity Monitor helps people safely mingle in a post-pandemic world.
A key value driver for the dashboard: real-time data. The main goal for the project was to measure the impact of policy decisions (such as the recommendation to maintain social distance) in real time, says Phil James, director of the National Urban Observatory Facility and professor of Urban Data at Newcastle University. Having the data enables fundamentally new types of policies, says James. For example, if the dashboard shows congestion in the city center, the city could elect to assess pollution charges on drivers who come into town. To be clear, Newcastle upon Tyne is not doing this now – and may not ever – but having the data enables what James calls “thought experiments.”
“We can imagine a city where we manage traffic flows or charges for private vehicles based on things like air quality. You can start to tie those things together,” he says.
Key takeaway: The dashboard project sets the table for future public service improvements and improved quality of life.
Jenny Nelson, digital program manager for the city of Newcastle, believes analytics technology that observes and extrapolates from human behavior will be a pillar of future urban management because the results of analytics can drive informed policy discussions.
“Real-time data gives you the potential to create new and different types of decision-making” and to adjust as needed according to conditions, says Nelson.
Sensor data enables smart resource management
The project: Smart waste management powered by sensor data helped Heidelberg, Germany optimize trash and recycling collection as needs proved variable during the pandemic.
Major benefits: Fewer truck runs saves time, labor, and fuel consumption and reduces emissions without affecting service quality.
With 160,000 residents, Heidelberg, a city in the German state of Baden-Württemberg, is a leader at deploying digital technology to improve life for its citizens while boosting sustainability. The city’s digital spinoff, Digital-Agentur Heidelberg GmbH, features a number of projects, including more efficient trash collection driven by sensor data. Trash receptacles outfitted with sensors help city managers track the waste levels in real time through a cloud-based dashboard.
“Instead of traveling to very isolated parts of the city in the forest every second week, the [truck fleet provider can] make data-based decisions on whether to make the trip. On the other hand, we will get an early notice if containers are overflowing, which leads to a nicer cityscape and fewer citizen complaints,” says Sebastian Warkentin, managing director, Digital-Agentur. Trash collection is therefore a more efficient and eco-friendly option during a time of volatile trash needs, helping the city achieve its sustainability goals.
The smart waste-management system has significantly reduced the noise level, street congestion, and air quality for residents, says Warkentin. It also helps Heidelberg analyze and forecast future waste management needs. The system uses a host of technologies, including Internet of Things (IoT) sensors, low-power wide-area network, cloud storage, and software.
As cities slowly come back, waste management systems powered by real-time sensor data prevent the inefficiency of doing pickups in areas that have not yet come back to their previous waste levels.
The smart waste management system has significantly reduced the noise level, street congestion, and air quality for residents. It also helps the city of Heidelberg forecast future waste-management needs.
Key takeaway: Agile methodology successfully applied to data projects can lead to new opportunities.
Most business leaders don’t have to ponder the nuances of trash collection to this degree, but Heidelberg showcases how something that starts as a germ of an idea can grow in unexpected ways.
Heidelberg did not start this waste collection project with the idea that the city would end up establishing a business. Project managers used an agile methodology to experiment with what worked and what needed improvement, and they kept going. The project resulted from co-innovation development among all the providers – including software, hardware, and garbage trucks – to which every partner brought expertise and technology to be tested.
Dashboard pinpoints road crash hotspots, improving public safety
The project: To address a rise in road crashes, Tennessee’s Hamilton County built a system using multiple data sources for law enforcement to pinpoint the most crash-prone spots.
Major benefits: The resulting dashboard is able to visualize likely hotspots for vehicle collisions, enabling emergency services to position personnel to potentially respond more quickly.
Just one more sad fact about the pandemic: contrary to reasonable expectations (given that there were fewer cars on many roads), the number of fatal car crashes increased in the state of Tennessee during the shutdown period when there were fewer vehicles on the road. In fact, the number of people killed on U.S. highways rose nearly 5% in the first nine months of 2020, according to the National Highway Traffic Safety Administration. Tennessee fared worse than the national average, with a 6% rise to 1,004 traffic deaths in 2020.
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Learn how virtual testing is expanding to mitigate more risks in the real world.
Hamilton County, which includes Chattanooga, had been working since 2019 to build a sophisticated dashboard using a wealth of geographic information system (GIS) data, state crash data from the Chattanooga Department of Transportation, and other public data sources (including Dark Sky weather information) to visualize where the next crash was likely to take place. Funded by the city of Chattanooga, the project cost in the mid-six figures, and the work was done by the Center for Urban Informatics and Progress (CUIP) at the University of Tennessee-Chattanooga, according to Reid Belew, marketing manager, CUIP.
One goal was for law enforcement to use the dashboard to mitigate conditions that are ripe for car crashes, hopefully reducing actual crashes in the process, according to Jeremy Roland, a recent graduate of the CUIP. Another important goal was to enable both local law enforcement and emergency services to more efficiently allocate resources. The hypothesis, still being tested with data, is that strategically locating officers has the potential to reduce response times and improve crash victim outcomes. “This affects things like where they position their police cars for a given day, where they set patrol routes for a given day,” says Roland.
Urban areas provide business leaders with takeaways on how municipal leaders use data. That includes their development of dashboards that start with one goal and – because the data quality is strong – lead to new, valuable benefits.
The third goal for the project was to give prescriptive insights to local governments about high-incident crash sites, enabling them to make improvements in some cases that would make the locations safer. For example, Roland says analysts took a closer look at one location in northern Chattanooga with a very high concentration of crashes happening throughout the data set time span.
“It turns out that at that location, there was a utility pole that had been placed a little too close to the main roadway, often causing crashes,” Roland says. Once the officials made the connection, they were able to move the pole. They plan to track activity in the area to determine if the move correlates with fewer collisions.
Key takeaway: Pilot projects are critical to test data analytics hypotheses.
Location data is just one indicator that the project team is analyzing to measure the dashboard’s effect. Most importantly, the Chattanooga team plans to examine whether emergency response times were reduced and by how much. In the meantime, Roland and his colleagues say they have gotten a very positive reaction from the police department. The team is evaluating future uses of the data.
In spite of the pandemic, the central role that cities play in our lives, and the economic life of the regions in which we live and work, is not likely to change much. Pressed to do more with less and to work with academic and business partners, urban areas provide business leaders with takeaways on how municipal leaders use data. That includes their development of dashboards that start with one goal and – because the data quality is strong – lead to new, valuable benefits.
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