Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 68, Issue 7, Pages 2346-2355Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2018.2890187
Keywords
Acoustic sensors; energy harvesting; event-driven sensors; microbial fuel cells (MFCs); underwater monitoring
Funding
- Swiss National Science Foundation projects MicroLearn: Micropower Deep Learning [162524]
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Minimizing the power consumption of always-on sensors is crucial for extending the lifetime of battery-operated devices that are required to monitor events continuously and for long periods. This paper proposes a novel programmable mu W event-driven acoustic detector featuring always-on audio pattern recognition. The event-driven detector detects up to eight programmable spectral-temporal features extracted with a low-power single-channel analog circuit and classifies the features by an onboard microcontroller. The event-driven detector is combined with novel microbial fuel cells (MFCs) to achieve self-sustainability in an underwater scenario. Experimental results demonstrate that the power consumption of the detector is only 26.89 mu W during always-on mode, achieving up to 59-dB sound pressure level of sensitivity. High detection accuracy of up to 95.89% in recognizing acoustic patterns has been experimentally verified. Accurate measurements with commercial MFCs demonstrate the capability to achieve self-sustainability in always-on monitoring.
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