Surreptitious smartphone services quietly tracking us as we move around have gotten privacy fiends up in arms. However, academics reveal that location tracking is not all about finding ways to sell us stuff. Researchers and scientists are altruistically using the data, too.
In one case, they're using mobile device-based mobility patterns to track exposure to pollution with more accuracy.
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Those scientists, led by academics at Massachusetts Institute of Technology (MIT), say that by tracking individuals’ movements, they’ll get a better picture of how many people are being exposed to pollution—they already know where the pollution is through sensor placement. It’s the peoples’ locations that they haven’t been aware of. Not knowing it means that although they know the amount of pollution, they don’t know how many individuals are exposed to it. The aggregate smartphone locations improve the quality of the assumptions, they say.
To test their theory, the scientists took existing New York City data (from 2013) and discovered that “exposure levels to particulate matter were significantly different when the daily movement of 8.5 million people was accounted for,” the team’s press release says.
The previous calculations were wrong. In the new model, the flow of people into areas for work, and when they went home, was being taken into account, and it changed the exposure levels.
“If you want to quantify exposure, you also need to know where people are,” says Carlo Ratti, of MIT’s Department of Urban Studies and Planning, and director of MIT’s Senseable City Lab, in the release. The study took place in that lab.
Using data to determine transportation needs
In a separate study, researchers were able to gain more timely and accurate analysis of urban travel patterns from a similar kind of smartphone tracking.
In that study, scientists from MIT and the Ford Motor Company used six weeks of mobile phone data from Boston to try to figure out if cities’ transportation requirements were being met.
“The great advantage of our framework is that it learns mobility features from a large number of users, without having to ask them directly about their mobility choices,” says senior paper author Marta González, associate professor of civil and environmental engineering at MIT, in their press release.
Previously, if one needed to find out what a population’s commute movements were, you’d have to ask them—a time-consuming and labor-intensive task with intrusive questionnaires, possibly.
These research-oriented data-use models are a bit more altruistic than most of the telco-data-as-a-service (TDaaS) models, which are where phone companies sell data that ties consumers with locations. That could be a $79 billion business by 2020, experts say. It tells businesses where anonymous consumers are when they are doing things like checking out comparative prices on their phones—at a competitor, maybe. Important for marketers.
Wi-Fi breadcrumb tracing is another positive use of the smartphone that can be used to “discover human motivations, predict how individuals react to change, and where to locate simple resources, such as automated teller machines,” I quoted experts as saying in March.
In one case, a Swiss university is developing ways to track people at music festivals, and on campus through their Wi-Fi radio breadcrumbs, which will help define and gain insight on pedestrian circulation patterns.
That allows for better resource placement, such as restaurants. But economics, of course, isn’t far off. It also allows planners to find out how far a person will walk for a certain priced menu, say, compared to another.
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