First self-learning edge AI sensor for wearables - video

December 17, 2020 // By Nick Flaherty
The BHI260AP self-learning edge AI sensor
The Bosch BHI260AP self-learning edge AI sensor System in Package (SiP) for wearables includes pre-trained classification libraries and can update its framework without a connection to the cloud or a smartphone

Bosch has developed the first self-learning sensor for wearables that it says can update its machine learning edge AI framework without access to the cloud or a smartphone. This can help extend battery life.

The BHI260AP self-learning edge AI sensor System in Package (SiP) enables manufacturers of wearable and hearable devices to provide highly personalized fitness tracking through the self-learning AI software in the sensor. It recognizes and adapts to a wide variety of movements and is able to learn any new fitness activity that is based on repetitive, cyclical patterns.

"The self-learning AI sensor will change how users interact with their fitness devices from a mere one-way approach to an interactive way of training," said Dr. Stefan Finkbeiner, CEO at Bosch Sensortec. "This new sensor combines Bosch Sensortec’s long-term experience in smart motion sensors with its strong competence in innovative software development."

Bosch has been a key partner of French AI software developer Cartesiam which allows this edge AI capability.

The Bosch self-learning AI software is available with a standard set of more than fifteen pre-learned fitness activities based on classification libraries, so no training is required before use. It also offers four product features: learn, personalize, auto track and enhance.

The learning mode offers users the option to add new fitness activities that were originally not supported, enabling them to customize the device to their individual needs. The personalization feature enables users to adapt existing, pre-learnt activities to their own individual style, increasing the accuracy of calorie counting and activity analyses.

With the auto track function, users can automatically track fitness activities without any manual intervention and analyze their intensity with activity type and count over time – enabling both endurance and strength training. Finally, manufacturers can add new fitness activities without having to modify the software or needing an original dataset. These new transferable exercises may be provided by coaches or star athletes, enabling benchmarking against the best and learning from experts, or simply from the users’ friends. This enhances the perceived value of devices and strongly helps the manufacturers to differentiate.

 

Next: Edge AI boost for battery life


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