Over two days this spring, he collected around 200 data points on the Princeton campus and in the surrounding area as a proof of concept for integrating visual images with sensor readings, using his friend's car and a University golf cart driven by a Facilities staff member.Īlong with adapting software to transmit and store the data, Aigbekaen used a computer vision technique called semantic image segmentation to categorize all the pixels of each image as greenery, buildings, sky or vehicles. For example, said Aigbekaen, areas near highways or busy roads that also have lots of trees may have lower carbon dioxide levels than similar spaces without vegetation, but these effects need more study. This type of monitoring is also relatively rare in developing countries, Aigbekaen noted.īy developing technology to sync images with air quality data, he hopes that future work can provide new insights into what factors lead to poor air quality, noise pollution or heat islands, as well as point to strategies to mitigate these problems. Many large cities around the world are studded with air quality monitoring stations, but these have limited ability to track dynamic, fine-scale differences in conditions tied to traffic, green space, buildings or industrial facilities. ![]() "It's hard to make decisions about cutting carbon emissions or other pollutants without the technology to monitor and measure them."Īffixed to the car with four powerful magnets was a metal box containing a suite of solar-powered sensors to measure pollution, noise, temperature and humidity-topped by a camera taking nearly 360-degree images of the car's surroundings.Īn electrical and computer engineering major with a passion for studying and improving urban spaces, Aigbekaen designed his thesis research to integrate images in new ways with air and noise pollution data, opening possibilities for investigating environmental quality at hyperlocal scales. "This kind of technology gives us new ways to understand our environment and the dynamic interactions of pollution, built spaces and transportation," said Aigbekaen. He put the technology through its proof-of-concept stage in suburban central New Jersey. By improving mobile measurements of air quality and geolocating them to sites like highways, buildings, parking lots and green spaces, Aigbekaen's research for his Princeton University senior thesis unveils critical information that could help cities become cleaner and more livable.
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