ArticleSensors (Basel, Switzerland)2021
Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- A Survey of Modern Data Acquisition and Analysis Systems for Environmental Risk Monitoring in Aquatic Ecosystems.Sensors (Basel, Switzerland) · 2026Review
- Adaptive Antenna for Maritime LoRaWAN: A Systematic Review on Performance, Energy Efficiency, and Environmental Resilience.Sensors (Basel, Switzerland) · 2025Review
- Optimal Distributed Finite-Time Fusion Method for Multi-Sensor Networks under Dynamic Communication Weight.Sensors (Basel, Switzerland) · 2023Article
- Mobility of LoRaWAN Gateways for Efficient Environmental Monitoring in Pristine Sites.Sensors (Basel, Switzerland) · 2023Article
- CEBA: A Data Lake for Data Sharing and Environmental Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Towards making the fields talks: A real-time cloud enabled IoT crop management platform for smart agriculture.Frontiers in plant science · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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®. We compared this network with previously available infrastructure, the results of which demonstrate that an in situ weather station was ∼5 ∘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 ∘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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.