 Hello, I'm Enrico Gregorato, Applications Engineer at ST Microelectronics. Thank you for joining me today for this demo on connecting the Sensitile Wireless Industrial Node to Azure IoT Central. In this demo, we will show how to connect ST's Sensitile Wireless Industrial Node, STWIN, with the Wi-Fi expansion to Azure IoT Central using the Azure One function pack. The STWIN and Azure One function pack are just a small part of a large ecosystem offered by ST to help you quickly and easily develop and ship your IoT solution. The STWIN is a small form factor board powered by an ultra-low power STM32 microcontroller and is packed with ST's industrial motion and environmental sensors. The Azure One function pack features all the drivers, middleware and sample applications needed to connect the STWIN to Azure and send live sensor data to the cloud. An Azure IoT Central application is provided to allow you to view the data being uploaded and to control the board from the cloud. The Azure One function pack webpage on ST.com includes a quick start guide with instructions on assembling the board, flashing a pre-compiled binary of the Azure One application and configuring the serial terminal to communicate with the board. We connect to the board via the serial port called STMicroelectronics STLink Virtual Comport. To view the output, you may need to reset the board. The board comes pre-provisioned with default Wi-Fi credentials. We will replace these and also provide credentials for connecting to Azure IoT Central. To obtain credentials for Azure IoT Central, we will use the link provided in the function pack documentation to instantiate the app within our Azure account. We can provide a custom name and select a pricing plan. With our application instantiated, I can add a new device. Select Sensitile Industrial Node and click on new. I will leave all of these parameters as they are and our Sensitile has now been instantiated inside our app. To access the device, I can click on the device name. Right now, there is no information being shown for this device and that is because the device has not yet connected to Azure IoT Central. To do this, we need to provision it. All the information required to provision the device with credentials to connect to your app is available under the connect button. Here we have the ID scope, the device ID and the primary key. These will be pasted into the serial terminal. We start with the ID scope. For automatic group enrollment, I will select no. Then the device ID. And finally, the primary key. The device will now attempt to connect to Azure IoT Central. We should shortly see information appearing in the screen. The device will now connect to Azure IoT Central. There we go. We now have information displaying about the board and we're waiting for some sensor data to arrive. This might take a few seconds. The app has started to receive sensor data from the board. We can now explore other features available in the app. For example, if we click on raw data, we can see all the telemetry and property messages being sent from the board to the app. We can expand one of the messages to view which sensor has sent the data and what the values are. In the telemetry tab, we can see graphs of the values being sent from the various sensors on the board. Last but not least, in the commands tab, we can see that we're able to issue commands and send them down to the board. For example, if we consider the accelerometer, which is part of the ISM330DHCX, we can see that the full scale is currently set to 2G. Let's suppose we want to change that. We can go to the commands tab, find the accelerometer, full scale, change the setting, for example, to 16G. We can see that the accelerometer full scale has been now set to 16G. Another interesting feature is the ability to export data being uploaded by the board. In order to do this, you need an Azure Storage account with a PNG of 16G. We can see that the accelerometer has been now set to 16G. Another interesting feature is the ability to export data being uploaded by the board. In Azure Storage account with a blob container, I've already pre-configured one for this demo. Entering data export, we need to create a destination. Provide a destination name, select the destination type as blob storage, and then we'll need to provide a connection string and a container name. These can be obtained from your storage account. Once we have created the destination, select the type of data to export, which can be telemetry or properties, we'll leave it as telemetry in this case, and then choose the destination, which we've just configured. Once the export has been set up, we can go and see the status of the export. When the export is ready, it will be in the healthy state. If we return to our storage container, we can see that data is being saved in the container. For example, if we view the contents of this file, we can see that there is sensor data that was uploaded by the board. This can be useful if you want to download this data for analysis offline. That concludes the demo for today. For more information on the STWIN or the Function Pack Azure 1, please refer to our website, www.st.com. Thank you for your time.