June 14, 2016

Case Study: The Cocktail Mixer Using IoT and Machine Learning Tools

Case Study: The Cocktail Mixer Using IoT and Machine Learning Tools

Building a cocktail mixer using the Internet of Things and machine learning techniques sounds like fun. However, take into account that the team had only 48 hours of hackathon to create the Proof of Concept, and they’ve managed to build a network of smart connected devices using machine learning tools. Looking ahead, Ciklum’s IoT team became an overall Winner of the Garage48, a 48-hour IoT & Machine Learning Hackathon.

Read below, how the team has managed to build a cocktail mixer using IoT and machine learning techniques in 48 hours, and why this network may bring benefits to your business.

What is this?

In general, the scheme of Scoofy network may be reflected in the following way:


How it works

Ciklum’s IoT team has named it “Project Scoofy”, a network of smart connected devices that knows what is best especially for you. It may be applied to coffee machines which memorize your choice and mix coffee as you like, or you can make cocktails for your friends during the party according to their favorite taste list. In simple words, every time you use the system, it memorizes your choice. Next time, as soon as you approach the machine, it recognizes you by the NFC tag of your smartphone and starts making your preferred drinks.


  1. When the user comes up to the smart device supporting ScoofyNet, he or she should authorize and connect to the machine to get personalized service. To simplify this process and make it seamless to the user, Ciklum’s IoT team has implemented the automatic reading of the unique BLE modules identifier in our smartphones or wearables, or NFC tag.
  2. Then the Scoofy device sends this identifier to the cloud over CloudMQTT service, and the system recognizes this person, and recovers all its tastes and preferences from the database.
  3. The system sends back to the Scoofy device (cocktail mixer, coffee machine or any other device) the data with personalized instructions and preferences. These instructions are created by the smart algorithms based on machine learning and big data analytics deployed in the cloud.
  4. As a result, smart Scoofy device will work according to the user’s tastes and preferences.


How can you apply it for your benefit?

The network may be applied not only for smart cocktail mixing or coffee making. It can also be applied in the office spaces for smart air conditioner, adjusting comfortable temperature when you enter the room. Using the mobile app, the user can compose and store the favourite drink recipes, or try the drinks which are suggested by the smart algorithm. The mobile app can be also integrated with any third-party payment systems for the users to purchase drinks directly.
The solution can be integrated with social networks, so you can taste the drinks liked or suggested by your friends. The analytics module will build consumption visualizations for the admin to study user preferences, control product sale and will notify when restock is needed.

Need an advice on how the network of smart connected devices may bring benefits to your business? Contact us today.