IoT company Ruff launches biometric face tracking module with edge processing
Chinese IoT company Ruff has launched a new face tracking module based on “IoT+” machine learning for biometric security on edge devices.
The Ruff Face ID Module features a 35mm by 42 mm AI chip for neural networking to support machine vision and speech recognition with ultra-low power consumption, according to the announcement. The module is suited for image classification, face detection and recognition, and multi-classification object detection and recognition, the company says. The module’s convolutional artificial neural network accelerator improves the efficiency of calculations.
The Ruff Face ID AI chip enables off-line processing at the edge, and advanced machine learning models for deep neural networks for processing video frames, speech synthesis, time series data, and feeds from cameras, microphones, or other sensors.
By providing cloud services for remote device management along with the face-tracking module, Ruff Face ID avoids common integration challenges to ease the installation and use of the technology by corporate clients and manufacturers.
CloudWalk recently announced the development of re-identification technology to extend facial recognition to people-tracking for public surveillance, and IARPA recently issued an RFI to investigate biometric tracking technology.