Step 1: Mounting WisBlock Parts
Assemble the RAK3372 WisBlock Core onto the RAK19003 WisBlock Base Board. Connect the RAK12027 vibration sensor and the RAK1906 environmental sensor to available slots. Attach the RAK1921 power module and insert an active SIM card into the RAK3372.
Step 2: Link to PC (via USB Cable)
Connect the assembled WisBlock unit (via the RAK3372) to your PC using a standard USB cable.
Step 3: Setup Arduino IDE and Load Files
Configure Arduino IDE for the RAK3372. Install necessary libraries for the RAK12027 vibration sensor (e.g., custom RAKwireless library or generic accelerometer library) and the RAK1906 (BME680). You will also need libraries for cellular MQTT communication (e.g., TinyGSM). Load the Arduino sketch designed to read vibration and temperature data and send it to Azure IoT Hub.
Step 4: Upload the Code
Select RAK3372 Board and the correct COM port. Upload the code to your WisBlock device. After successful upload, open the Serial Monitor (set Baud rate to 15200) to observe vibration readings (e.g., RMS acceleration), temperature, and cellular network status/data transmission. The device will periodically send vibration and temperature data directly via cellular to Azure IoT Hub. Azure Stream Analytics will monitor this data for anomalies (e.g., unusual vibration patterns, sudden temperature spikes), triggering alerts via Azure Logic Apps for maintenance teams, enabling predictive maintenance and preventing costly equipment failures. Power BI can be used for comprehensive data visualization.
Explanation: The code initializes the RAK3372 cellular module, the RAK12027 vibration sensor, and the RAK1906 temperature sensor. It continuously acquires vibration data (e.g., peak acceleration, RMS values) and machine temperature. This sensor data is packaged into a JSON payload and sent via MQTT over the cellular network to Microsoft Azure IoT Hub. Azure Stream Analytics processes the incoming data stream in real-time, applying rules to detect anomalies in vibration or temperature that may indicate impending equipment failure. If an anomaly is detected, Azure Logic Apps trigger alerts (e.g., email to maintenance team, create a work order in a CMMS). This enables a predictive maintenance strategy, reducing downtime, optimizing operational costs, and extending machinery lifespan.
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