AI video analytics meets Formula 1 for the safety of racers and the audience
Racing has long used the latest technologies and Big Data to improve safety at major events. Smart cameras could drive this development. Learn how in this article.
The safety of drivers, teams, and fans is always a major issue in Formula 1 and in racing in general. Although the premier class has not had a driver fatality since David Ferrer's tragic accident at the Historic Grand Prix in 2017, spectacular accidents have repeatedly reminded fans and officials that motorsport still involves a great deal of risk.Data-driven safety in racing
In 2015, the Fédération Internationale de l'Automobile (FIA) launched an accident database available to all national federations to help improve safety at race tracks around the world. This database stores information on the vehicles involved, details of speed, acceleration and the type of accident, laying the foundation for data-driven safety in racing.
When it comes to fan safety, high standards for circuit layout and equipment, as well as the presence of trained safety personnel, help prevent accidents at the edge of racetracks. Nevertheless, in many cases, humans are the bottleneck in racetrack control.
AI Video Analytics to support racing safety crews
Where the human eye reaches its limits in monitoring complex events, smart technology is ready to help make races safer. Surveillance cameras equipped with AI video analytics and connected via IoT can detect critical incidents faster and more reliably than humans and help officials analyze what's happening on and around the track - in real-time and retrospective.
Azena provides an operating system and Application Store for security cameras, enabling car racing operators to empower their video systems with powerful features. Equipped with Artificial Intelligence from our Application Store, surveillance cameras can perform a range of safety-related tasks, some of which we feature here.
Ensure fan safety at the edge of race tracks
Even though there are strict guidelines from associations for track layout and safety, including spacing rules to prevent fans from being injured or killed in accidents, we all remember terrifying incidents at rally circuits, for example. Security personnel is often overwhelmed by the need to control fan behavior that is dynamic and difficult to predict.
This is where smart video cameras can help to quickly detect and automatically alert fans entering secured areas. The following example shows how AI video technology is already being used successfully on train platforms. Here cameras continuously analyze people's behavior and detect when they enter marked areas or cross virtual lines. Similarly, in racing, AI video analytics can prevent people from becoming victims of accidents involving vehicles.
AI Video Analytics supporting wrecker crews
The challenge in recovering crashed vehicles after accidents is twofold: on the one hand, recovery crews have to recognize critical events quickly and react immediately. On the other hand, traces of accidents must be completely removed. In both tasks, smart video cameras that survey the entire race track can help to take action quickly and reliably.
AI video analytics software enables cameras at race tracks to detect both large objects, such as broken vehicles, and small objects, such as vehicle parts scattered on the roadway due to a crash. Video analytics for object recognition lets cameras not only identify objects but also classify them to detect anomalies.
In our Application Store for security cameras, you can find lots of camera apps for object recognition, using machine learning, which can be trained to recognize specific objects.
Beyond security: AI Video Analytics to improve fan experience
Today's races are mass events where thousands of fans need to be managed and controlled to ensure smooth operations and a superior fan experience. The challenge for operators and promoters is to provide the best possible fan experience at all times, from parking and smooth check-in to a pleasant stay with catering and a smooth exit at the end of a race.
Surveillance cameras equipped with AI Video Analytics can not only help improve safety at race tracks. They can also help operators improve operations along the visitor journey.
Example: Detect queues and crowds at entrances and kiosks
Waiting in lines is the #1 visitor experience killer at events. At large events, it is difficult for security personnel to predict when and where the crowd will move. Therefore, operators should at least be able to react quickly when queues form at beverage booths and toilets.
CCTV cameras equipped with AI Video Analytics for crowd detection can “see” more and trigger actions faster than humans can. The apps from our Application Store enable the cameras to detect the density of crowds in certain areas.
More examples of how AI-enabled video cameras can improve racing fan experience:
- Automate parking access management using license plate recognition
- Monitor parking lots to identify bottlenecks and direct traffic to available capacity
- Monitor and control seat occupancy on grandstands
- Supervise compliance with hygiene and spacing rules during the pandemic
- Identify waste and debris on seats and in aisles and initiate cleanup service
Worth reading: Whitepaper on using smart cameras to deliver a superior fan experience
The examples above are just a small sample of the nearly endless possibilities AI Video Analytics offer for surveillance cameras to help improve race safety and operations.
For many applications, there are ready-made camera apps in our Application Store. If there is no app for your individual application yet, we can check to train a similar application. Do not hesitate to contact us if you are interested in getting more out of your camera systems!