Development & evaluation of a ML concept for a "human understanding" coffee machine
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.
- Review of the state of the art & science on AI/ML processes for suitability in the field of coffee preparation, as well as for human taste perception & assessment.
- Evaluation of existing data and collection of additional data needed to validate the approach.
- Data analysis using ML algorithms to search for patterns in the collected data and, if necessary, collection of further data
- Extensive and visual processing of the results from the data analysis
- Determination of the influence of recipe parameters on context-triggered taste evaluations
- Interest in the development and evaluation of AI/ML systems
- Solid programming skills (C++ and/or Python)
- Experience in implementing own SW on HW
- Reliable and independent way of working
- Interest in coffee, data analysis and data collection