Researchers use WiFi to count people

Los Angeles: Researchers have demonstrated that a WiFi signal can be used to count the number of people in a given space, an advance that may one day lead to improved search-and-rescue efforts during a disaster.

"Our approach can estimate the number of people walking in an area, based on only the received power measurements of a WiFi link," said Yasamin Mostofi, a professor of electrical and computer engineering at the University of California - Santa Barbara.

This approach does not require people to carry WiFi-enabled telecommunications devices for them to be counted, Mostofi said.

To enable people-counting through WiFi, researchers put two WiFi cards at opposite ends of a target area, a roughly 70-square-metre 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 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.

The findings have 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, researchers said.

Previous work in the research lab involved imaging stationary objects/humans through walls with WiFi signals, and Mostofi plans to eventually bring the two projects together in the future.