MOODY: Harnessing a coin cell battery for emotion recognition
(Nur auf Englisch) In an era where technology seamlessly integrates into our daily lives, CSEM unveils MOODY—a breakthrough in ultra-low-power (ULP) vision systems that can discern human emotions from the power of a single coin cell battery. This innovation exemplifies CSEM’s commitment to energy efficiency at a sub-milliwatt (sub-mW) power level enabling long-lasting operation on edge platforms for real-time inference. This opens a new realm of possibilities for human-machine interaction (HMI), access control, or driver safety by overcoming conventional energy limitations associated with machine learning (ML) applications.
MOODY: A Glimpse into the Future
Imagine a world where your devices understand your emotions, react to your presence, and anticipate your needs, all while running on the smallest energy footprint imaginable. This is the world CSEM is creating with MOODY, a sensor that can discern human emotions from a mere coin cell battery, challenging the status quo of energy-intensive ML applications.
“Central to MOODY is CSEM’s ERGO640 high dynamic range (HDR) image sensor and Visage ML accelerator—technological marvels that empower MOODY to process data directly at the source with unparalleled energy efficiency,” explains Dr. Petar Jokic, Senior R&D Engineer at CSEM. “These components, in harmony with advanced embedded learning algorithms and resource-efficient software, render MOODY an ideal candidate for spearheading the future of next-generation ULP ML and HMI applications.”
Disruptive innovations: The three pillars of MOODY
CSEM’s disruptive ULP innovations extend beyond MOODY
CSEM’s leadership in ULP vision systems and edge artificial intelligence (AI) extends far beyond MOODY. It offers eye-gaze and gesture tracking for enhanced safety in autonomous aviation and autonomous vehicles, facial recognition technology for secure identification for access control and efficient human-machine interactions, as well as advanced vision technology with edge processing with the potential to improve patient care, driver safety, building management, and more. This selection represents a snapshot of CSEM’s commitment to technological advancement and its capacity to equip its partners with the tools necessary for success.