Automatic Classification of Daily Fluid Intake

Despite the potential health benefits of being able to monitor and log one’s food and drink intake, manually performing this task is notoriously hard. While researchers are still exploring methods of automating this process for food, less work has been done in automatically classifying beverage intake. In this paper, we present a novel method that utilizes optical, ion selective electrical pH, and conductivity sensors in order to sense and classify liquid in a cup in a practical way. We describe two experiments, one that uses a high end commercial off-the-shelf spectrometer, and the other which uses a cheap sensor package that we engineered. Results show both that this method is feasible and relatively accurate (up to 79% classification for 68 different drinks), but also that we would be able to build this in such a way as to make it practical for real-world deployment. We describe the vision for building a sensor rich cup capable of determining the kind of liquid a person is drinking, as well as the opportunities that the success of such sensors may open.

PDF file

In  Pervasive Health 2010 Proceedings

Publisher  IEEE
© 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.


> Publications > Automatic Classification of Daily Fluid Intake