Innovative method combines video analytics with edge computing to accelerate onboard intelligence.
Computing developer FogHorn and Porsche have developed a multi-factor authentication prototype designed to improve auto security with a real-time facial recognition system and edge analytics.
The prototype, unveiled the Startup Autobahn Expo Day, uses two forms of authentication. The face detection can process infrared video to identifying if the person is the car owner, without having to send the data to a central location. The second mechanism swaps a car fob with a smartphone, thwarting car thieves.
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“FogHorn developed an innovative way for the automotive industry to leverage video analytics with edge computing to accelerate onboard intelligence,” says Chad Boulanger, managing director of EMEA, at FogHorn.
Porsche does not skimp on car technology, Autoguide called its infotainment tech the best on the market last year and it has released a video of its own autonomous driving system. Volkswagen, Porsche’s parent company, has also made major investments in self-driving.
The ability to process most of the computing inside the car is seen as critical for autonomous vehicle development. Autonomous vehicles need to process a lot of decisions in real-time, so having most of the information stored internally reduces the risks of accidents during low bandwidth or a blackout.
Some analysts say that 5G is also a necessity for self-driving, although if most processing can be done internally, this would not appear to be essential for a driverless car to function.
During this 100-day challenge we partnered with FogHorn to evaluate their capabilities of solving a persistent challenge in the driver experience of easier access to their vehicle seamlessly – without compromising on security,” said Matthias Hub, IT Project Manager and Prototyper at Porsche. “This project supports our commitment to put the customer’s need in the center of what we are doing and at the same time using leading-edge technologies.”
