Public Channels for Tag: accelerometer

Channel ID:
432825
Author:

accelerometer ,nodemcu

Channel ID:
224824
Author:

Data Acquision System Beharum project Automated systems for monitoring behaviour of grazing ruminants

Channel ID:
2933585

This channel is used for logging real-time sensor data from a smart insole system. It captures pressure data from four Force Sensitive Resistors (FSRs) and motion data from an MPU9250 accelerometer. The data is timestamped using the internal millis() func

Channel ID:
2859964

This ThingSpeak channel collects and visualizes real-time step data from a MATLAB Mobile-based fitness tracker. The system uses an accelerometer to detect steps, compute step rate, and analyze movement patterns.

Channel ID:
2330566

Here in this channel , we display the health related data that are measured by the sensors.

Channel ID:
1731191

Visualize the data obtained from the built-in accelerometer and gyroscope of the Nano 33 IoT in both graphical and numerical form.

Channel ID:
1700879
Author:

To detect the stability of land via the built-in accelerometer and gyroscope of Arduino Nano 33 IoT board.

Channel ID:
1245251
Author:

Visualization of sensor data from phone and other channels as well

Channel ID:
1246071
Author:

Uploaded sensor data from a phone. Created visualisation and analytics.

Channel ID:
1096533
Author:

Data Visualizations of Scissor Lift Usage

Channel ID:
34548
Author:

Biorhythm, Cardiac.. The e-Health Sensors allows users to perform biometric and medical applications where body monitoring is needed by using 10 different sensors: pulse, oxygen in blood (SPO2), airflow (breathing), bo, etc..

Channel ID:
927579

DEVELOPMENT OF LOW-COST REAL-TIME STRUCTURAL HEALTH MONITORING SYSTEM FOR BRIDGES IN NIGERIA. BRIDGE AND STRUCTURES DIVISION, ROAD RESEARCH DEPARTMENT. NIGERIAN BUILDING AND ROAD RESEARCH INSTITUTE (NBRRI).

Channel ID:
994742
Author:

accelerometer, movement, portrait, landscape

Channel ID:
742711
Author:

IoT Vibration Monitor. KingM

Channel ID:
716389
Author:

Read data from a RaspberryPi (accelerometer).


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