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MATT3R introduces K3Y device that transforms Tesla cameras into “smart dashcams”

Izzy WoodBy Izzy WoodJuly 11, 20242 Mins Read
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MATT3R introduces K3Y device that transforms Tesla cameras into “smart dashcams”
MATT3R, an emerging AI technology company, has announced the pre-order availability of its K3Y device, which enables enables Tesla vehicle owners to transform their car’s built-in external cameras into a “smart dashcam system”.

With shipments expected to begin in late 2024, the K3Y is a USB device that fits in the glove box of Tesla vehicles and has been designed as a bridge between the vehicle’s external cameras and the user’s phone, recording footage from the front, side and rear cameras to provide a surround view of every trip.

The device uses advanced AI technology to flag events such as honks, harsh braking, front collision warnings and autopilot disengagement.

Users can access footage through the CONSOL3 mobile app – available for both iOS and Android – which enables users to select specific points on a map and view footage from the front, side or rear cameras. Events and incidents are automatically flagged, and footage can be accessed remotely if the K3Y is connected to wi-fi.

The app also supports third-party extensions, enabling additional capabilities such as cloud storage uploads and driver rewards. MATT3R is currently working with partners on various extensions, with announcements expected in the coming weeks and months.

“We are excited to introduce the K3Y, a must-have companion for Tesla owners and fleets,” said MATT3R founder and CEO Hamid Abdollahi. “Our goal is to contribute to a safer future of mobility by offering a scalable platform that leverages advanced AI and integrates seamlessly with Tesla’s existing technology. The K3Y device and our scenario digital twin technology highlight our commitment to innovation and enhancing road safety for all.”

The company says it is also developing software solutions to support the research and development of ADAS. These solutions aim to convert raw driving data into simulation-ready scenarios, helping train ADAS algorithms.

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