Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable Motion Sensors

Rhea-AI Summary

Qeexo and STMicroelectronics (STM) have announced the integration of ST’s machine-learning core (MLC) sensors with Qeexo AutoML. This collaboration aims to enhance the development of next-generation IoT applications by leveraging machine learning capabilities in low-power devices. The MLC sensors significantly reduce system power consumption by processing data directly at the sensor level, which enhances battery life and efficiency. This partnership supports various applications, including industrial and IoT use cases, allowing developers to deploy machine learning algorithms without burdening system resources.

Positive

• Integration of ST's MLC sensors with Qeexo AutoML enhances edge device performance.
• Significant reduction in overall power consumption for IoT applications.
• Enhanced battery life due to efficient processing capabilities at the sensor level.

Negative

• None.

Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable Motion Sensors 

Mountain View, CA and Geneva, Switzerland, July 7, 2021 – Qeexo, developer of the Qeexo AutoML automated machine-learning (ML) platform that accelerates the development of tinyML models for the Edge, and STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST’s machine-learning core (MLC) sensors on Qeexo AutoML.

By themselves, ST’s MLC sensors substantially reduce overall system power consumption by running sensing-related algorithms, built from large sets of sensed data, that would otherwise run on the host processor. Using this sensor data, Qeexo AutoML can automatically generate highly optimized machine-learning solutions for Edge devices, with ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint. These algorithmic solutions overcome die-size-imposed limits to computation power and memory size, with efficient machine-learning models for the sensors that extend system battery life.

“Delivering on the promise we made recently when we announced our collaboration with ST, Qeexo has added support for ST’s family of machine-learning core sensors on Qeexo AutoML,” said Sang Won Lee, CEO of Qeexo. “Our work with ST has now enabled application developers to quickly build and deploy machine-learning algorithms on ST’s MLC sensors without consuming MCU cycles and system resources, for an unlimited range of applications, including industrial and IoT use cases.” 

“Adapting Qeexo AutoML for ST’s machine-learning core sensors makes it easier for developers to quickly add embedded machine learning to their very-low-power applications,” said Simone Ferri, MEMS Sensors Division Director, STMicroelectronics. “Putting MLC in our sensors, including the LSM6DSOX or ISM330DHCX, significantly reduces system data transfer volumes, offloads network processing, and potentially cuts system power consumption by orders of magnitude while delivering enhanced event detection, wake-up logic, and real-time Edge computing.” 

About Qeexo

Qeexo is the first company to automate end-to-end machine learning for embedded edge devices (Cortex M0-M4 class). Our one-click, fully-automated Qeexo AutoML platform allows customers to leverage sensor data to rapidly build machine learning solutions for highly constrained environments with applications in industrial, IoT, wearables, automotive, mobile, and more. Over 300 million devices worldwide are equipped with AI built on Qeexo AutoML. Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint. For more information, go to http://www.qeexo.com.

About STMicroelectronics

At ST, we are 46,000 creators and makers of semiconductor technologies mastering the semiconductor supply chain with state-of-the-art manufacturing facilities. An independent device manufacturer, we work with more than 100,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and 5G technology. Further information can be found at www.st.com.

For Press Information Contact:

Lisa Langsdorf
GoodEye PR for Qeexo
Tel: +1 347 645 0484
Email: lisa@goodeyepr.com

Michael Markowitz
Director Technical Media Relations
STMicroelectronics
Tel: +1 781 591 0354
Email: michael.markowitz@st.com

Attachment

• T4378D -- Jul 7 2021 -- ST_Qeexo MLC sensor cooperation_FINAL FOR PUBLICATION

FAQ

What is the collaboration between Qeexo and STMicroelectronics about?

Qeexo and STMicroelectronics are collaborating to integrate ST's machine-learning core sensors with Qeexo AutoML, enhancing IoT application development.

How do ST's MLC sensors benefit IoT applications?

ST's MLC sensors reduce power consumption and improve efficiency by processing data directly at the sensor level, extending battery life.

What is the significance of the Qeexo AutoML platform for developers?

Qeexo AutoML allows developers to quickly build and deploy machine-learning algorithms on ST's sensors without using significant system resources.

When was the announcement made regarding the Qeexo and STM collaboration?

The announcement was made on July 7, 2021.

What are the applications of the technology developed by Qeexo and STM?

The technology is applicable in various sectors, including industrial and IoT applications.