Privacy-free crowd monitoring: 12-month implementation

by Crowdscan

CrowdScan monitors and count the number of people in real-time without cameras or smartphones.

Worldwide evolutions and events show that monitoring and managing crowds has become crucial in smart cities, public transportations systems, and airports. Just think of increasing urbanisation, the rise of mega-events and the Covid 19 pandemic. At the same time, there is a growing concern for safety and privacy, resulting in ethical debates and, ultimately, appropriate legislation. With our solutions, we can balance both. By using the Microsoft Azure services, a scalable infrastructure is guaranteed, which enables the customer to capture the real-time analytics and insights.

We offer an innovative and proven technology solution for targeted and responsible crowd management. Our services cover four levels and are tailored to specific sectors and contexts. Depending on the specific needs, you can choose from four levels of service. Crowd Density Counting focuses on the basics: counting the exact number of attendees. Crowd Density Analytics goes a step further, by providing more details about the movements of the crowd. Crowd Density Prediction is used to make predictions, based on previous insights, about coming evolutions and movements. Integrated Management, finally, focuses on an integrated total solution that we develop in co-creation with the customer.

The solution uses safe, low-energy electromagnetic radio waves (868 MHz) to accurately and anonymously define the number of people present at a location. The combination of a gateway with sensors ensures accurate measurement and real-time processing, tailored to each situation and location. We measure the average attenuation of a wireless sensor network in relation to the empty environment. To do this, we place several sensors (nodes) around the location at a height of 1,5 meter from ground level, which send each other signals using low-energy radio waves. Beforehand, we perform a baseline measurement in the still empty space, to determine the optimal strength of the signals. When the area of interest fills up, the attenuation of the signals can be used to determine exactly how many people are present. This information reaches the nearby gateway, which then immediately sends the data to the cloud for processing and visualisation.

At a glance