The system uses smartphones to collect fingerprints of location data and label them automatically.
A system developed by a team of researchers at KAIST uses Wi-Fi signals to provide global indoor localisation.
The method, which makes use of numerous smartphones to collect fingerprints of location data, can be utilised in any building in the world, provided the floor plan is available and there are Wi-Fi fingerprints to collect, said Professor Dong-Soo Han of the School of Computing Intelligent Service Lab.
To accurately collect and label the location information of the Wi-Fi fingerprints, the research team analysed indoor space utilisation. This led to technology that classified indoor spaces into places used for stationary tasks (resting spaces) and spaces used to reach said places (transient spaces), and utilised separate algorithms to optimally and automatically collect location labelling data.
Figure 1: The system classifies indoor spaces into places used for resting spaces and spaces used to reach said places. (Source: KAIST)
Tthe team previously implemented a way to automatically label resting space locations from signals collected in various contexts such as homes, shops, and offices via the users’ home or office address information. Now, their latest method allows for the automatic labelling of transient space locations such as hallways, lobbies and stairs using unsupervised learning, without any additional location information. A test conducted by the researchers showed that the system is capable of accuracy up to three or four metres given enough training data. The accuracy level is comparable to technology using manually-labelled location information.
"This technology allows the easy deployment of highly accurate indoor localization systems in any building in the world. In the near future, most indoor spaces will be able to provide localisation services, just like outdoor spaces," said Han, noting that smartphone-collected Wi-Fi fingerprints have been unutilised and often discarded, but now they should be treated as invaluable resources, which create a new big data field of Wi-Fi fingerprints.
This new indoor navigation technology is likely to be valuable to Google, Apple or other global firms providing indoor positioning services globally. The technology will also be valuable for helping domestic firms provide positioning services, the researchers said.
The team's global indoor localisation system deployment technology will be added to KAIST's indoor localisation system, called KAILOS.
KAILOS was released in 2014 as KAIST’s open platform for indoor localisation service, allowing anyone in the world to add floor plans to KAILOS and collect the building’s Wi-Fi fingerprints for a universal indoor localisation service. As localisation accuracy improves in indoor environments, despite the absence of GPS signals, applications such as location-based SNS, location-based IoT and location-based O2O are expected to take off.