In news that is sure to shake up the ride hailing industry, Uber announced on Wednesday that it will soon unveil its newest Volvo self-driving car. Just as electric vehicles have already made a significant impact, undoubtedly driverless cars mark another big shift in mobility.
In addition to the autonomous driving technology what also stood out to us in the announcement was the detail that
“the new XC90 vehicles have an interior fish-eye camera to scan for lost items”.
People leaving their belongings behind is a story as old as transport itself. Train passengers have been forgetting umbrellas on the underground for more than a hundred years, and passengers losing laptops and phones in ride hailing and shared cars is just the latest version of this.
But while the inconvenience of leaving something behind hasn’t changed, the technology to prevent this problem has.
By announcing that they will soon scan for lost items, Uber also joins Elon Musk in heralding the use of Computer Vision to scan for objects and issues in car interiors.
Why are we so interested in this? Because at CleanAI we have been working on this exact problem. After researching the dirtiness of shared cars we developed a solution for detecting dirty and messy car interiors using Machine Learning algorithms and advanced sensors. If a customer has left something behind they receive an immediate notification alerting them so that they can quickly retrieve their belongings.
To address the understandable privacy concerns that cameras in cars raise, our solution Cleanride is only activated AFTER the ride is done and the occupants are out of the car — they are never filmed during the ride.
To see big players like Uber and Tesla planning to use AI to scan for lost items is exciting. But there’s no need to wait! If you’re a car sharing operator, corporate fleet manager or OEM, then contact us to integrate our solution in your vehicles today!
And to learn more about how we developed a custom AI detection model for car interiors, check out our article.
The CleanAI team