Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection
dc.contributor.author | Garg, Nakul | |
dc.contributor.author | Takawale, Harshvardhan | |
dc.contributor.author | Bai, Yang | |
dc.contributor.author | Shahid, Irtaza | |
dc.contributor.author | Roy, Nirupam | |
dc.date.accessioned | 2023-09-14T17:03:21Z | |
dc.date.available | 2023-09-14T17:03:21Z | |
dc.date.issued | 2023-05-09 | |
dc.description.abstract | Acoustic sensing has conventionally been dependent on highfrequency sampling of analog signals and frequency domain analysis in digital domain which is power-hungry. While these techniques work well for regular devices, low-power acoustic sensors demand for an alternative approach. In this work, we propose Lyra, a novel low-power acoustic sensing architecture that employs carefully designed passive structures to filter incoming sound waves and extract their frequency components. We eliminate power-hungry components such as ADC and digital FFT operations and instead propose to use low-power analog circuitry to process the signals. Lyra aims to provide a low-power platform for a range of maintenance-free acoustic event monitoring and ambient computing applications. | |
dc.description.uri | https://doi.org/10.1145/3576914.3589562 | |
dc.identifier | https://doi.org/10.13016/dspace/ovsp-vcrl | |
dc.identifier.citation | Nakul Garg, Harshvardhan Takawale, Yang Bai, Irtaza Shahid, Nirupam Roy. 2023. Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection. In Cyber-Physical Systems and Internet of Things Week 2023 (CPS-IoT Week Workshops ’23), May 09–12, 2023, San Antonio, TX, USA. ACM, New York, NY, USA, 7 pages. | |
dc.identifier.uri | http://hdl.handle.net/1903/30486 | |
dc.language.iso | en_US | |
dc.publisher | Association for Computer Machinery (ACM) | |
dc.relation.isAvailableAt | College of Computer, Mathematical & Natural Sciences | en_us |
dc.relation.isAvailableAt | Computer Science | en_us |
dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_us |
dc.relation.isAvailableAt | University of Maryland (College Park, MD) | en_us |
dc.subject | low-power sensing | |
dc.subject | IoT | |
dc.subject | ambient sensing | |
dc.subject | ambient computing | |
dc.subject | acoustic metamaterial | |
dc.subject | spectral sensing | |
dc.subject | structural filters | |
dc.subject | passive computing | |
dc.title | Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection | |
dc.type | Article | |
local.equitableAccessSubmission | No |
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