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Researchers demonstrate ability to count people using WiFi

09 June 2015

UCSB researchers use a common wireless signal to count the number of people in a designated space without relying on them to carry personal devices.

Researchers working in UCSB professor Yasamin Mostofi's lab use WiFi to count the number of people in a given space

Researchers working in Professor Yasamin Mostofi’s lab at the University of California Santa Barbara (UCSB) are proving that wireless signals can do more than provide Internet access. They have demonstrated that a WiFi signal can be used to count the number of people in a given space, leading to diverse applications, from energy efficiency to search-and-rescue.

“Our approach can estimate the number of people walking in an area, based on only the received power measurements of a WiFi link,” says Professor Mostofi. This approach does not require people to carry WiFi-enabled telecommunications devices for them to be counted.

To demonstrate their people-counting technique, the researchers put two WiFi cards at opposite ends of a target area, a roughly 70m2 space. Using only the received power measurements of the link between the two cards, their approach can estimate the number of people walking in that area.

So far, they have successfully tested with up to, and including, nine people in both indoor and outdoor settings.

“This is about counting walking people, which is very challenging,” says Mostofi. “Counting this many people in such a small area with only WiFi power measurements of one link is a hard problem, and the main motivation for this work.”

This people-counting method relies in large part on the changes of the received wireless signal, according to the researchers. The presence of people attenuates the signal in the direct line of sight between the WiFi cards if a person crosses the line of sight, and human bodies also scatter the signal — resulting in a phenomenon called multi-path fading — when they are not in the direct line of sight path.

By developing a probabilistic mathematical framework based on these two key phenomena, the researchers have then proposed a way of estimating the number of people walking in the space.

With the near-ubiquity of WiFi in many settings, the researchers’ findings have the potential for many diverse applications. For instance, the ability to estimate the number of people in a given space could be used in smart homes and buildings, so air conditioning and heating could be adjusted according to the level of occupancy.

Security and search-and-rescue operations could also take advantage of occupancy estimation. Previous work in the research lab involved imaging stationary objects/humans through walls with WiFi signals, and Mostofi plans to bring the two projects together in the future.


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