Overview

This code provides an example implementation of an Azure IoT Client using a Cellular data connection. The code follows the style and content of the othere examples Microsoft provides (see https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-get-started-physical) but is taliored to use the ARM Mbed OS (currently at v5.x) and the ARM Easy-Connect framework.

Generally speaking, there are two steps necessary to exercise this example code:

1. Setting up and configuring an Azure IoT Hub
2. Creating the IoT Client code and running it on the IoT End Device

This repository focues on step #2. To learn more about step #1 refer to the Element14 Web Site blog post or any of the Microsoft examples.

Hardware Used

The hardware platform used for this project consists of:

• STM32L4 Nucleo-144, Cortex-M4 development board
• Motion MEMS and environmental sensor board
• Avnet RSR1157 NBIoT BG96 Expansion Board

Note

The code used to develop this example utilized the following STM32 Nucleo-L496ZG and Quectel BG96 Module Firmware:

• BG96 Modem SW Revision: BG96 SW Revision: BG96 Rev:BG96MAR02A07M1G
• STM32L Version: 0221 / Build: May 30 2018 10:37:36

Required Software Tools

1. The mbed-cli is available from: https://github.com/ARMmbed/mbed-cli
2. Latest version of GNU ARM Embedded Tool chain, available at: https://developer.arm.com/open-source/gnu-toolchain/gnu-rm/downloads

Building the samples:

To build the Sample program, you must use the mbed command line tools (mbed-cli). This is because the on-line tools do not allow you to modify the build parameters of the compiler but when using the CLI, you are able to specify a build profile to compile with.

Command Line Steps

1. Import the azure-iot-mbed-client project:

**mbed import  https://github.com/Avnet/azure-iot-mbed-client**

2. Edit the AvnetBG96_azure_client.cpp file and correctly set your connection string and device ID¹ (lines #66 and #68):

   static const char* connectionString = "HostName=XX;DeviceId=xx;SharedAccessKey=xx"; static const char* deviceId = "xxxx"; /must match the one on connectionString/

4. Goto the azure-iot-mbed-client folder and ensure the mbed_settings.py file has the correct path to your compiler using GCC_ARM_PATH

5. Build the program by executing the command:

**mbed compile -m NUCLEO_L496ZG -t GCC_ARM --profile toolchain_debug.json**

6. The executable program will be located at: BUILD/NUCLEO_L496ZG/GCC_ARM-TOOLCHAIN_DEBUG/azure-iot-mbed-client.bin

7. Copy the executable program the Nucleo board that is connected to your PC, and once copied, press the reset button.

Execution Output

When the program is run, you will see output similar to:

The example program interacts with Azure IoTHub sending sensor data and receiving messeages (using ARM Mbed OS v5.x) [using IKS01A2 Environmental Sensor]

[EasyConnect] Using BG96
[EasyConnect] Connected to Network successfully
[EasyConnect] MAC address 19:95:91:41:02:72:20 [EasyConnect] IP address 10.192.59.128
[ Platform ] BG96 SW Revision: BG96 Rev:BG96MAR02A07M1G
[ Platform ] Time set to Tue Sep 4 20:59:13 2018

(0001)Send IoTHubClient Message@20:59:13 - OK. [RSSI=99]
(0002)Send IoTHubClient Message@20:59:25 - OK. [RSSI=17]
(0003)Send IoTHubClient Message@20:59:31 - OK. [RSSI=17]
(0004)Send IoTHubClient Message@20:59:37 - OK. [RSSI=17]
(0005)Send IoTHubClient Message@20:59:43 - OK. [RSSI=17]

Each time the a message is sent to the Azure IoT Hub, it can be displayed using the iothub-explorer monitor-events command. When used, the output will resemble:

{
  "ObjectName": "Avnet NUCLEO-L496ZG+BG96 Azure IoT Client",
  "ObjectType": "SensorData",
  "Version": "1.0",
  "ReportingDevice": "STL496ZG-BG96",
  "Temperature": 90.68,
  "Humidity": 54,
  "Pressure": 1008,
  "Tilt": 2,
  "ButtonPress": 0,
  "TOD": "Thu 2018-09-06 19:36:45 UTC"
}
---- application properties ----
{}

Time TOD stamp in the message will match the time displayed when the message is sent, e.g., the Message@<<>> will match "TOD" : "<<>>"

Next steps

After You’ve run this sample application, collected sensor data, and interacted with your IoT hub, you may want to exercise some of the other Azure IoT scenarios. See the following tutorials:

Scenario	Azure service or tool
Manage IoT Hub messages	iothub-explorer tool
Manage IoT Hub messages	VS Code Azure IoT Toolkit extension
Manage your IoT device	Azure CLI 2.0 and the IoT extension
Manage your IoT device	VS Code Azure IoT Toolkit extension
Save IoT Hub messages to Azure storage	Azure table storage
Visualize sensor data	Microsoft Power BI
Visualize sensor data	Azure Web Apps
Forecast weather with sensor data	Azure Machine Learning
Automatic anomaly detection and reaction	Azure Logic Apps

Footnotes

1. This information is available from your IoT Hub. ↩