论文标题
智能杯：用于饮料分类和新鲜度检测的基于阻抗感应的液体进气口监测系统
Smart Cup: An impedance sensing based fluid intake monitoring system for beverages classification and freshness detection
论文作者
论文摘要
本文提出了一种新型的饮料摄入量监测系统，可以准确识别饮料种类和新鲜度。通过将碳电极安装在商业杯上，系统可以测量杯中流体的电化学阻抗谱。我们研究了电化学阻抗光谱频谱的频率敏感性以及振幅，相位以及真实和虚构成分诸如饮料分类之类的特征的重要性。结果表明，低频域（100 Hz至1000 Hz）的特征比较高的频域为饮料分类提供了更有意义的信息。使用有监督的机器学习方法将二十种饮料（包括碳酸饮料和果汁）分类为几乎完美的精度。在新鲜度识别中也观察到了相同的性能，其中研究了四种不同种类的牛奶和果汁。
This paper presents a novel beverage intake monitoring system that can accurately recognize beverage kinds and freshness. By mounting carbon electrodes on the commercial cup, the system measures the electrochemical impedance spectrum of the fluid in the cup. We studied the frequency sensitivity of the electrochemical impedance spectrum regarding distinct beverages and the importance of features like amplitude, phase, and real and imaginary components for beverage classification. The results show that features from a low-frequency domain (100 Hz to 1000 Hz) provide more meaningful information for beverage classification than the higher frequency domain. Twenty beverages, including carbonated drinks and juices, were classified with nearly perfect accuracy using a supervised machine learning approach. The same performance was also observed in the freshness recognition, where four different kinds of milk and fruit juice were studied.
