In the digital era we live in, Wi-Fi has become the heart of global connectivity, allowing more than 18 billion devices around the world to stay connected at all times.
But this technology also offers a highly valuable functionality: it is capable of providing information related to the geolocation of devices.
However, growing privacy concerns have driven the implementation of techniques that make it more difficult to collect essential data for Location Analytics services.
In response to these concerns, Galgus has developed an innovative solution that promises to revolutionize the way data from devices, including those not connected to the Wi-Fi network, is collected and analyzed.
The big challenge: How to overcome MAC address randomization?
In the mid-2010s, major mobile operating systems introduced MAC address randomization, a method that continuously changes the visible MAC address of a device when it is not connected to a Wi-Fi network.
This mechanism, designed to protect user identity and privacy, has posed a significant challenge for Wi-Fi data analytics systems, which traditionally rely on the stability of these addresses to identify and track devices.
With over 80% of devices using this randomization technique, the accuracy of data collection has drastically decreased, impacting the ability of systems to provide location-based services and device tracking.
It is in this context that Galgus has stepped forward with an innovative solution that mitigates this problem and significantly improves the accuracy of the analytics.
Galgus addresses this challenge with its own AI algorithms, delivering a unique solution in the market.
The solution developed by Galgus combines the generation of nearly unique and stable identifiers for non-connected Wi-Fi devices with advanced machine learning techniques applied to received signal strength (RSSI).
This approach is based on the inherent ability of Wi-Fi devices to announce Information Elements encapsulated in Probe Request frames, which cannot be deliberately modified by users.
Implemented directly in the access points (APs), Galgus’ system generates fingerprints from the information elements present in the frames emitted by nearby mobile devices.
These fingerprints are combined with unsupervised clustering techniques in a multidimensional RSSI space, which allows for differentiating devices even when they share similar characteristics.
The result is a significant improvement in the ability to identify and track devices, overcoming the obstacles imposed by MAC address randomization. In this way, this invention joins other patents currently being exploited by Galgus.
Real-world tests: impressive results
To validate the effectiveness of this technology, Galgus conducted experimental tests in a real-world environment, specifically on a university campus.
During these tests, multiple access points were deployed to capture the signals of non-associated devices, meaning those that were not connected to the Wi-Fi network.
The results were remarkable: the system achieved a nearly 90% accuracy in real-time counting of non-connected devices and a 98% accuracy in the total count for the experiment.
This represents a substantial improvement compared to traditional methods, which only achieve 22% accuracy.
This success demonstrates not only the viability of Galgus’ technology in real-world scenarios but also its potential to transform the way Wi-Fi device data is collected and used, enabling more accurate and effective applications across a wide range of fields.
What impact does this technology have?
The implications of this technology are profound and varied. The ability to identify and track devices with high accuracy, even in the presence of MAC address randomization, opens up new possibilities in areas such as crowd management, location-based marketing, and the optimization of smart infrastructures.
Galgus has successfully overcome a significant technical obstacle, while also paving the way for the development of more accurate services tailored to the needs of an increasingly connected world.
This advancement underscores Galgus’ commitment to innovation and the continuous improvement of Wi-Fi technologies, ensuring that their solutions not only address current challenges but also anticipate future market demands.
