Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

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

Qeexo, developer of the Qeexo AutoML, and Bosch Sensortec GmbH, a technology leader in MEMS sensing solutions, 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.

Recommended AI News: T-Mobile Magenta Drive for BMW Powers America’s First 5G Connected Cars

Related Posts
1 of 41,049

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.

Recommended AI News: Titaniam Announces Completion of Product Suite to Push Back on the Ransomware Problem

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.