One of the biggest challenges in applying WiFi to count and track mobile devices is to be able to do so accurately with those that are not connected to the network and that randomise (spoof) their MAC addresses. If these are not properly accounted for, we can deviate a lot from the real figures.
In fact, this is a problem that affects 95% of modern smartphones and prevents most WiFi analytics solutions from obtaining useful metrics. This behaviour causes these devices to pretend there are many more or fewer devices than there really are, by continually changing their MAC addresses to distort the data.
To make an analogy, it would be as if most cars have constantly changing number plates to fool traffic surveillance systems.
To this end, Galgus has developed our patented Fingerprint technology. A completely disruptive solution worldwide, recognised by Gartner. It creates a unique and stable fingerprint for each device, regardless of the MACs it shows and even if several devices of exactly the same type enter the analysis area.
Continuing with the analogy, it would be like building a reliable identifier for each car based on make and model, type of rims, colour, scratches, etc., without looking at the number plate as we know it is not reliable.
This is why we are able to track, locate and count devices much more reliably. We use artificial intelligence algorithms developed and patented (in Europe and the USA) by our R&D team.
Metrics with an accuracy not offered by other solutions on the market
The figures say it all: with Galgus Fingerprint we achieve 100% accuracy in the connected count and around 95% in the unconnected count, which is an order of magnitude between 8x and 12x higher than other WiFi analytics solutions, which are less than 10% accurate.
These results have been published and contrasted by the scientific community thanks to their defence at the IEEE Radio & Wireless Week conference.
These figures make it possible to produce real-time and historical metrics of high value for counting, presence detection, tracking, visitor segmentation, calculation of dwell times, heat maps, visitor funnels, recurrence, movement between areas (journey), correlation between areas, benchmarking between similar venues, etc.
This data can be compared with other available sources of information (weather, security camera, ticketing or pricing data, etc.) and exploited to improve the design and operation of the environment.
All analytics can be accessed both from our cloud dashboard and from API calls.
A wide range of applications
The applications of this technology are multiple and cross-cutting, as it can be adapted to a wide range of scenarios.
These include the ability to locate WiFi devices in real time in different environments, such as smart cities, airports, shopping centres and hotels, using only the WiFi network deployed.
All of this without requiring users to request permissions, install invasive applications, activate their GPS or Bluetooth, or use the device. They don’t even need to have the WiFi button on.
In conclusion, with the Galgus Fingerprint we have managed to break down a barrier that makes it possible to get the most out of the investment in a WiFi deployment that goes beyond providing advanced connectivity for challenging environments.
If you want to know more about this solution, we encourage you to contact our team, who will give you all the details you need to know.
