How a new Wi-Fi 'localizer' could create smarter homes, safer drones

By using Wi-Fi's ability to hop channels, the system, known as Chronos, can see who's using a wireless network, potentially eliminating the need for a Wi-Fi password.

Mary Knox Merrill / The Christian Science Monitor/File
People work on computers and use Internet access in the reading room at the Boston Public Library, Copley Branch, in Boston, MA, November 17, 2009. Researchers at MIT have developed a technology that can track who is using a Wi-Fi network in an apartment or public space using measurements taken from a single access point.

Losing a signal or getting kicked off a Wi-Fi network can often be an inconvenience or a disruption.

It can even lead to theft — though of a relatively harmless variety — with 32 percent of users telling an industry trade group in 2011 that they had stolen a neighbor’s Wi-Fi in order to go online.

But instead of a desperate search, what if a Wi-Fi signal could find you instead, even in a room full of people all using the same network?

That’s the idea behind a new system developed by researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). It finds a particular user by calculating the “time-of-flight,” a measurement of how long it takes for a signal to travel from a user’s computer or phone to a single Wi-Fi source.

This number is then multiplied by the speed of light to determine the distance it takes a Wi-Fi signal to travel, with an accuracy of 0.47 nanoseconds, or less than half a billionth of a second.

The system, known as Chronos, could potentially eliminate the need for Wi-Fi passwords by automatically finding unauthorized users or allow smart home technology to automatically adapt depending on how many people are at home.

“Imagine having a system like this at home that can continuously adapt the heating and cooling depending on [the] number of people in the home and where they are,” says Dina Katabi, a professor of electrical engineering and computer science at MIT, who co-authored the paper, in a press release.

During a test in a two-bedroom apartment with four people, the researchers found that it could identify what room someone was in 94 percent of the time, while a test at a local coffee shop found users with 97 percent accuracy.

It could also make drones safer by automatically detecting whether a person is nearby using the location of their Wi-Fi device, the researchers say.

For a drone equipped with a camera, Chronos could potentially create better shots by closely following how a person moves by tracking their Wi-Fi device, says Deepak Vasisht, a researcher at CSAIL and the paper’s lead author, in an email to the Monitor.

Testing a drone indoors, they found the system could maintain a safe distance from a user with a margin of error of about 1.5 inches.

The system builds on previous efforts in Wi-Fi “localization” by using information from a single Wi-Fi access point to calculate the time-of-flight.

Previous efforts required four or five access points to make an estimate of the time-of-flight by measuring the differences in angle between the Wi-Fi receiver’s antennas and a user’s device. But that can be a challenge for small businesses such as coffee shops or stores that may only have a single Wi-Fi access point, the researchers say.

“We have been working on indoor localization for a while and at one stage, realized that if we can measure distances, in addition to the angle, we can do the localization with just one access point,” Mr. Vasisht says.

They noted that other systems that don’t use Wi-Fi, such as an ultra wideband radio that can span a gigahertz or more, can calculate the time-of-flight much more accurately than methods that used several Wi-Fi access points.

So they decided to program a Wi-Fi system to emulate the radios, which tend to be expensive.

Chronos works by moving across different frequencies, collecting a variety of distance measurements, which can be used to make a much more accurate time-of-flight calculation.

But this method had some challenges, including a delay as the system detects the presence of “packets” of Web information sent from user’s device to a Wi-Fi receiver.

To combat this issue, the MIT team made use of the fact that pieces of each packet are transmitted on several smaller frequencies that are contained within a series of Wi-Fi bands clustered around the common frequencies of 2.4 GHz and 5 GHz.

In a room full of furniture, Wi-Fi signals often bounce off objects and walls, causing a series of time delays in the various measurements. To solve this issue, the researchers used an algorithm to determine the various delays. Then, they identified the path with the smallest time-of-flight as the most direct path.

There was one further complication — every time the system hopped to a new band, the hardware resets, causing a delay known as a “phase offset.” But by using the acknowledgments a user receives when they send a piece of information through Wi-Fi, they were able to cancel out these delays.

The researchers say this localizing effect could have a number of applications, such as finding lost devices or enhancing “geofencing” technology that restricts Wi-Fi access to specific boundaries.

Security has been a large-scale concern for some users. While people will admit to stealing Wi-Fi to gain access, 40 percent of users said they were more comfortable sharing their house key than their Wi-Fi password.

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