Diet-Aware Dining Table – A Smart Surface to Observe Tabletop Dietary Behaviors

We are what we eat. Our everyday food choices affect our long-term and short-term
health. In the traditional health care, professionals assess and weigh each individual’s
dietary intake using intensive labor at high cost. In this paper, we design and implement
a diet-aware dining table that can track what and how much we eat. To enable automated
food tracking, the dining table is augmented with two layers of weighing and RFID sensor
surfaces. We devise a weight-RFID matching algorithm to detect and distinguish how
people eat. To validate our diet-aware dining table, we have performed experiments,
including live dining scenarios (afternoon tea and Chinese-style dinner), multiple dining
participants, and concurrent activities chosen randomly. Our experimental results have
shown encouraging recognition accuracy, around 80We believe monitoring the dietary
behaviors of individuals potentially contribute to diet-aware healthcare.