@inproceedings{10.1145/3447993.3483246,
author = {Huang, Yongzhi and Chen, Kaixin and Wang, Lu and Dong, Yinying and Huang, Qianyi and Wu, Kaishun},
title = {Lili: Liquor Quality Monitoring Based on Light Signals},
year = {2021},
isbn = {9781450383424},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3447993.3483246},
doi = {10.1145/3447993.3483246},
abstract = {In industrialized wine production, brewing and aging are two key steps. These two
processes require the liquors to be bottled for a long time, sometimes more than ten
years. The liquor is vulnerable and highly susceptible to microbial contamination
during storage, causing undetectable deterioration. During the production process,
wineries control the indoor temperature and carbon dioxide concentration to slow down
other microorganisms' reproduction speed. These methods, however, do not prevent pathogenic
microorganism growth. Currently, microbial culture methods are not suitable for real-time
liquor quality monitoring in wineries. Therefore, we have designed a lightweight monitoring
system called Lili, which uses light signals to monitor real-time liquor quality changes.
Lili detects the changes in surface tension and absorption spectrum caused by microbial
metabolites and growth during deterioration. Lili employs eight LEDs and one photodiode
to achieve fine-grained surface tension and absorption spectrum measurements. By analyzing
these changes, Lili realizes real-time quality monitoring. In this paper, the characteristic
offset degree measurement and the absorption spectrum dimension expansion are two
critical technologies. In addition, we implemented countermeasures against ambient
light noise and sloshing interference. Lili's surface tension and absorption spectrum
measurement errors are only 0.89 mN/m and 2.4%, respectively, making it useful to
identify the contamination duration, microorganism content and microorganism composition.
These two data points can be used to determine potential issues with liquor quality
when the liquor becomes health-threatening or even just contaminated, with an accuracy
of 97.5%.},
booktitle = {Proceedings of the 27th Annual International Conference on Mobile Computing and Networking},
pages = {256–268},
numpages = {13},
keywords = {modeling, fine-grained, light signal, absorption spectrum, long-term monitoring, liquor quality},
location = {New Orleans, Louisiana},
series = {MobiCom '21}
}