The Formula of Using Artificial Intelligence in F1 Races, Formula One sport is known to use the best of technologies and has never hesitated to spend on the safety of their drivers. It is not just a car race, but also a race of technology and is popularly crowned as the Pinnacle of Motorsport. Now the F1 teams are gearing up to introduce artificial intelligence in the races. They are set to use cloud-based real-time analysis and machine learning techniques to enhance race metrics.
F1 will use Amazon Web Services (AWS), which will provide a cloud computing platform and can store a large amount of data. Researchers are going to store more than 61 years of F1 historic race data using AWS and use it for further analysis by predicting tactics for the drivers. They will also use AWS to get race statistics and make the most favorable predictions and decisions. These services include AWS’s SageMaker, which is a machine learning service with which data scientists and developers can quickly and easily train ML-based models and put them to use. Other AWS services that can be used include AWS Lambda, the event-driven, serverless computing platform, and Amazon Kinesis Data Analysis, which helps with streaming data in real-time.
Why Does F1 Need AI?
The F1 cars are extremely high tech. They have more than 200 sensors on the car and engineers have to be glued to their computers to monitor each sensor on their machines throughout the span of race to make decisions for the next move.
Instead, they can have AI to replace humans which will not only help in monitoring but also take right decisions. A lot of instances in F1 depict flaws due to human decision-making, so that can be eliminated with the advent of AI. Such systems can be trained to avoid accidents due to crashes and know about a failure of some part of the car, beforehand.
The advent of AI has also made them possible to do a lot of mechanical work in no time. So, they can be deployed to use for the repair and maintenance of the cars. The F1 teams, in spite of being very experienced and in spite of the skillsets and the enormous amount of money that they have, fail quite often to predict the best next move. Using AI in places like this would make them predict quite accurately about what move to make next.
Which Data Is Needed?
Since all the advances that AI can make with ML models depend entirely on the data it is given, the teams need to have an avalanche of data so that the ML algorithms at work give more precise predictions. This data involves telemetric data, apart from the historic one. This data can be temperature, pressure, frequency, speed and is received from onboard sensors. There also needs to be informed of individual team drivers like steering, acceleration and brake, along with data such as lap times, top speeds, pit stop times, wind speeds on the track, and others for precise forecasting.
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