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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ftunivtoulon:oai:HAL:hal-03610009v1 2024-06-23T07:56:58+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 ftunivtoulon 2024-06-11T00:04:07Z 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 Université de Toulon: HAL Bali ENVELOPE(-20.233,-20.233,64.067,64.067) |
institution |
Open Polar |
collection |
Université de Toulon: HAL |
op_collection_id |
ftunivtoulon |
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 |
long_lat |
ENVELOPE(-20.233,-20.233,64.067,64.067) |
geographic |
Bali |
geographic_facet |
Bali |
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 |
_version_ |
1802650390765764608 |