LiquidListener: Supporting Ubiquitous Liquid Volume Sensing via Singing Soundsopen access
- Authors
- Kim, Taewon; Park, Seohyeon; Oh, Sangeun; Kim, Hyosu
- Issue Date
- 2024
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Acoustic sensing; Acoustic sensors; Acoustics; Containers; Liquids; Medical services; Mobile handsets; mobile healthcare services; Sensors; Smart phones; smarthome applications; ubiquitous liquid volume sensing; Usability; Volume measurement
- Citation
- IEEE Access, v.12, pp 39833 - 39846
- Pages
- 14
- Journal Title
- IEEE Access
- Volume
- 12
- Start Page
- 39833
- End Page
- 39846
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73088
- DOI
- 10.1109/ACCESS.2024.3375392
- ISSN
- 2169-3536
- Abstract
- This work proposes LiquidListener, a novel liquid volume sensing method for containers. Specifically, it enables the ubiquitous measurement of liquid volume not available in existing work due to <italic>i</italic>) dependencies on dedicated sensing hardware (e.g., capacity sensors) and containers (e.g., transparent containers) and <italic>ii</italic>) a high training intensity. A key enabler of LiquidListener is listening to <italic>singing sounds</italic>. When a user taps a container using solid objects, such as pens and teaspoons, the container vibrates freely and produces a singing sound. As the container is filled with more liquid, the pitch of the sound decreases. Based on this relationship, we develop acoustic-based liquid volume sensing algorithms that support the precise measurement of liquid volume while using only a smartphone and requiring minimal user effort for calibration. The extensive experiments demonstrate that LiquidListener can support high accuracy with an average error ratio of 2.3% in sensing the liquid volume in various containers. In addition, the experimental results indicate that it can still maintain a similar level of accuracy in diverse and dynamically changing environments, even without additional calibration. Authors
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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