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Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network

IoT-enabled devices are making it easier and cheaper than ever to capture in situ environmental data and deliver these data—in the form of graphical visualisations—to farmers in a matter of seconds. In this work we describe an aquaculture focused environmental monitoring network consisting of LoRaWA...

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Detalles Bibliográficos
Autores principales: Bates, Harvey, Pierce, Matthew, Benter, Allen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659442/
https://www.ncbi.nlm.nih.gov/pubmed/34883973
http://dx.doi.org/10.3390/s21237963
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author Bates, Harvey
Pierce, Matthew
Benter, Allen
author_facet Bates, Harvey
Pierce, Matthew
Benter, Allen
author_sort Bates, Harvey
collection PubMed
description IoT-enabled devices are making it easier and cheaper than ever to capture in situ environmental data and deliver these data—in the form of graphical visualisations—to farmers in a matter of seconds. In this work we describe an aquaculture focused environmental monitoring network consisting of LoRaWAN-enabled atmospheric and marine sensors attached to buoys on Clyde River, located on the South Coast of New South Wales, Australia. This sensor network provides oyster farmers operating on the river with the capacity to make informed, accurate and rapid decisions that enhance their ability to respond to adverse environmental events—typically flooding and heat waves. The system represents an end-to-end approach that involves deploying a sensor network, analysing the data, creating visualisations in collaboration with farmers and delivering them to them in real-time via a website known as FarmDecisionTECH [Formula: see text]. We compared this network with previously available infrastructure, the results of which demonstrate that an in situ weather station was ∼5 [Formula: see text] C hotter than the closest available real-time weather station (∼20 km away from Clyde River) during a summertime heat wave. Heat waves can result in oysters dying due to exposure if temperatures rise above 30 [Formula: see text] C for extended periods of time (such as heat waves), which will mean a loss in income for the farmers; thus, this work stresses the need for accurate in situ monitoring to prevent the loss of oysters through informed farm management practices. Finally, an approach is proposed to present high-dimensional datasets captured from the sensor network to oyster farmers in a clear and informative manner.
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spelling pubmed-86594422021-12-10 Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network Bates, Harvey Pierce, Matthew Benter, Allen Sensors (Basel) Article IoT-enabled devices are making it easier and cheaper than ever to capture in situ environmental data and deliver these data—in the form of graphical visualisations—to farmers in a matter of seconds. In this work we describe an aquaculture focused environmental monitoring network consisting of LoRaWAN-enabled atmospheric and marine sensors attached to buoys on Clyde River, located on the South Coast of New South Wales, Australia. This sensor network provides oyster farmers operating on the river with the capacity to make informed, accurate and rapid decisions that enhance their ability to respond to adverse environmental events—typically flooding and heat waves. The system represents an end-to-end approach that involves deploying a sensor network, analysing the data, creating visualisations in collaboration with farmers and delivering them to them in real-time via a website known as FarmDecisionTECH [Formula: see text]. We compared this network with previously available infrastructure, the results of which demonstrate that an in situ weather station was ∼5 [Formula: see text] C hotter than the closest available real-time weather station (∼20 km away from Clyde River) during a summertime heat wave. Heat waves can result in oysters dying due to exposure if temperatures rise above 30 [Formula: see text] C for extended periods of time (such as heat waves), which will mean a loss in income for the farmers; thus, this work stresses the need for accurate in situ monitoring to prevent the loss of oysters through informed farm management practices. Finally, an approach is proposed to present high-dimensional datasets captured from the sensor network to oyster farmers in a clear and informative manner. MDPI 2021-11-29 /pmc/articles/PMC8659442/ /pubmed/34883973 http://dx.doi.org/10.3390/s21237963 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bates, Harvey
Pierce, Matthew
Benter, Allen
Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title_full Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title_fullStr Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title_full_unstemmed Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title_short Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network
title_sort real-time environmental monitoring for aquaculture using a lorawan-based iot sensor network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659442/
https://www.ncbi.nlm.nih.gov/pubmed/34883973
http://dx.doi.org/10.3390/s21237963
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