There are over 170 companies developing technologies for indoor location positioning, enabling phones to track their locations inside malls, stores, offices, hospitals, airports and more. Not a week goes by without announcements being released of new deployments of indoor location technology. But virtually all the indoor location systems on the market have to be deployed and customized one site at a time. And deploying and customizing these systems takes a lot of time and effort.
A new technology brings the promise of changing all that, of enabling indoor location systems to work everywhere, or enabling them to be deployed in new much much more easily. SLAM stands for "simultaneous localization and mapping," basically a self-learning approach whereby a system learns about a site automatically while walking around it, and does its best to estimate locations from the start. SLAM has been around in the aeronautical and robot communities for years, and is now being implemented for mobile.
To understand how SLAM works, consider the two most common indoor location technologies already on the market. The first is called fingerprinting. In fingerprinting, a phone or laptop is used to record the Wi-Fi and Bluetooth signals at hundreds of places throughout a site. The collection of signals at any place is called the "fingerprint" for that place, in that the exact collection of signals should be slightly different at every place. Generally speaking, signals should be stronger the closer the phone is to the source of the signal (the Wi-Fi access point or the Bluetooth beacon), but signals also vary based on what objects are interfering with the signal, walls that signals can bounce off of, and many more factors. Recording fingerprints in a database enables a system, in principle, to identify a location based on the set of signals observed.