[2603.28787] Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing

[2603.28787] Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing

arXiv - AI 4 min read

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Abstract page for arXiv paper 2603.28787: Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing

Electrical Engineering and Systems Science > Signal Processing arXiv:2603.28787 (eess) [Submitted on 20 Mar 2026] Title:Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing Authors:Yongzhi Huang View a PDF of the paper titled Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing, by Yongzhi Huang View PDF HTML (experimental) Abstract:Traditional liquid identification instruments are often unavailable to the general public. This paper shows the feasibility of identifying unknown liquids with commercial lightweight devices, such as a smartphone. The key insight is that different liquid molecules have different viscosity coefficients and therefore must overcome different energy barriers during relative motion. With this intuition in mind, we introduce a novel model that measures liquids' viscosity based on active vibration. However, building a robust system using built-in smartphone accelerometers is challenging. Practical issues include under-sampling, self-interference, and the impact of liquid-volume changes. Instead of machine learning, we tackle these issues through multiple signal processing stages to reconstruct the original signals and cancel out the interference. Our approach estimates liquid viscosity with a mean relative error of 2.9% and distinguishes 30 types of liquids with an average accuracy of 95.47%. Comments: Subjects: Signal Processing (eess.SP); Artificial Intelligence (cs.AI); Computational Engineering...

Originally published on April 01, 2026. Curated by AI News.

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