Socionext and Innatera Introduce Integrated 60 GHz FMCW Radar and Neuromorphic Edge AI for Human Presence Detection
Langen/Germany, Yokohama/Japan -- February 23, 2026 --- Socionext and Innatera today announced a jointly developed human-presence detection solution that combines 60 GHz FMCW radar sensing with neuromorphic edge AI to deliver reliable, always-on detection with drastically reduced power consumption. A live demonstration of technology will be showcased at Embedded World 2026 in Nuremberg (Booth 4A-628).
The solution integrates Socionext’s compact 60 GHz FMCW radar, which captures detailed 3D environmental information under all lighting and weather conditions, with Innatera’s ultra-low-power Spiking Neural Processor, which interprets radar patterns directly at the sensor edge. The neuromorphic processor distinguishes human from non-human motion - including stationary individuals - achieving over 99% detection accuracy while maintaining sub-milliwatt power levels. This enables devices such as cameras and radios to remain asleep until real human presence is confirmed, extending battery life by 3–6×.
“Our 60 GHz FMCW radar delivers precise, privacy-preserving sensing in a compact form factor, making it ideal for battery-powered IoT devices,” said Matthias Neumann, Senior Marketing Manager Smart Devices & Industrial at Socionext. “Together with Innatera, we are demonstrating a presence-detection solution that raises the bar for accuracy, integration flexibility, and real-world reliability.”
“Neuromorphic computing is unlocking a new generation of always-on functions in devices, through powerful, brain-like processing of sensor data within a tiny energy footprint,” said Sumeet Kumar, CEO at Innatera. “Combining our Spiking Neural Processor with Socionext’s FMCW radar enables robust, real-time human-presence detection at power levels no conventional AI system can match.”
At Embedded World 2026, attendees will be able to experience firsthand how the joint solution:
- Detects human presence accurately, including stationary individuals
- Filters out motion from animals, foliage, and environmental noise
- Operates fully on-device with no cloud dependency
- Supports compact, battery-efficient consumer, industrial, and automotive designs
Target applications include smart doorbells and cameras, smart-building occupancy sensing, in-cabin automotive monitoring, elderly-care and industrial safety systems, and gesture-driven interfaces.
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