Dries Van Vaerenbergh & Wouter Lemaire - Digital stories

For many of us, coffee is the fuel that keeps us going and a welcome source of support when our energy is flagging. Naturally, the nearly universal love for these aromatic beans led our research-oriented team to envision opportunities to optimise coffee maker use and maintenance. Enter SAP Leonardo IoT!

Solving two important challenges

It might seem like an unusual starting point for a machine-learning project, but we learned from our customers that coffee is top of mind. So, why not optimise the consumption of this black gold? Two important functionalities topped our list:

  • Filter maintenance prediction: most coffee machines use water filters to purify incoming water before the coffee is brewed. A sensor placed between the filter and the machine would inform people when the filter is no longer working well, based on water pressure and the time it takes for water to flow through the filter.
  • Pay by use: by measuring water flow, it’s possible to get a clear picture of how much coffee people consume, as well as the different types of coffee they choose. The amount of water used determines the type of coffee.
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Coffee with a mind of its own at SAP Belgium

Flexso Digital used a water flow sensor to quantify the amount of water moving from the supply into the coffee machine. All other variables (coffee type, filter flow-through) can be derived from this figure. The Flexso Smart Coffee Machine was born. Now for the perfect place to test it in a real-life office scenario...

After renovating its offices, SAP Belgium unveiled the SAP Experience Center, where its team gives demos of SAP technologies to customers. Flexso’s Smart Coffee Machine demo found an ideal new home there. An iPad is located next to the coffee machine, with a responsive web app that visualises coffee consumption for each user.

Behind the technological scenes

This innovative solution is made up of much more than a sensor. To get rich coffee-related insights from the machine, the team used a Raspberry Pi to send the sensor data to SAP Leonardo IoT on SCP CloudFoundry.

On top of the Leonardo IoT service, we used the flexible plugins offered by SAP Web IDE to develop a UI5 app that visualises coffee machine data. Even more, we integrated the IoT platform with an SAP backend through SAP Cloud Integration. To define the coffee type based on the amount of water used, we relied on IoT Edge processing before sending the data to the cloud.

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Streamlining coffee payment and consumption

  • A flexible IoT solution capable of analytics, onboarding and security.
  • Easy setup and customisation.
  • Users can see an intuitive, up-to-date visualisation of their coffee consumption patterns.
  • Streamlines the implementation of accurate pay-per-use models in industrial coffee machines.

Conclusion? The versatility and easy integration of SAP technologies combined with clever minds means it’s easy to make any asset intelligent – even a coffee maker!

Discover the full story and technical background at the SAP community! And if you want to add intelligence to your assets or business processes? Get in touch!

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