WiNE

Abstract

Food analytic and estimation of food nutrients have an increasing demand in recent years to monitor and control food intake and calorie consumption by individuals. Microwave ovens have recently replaced conventional cooking methods due to efficient and quick heating and cooking techniques. Users estimate the food nutrient composition by using some lookup information for each of the food's ingredients or by using applications that map the picture of the food to their pre-defined dataset. These techniques are often time-consuming and not in real-time and thus can result in low accuracy. In this paper, we present WiNE, a system that introduces a new technique to estimate food nutrient composition and calorie content in real-time using microwave radiation. Our system monitors microwave oven leakage in the time and frequency domains and estimates the percentage of nutrients (carbohydrate, fat, protein, and water) present in the food. To evaluate the real-world performance of WiNE, we build a prototype using software-defined radios and conducted experiments on various food items using household microwave ovens. WiNE can estimate the food nutrient composition with a mean absolute error of ≤ 5% and the calorie content of the food with a high correlation of ~ 0.97.