Beer IoT: Reporting measurements to Azure IoT Hub

As we have now fully functioning thermal solution running on Windows 10 IoT Core it’s time to focus to other components of our beer freezing solution. Our solution measures and calculates metrics of cooling beer but it doesn’t report this data anywhere. In this blog post we will set up Azure IoT Hub for our solution so it starts reporting measurements to Microsoft Azure.

Beer IoT: Estimating beer cooling time

In my last beer IoT post we measured out cooling rate of beer. In this post we try to estimate how long it takes for beer to start freezing. It’s actually simple calculation and we add it to our beer IoT background service before we focus on data reporting and persisting questions.

Beautiful cross-browser equations with MathJax

Some posts about my IoT solution that helps me to cool eisbock beer to freezing needed mathematical equations. I know I can use poorly supported MathML or bitmap images but both of these solutions come with problems. I tried to find some better solution and found MathJax.

Beer IoT: Making cooling rate calculation testable

My previous beer IoT post introduced how to measure cooling rate of beer. As I introduced the first calculation there I implemented it in code the way it just works and gets calculations done. Now it’s time to focus on the implementation and make some small improvements that clean up code and improve technical design.

Beer IoT: Measuring cooling rate

As thermal sensors are connected and we have code to read temperatures it’s time to get serious and start real work on supporting the cooling process of eisbock. We start with measuring temperatures, calculating cooling rate and estimating how long it takes for beer to freeze. This post focuses on cooling rate.

Beer IoT: Moving to ITemperatureClient interface

My previous blog post “Measuring temperature with Windows 10 IoT Core and Raspberry Pi” introduced you my simple solution for measuring temperatures. In this blog post we go step further and make some modifications to solution architecture so we don’t have to keep sensors connected all the time and as a result we can also emulate temperatures and situations that are not easy to produce in home or office.

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