R&D Projects
ARGOS: Analytics, prediction, and passive crowd control using WiFi technology.
Technological innovation project of the R&D Department of Galgus.
Improvement of data processing technologies in a network of coordinated WiFi nodes to collect anonymous data from nearby mobile devices without requiring the installation of an application.
Call for proposals.
Call for proposals 2020 for grants in the development of technological solutions based on artificial intelligence and other digital enabling technologies C007/20-ED.
Duration.
1 year
Project budget.
341.560€
Grant awarded.
153.702€
The main objective of the ARGOS project is the development and functional improvement of technologies for massive data processing in a network of coordinated WiFi nodes. The project aims to collect anonymized data from mobile devices passing near these nodes without the need for installing an application. Additionally, the collected data is processed in the cloud for interpretation and application in various business logics, such as security, surveillance, marketing, and studies.
The final outcome will allow for the localization and counting of individuals for various business applications, such as generating real-time heat maps, setting up alerts, defining boundaries, predicting crowd dynamics, and analyzing crowds in high-density environments (football stadiums, airports, train stations, universities, supermarkets, etc).
The major technical and competitive advantage over other analytics technologies is based on:
- No user collaboration is required. Galgus’ technology does not rely on the installation of mobile applications or access to GPS. Users with their mobile phones simply need to be near the WiFi node network in the areas of interest. Galgus’ technology can detect the periodic signals emitted by mobile devices and process them. It is not necessary for users to have their WiFi enabled, although if they do, information can be collected more frequently.
- Data capture does not contain personal information, ensuring compliance with data protection laws (LOPD and GDPR) by anonymizing the data before uploading it to the cloud. The collected data cannot be linked to personal information.
The proposed technological solution is a low-cost system for counting, analytics, profiling, and prediction of crowd dynamics in events and massive spaces. This is achieved through the use of robust, reliable, and affordable technology for processing massive data collected from WiFi access points, providing contextual intelligence (events in space and time) that is crucial in massive events without being invasive or undermining citizens’ privacy.
ARGOS arises from a real market need to control and predict people’s movements. To meet this demand, there are multiple solutions available, but none that do not require the collaboration of individuals with the system. This detail is more necessary than ever to safeguard people’s privacy and increase the system’s reliability and accuracy, as it is not necessary for each individual to install apps or turn on their GPS or communication systems on their mobile devices. With the technology that Galgus aims to demonstrate within this project, it will be sufficient for individuals to pass near our nodes (with their smartphone in their pocket, for example).
The unique and differentiating features of our project are:
- Based on WiFi technology: Our systems are built on WiFi technology, which is at the core of Galgus’ activity and allows us to develop innovative systems that go beyond simply providing internet access to devices.
- Based on widely adopted and more cost-effective technology than alternatives: There are nearly 20 billion WiFi devices in the world, more than the number of people. This makes the crowd dynamics system much more affordable than any image-based alternative.
- Cloud-based control tool accessible from any device and location: We provide a cloud-based dashboard (control center) where administrators can monitor and analyze the entire state of the event/area, as well as profile and predict crowd movements in order to improve their security, marketing, surveillance, and research actions, among others.
- Pre-processing capability in access points to preserve privacy: The access points themselves can pre-process information (following the edge computing paradigm) and only upload anonymized, aggregated, and cleaned data to the cloud for the network owner to leverage.
- Compatible with a wide range of WiFi access points: It is crucial for the system to work with a wide range of WiFi devices, including both low-cost and Tier 1 and Tier 2 devices, so that customers can choose the ones that best suit their needs. Optimization of data collection algorithms is essential for minimizing energy and resource consumption (processor, memory, and radios).
- GDPR compliance without requiring user consent: We ensure compliance with the recent General Data Protection Regulation (GDPR), as well as national data protection regulations. Users’ privacy and anonymity are guaranteed.
- Solution based on standards: The proposed solution is 100% compatible with the standard governing the operation of WiFi networks, i.e., IEEE 802.11.
- Automatic anomaly detection: As it is radio technology, it can also detect radio anomalies such as signal jammers, external interference, or hacker attacks.
- High robustness against failures: If an access point stops functioning, the rest of the network’s access points can still detect WiFi devices in the area of interest.
- Easy deployment: The access points can be powered through Power over Ethernet (PoE) or traditional power supply, making their deployment in a city, sports stadium, or convention center very simple.
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