Sensing Urban Change

Cities turn to the Internet of Things (IoT).


  • London and Dublin are deploying networked sensors as part of an effort to make themselves more livable and better prepared for the future

  • These cities are some of the first places to test how to efficiently deploy IoT systems city-wide

  • Smart cities projects point the way for understanding sensor applications and the power of IoT, and more



Four days a week, Duncan Wilson rides his white Ducati 899 motorcycle through 8 miles of bumper-to-bonnet London traffic to his office at Imperial College. As he passes Hyde Park, a sensor mounted on a utility box just inside Victoria Gate detects levels of nitrogen oxides, sulfur oxides, and particulate matter. It’s one of nearly 80 such devices recently deployed throughout London to help the city identify its most polluted areas, or black spots, and better grasp how to combat smog.

“If we think about the black spots, they’re all based around major intersections and traffic routes,” says Wilson, an Intel research director leading the project, called Sensing London. “We’re monitoring parks to make the case for preserving this green space.”

Sensing London, a collaboration between the Intel Collaborative Research Institute for Sustainable Connected Cities, Imperial College, University College, the Future Cities Catapult, and members of London city council, is one of many efforts around the globe using the Internet of Things to deal with issues like climate change and stretched resources. These projects range from grassroots efforts to huge undertakings between government, corporate, academic, and civic groups.

In Barcelona, sensors in waste bins alert trash collection services when they’re full. At the Port of San Diego, engineers have deployed sensors in an HVAC system to help reduce energy use and prepare for tightening state regulations.

The common thread among smart-city projects is the principle that data—and insights from data—can lead to better ideas, decisions, and results.

In one month, we had a program set up.

Duncan Wilson, Intel research director

London Air

London, which sprawls across 607 square miles, has nearly 2.5 million cars and trucks on its roads. More than 30 percent of these vehicles are fueled by diesel, which releases far more nitrogen dioxide and particulate matter than vehicles running on unleaded gasoline. These pollutants, some of which were recently measured at higher levels in London than in Beijing, were linked to 9,500 premature deaths in London in 2010.

Monitoring London’s air in its entirety is, for the time being, impossible. So Sensing London decided to focus on three strategic locations in addition to Hyde Park: Tower Bridge, where cars idle for several minutes three times a day, as the bridge is raised for ships to pass; Elephant and Castle, where researchers are studying a nitrogen oxides-absorbing paint; and the Northern borough of Enfield, which is sandwiched between two old and overwhelmed highways.

For the Enfield portion, “In one month, we had a program The sensors capture data that an on-site system-on-a-chip gateway processes in real time. The gateway then sends the data to the cloud, which provides flexible and scalable processing infrastructure for applications that transform numbers into meaningful, actionable information.

It’s not without complications, however. The placement of the sensor and its casing, temperature, humidity, and wind are among many things that can lead to inaccurate data.

To help compensate, the ICRI team calibrated its sensors with London’s three high-fidelity air quality stations. Algorithms added to those gateways helped align the numbers.

“We’ve been learning a lot about the performance of electrochemical sensors themselves, and we’ve been updating the algorithms used to process the data,” Wilson says. “While one approach to IoT is to send data right to the cloud, we’re also investigating at-the-edge processing, where we send the transformed data to the cloud.”

The advantage of cutting the noise from the captured data, Wilson says, is that the cloud doesn’t get filled with meaningless data. It’s filtered out before it leaves the gateway processor.