Small sensors atop a fleet of garbage trucks in a garage in Cambridge, Massachusetts
From their perch on roving vehicles, these sensors can detect gas leaks, air pollution, traffic, and other issues in the urban environment. Courtesy of Senseable City Lab

A collaboration between the city and MIT’s Senseable City Lab, these sensor-equipped vehicles can detect gas leaks, potholes, and other urban hurdles across their paths.

Many smart cities collect data via fixed monitoring stations that only measure certain areas and can’t be relied upon to keep an eye on fluctuations across an entire city, or even across different sides of the street. But what if infrastructure often dismissed as a congestion-causing nuisance could help create a more nuanced data picture?

In Cambridge, Massachusetts, clunky garbage trucks are already buzzing with all sorts of sensors. Cambridge, in partnership with MIT’s Senseable City Lab, launched a program earlier this year called City Scanner that uses the city’s garbage trucks as roving information gatherers measuring variables including air pollution, infrastructure decay, and traffic.

Although drive-by sensing has been around for at least a decade, the team believes this is the first low-cost and self-sufficient sensing platform that can be easily plugged into urban vehicles. Urban sensing platforms, the team explains, are typically too bulky to install within a vehicle, and often use stationary structures to house the electronics from the elements.

In its first iteration, City Scanner has outfitted five trucks with accelerometers, air-quality sensors, infrared cameras, and wireless signal monitors. The trucks collect data on the state of the city as they ride along their designated routes and the sanitary workers collect trash. That information is transmitted via wi-fi hotspots back to the Senseable City Lab. (Eventually, the trucks might be able to send data over 4G in the event that wi-fi’s not available.)

The team’s sensors can measure air pollution, traffic congestion, gas leaks, and other urban issues from a perch atop a vehicle. (Courtesy of Senseable City Lab)

Once the data has been collected, researchers and city officials can review it to pinpoint when and where to respond to issues. Each set of collected data, such as air quality or infrastructure readings, currently sorts into separate feeds, but the researchers hope to improve the software to allow an overlay of data. So far, the team has picked up on energy leaks in buildings, as well as potholes.

During early journeys, the truck’s vibrations affected the equipment and its readings. To compensate, says the lab’s director, Carlo Ratti, the team needed to redesign the box where the sensors were stored. “Also, we learned that the thermal cameras can be made biased by hot components of the truck, such as exhaust pipe or the or emitted gases,” adds Ratti. “This learning process is part of the research.”

Ultimately, Ratti’s team hopes to roll the project out in other cities, and across different fleets. The Senseable City Lab team is already working on a more compact design to house the components, with the idea that they could be placed on top of other vehicles, like school buses.

Currently, the entire City Scanner kit is about $1,000, and includes a basic set of sensors, others that plug in as needed, and a solar panel. “This might seem a lot, but you should consider that with just a few sensors, you can scan an entire city regularly,” Ratti says.

Ratti also imagines it as a way to establish a system that allows city officials to more accurately detect abnormalities in the environment and be more responsive to them. “We live in a “smart dust” present,” says Ratti. “We have small sensors and communication technologies in our pockets, and this is simply going to continue.” Because these sensors are so small, they can easily be grouped together or swapped out to allow for many different types of data to be collected at the same time, in many areas at once. “We see the platform as a basis for engaging people and democratizing urban data,” Ratti says.

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