San Francisco, CA and Beijing, China — Three years ago, Xiaomi shook up the smartphone market with the introduction of the Mi MIX — a line of high-end phones that launched the concept of full-screen displays. Now, this Chinese powerhouse is once again utilizing the same software technology that enabled the Mi MIX's success in its new Mi 9 and Mi 9 SE models: Elliptic Labs' INNER BEAUTY® Virtual Proximity Sensor™. INNER BEAUTY uses ultrasound, sensor fusion and machine learning to replace a phone's traditional hardware proximity sensor with pure software, enabling both larger screens and cleaner design.
"Our Virtual Smart Sensor Platform™ not only eliminates the IR hardware sensor requirement, providing OEMs with greater design choice, but it also lets OEMs offer a variety of extra features for smartphones and IoT devices, including gestures and presence detection," explained Laila Danielsen, CEO of Elliptic Labs.
Xiaomi's mass-market Mi 9 line is a significant turning point for the industry, indicating that the breakthrough enabled by Elliptic Labs' Virtual Smart Sensor Platform is moving from more expensive phones to the high-volume arena. Prior to Elliptic Labs' inclusion in the first Mi MIX phone, all smartphones required hardware proximity sensors and their corresponding eyeholes on the front of the phone's screen, typically within a massive bezel. These sensors were needed in order to turn off the screen and disable touch functionality whenever a user was on a call. Elliptic Labs' patented algorithms replace these traditional optical infrared hardware sensors, eliminating the need for such unsightly eyeholes and bezels. The INNER BEAUTY Virtual Proximity Sensor is also display-agnostic, supporting all screens form OLED to LCD.
Xiaomi announced its new Mi 9 and Mi 9 SE smartphone models today.
INNER BEAUTY is a registered trademark of Elliptic Labs.
Virtual Proximity Sensor and Virtual Smart Sensor Platform are trademarks of Elliptic Labs.
All other trademarks or service markets are the responsibility of their respective organizations.
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