Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring

International audience This paper presents a mixed analog-digital alwayson ultra low-power wake-up based on pulse pattern analysis. It is used for triggering a high performance multi-channel recorder only when necessary. Its architecture makes the most of ultralow power analog primitives coupled wit...

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Main Authors: Marzetti, Sebastián, Gies, Valentin, Barchasz, Valentin, Best, Paul, Paris, Sébastien, Barthelemy, Hervé, Glotin, Hervé
Other Authors: Institut des Matériaux, de Microélectronique et des Nanosciences de Provence (IM2NP), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon) (LIS)
Format: Conference Object
Language:English
Published: HAL CCSD 2021
Subjects:
Online Access:https://hal.science/hal-03610009
https://hal.science/hal-03610009/document
https://hal.science/hal-03610009/file/2020%20-%20CONF%20IEEE%20-%20Sperm%20Whales%20Detector.pdf
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record_format openpolar
spelling ftunivaixmarseil:oai:HAL:hal-03610009v1 2024-04-21T08:12:21+00:00 Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring Marzetti, Sebastián Gies, Valentin Barchasz, Valentin Best, Paul Paris, Sébastien Barthelemy, Hervé Glotin, Hervé Institut des Matériaux, de Microélectronique et des Nanosciences de Provence (IM2NP) Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS) Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon) (LIS) Bali, Indonesia 2021-01-27 https://hal.science/hal-03610009 https://hal.science/hal-03610009/document https://hal.science/hal-03610009/file/2020%20-%20CONF%20IEEE%20-%20Sperm%20Whales%20Detector.pdf en eng HAL CCSD hal-03610009 https://hal.science/hal-03610009 https://hal.science/hal-03610009/document https://hal.science/hal-03610009/file/2020%20-%20CONF%20IEEE%20-%20Sperm%20Whales%20Detector.pdf info:eu-repo/semantics/OpenAccess 2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS) https://hal.science/hal-03610009 2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS), Jan 2021, Bali, Indonesia Ultra Low-Power Always-on Wake-up Pattern Detection Embedded Artificial Intelligence Biosonar pulse train [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics [SDE.BE]Environmental Sciences/Biodiversity and Ecology [SPI.AUTO]Engineering Sciences [physics]/Automatic [SPI.TRON]Engineering Sciences [physics]/Electronics info:eu-repo/semantics/conferenceObject Conference papers 2021 ftunivaixmarseil 2024-03-28T01:08:54Z International audience This paper presents a mixed analog-digital alwayson ultra low-power wake-up based on pulse pattern analysis. It is used for triggering a high performance multi-channel recorder only when necessary. Its architecture makes the most of ultralow power analog primitives coupled with an embedded digital low power system for fine tuning the pulse detector in order to maximise its efficiency. Such system allows long term biodiversity study, as most of the bioacoustic energy is pulsed. As an example, a case study demonstrates on real sperm whale biosonar the efficiency of our system. Architecture and features extraction using analog primitives are first detailed, followed by embedded digital implementation of the automatic gain control for the pulse detector. Always-on current consumption of this intelligent wakeup is 14µA, with an area under the ROC curve equal to 75%. This allows an autonomy of 2 years on a single CR2032 battery cell. Conference Object Sperm whale Aix-Marseille Université: HAL
institution Open Polar
collection Aix-Marseille Université: HAL
op_collection_id ftunivaixmarseil
language English
topic Ultra Low-Power
Always-on Wake-up
Pattern Detection
Embedded Artificial Intelligence
Biosonar
pulse train
[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SPI.AUTO]Engineering Sciences [physics]/Automatic
[SPI.TRON]Engineering Sciences [physics]/Electronics
spellingShingle Ultra Low-Power
Always-on Wake-up
Pattern Detection
Embedded Artificial Intelligence
Biosonar
pulse train
[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SPI.AUTO]Engineering Sciences [physics]/Automatic
[SPI.TRON]Engineering Sciences [physics]/Electronics
Marzetti, Sebastián
Gies, Valentin
Barchasz, Valentin
Best, Paul
Paris, Sébastien
Barthelemy, Hervé
Glotin, Hervé
Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
topic_facet Ultra Low-Power
Always-on Wake-up
Pattern Detection
Embedded Artificial Intelligence
Biosonar
pulse train
[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SPI.AUTO]Engineering Sciences [physics]/Automatic
[SPI.TRON]Engineering Sciences [physics]/Electronics
description International audience This paper presents a mixed analog-digital alwayson ultra low-power wake-up based on pulse pattern analysis. It is used for triggering a high performance multi-channel recorder only when necessary. Its architecture makes the most of ultralow power analog primitives coupled with an embedded digital low power system for fine tuning the pulse detector in order to maximise its efficiency. Such system allows long term biodiversity study, as most of the bioacoustic energy is pulsed. As an example, a case study demonstrates on real sperm whale biosonar the efficiency of our system. Architecture and features extraction using analog primitives are first detailed, followed by embedded digital implementation of the automatic gain control for the pulse detector. Always-on current consumption of this intelligent wakeup is 14µA, with an area under the ROC curve equal to 75%. This allows an autonomy of 2 years on a single CR2032 battery cell.
author2 Institut des Matériaux, de Microélectronique et des Nanosciences de Provence (IM2NP)
Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)
Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon) (LIS)
format Conference Object
author Marzetti, Sebastián
Gies, Valentin
Barchasz, Valentin
Best, Paul
Paris, Sébastien
Barthelemy, Hervé
Glotin, Hervé
author_facet Marzetti, Sebastián
Gies, Valentin
Barchasz, Valentin
Best, Paul
Paris, Sébastien
Barthelemy, Hervé
Glotin, Hervé
author_sort Marzetti, Sebastián
title Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
title_short Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
title_full Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
title_fullStr Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
title_full_unstemmed Ultra Low-Power Always-On Wake-Up by Pulse Pattern Adaptive Recognition for Long Term Biodiversity Monitoring
title_sort ultra low-power always-on wake-up by pulse pattern adaptive recognition for long term biodiversity monitoring
publisher HAL CCSD
publishDate 2021
url https://hal.science/hal-03610009
https://hal.science/hal-03610009/document
https://hal.science/hal-03610009/file/2020%20-%20CONF%20IEEE%20-%20Sperm%20Whales%20Detector.pdf
op_coverage Bali, Indonesia
genre Sperm whale
genre_facet Sperm whale
op_source 2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS)
https://hal.science/hal-03610009
2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS), Jan 2021, Bali, Indonesia
op_relation hal-03610009
https://hal.science/hal-03610009
https://hal.science/hal-03610009/document
https://hal.science/hal-03610009/file/2020%20-%20CONF%20IEEE%20-%20Sperm%20Whales%20Detector.pdf
op_rights info:eu-repo/semantics/OpenAccess
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