Creating a TinyML classification model to identify the correct execution of gym exercises
Set up a model for the User Activity Recognition with the Accelerometer sensor of the smartphone, using a crowdsensing IoT app.
One of the powers of machine learning is the ability to analyze variables indirectly by measuring a completely different one. Mov to IAQ!
Application that collects data from the accelerator sensor of the mobile phone using the Generic Sensor API and recognize the user activity.
Learn how to visualize the MPU6050 angle data from the i2cdevlib in the Arduino Framework using Processing and Toxiclibs library.
BMA250 is a small, thin, ultralow power, 3-axis accelerometer with high resolution (13-bit) measurement at up to ±16 g.
Adding machine learning capabilities to TI-RSLK robot kit using Edge Impulse TinyML running on accelerometer data.
H3LIS331DL is a low-power high performance 3-axis linear accelerometer belonging to the “nano” family, with digital I²C serial interface.
How to attach a sensor to the Redtree Hydra and share it with other robots.
Recognition of human activity through an accelerometer using AWS Lambda and API services
Eat Them Up: Use Edible Paper and Edible Ink, with a TOMU/BOMU and Raspberry Pi Zero add on for a DIY NashPen. Gift one to John Nash.
Discover how to capture magnetometer, accelerometer, and gyroscope data from the MPU9250 9-axis sensor using the Raspberry Pi.
The MPU6050 accelerometer gyroscope is a widely used chip with a 16-bit measurement resolution on every six-axe sense. Let us build one.
Capture and analyze 6-axis motion data with an ESP32 and MPU6050, enabling real-time visualization and motion tracking via MQTT.
A wearable solution to detect potential drowning and alert guardians for help. My largest project so far, Github profile is at the Comment!
WiFi connected mini-blinds opener using ESP8266 microcontroller.
Cloud based and edge based activity recognition using Azure and Generic Sensors Api.
Learn how to get more accurate linear and gyroscopic acceleration values from the MPU9250 using a simple calibration technique.
This is a portable device that senses motion and will send a notification via email, text, phone call, etc. using IFTTT.
Learn how to use the ADXL345 accelerometer sensor and how to interface it with an Arduino.
Theoretically, this object would be used to count pets as they enter an animal shelter.
To build an ML pencil that will recognize 5 Hindi alphabets by analyzing their accelerometer and gyroscope data using Machine Learning.
Motion-controlled air drums using MPU-6050 accelerometer. Swing drumsticks forward/left/right to play different sounds. No coding requried.
A handheld game about appealing to authority as a marginalized activist
