WiFiSLAM needs similar data to be gathered in advance inside a particular building before it can offer location fixes. A person running another special app must walk around a building a few times, entering every room at least once. Algorithms originally developed for robot navigation process the changing pattern of Wi-Fi fingerprints and footsteps to re-create the path the person covered. That trace is then manually associated with a map of the place so that WiFiSLAM can tell a user in that environment where they are.
Other technology that uses Wi-Fi to for location sensing relied on expensive additional equipment, says Atreya. “I could walk into your building and have Wi-FI location working within an hour,” he says, claiming this will allow WiFiSLAM to be rapidly adopted by many places.
Eladio Martin, a researcher at University of California, Berkeley, is part of a team developing another Wi-Fi-based location app that’s accurate to 1.5 meters. Like WiFiSLAM’s, Martin’s team uses Wi-Fi fingerprinting and needs no equipment other than a cell phone, although it is currently just an academic project.
“Public buildings and especially those related to health care are some of the main candidates for the implementation of this technology,” he says. Martin is not familiar with WiFiSLAM’s implementation, but says that academic work published by members of the company suggests they could reduce the computational load of calculating traces from Wi-Fi fingerprints, which would make the technology more scalable.
WiFiSLAM plans to deploy the technology in a number of hospitals—including Stanford hospital—as well as shopping malls. The technology will initially take the form of stand-alone apps for navigation, for example, an app provided by a particular mall. However, the technology could eventually be built into apps with more general mapping functions.