industry news
Subscribe Now

Qeexo, and Bosch Enable Developers to Quickly Build and Deploy Machine-Learning Algorithms to Bosch AI-Enabled Sensors

Machine learning algorithms created using Qeexo’s AutoML can now be deployed on Arduino Nicla Sense ME with Bosch BHI260AP and BME688 sensors

Qeexo, developer of the Qeexo AutoML, and Bosch Sensortec GmbH, a technology leader in MEMS sensing solutions, today announced that machine learning algorithms created using Qeexo’s AutoML can now be deployed on Arduino Nicla Sense ME with Bosch BHI260AP and BME688 sensors. Qeexo AutoML is an automated machine-learning (ML) platform that accelerates the development of tinyML models for the Edge.

Bosch’s BHI260AP self-learning AI sensor with integrated IMU, and BME688, a 4-in-1 gas sensor with AI, significantly reduce overall system power consumption while supporting a wide range of applications for different segments of the IoT market.

Using Qeexo AutoML, machine learning (ML) models–that would otherwise run on the host processor–can be deployed in and executed by BHI260AP and BME688. Its highly efficient machine learning models–that overcome traditional die-size-imposed limits to computational power and memory size–extend to applications that transform and improve lives. For example, they can be used for: Monitoring environmental parameters, including humidity and Air Quality Index (AQI); and capturing information embedded in motion, such as person-down systems to fitness apps that check posture. These devices typically have a longer time between charges and provide actionable information.

“Qeexo’s collaboration with Bosch enables application developers to quickly build and deploy machine learning algorithms on Bosch’s AI integrated sensors,” said Sang Won Lee, CEO of Qeexo. “Machine learning solutions running on Bosch’s AI integrated sensors are light-weight and do not consume MCU cycles or additional system resources as seen with traditional embedded ML.”

“Bosch Sensortec and Qeexo are collaborating on machine learning solutions for smart sensors and sensor nodes. We are excited to see more applications made possible by combining the smart sensors BHI260AP and BME688 from Bosch Sensortec and AutoML from Qeexo.” said Dr. Stefan Finkbeiner, CEO at Bosch Sensortec.

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.

Qeexo Co.

About Bosch Sensortec GmbH

Bosch Sensortec GmbH is a fully owned subsidiary of Robert Bosch GmbH dedicated to the world of consumer electronics; offering a complete portfolio of micro-electro-mechanical systems (MEMS) based sensors and solutions that enable mobile devices to feel and sense the world around them. Bosch Sensortec develops and markets a broad portfolio of MEMS sensors, solutions and systems for applications in smart phones, tablets, wearable devices, and various products within the IoT (Internet of Things).

One thought on “Qeexo, and Bosch Enable Developers to Quickly Build and Deploy Machine-Learning Algorithms to Bosch AI-Enabled Sensors”

Leave a Reply

featured blogs
May 2, 2024
I'm envisioning what one of these pieces would look like on the wall of my office. It would look awesome!...

featured video

Why Wiwynn Energy-Optimized Data Center IT Solutions Use Cadence Optimality Explorer

Sponsored by Cadence Design Systems

In the AI era, as the signal-data rate increases, the signal integrity challenges in server designs also increase. Wiwynn provides hyperscale data centers with innovative cloud IT infrastructure, bringing the best total cost of ownership (TCO), energy, and energy-itemized IT solutions from the cloud to the edge.

Learn more about how Wiwynn is developing a new methodology for PCB designs with Cadence’s Optimality Intelligent System Explorer and Clarity 3D Solver.

featured paper

Altera® FPGAs and SoCs with FPGA AI Suite and OpenVINO™ Toolkit Drive Embedded/Edge AI/Machine Learning Applications

Sponsored by Intel

Describes the emerging use cases of FPGA-based AI inference in edge and custom AI applications, and software and hardware solutions for edge FPGA AI.

Click here to read more

featured chalk talk

Electrical Connectors for Hermetically Sealed Applications
Sponsored by Mouser Electronics and Bel
Many hermetic chambers today require electrical pathways to provide internal equipment with power, data or signals, or to receive data and signals from equipment within the chamber. In this episode of Chalk Talk, Amelia Dalton and Brad Taras from Cinch Connectivity Solutions explore the role that seals and connectors play in the performance of hermetic chambers. They examine the methodologies to determine hermetic seal leaks, the benefits of epoxy hermetic seals, and how Cinch Connectivity’s epoxy-based seals and hermetic connectors can add value to your next design.
Aug 22, 2023
29,856 views