Personalized coffee consumption analysis system
BeanBook's Year in Review feature generates multi-dimensional consumption reports based on the coffee record data accumulated by users throughout the year, using statistical analysis algorithms. The system tracks the following core metrics:
- Total quantity of coffee consumed and change in trend
- Preferred origin and species distribution
- Correlation between brewing parameters and scores
- Evolution of flavor preferences
In terms of data visualization, interactive charts are used to show consumption habits, such as heat maps showing high-frequency drinking times at different times of the day, and radar charts comparing flavor ratings by category. The system also recognizes consumption patterns that users are not aware of, such as certain roasts being more popular during certain seasons.
For the technical implementation, the back-end uses a time-series database to store records and the front-end renders dynamic charts via D3.js. These insights not only enhance the user's coffee experience, but also provide purchasing decision support for professional users.
This answer comes from the articleBeanBook: an AI-powered coffee tracking and logging toolThe
