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aiSensing Deploys Highly Successful End-Point AI Vibration Sensor Using SensiML Analytics Toolkit and QuickLogic EOS S3

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SensiML Corporation announced the successful deployment of an AI-based vibration sensor by its customer, aiSensing, for a leading Taiwanese manufacturer. This intelligent sensor monitors vibration patterns, detects anomalies, and issues maintenance requests, enhancing factory productivity and reducing equipment downtime. The local AI implementation ensures low costs, fast response times, and high data security. Developed on QuickLogic's EOS S3 SoC, this predictive maintenance solution is a significant advancement in smart manufacturing.

Positive
  • Successful deployment of AI-based vibration sensor enhances factory productivity.
  • Reduction in equipment downtime due to proactive maintenance requests.
  • Local AI implementation offers low cost and fast response times.
  • Developed on QuickLogic's EOS S3 SoC, ensuring sufficient processing power.
Negative
  • None.
  • Monitors equipment health and issues maintenance requests
  • Increases factory productivity and reduces downtime for major manufacturer
  • Implements local AI for low cost, fast reaction times, and high data security

PORTLAND, Ore., July 20, 2022 /PRNewswire/ -- SensiML™ Corporation, a leading developer of AI tools for building intelligent Internet of Things (IoT) endpoints, today announced that its customer, aiSensing, has successfully completed and deployed an endpoint AI-based vibration sensor for a large multi-national manufacturer in Asia. This intelligent endpoint monitors vibration patterns for multiple machines, detects potential anomalies, and issues maintenance requests when necessary. The result is reduced equipment downtime and higher overall factory productivity. Since the AI implementation is local, rather than cloud-based, the system features low cost, low latency and fast reaction times while simultaneously providing higher data security.

aiSensing's customer is one of the largest and most successful manufacturing companies in Taiwan. It is the leading manufacturer of specialty adhesives, footwear adhesives, hot-melt adhesives, and liquid and powder coatings. The company has adopted this Edge AI-based approach to detect anomalies for vacuum pumps and chilling machines used in its manufacturing flow, including problems related to lack of lubrication, water leakage, bearing failures, and belt failures. By identifying potential problems before they arise, maintenance issues can be addressed in a managed way rather than as ad hoc emergency situations. This type of predictive maintenance is a key component of modern smart manufacturing initiatives.

The AI-based endpoint was developed on a QuickLogic EOS S3 ultra-low power multi-core Arm Cortex® MCU-based SoC, which delivered more than enough processing bandwidth for the application at a low cost. The AI application running on the QuickLogic device was built using the SensiML Analytics Toolkit, which provided a complete solution for the quick development of this sophisticated IoT endpoint.

"Smart manufacturing is a significant trend across a broad range of industries," said Chris Rogers, chief executive officer at SensiML. "Predictive maintenance is one of the core initiatives in that trend, and aiSensing's vibration sensor is a great example of how to effectively use AI to implement a practical and cost-effective predictive maintenance solution."

"Our endpoint AI-based vibration sensor has been very successful," said Dennis Chu, chief technology officer at aiSensing. "Its low power consumption, fast response times, and low cost are the ideal combination of features for this predictive maintenance application. With the SensiML tools, we can easily modify the design to address new and unique requirements for our customers."

The SensiML Analytics Toolkit, QuickLogic EOS S3 SoC, and aiSensing's endpoint AI vibration sensor are each available now.

For more information on the SensiML tools, visit the SensiML website at: https://sensiML.com/products. More information on QuickLogic's EOS S3 SoC is available at https://www.quicklogic.com/products/soc. For more information on the aiSensing vibration sensor, visit: https://www.youtube.com/watch?v=z7TPI7i2vn4.

About SensiML
SensiML, a subsidiary of QuickLogic (NASDAQ: QUIK), offers cutting-edge software that enables ultra-low power IoT endpoints that implement AI to transform raw sensor data into meaningful insight at the device itself. The company's flagship solution, the SensiML Analytics Toolkit, provides an end-to-end development platform spanning data collection, labeling, algorithm and firmware auto generation, and testing. The SensiML Toolkit supports Arm® Cortex®-M class and higher microcontroller cores, Intel® x86 instruction set processors, and heterogeneous core QuickLogic SoCs and QuickAI platforms with FPGA optimizations. For more information, visit www.sensiml.com.

SensiML and logo are trademarks of SensiML. All other trademarks are the property of their respective holders and should be treated as such.

Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/aisensing-deploys-highly-successful-end-point-ai-vibration-sensor-using-sensiml-analytics-toolkit-and-quicklogic-eos-s3-301589901.html

SOURCE SensiML Corporation

FAQ

What is the significance of the AI-based vibration sensor deployed by aiSensing?

The AI-based vibration sensor enhances factory productivity and reduces equipment downtime by monitoring vibration patterns and issuing maintenance requests.

How does the local AI implementation of the sensor benefit manufacturers?

The local AI implementation offers low costs, fast reaction times, and high data security compared to cloud-based solutions.

Which company developed the AI tools used in the vibration sensor?

SensiML Corporation developed the AI tools, specifically the SensiML Analytics Toolkit.

What technology powers the AI-based vibration sensor?

The sensor is developed on QuickLogic's EOS S3 ultra-low power multi-core Arm Cortex MCU-based SoC.

What industry is adopting the predictive maintenance solutions discussed in the PR?

The manufacturing industry is adopting predictive maintenance solutions as part of the smart manufacturing trend.

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