PowerPhone: Unleashing the Acoustic Sensing Capability of Smartphones

dc.contributor.authorCao, Shirui
dc.contributor.authorLi, Dong
dc.contributor.authorLee, Sunghoon Ivan
dc.contributor.authorXiong, Jie
dc.date.accessioned2025-04-01T14:55:18Z
dc.date.available2025-04-01T14:55:18Z
dc.date.issued2023-10-02
dc.descriptionACM MobiCom '23: Proceedings of the 29th Annual International Conference on Mobile Computing and Networking
dc.description.abstractAcoustic sensing on smartphones has gained extensive attention from both industry and research communities. Prior studies suffer from one fundamental limit, i.e., audio sampling rates on smartphones are constrained at 48 kHz. In this work, we present PowerPhone, a software reconfiguration to support higher sampling rates on both microphones and speakers of smartphones. We reverse-engineered more than 100 smartphones and found that their sampling rates can be reconfigured to 192 kHz. We conducted benchmark experiments and showcased field studies to demonstrate the unleashed sensing capability using our reconfigured smart-phones. First, we improve the sensing resolution from 7 cm to 1cm and enable multi-finger gesture recognition on smart-phones. Second, we push the sensing granularity of subtle movements to 2 μm and show the feasibility of turning the smartphone into a micrometer-level machine vibration meter. Third, we increase the sensing range to 6 m and showcase room-scale human presence detection using a smartphone. Finally, we demonstrate that PowerPhone can enable new applications that were previously infeasible. Specifically, we can detect the home appliance status by analyzing ultrasonic leakages above 24 kHz from the wireless charger while charging a smartphone. Our open-source artifacts can be found at: https://powerphone.github.io.
dc.description.sponsorshipThis work is partially supported by National Institutes of Health (NIH) under Award Number 5R01MH122371-04.
dc.description.urihttps://dl.acm.org/doi/10.1145/3570361.3613270
dc.format.extent16 pages
dc.genreconference papers and proceedings
dc.genrepostprints
dc.identifierdoi:10.13016/m2jozw-u8nv
dc.identifier.citationCao, Shirui, Dong Li, Sunghoon Ivan Lee, and Jie Xiong. "PowerPhone: Unleashing the Acoustic Sensing Capability of Smartphones." In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking, 16. ACM MobiCom 23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3570361.3613270.
dc.identifier.urihttps://doi.org/10.1145/3570361.3613270
dc.identifier.urihttp://hdl.handle.net/11603/37881
dc.language.isoen_US
dc.publisherACM
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.titlePowerPhone: Unleashing the Acoustic Sensing Capability of Smartphones
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-3144-5104

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