July 23, 2019

[Raanana, Israel]: Celeno, a leading provider of smart, innovative Wi-Fi solutions announced today that Orange Labs will engage in researching AI classifiers for human postures, behaviors and events to increase contextual interpretation of situations in the home. The research will be enabled by Celeno’s recently announced Wi-Fi Doppler Imaging technology which is built in their Wi-Fi 5 and Wi-Fi 6 silicon solutions. The research is aimed at enhancing the quality of experience of smart home applications.

Celeno’s imaging technology employs the Doppler Effect and standard Wi-Fi packets to accurately characterize and represent complex motions and movements of people, pets and objects. This captured data (a.k.a. Doppler Spectrograms) will be used by Orange Labs to research Machine Learning classifiers to accurately locate, track, count and analyze behavior and events while increasing the overall contextual interpretation of a situation.

“Direct Doppler Imaging could identify and analyze complex movements and motions which can add context and insights on human behavior for richer applications and services. This, in turn, could be used to develop new smart home applications such as intrusion detection, home security, or assisted living to provide additional value to consumers”, said Lior Weiss, VP Marketing and BD of Celeno. “We are proud to collaborate with Orange Labs on Wi-Fi Doppler Imaging and the new home applications it could enable.”

Since this technology is based on standard Wi-Fi and could be embedded in standard Wi-Fi network devices, the consumers benefit from a non-intrusive solution that does not invade privacy and does not require any wearable devices.

Jean-Philippe Javaudin, research program manager, Orange Labs, said, "Tests of the Wi-Fi Doppler Imaging technology is an opportunity for Orange Labs to investigate additional sources of information in the home. Enrichment of context information would help for further improvement of the accuracy and performance of Orange smart home services”.


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