This article describes how to build acoustical neural networks by taking advantage of the physical properties of microphone data to extract information relevant to such classification tasks, and it will show how to perform sound recognition with Qeex...
This article describes how to build basic Air Gesture recognition with the embedded Machine learning capabilities of the SensorTile.box and the third part platform Qeexo AutoML, exploiting the embedded Machine Learning Core (MLC) feature of the onboa...
In industrial environments, it is often important to be able to recognize when a machine needs to be serviced before the machine experiences a critical failure. This type of problem is often called predictive maintenance. In this tutorial, we are sol...
1 - Introduction The Yoga Pose recognition algorithm described here is intended for wearable devices, since all the data logs have been acquired with the device placed on the left leg, with the orientation described in section 2. Fourteen different c...
This article is for people who are used to develop their applications using the Arduino IDE but who are not familiar yet with how to use ST products in the Arduino world. This concept combines the best performance hardware with an easy Arduino IDE fo...
Motion Magnetic Sensor library application and functions in X-CUBE-MEMS1 1. Motion Magnetic Sensor library The description of MotionMC library for the magnetic sensor calibration gives the opportunity to get a more detailed overview on the magnetic ...
1. Motion e-Compass library Among the wide portfolio of ST sensors, the E-Compass is a proof of a well-done sensor integration. This library acquires data from the accelerometer and magnetometer and provides information about the device orientation a...
Motion Active Time Library application and functions in X-CUBE-MEMS11. Motion Active Time Library In some real cases, it is important to know in real-time how long an activity lasts, and if the activity is running in a particular moment. MotionAT ...
Motion Activity Recognition library application and functions in X-CUBE-MEMS11. Motion Activity Recognition library Activity recognition is one of the most common and requested in nowadays personal electronics landscape, especially as regards the we...
Motion Automatic Calibration Library application and functions in X-CUBE-MEMS11.Motion Automatic Calibration Library Let's start this diving into the FW libraries for ST motion MEMS sensors with the first one: Motion Automatic Calibration (MotionAC)...
The X-CUBE-MEMS1 expansion software - MEMS drivers family1. MEMS drivers family overview Although this article series will be mainly focused on the library package X-CUBE-MEMS1 and on the related motion algorithms, it's worth spending a few words o...
The X-CUBE-MEMS1 expansion software package - test utilities1. BSP for sensor expansion board This software is based on the STM32CubeHAL hardware abstraction layer for the STM32 microcontroller. The package extends STM32Cube by providing a board sup...
The X-CUBE-MEMS1 expansion software package - an overview1. X-CUBE-MEMS1 expansion software package The X-CUBE-MEMS1 expansion software package for STM32Cube is a library package we already encountered in a past series of posts, running on the STM32...
The STM32Cube environment - the starting point for a tour inside the motion libraries1. STM32Cube environment If you decides to start developing from scratch, you must well know the STM32Cube ecosystem. This is a set of tools -maybe one of the most...
This article will explain how to get started with SensortTile.box smartphone app, starting with the description of the proposed Example Applications in in terms of Input, Functions and Output and will explain how to build your own Application. 1. Con...
This article continues describing how to use the Machine Learning Core (MLC) configuration in the ST MEMS sensors that can be found on the STWIN evaluation board. This example shows how MLC functionality embedded in ISM330DHCX can be used for fan rac...
In this article, the third of a series of MLC AI tips articles, we will explain how to evaluate the performance of a trained decision tree model in order to build the best possible model for the Machine Learning Core embedded in the latest generation...
In this article, the third of a series of MLC AI tips articles, we will explain how to choose the features to train a decision tree, how to choose the window size to use to compute those features and how to apply the right filters to leverage frequen...
In this article, the second of the MLC AI tips articles, we will explain how to manage a robust and meaningful data collection to train decision trees that can be embedded on the Machine Learning Core of our ST MEMS sensors.1. Introduction The usual...
In this article, the first of a series of MLC AI tips articles, we will explain what decision trees are and how to embed a solution based on decision trees into the latest generation of ST MEMS sensors, which feature a built-in machine learning core ...
