SensEI Podcasts
SensEI Blog
Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable Motion Sensors
Qeexo and STMicroelectronics Speed Development of Next-Gen IoT Applications with Machine-Learning Capable [...]
Machine-learning capable motion sensors intended for IoT
Qeexo, developer of the Qeexo AutoML automated machine-learning (ML) platform, and STMicroelectronics have announced the availability of ST’s machine-learning core (MLC) sensors on Qeexo AutoML.
Qeexo adds AutoML to STMicro MLC sensors to speed tinyML, IIoT development
Machine learning developer Qeexo and semiconductor STMicroelectronics have teamed up to allow STMicro’s machine learning core sensors to leverage Qeexo’s AutoML automated machine learning platform that accelerates the development of tinyML models for edge devices.
IoT News of the Week for July 9, 2021
Anyone can now build smarter sensors using Qeexo and STMicroelectronics sensors: This is a cool example of ML at the edge.
Cross-Platform Swift at Scale
The dream of every developer is to be able to write code [...]
Arm’s Startup Day Shows its Support for Future Hardware Startups
Finding new tech often means looking at startups. To support this critical [...]
Qeexo和意法半导体合作提供具备机器学习功能的 运动传感器 加快下一代物联网应用开发
Qeexo AutoML自动化机器学习(ML)平台的开发者Qeexo公司和服务多重电子应用领域的全球半导体领导者意法半导体 (STMicroelectronics,简称 ST;纽约证券交易所代码:STM)宣布,意法半导体的机器学习核心(MLC)传感器已加入能够加快边缘设备tinyML微型机器学习模型开发的Qeexo AutoML平台。
Model Performance Evaluation in Qeexo AutoML
Introduction Qeexo AutoML provides feedback on trained models through tables and charts. [...]
STWin Now Supports DFU-Util
Starting with Qeexo AutoML 1.15.0, existing STWin users will have the option [...]
Integrating AutoML with front-end Apps
A demo Qeexo has shown at various trade shows that always gets [...]
AI In the Industry
It is not recent that AI has begun to find a significant [...]
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 [...]
A Step by Step Guide to Robot Arm Demo
In this article: PrerequisitesData CollectionData SegmentationBuilding ModelModel Performance & Live Classification In [...]
Using AutoML to detect motor issues
Use Qeexo's AutoML to monitor the motor's status on a Fischertechnik robot. [...]
Qeexo AutoML Best Practice Guide
This document is intended to help you learn more about fundamental [...]
TDK to acquire Qeexo to enable complete smart edge platforms
TDK to acquire Qeexo, Co, a leading developer of automated machine-learning (ML) [...]
Qeexo AutoML 1.19.0 New Feature Introduction
In this article, we are going to introduce you some of the [...]
TDK announces availability of automated ML Platform Integration for Arm® Keil® MDK
TDK’s new group company Qeexo launches AutoML for Arm Keil MDK Qeexo [...]
Qeexo AutoML Version 1.20.0 New Feature Introduction
In this article, we are going to introduce you some of the latest and greatest new features and improvements released in Qeexo AutoML 1.20.0.
Revolutionizing Motor Health: A Glimpse into Condition-Based Monitoring with Qeexo AutoML
In the sprawling world of industries powered by machines and motors, the quest for effective condition-based monitoring has been relentless. The intricacies of maintaining optimal motor conditions within vast and dynamic environments have long presented a challenge. Enter the transformative solution: Effective Motor Condition-Based Monitoring, developed and scalable from Qeexo AutoML to ensure motor health. This blog delves into the innovation, technology, and impact behind this simple, yet highly effective approach to motor maintenance.
CEATEC 2024 – Chiba, Japan
October 15-18, 2024TDK SensEI will showcase its latest Industrial Edge AI [...]
What is edgeRX?
In today's fast-paced industrial environment, keeping critical machines running smoothly is [...]
What is Condition-Based Monitoring and Predictive Maintenance?
Condition-based Monitoring (CbM) and Predictive Maintenance (PdM) are crucial for deploying [...]