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http://hdl.handle.net/10397/96067
Title: | HearLiquid : nonintrusive liquid fraud detection using commodity acoustic devices | Authors: | Yang, YN Wang, YW Cao, JN Chen, JL |
Issue Date: | 1-Aug-2022 | Source: | IEEE internet of things journal, 1 Aug. 2022, v. 9, no. 15, p. 13582-13597 | Abstract: | Liquid fraud has plagued people with huge health risks. Liquid fraud detection can help to reduce the risk of liquid hazards. However, existing systems that use biochemical tools or radio frequency signals for liquid sensing are either expensive, intrusive, or inconvenient for public use. In this article, we propose HearLiquid, a low-cost and nonintrusive liquid fraud detection system using commodity acoustic devices. Our insight comes from the fact that acoustic impedance of different liquids results in distinct absorption of the acoustic signal across different frequencies when it travels through the liquid. In specific, we extract the liquid’s acoustic absorption and transmission curve (AATC) over multiple frequencies of the acoustic signal for liquid fraud detection. However, accurately measuring the AATC faces multiple challenges. First, due to the hardware diversity and imperfection, different acoustic devices introduce diverse frequency responses, which brings significant deviations to AATCs of the same liquid. Second, different relative positions between acoustic devices and the liquid container result in variations in the AATC, making the detection result inaccurate. To overcome these challenges, we first calibrate the AATC using a dedicated reference AATC to remove the effect of hardware diversity. To bear the variations in AATCs measured from different relative positions, we apply a well-orchestrated data augmentation technique to automatically generate sufficient AATCs for different positions using a small number of collected data. Finally, AATCs are used to train the liquid detection model. We conduct extensive experiments on many important liquid fraud cases and achieve liquid detection accuracy of 92%–97%. | Keywords: | Acoustic absorption and transmission Acoustic signal Liquid fraud detection |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE internet of things journal | EISSN: | 2327-4662 | DOI: | 10.1109/JIOT.2022.3144427 | Rights: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Y. Yang, Y. Wang, J. Cao and J. Chen, "HearLiquid: Nonintrusive Liquid Fraud Detection Using Commodity Acoustic Devices," in IEEE Internet of Things Journal, vol. 9, no. 15, pp. 13582-13597, 1 Aug.1, 2022 is available at https://dx.doi.org/10.1109/JIOT.2022.3144427. |
Appears in Collections: | Journal/Magazine Article |
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Yang_HearLiquid_Non-intrusive_Detection.pdf | Pre-Published version | 9.22 MB | Adobe PDF | View/Open |
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