This project initially began in the Boston University Spark! Innovation Fellowship Program, with early development done on a Flair Classic with a Pressure Kit.
The Problem – Pressure Profiling
Great tasting espresso is hard to make, especially for a home user without access to expensive equipment. Among the many variables that go into making espresso, the applied pressure to the coffee is an important one for ensuring consistency and reproducibility between each shot. And while there are some current solutions for tracking pressure, they are cost prohibitive for the majority of users.
The Idea – Computer Vision Tool
To use a smartphone selfie camera to take a video of the pressure gauge while making espresso, and then utilize a computer vision algorithm to extract the pressure values from the video.
Our team has developed a computer vision algorithm that converts a video of an analog pressure gauge to digital values by using the selfie camera on a smartphone without the need for additional equipment.
We also began the development of a companion journaling app so that users can track each shot and more easily reproduce their favorite shots. This app is intended to help users decrease waste, reduce frustration, and have a more enjoyable experience when making espresso at home.
Future features include the ability to provide recommendations to users based on the qualitative and quantitative factors that they are tracking for each shot of espresso, as well as provide a platform and educational system that would help guide new espresso makers through the detailed process of making high quality espresso. This would be achieved by incorporating existing content from the espresso community, in addition to providing a set of guiding principles for new espresso makers to follow and experiment with.
Additional features include the ability for users to share their recipes with others, as well as allowing cafes and roasters to provide recommended recipes and profiles for their own beans.