This paper addresses the optimisation issue of beverage and food preparation in terms of sustainability, nutrition and taste. The research is based on the architecture for CONtext-aware Food and bEverage preparation Systems. To validate the proposed architecture, a Data Acquisition system for a CONtext-aware Fully Automated Coffee machine was designed and implemented to collect experimental data. This paper details the development of the system, the experimental setup and procedure, the dataset obtained, and an initial analysis of the collected data. The collected data will serve as a basis for further research, the aim of which is to understand which parameters have a significant influence on the preferred Coffee-to-Water Ratio - which directly has an influence on the ecological footprint of coffee - of consumers in different context settings. The research findings contribute to the development of intelligent and context-aware pervasive systems in the domain of sustainable and nutritious food and beverage preparation.