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Given the increasing amount of time people spent on driving, the physical and mental health of drivers is essential to road safety. Breathing patterns are critical indicators of the well-being of drivers on the road. Existing studies on breathing monitoring require active user participation of wearing special sensors or relatively quiet environments during sleep, which are hardly applicable to noisy driving environments. In this work, we propose a fine-grained breathing monitoring system, BreathListener, which leverages audio devices on smartphones to estimate the fine-grained breathing waveform in driving environments. By investigating the data collected from real driving environments, we find that Energy Spectrum Density (ESD) of acoustic signals can be utilized to capture breathing procedures in driving environments. To extract breathing pattern in ESD signals, BreathListener eliminates interference from driving …