Developing & building a data acquisition system for an AI-based "human-understanding" coffee machine.

Context

Coffee is one of the most consumed beverages - not only in Germany - but worldwide. To get back on track after a hard night's sleep, the only thing that helps us the next morning is a suitably strong coffee. How nice would it be if the machine could recognize this automatically and serve us an individual coffee - matching our personal state of health? The foundation to make this vision come true will be worked out in this thesis - by developing a demonstrator. WMF GmbH is one of the leading manufacturers of professional coffee machines and has dominated the market for several years through innovations. WMF is very interested in bringing their machines - through the integration of AI - to the next level.

Tasks

• Review of the state of the art for the selected functionality, AI/ML processes and the topic of coffee
• Design of a concept for data acquisition and communication of all components
• Integration of the machine into the ITIV network and payment system
• Development & implementation of a HMI (contacting/recognition of potential customers)
• Connection of an existing image processing system for the classification of human emotions
• Implementation of a feedback function for consumers
• Acquisition of environmental parameters and user profiles for the system
• Implementation of the selected system in a demonstrator

Requirements

• Interest in the development of AI/ML systems
• Sound programming skills (C++ and/or Python)
• Experience in implementing own SW on HW
• Reliable and independent way of working
• Interest in coffee, image processing techniques, data analysis and data collection