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센서
여러 센서에 연결하여 데이터를 읽습니다.
함수
도움말 항목
- Read and Plot Real-Time Data from BNO055 Sensor in NDOF Mode
This example shows you how to read and plot calibrated data from a Bosch Sensortec BNO055 a 9-axis absolute orientation sensor in real time.
- Calibrate BNO055 Sensors
Steps to calibrate the BNO055 sensors.
- Limitations
Limitations when using sensors and GPS receiver.
- Calculate Pitch and Roll on Arduino Using IMU Sensor (Simulink)
This example shows how to read the acceleration and angular velocity data from IMU sensor mounted on Arduino® hardware and calculate the pitch and roll angles.
- Measure LSM9DS1 Sensor Outputs Using Nano 33 BLE Sense
Read data from a LSM9DS1 sensor using Bluetooth®.
문제 해결
Troubleshoot sensors.
추천 예제
Estimating Orientation Using Inertial Sensor Fusion and MPU-9250
Get data from an InvenSense MPU-9250 IMU sensor, and to use the 6-axis and 9-axis fusion algorithms in the sensor data to compute orientation of the device.
Wireless Data Streaming Using BNO055 and Bluetooth and Estimating Orientation Using Sensor Fusion
Get data from a Bosch BNO055 IMU sensor through HC-05 Bluetooth® module and to use the 9-axis AHRS fusion algorithm on the sensor data to compute orientation of the device. The example creates a figure which gets updated as you move the device.
Plot Position Using GPS Connected to Arduino Hardware
Get the geographic location using the GPS module connected on Arduino hardware and plot the location in a map.
IoT-Based Automatic Cooling Fan Control Using ThingSpeak and Arduino Hardware
Create a ThingSpeak™ channel and use the MATLAB® functions to collect the temperature data from a BMP280 sensor connected to your Arduino® board, and then use MATLAB Analysis in ThingSpeak to trigger the automatic control of a CPU cooling fan kept in the room and then monitor the usage of the fan by calculating the runtime. This example also shows you how to set up an email alert if the fan turns on, by using MATLAB functions in ThingSpeak.
IoT-Based Temperature Monitoring Using ThingSpeak and Arduino Hardware
Create a ThingSpeak™ channel and use MATLAB® functions to collect the temperature data from a BMP280 sensor connected to your Arduino® board, and then use MATLAB Analysis in ThingSpeak to analyze the maximum and minimum temperature. This example also shows you how to set up an email alert if the room temperature exceeds a threshold value, by using MATLAB functions in ThingSpeak.
Classify and Count Fruits Using Arduino Nano 33 BLE Sense, ThingSpeak, and Machine Learning
Collect RGB values of three types of fruits using the APDS9960 sensor embedded in an Arduino® Nano 33 BLE board and use the MATLAB® 분류 학습기 (Statistics and Machine Learning Toolbox) app to train a machine learning model with the RGB values to classify the fruits. This example also shows how to use the ThingSpeak™ platform for tracking the number of fruits in a box and setting up an email alert if the number of any one of the three types of fruits drops to zero.
Identify Shapes Using Machine Learning on Arduino Nano 33 BLE Sense Hardware
Use MATLAB® Support Package for Arduino® Hardware to identify shapes using a machine learning algorithm. This example uses the Arduino Nano 33 BLE Sense hardware board with an onboard LSM9DS1 inertial measurement unit (IMU) sensor.
Human Activity Recognition Using ESP32 Board and LSM9DS1 IMU Sensor
Classify and predict one of three different physical human activities: Sitting, Standing and Walking based on data acquired using an ESP32 board and an lsm9ds1 sensor. This example uses 분류 학습기 (Statistics and Machine Learning Toolbox) app to train a machine learning model with the sensor data. To access all the files for this example, click Open Live Script and download the attached files.
Perform Predictive Maintenance on Rotating Device Using ESP32 Board, ThingSpeak, and Machine Learning
Predict and monitor the health of a rotating device using machine learning algorithm. You can use this example for predictive maintenance of any rotating device or piece of equipment so that you can fix them before they fail.
