Better Understanding Cities with Technology
Cities are in constant motion. They’re where business flourish, people visit and social ties are built. In such a vibrant environment, the question of how to maintain roads, deliver services, unsnarl traffic, and have people co-exist is equally as constant. What makes it an even greater challenge is the solution for today’s problem might not work tomorrow. The answer rather lies in envisioning possibilities through a combination of design, science, and technology. That’s what the team at MIT’s Senseable City Lab does, and it’s what Umberto Fugiglando helps facilitate as its research manager and partnership lead.
We want to explore how technology can help us better understand cities, and how we can accelerate this by working with industries and public administrations,” he says.
Technology, though, isn’t the answer, merely a tool in the process. To reach a solution, it takes experimentation, asking questions, and hitting a problem from multiple angles. It’s not quick and it’s not a remote endeavor. It relies on local knowledge and local feedback, something that the people at the lab understand and something they implement at Senseable City labs all over the world, all to find out what’s right for that place.
Technology is a tool in the process. Solutions take experimentation, asking questions, and hitting problems from multiple angles. Solutions rely on local knowledge and local feedback
It Starts with a Question Usually, it’s some form of “What if…?”, in the hopes of answering how to use cities in different ways. A recent lab project was to look at cars and see a role for them other than pure transportation, Fugiglando says. It started in Cambridge, Massachusetts, and what researchers in the lab saw was that since automobiles are already on the street, they could be used to collect data.
Scientists went about developing modular, autonomous, solar-powered sensors that can be magnetically attached to small vehicles. The result was that air quality could be monitored and city officials could see pollution hot spots or how temperatures greatly fluctuated within a short distance.
“In the same street, you could really have the best air quality in the city and a few meters away the worst,” he says.
But they realized that the sensors could detect more, and in another project, they’ve used them to monitor tree health, which plays a significant part in mitigating temperature, humidity and climate change. Traditionally, trees are checked manually or with satellite equipment. The former takes time. Someone needs to be available to do the work, and they can’t inspect every part. The latter can be low resolution and miss parts, especially the lower trunk, the area where cars are good at seeing. The lifespan of a city tree is short, and by partnering with Carabinieri Forestali, the Italian national forest service, the hope is to test the data-gathering capabilities and detect deterioration before it’s taken hold.
“This research can really revolutionize the way we monitor and maintain all the green infrastructure that we have in the cities,” Fugiglando says.
It’s like yet another project that monitors the structural health of bridges. Similarly with trees, monitoring can be expensive and time consuming, as it relies either on visual inspections or on sensory systems that need to be physically installed on a bridge.
The lab team wondered whether something more common could be used. The answer? Cell phones, which come with an accelerometer that can sense vibration, a key element in determining structural integrity. Researchers drove back and forth across the Golden Gate Bridge in San Francisco and the Harvard Bridge in Boston, and while the initial experiment was short, the data showed that a crowd-sourcing model was effective enough to expand the project in the United States and Italy.
Fugiglando acknowledges the shortcomings. Cell phones can’t be as precise as high-tech equipment, but they’re cheaper, and he likens their usage to a doctor’s appointment. Blood pressure and temperature readings are taken first. They’re not conclusive, but the results can give an early warning sign of what might need more attention. In the bridge’s case, it might call for something like an engineer’s inspection.
The Setup Matters MIT brings experience and research, but Fugiglando says that not all projects can be based in Cambridge, because what works in Singapore doesn’t necessarily apply in Dubai or Stockholm.
Or Amsterdam. The question there was how to reinvent mobility. Researchers knew that the future was electric and autonomous, but since the city has more canals than roads, the challenge, he says, couldn’t center on the car. The ensuing project lasted for almost five years and resulted in inventing a modular, self-driving boat. It can ferry people, but the intent is to use it for public needs, like trash collection, something that wasn’t necessarily imagined at the start.
“There was a good project that we had with the city, but that triggered a broader engagement, and we decided to scale the project to a more long lasting structure that engages a broader base of stakeholders—from a project to a fully-fledged local research lab,” Fugiglando says.
That dynamic has led to establishing permanent satellite Senseable City labs in the above-mentioned places. Whatever the project, the setup allows for collaboration and for all the stakeholders to have a say in what’s working and what might work better. “In this way, we constantly have a flow of information,” he says.
It’s that collaborative effect that marks the MIT lab — a group of more than 40 people that includes architects, sociologists, economists, biologists, computer scientists and designers. With his applied mathematics background, Fugiglando can act as translator, explaining the details to executives and government officials, so whatever the solution, it fully takes into account the people who will be impacted and who should benefit.
“Cities are complex systems, and you really need to reflect that complexity in your team,” Fugiglando says. “Otherwise, the risk is treating people just as data points.”