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Oslo, Norway, and San Francisco, USA — Elliptic Labs, a global AI software company, has launched the Virtual Security Sensor™, a presence-detection solution used to improve the security of data stored on laptops.  The new technology is based on Elliptic Labs' Virtual Smart Sensor Platform™ and in addition to providing security benefits also improves power consumption and delivers additional user experiences, such as touch-free gestures and breathing detection.

Elliptic Labs' patented Virtual Smart Sensor Platform uses algorithms, proprietary machine learning tools and sensor fusion to create Virtual Smart Sensors™ that outperform hardware sensors.  The new Virtual Security Sensor leverages a laptop's existing speaker and microphone to generate and process ultrasound waves to detect presence. Since it is entirely software based, the solution doesn't take up any physical space thus allows clean industrial design. When the user moves away from the laptop, the Virtual Security Sensor detects the user's absence, locks up the device and can be shifted into the Windows modern standby low-power state.  The Virtual Security Sensor runs in a low-power duty-cycle mode to scan for the return of the user and can automatically log the user back in using facial recognition.

"By using our groundbreaking AI software for presence detection, we eliminate the need for costly hardware sensors, improve data protection and increase convenience for laptop users," said Elliptic Labs CEO Laila Danielsen. The patented, 100%-software-based Virtual Security Sensor is able to distinguish between a person sitting in front of the camera and an inanimate object without having to use a costly hardware sensor or activate a more power-hungry and privacy-intrusive front-facing camera.

Virtual Smart Sensor and Virtual Smart Sensor Platform are trademarks of Elliptic Labs.

All other trademarks or service markets are the responsibility of their respective organizations.

This work is partially supported by the EU H2020 Grant for SME Instrument Phase II, Project IMIR-UP (Grant No.849692).