智能杯：基于阻抗传感的液体摄入监测系统，用于饮料分类和新鲜度检测
Smart Cup: An impedance sensing based fluid intake monitoring system for beverages classification and freshness detection
摘要：
本文提出了一种新型的饮料摄入量监测系统，可以准确地识别饮料的种类和新鲜度。通过在商用杯子上安装碳电极，该系统测量杯子中流体的电化学阻抗谱。我们研究了电化学阻抗谱对不同饮料的频率敏感性，以及振幅，相位，实部和虚部等特征对饮料分类的重要性。结果表明，来自低频域（100 Hz至1000 Hz）的特征比高频域的特征为饮料分类提供了更有意义的信息。包括碳酸饮料和果汁在内的20种饮料使用监督机器学习方法以近乎完美的准确度进行分类。在新鲜度识别中也观察到了同样的表现，其中研究了四种不同的牛奶和果汁。
英文摘要：
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.
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