 OK, so so we've now shown you all the different aspects of the node and how to get the information. Different networks like sigfox so the last element of the workshop is to now transfer that information up to the cloud so we have randomly chosen Microsoft Azure to do this so we've had a bit of help from one of the Microsoft people to generate a nice web page for us. And a little application that ports the information from our conduit up to the cloud. So what we're doing inside our laptop that's connected to our gateway is this so our node is sat there. Talking to our. Multitech gateway so we can see the information appearing in the debug window of our application server on our laptop here that's connected to the gateway also included inside the Multitech gateway is an MQTT broker. So so this is going to send us the information up to the cloud, but to do that we'll need an MQTT client to do that so the client has to talk to the broker so on the PC we have a little application running called STM Laura to Azure.exe and this is providing our interface so that we can send the data up to the cloud. Also running on the PC we have a device explorer and that is monitoring what's going on on the cloud and configuring the cloud side of things so that we can see what's actually happening on the Azure side. Then we can log into a web address. And from any laptop around the world and we can actually see the information that our node is creating. For the temperature readings, wherever we are around the world so to do this will first have an introduction of the cloud services from the Microsoft engineer so I have a small video that we can run which will explain. What goes on and what features are available inside the Microsoft Azure. Hi, my name is Stepan Bechinsky and I'm technical consultant at Microsoft and I am responsible for Internet of Things in central and east Europe. Congratulations. You just finished the first part of potential IoT solution. You know how to connect your Lora device to Lora network service to send the data from the sensors. What can be the next step? The next step can be cloud. The question is why to use the cloud? Think about this. Imagine you are getting data from the Lora device every single second. It creates more than 31 and a half million of the records in a year and imagine you can have a couple of hundreds or maybe thousands of devices. What you need is to process and analyze big data. In cloud solution you have almost infinite compute power so you can really analyze huge amount of data. You can store it. You can visualize the data and you can use some advanced technologies like machine learning and artificial intelligence. So the second step for your solution is probably connect your Lora network service to cloud. The typical solution is that the Lora network service is connected directly to cloud or it can be connected through another computer called gateway. Every IoT solutions we can split into three parts. The first part is responsible for device connectivity. This part you have almost done. So what you have? You have your device and the device is connected to some gateway. So the next step is to connect the gateway to the cloud. The cloud gateway, which is this part is responsible for device communication. So using the cloud gateway, you typically can speak to devices and treated data from the devices. Second part of every IoT solution is responsible for storing data, processing data and data analytics. And of course very important part here is something called device management. So using device management you can update firmware in your devices. For example, you can provision a new devices. You can store the information and metadata about your devices. The last part of the solution is of course about presenting data to your customers. In this part is very important not just to show some simple charts or stuff like that. It's very important to connect data from the sensors to existing business system. Like SAP, Microsoft Dynamics and so on. Because customers and people want to use their existing solutions. They don't want to learn something new. In Microsoft Azure it can look like this. So Microsoft Azure is a cloud provided by Microsoft. And we are supporting a lot of things related to IoT. So first we have the service which is called IoT Hub. The IoT Hub is service which is responsible with bidirectional device communication. And it is responsible for device management. Using stream analytics you can analyze data in real time. Using DocumentDB you can store almost infinite amount of the data. And the last part of our solution is Azure Function. And the Azure Function can be used to present data. Or you can use it to connect data to another systems like SAP. This is very basic IoT solution you can use. And the result looks like this. This is the chart showing real time data from Lora devices connected to network service. Everything runs in the cloud. So you can visualize data from thousands of devices. And it will scale automatically. And you will not need to run your own data center. Thank you for attention and enjoy your training. If we now go back to our laptop that's connected to the multi-tech gateway. We can now go and open our MQTT client. Which is that one there. And we can go and see the information that we need to put in there. If I bring that down a bit. So we need to put in the IP address of our gateway. Which is 192.168.2.1. And then we need a connection string for the device that we want to monitor inside our gateway. That we want to upload to the cloud. To do that we need to go and register our device on the cloud. So this is where we need our device explorer application software. I'll wait for my screen to refocus. And in here we can go to the management of our device. So here we can see all the devices that are currently registered on the cloud. And my device I believe is the second one down there. If I check with my terminal window. I go back to my terminal window. And my address ends 850D. Which is line 2 of that list. So if I right click on that one. Copy the connection string. And paste that into there. And now start my MQTT client. So this should now send information from the device that has that connection string up to the cloud. So the sensor now is designed to be about every 90 seconds. So we will have to wait for it to appear. Whilst we're waiting for that. In my cloud screen. I can now go monitor the data. Select the board that I'm interested in. Which is 850D. And now I can monitor actually what's going on on the cloud as well. So I'm waiting for receiving events. So you can see my client has sent an event now. And there you can see I've had the response back from the cloud. And now that piece of information has gone up to the cloud. So therefore now that piece of information should be available for my graph to go and have a look at. So if I now go back to the graph. If I go and open the link that we had for our graph. I click on that. It should now go off and open the correct web page. And you can see today's date is the 20th of the 12th at 2.15 or 2.14. You can see that I had a value of 26 degrees. And the value that I've just sent to the cloud was 26 degrees. I've now had a value of 27 degrees that's gone up to the cloud. So I've now had two values that have appeared on the cloud. And if I now wait for my web page to refresh. It should automatically refresh. We should see the change. There we go to 27 degrees hopefully yes. So if I now go back and wait for another variable to come in. There we go. So a third variable has come in now. So we're now back to 26 degrees again. So I will move my board to somewhere a little warmer near my laptop exhaust fan again. And hopefully we should get some higher temperature readings in a few minutes. And if we go back to our graph. You can see there the 26 degrees has come in. And fingers crossed when the next value comes in. We should get a large increase in temperature. As my board is now being warmed by the exhaust fan of the laptop. So we've now jumped up the temperature. I can see on the gateway screen to 38 degrees. So we can now have a value of 38 degrees that's gone through. And it will take a few seconds for our graph to come in for 38 degrees. And one of the benefits of the cloud services once you've set it up. The graph will auto scale as you can see there. And it's now loaded the new temperature information into the graph. So whatever information you're sending from your node to your gateway. You can then find a way of transferring that up to the cloud. And anyone around the world can now view this information with that web address that we have on the Azure website. Thank you.