Dyson CameraJet toothbrush features embedded camera and AI to target gaps between teeth
Dyson has unveiled the CameraJet, a revolutionary toothbrush with an embedded camera and machine learning technology that identifies gaps between teeth and delivers targeted mouthrinse jets to those spaces. The device combines advanced features including a 100k-pixel macro lens camera powered by the Gap Optical Targeting algorithm, variable sonic oscillation, a conical jet system, and an anti-gravity tank. The development took over six years and involved training on 470,000 dental images and a five-year collaboration with the National University of Singapore's Faculty of Dentistry to develop proxy plaque for testing.
Dyson makes lots of interesting and innovative products, but I was surprised they came up with a toothbrush. I've been using a Philips Sonicare for years and I can't praise it enough. The CameraJet is really tempting me though :)
How does the camera in Dyson CameraJet work?
The camera with 100,000 pixels and macro lens works with the Gap Optical Targeting AI algorithm, scanning 28 live images per second. The system identifies, tracks and predicts gaps between teeth in real time, and within 100 milliseconds of detecting a gap, it triggers a precision jet burst of mouthrinse to that location.
What is the difference between Dyson's conical jet and traditional water flossers?
Traditional water flossers use a sharp needle-type jet that pierces through plaque but fails to remove it completely due to plaque's stickiness. Dyson's broader conical jet sweeps and removes plaque in one action while operating at lower pressure, making it gentler on gums and enamel.
How does the toothbrush recharge and refill?
The toothbrush charges and refills using a dedicated docking station that automatically refills the mouthrinse reservoir in just three seconds. The station also stores the device upright and charges it between uses, with a travel case included for portability.
How long did the development of Dyson CameraJet take?
Development took over six years of research and engineering. The project involved training the algorithm on 470,000 dental images and a five-year collaboration with the National University of Singapore's Faculty of Dentistry to develop proxy plaque for accurate testing.
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- Dyson CameraJet
- Dyson
- Gap Optical Targeting
- James Dyson
- National University of Singapore
- Philips Sonicare