Indoor positioning: Crowd-sourcing and the ‘Second wave’
As we all know, GPS is perfectly fine when locating a device outdoors, but falls short when attempting to do the same indoors or in built-up urban areas, so-called urban canyons. This has meant that other technologies have also been required for locating devices indoors with Wi-Fi the most commonly utilized technology to-date – through techniques such as pattern matching (fingerprinting) or trilateration using signal strengths.
The issue with fingerprinting, with any wireless technology, is scalability. Time consuming manual surveys are required of venues; this is before considering the changeable indoor environment may need repeated re-surveying to maintain its positioning accuracy. Using signal strengths for trilateration encounters difficulties with accuracy itself, where it is just not precise enough, typically around 30 meters, to create a compelling use-case. So what’s the solution?
It’s been well publicized that Apple and Google have been ‘crowd-sourcing’ their RF databases, to aid GPS and reduce time-to-first-fix for some time. However, Google recently announced that venue owners can manually survey their venues to help provide better indoor location to Google Maps users, something that Qubulus also offers. This removes the time-consuming ‘manual’ element, improving the scalability of the solutions offered.
IC manufacturers are also getting in on the act. With CSR announcing its SiRFusion platform in November 2011, which not only cleverly amalgamates data from a number of different wireless technologies and MEMS sensors, but also crowd-sources location data which is pulled from a cloud-based system to help improve positional accuracy. Broadcom and TI have also announced indoor positioning products recently, making use of a range of wireless technologies and MEMS sensors. The increased focus on services to complement the hardware, akin in some ways to the provision of satellite location (ephemeris) data for use with GPS, is vital to improving the scalability of indoor positioning solutions, as is Google’s announcement that it would be crowd sourcing the RF environment in venues through its ‘Floor Plan Marker’ application.
This first wave of solutions utilizing multiple wireless technologies and MEMS sensors with crowd-sourced location data will provide increased indoor location accuracy and scalability, enabling compelling use-cases. As this market becomes established, and as even higher accuracy technologies become commercially available, it is expected that there will be demand for a ‘second wave’ of improved solutions; these services to improve the scalability and accuracy of current solutions are therefore vital in order to achieve this. Second wave technologies such as Nokia’s Bluetooth HAIP, and continuing enhancements to existing solutions, offer improved accuracies to enable increasingly interesting use-cases – such as product-level search and navigation, high precision proximity-based marketing, or augmented reality – for venue owners, marketers, and consumers.