@ARTICLE{10135123,
  author={Huang, Yongzhi and Chen, Kaixin and Zhao, Jiayi and Wang, Lu and Wu, Kaishun},
  journal={IEEE Transactions on Mobile Computing}, 
  title={Beverage Deterioration Monitoring Based on Surface Tension Dynamics and Absorption Spectrum Analysis}, 
  year={2023},
  volume={},
  number={},
  pages={1-18},
  abstract={Biochemical information sensing has always been one of the challenges in ubiquitous sensing research for mobile computing. Microorganisms will cause undetectable deterioration in drink production, such as wine and beverage, and microbial contamination is highly susceptible during storage like some liquors can be bottled for sometimes over ten years. Microbial culture methods are common for quality monitoring but unsuitable for real-time beverage quality monitoring. As far as we know, we are the first to use ubiquitous sensing for real-time microbial contamination detection. We designed a lightweight monitoring system called Microbe-Radar, which uses light signals to monitor real-time beverage quality. Microbe-Radar uses eight LEDs and a photodiode to detect fine-grained surface tension and absorption spectrum changes caused by microbial metabolites and growth during deterioration. Characteristic offset degree measurement and absorption spectrum dimension expansion are two critical technologies. Moreover, we implemented countermeasures against ambient light noise and sloshing interference. Microbe-Radar's surface tension and absorption spectrum measurement errors are only 0.89 mN/m and 2.4%, respectively, making identifying the contamination duration, microorganism content, and microorganism composition worthwhile. Experiments showed Microbe-Radar could determine potential issues with liquor quality when the liquid becomes health-threatening or even just contaminated, with an accuracy of 97.5%. Microbe-Radar can also be extended to beverage deterioration warning, with deterioration prediction accuracy of more than 90.6% for five beverages (milk, apple juice, etc.).},
  keywords={},
  doi={10.1109/TMC.2023.3279837},
  ISSN={1558-0660},
  month={},}