Beer IoT

I have RaspberryPi 2 with Windows 10 IoT Core and I plan to use it for some brewing activities. In this blog post I introduce how to measure temperature with RaspberryPi using DS18B20 thermal sensors. This post is also example about how easy it is to get started with your IoT stuff using Microsoft tooling.

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.

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.

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.

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.

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.

When cooling beer we want to store history of temperatures for two reasons. First, it gives us valuable history data for next cooling sessions. As a second thing we can ask measurements when we temporarily lost connection with IoT Hub. In this posting we make some analyzis and then build up database for our beer cooling solution.

We are eager to try out our beer cooling solution and we want to see it in action. We want to visualize our data and keep eye on temperature of cooling beer. Before doing anything more complex like building web or mobile app we make a quick shortcut and bring our data to web, desktop and mobile. This post is about Power BI in action.

Our beer cooling solution is not controllable through IoT Hub and it reports data there. We can control our device through simple command line application but it is not enough for us. In this post we start building Universal Windows Application that helps us monitor temperatures. In this post we focus on mobile application.