A new white paper from POLYN Technology highlights the value of machine learning for on-device vibration monitoring in industrial devices and vehicles.
The white paper looks at the way vibration data is analyzed in industrial and automotive environments and how it can be done more efficiently.
“Vibration analysis is vital to spotting equipment problems and defects and making repairs before failures occur,” said Eugene Zetserov, Vice President of Marketing and Business Development for POLYN. “Advancements in AI models, data processing and the availability of IIoT sensors enable valuable insights unlike anything we’ve seen before.”
He added, “The challenge is in processing the vibration data in a way that minimizes power and communication requirements. The solution is in on-device analysis with neural networks.”
POLYN is a fabless semiconductor company, offering ultra-low-power, high-performance Neuromorphic Analog Signal Processing (NASP) technology, IP and Tiny AI chips based on NASP. POLYN’s Neural-Net-To-Chip automation tools support fast, cost-effective development of application specific solutions performing sensor data pre-processing on-device.
The white paper, titled “Vibration Monitoring On-Device with Machine Learning” is available for download at the POLYN website.
For more information about POLYN Technology, visit polyn.ai.
