WiNE: Monitoring Microwave Oven Leakage to Estimate Food Nutrients and Calorie

A. Banerjee, K. Srinivasan
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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. and time-frequency domains.
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葡萄酒:监测微波炉泄漏以估计食物的营养和热量
近年来,监测和控制个人的食物摄入和热量消耗对食品营养成分的分析和估计的需求越来越大。由于加热和烹饪技术的高效和快速,微波炉最近取代了传统的烹饪方法。用户通过使用每种食物成分的查找信息或使用将食物图片映射到预定义数据集的应用程序来估计食物的营养成分。这些技术通常是耗时的,并且不是实时的,因此可能导致较低的准确性。本文介绍了WiNE系统,该系统引入了一种利用微波辐射实时估算食品营养成分和热量的新技术。我们的系统监测微波炉在时间和频率域的泄漏,并估计食物中存在的营养物质(碳水化合物,脂肪,蛋白质和水)的百分比。为了评估WiNE在现实世界中的性能,我们使用软件定义的收音机构建了一个原型,并使用家用微波炉对各种食品进行了实验。WiNE估算食品营养成分的平均绝对误差≤5%,估算食品卡路里含量的高度相关系数为~ 0.97。和时频域。
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