The world’s first autonomous imager technology that activates smartphones and small appliances through face recognition or other specific patterns.
Called µWAI (micro-WAY) and sized as small as a 1€ coin, the autonomous imager features a novel readout and processing architecture co-designed with an optimized algorithmic pipeline, in which the recognition results from a sequence of elementary algorithms, to provide ultralow-power wake-up modes and compact silicon implementation to keep costs down.
It is the first smart image sensor jointly featuring auto-exposure for all lighting conditions and 88dB dynamic range, as well as motion detection and feature extraction for event-based functioning, and AI-based object recognition that triggers highly reliable identification. These key features also enable highly reliable decision-taking for a few tens of pJ/pixel/frame, which outperforms existing off-the-shelf systems. The pJ/pixel/frame measures the energy spent by each pixel for every single image within a frame of images. A typical implementation requires about 10,000 times more energy than µWAI.
The autonomous imager is the world’s first highly efficient, compact, and ultralow-power, the smart-awaken system designed for everyday small appliances. It also includes:
- Energy efficiency: consuming 10k less than low-power camera plus processor set,
- Privacy-compliant, AI-based recognition: nearly human-detection performance (95 percent),
- Wide operating lighting sensitivity to ensure accurate recognition in extremely variable conditions,
- Five-year, always-on CR1025 battery lifetime, and
- The 3-6µW operation, which is required for the Internet of Things and can work with a button cell that lasts five years.
Applications and functions include automatic switching and face identification in mobile devices, contactless smart switching of household appliances, and sport-and-entertainment devices in smart homes. µWAI also provides face recognition, people counting, alarm triggering in smart buildings, vehicle-interior situation awareness, driver identification, parking-situation awareness, and a smart-unlocking system in automobiles.
“The recognition engine is optimized to recognize faces when movement is detected. CEA-Leti’s team is working hand-in-hand with STMicroelectronics to develop specific smart-imager products as we consider extending the technology to other use cases,” said Antoine Dupret, CEA-Leti’s industrial partnership manager. “We target adapting the recognition engine as IP embedded in various cameras and optimizing the performance of the imager to the requirements of our partner’s customers.”
For more information, visit www.cea.fr
