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 μW 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 26.89μW 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.
Titolo: | Self-Sustaining Acoustic Sensor with Programmable Pattern Recognition for Underwater Monitoring | |
Autore/i: | Mayer P.; Magno M.; Benini L. | |
Autore/i Unibo: | ||
Anno: | 2019 | |
Rivista: | ||
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/TIM.2018.2890187 | |
Abstract: | 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 μW 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 26.89μW 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. | |
Data stato definitivo: | 2020-02-12T11:23:23Z | |
Appare nelle tipologie: | 1.01 Articolo in rivista |