Affiliation:
1. The University of Tokyo, Interactive Intelligent Systems Laboratory, Hongo, Bunkyo-ku, Tokyo, Japan
Abstract
Inappropriate alcohol drinking may cause health and social problems. Although controlling the intake of alcohol is effective to solve the problem, it is laborious to track consumption manually. A system that automatically records the amount of alcohol consumption has a potential to improve behavior in drinking activities. Existing devices and systems support drinking activity detection and liquid intake estimation, but our target scenario requires the capability of determining the alcohol concentration of a beverage. We present Al-light, a smart ice cube to detect the alcohol concentration level of a beverage using an optical method. Al-light is the size of 31.9 x 38.6 x 52.6 mm and users can simply put it into a beverage for estimation. It embeds near infrared (1450 nm) and visible LEDs, and measures the magnitude of light absorption. Our device design integrates prior technology in a patent which exploits different light absorption properties between water and ethanol to determine alcohol concentration. Through our revisitation studies, we found that light at the wavelength of 1450 nm has strong distinguishability even with different types of commercially-available beverages. Our quantitative examinations on alcohol concentration estimation revealed that Al-light was able to achieve the estimation accuracy of approximately 2 % v/v with 13 commercially-available beverages. Although our current approach needs a regressor to be trained for a particular ambient light condition or the sensor to be calibrated using measurements with water, it does not require beverage-dependent models unlike prior work. We then discuss four applications our current prototype supports and future research directions.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction
Cited by
25 articles.
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