PowerPhone: Unleashing the Acoustic Sensing Capability of Smartphones
Shirui Cao, Dong Li, Sunghoon Ivan Lee, Jie Xiong
摘要
Acoustic 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 smartphones. First, we improve the sensing resolution from 7 𝑐𝑚 to 1 𝑐𝑚 and enable multi-finger gesture recognition on smartphones. 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.
• Human-centered computing → Ubiquitous and mobile computing systems and tools.
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