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Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents

Underwater sensor networks play a crucial role in collecting valuable data to monitor offshore aquaculture infrastructures. The number of deployed devices not only impacts the bandwidth for a highly constrained communication environment, but also the cost of the sensor network. On the other hand, in...

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Autores principales: Montiel-Caminos, Juan, Hernandez-Gonzalez, Nieves G., Sosa, Javier, Montiel-Nelson, Juan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383303/
https://www.ncbi.nlm.nih.gov/pubmed/37514843
http://dx.doi.org/10.3390/s23146549
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author Montiel-Caminos, Juan
Hernandez-Gonzalez, Nieves G.
Sosa, Javier
Montiel-Nelson, Juan A.
author_facet Montiel-Caminos, Juan
Hernandez-Gonzalez, Nieves G.
Sosa, Javier
Montiel-Nelson, Juan A.
author_sort Montiel-Caminos, Juan
collection PubMed
description Underwater sensor networks play a crucial role in collecting valuable data to monitor offshore aquaculture infrastructures. The number of deployed devices not only impacts the bandwidth for a highly constrained communication environment, but also the cost of the sensor network. On the other hand, industrial and literature current meters work as raw data loggers, and most of the calculations to determine the fundamental frequencies are performed offline on a desktop computer or in the cloud. Belonging to the edge computing research area, this paper presents an algorithm to extract the fundamental frequencies of water currents in an underwater sensor network deployed in offshore aquaculture infrastructures. The target sensor node is based on a commercial ultra-low-power microcontroller. The proposed fundamental frequency identification algorithm only requires the use of an integer arithmetic unit. Our approach exploits the mathematical properties of the finite impulse response (FIR) filtering in the integer domain. The design and implementation of the presented algorithm are discussed in detail in terms of FIR tuning/coefficient selection, memory usage and variable domain for its mathematical formulation aimed at reducing the computational effort required. The approach is validated using a shallow water current model and real-world raw data from an offshore aquaculture infrastructure. The extracted frequencies have a maximum error below a 4%.
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spelling pubmed-103833032023-07-30 Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents Montiel-Caminos, Juan Hernandez-Gonzalez, Nieves G. Sosa, Javier Montiel-Nelson, Juan A. Sensors (Basel) Article Underwater sensor networks play a crucial role in collecting valuable data to monitor offshore aquaculture infrastructures. The number of deployed devices not only impacts the bandwidth for a highly constrained communication environment, but also the cost of the sensor network. On the other hand, industrial and literature current meters work as raw data loggers, and most of the calculations to determine the fundamental frequencies are performed offline on a desktop computer or in the cloud. Belonging to the edge computing research area, this paper presents an algorithm to extract the fundamental frequencies of water currents in an underwater sensor network deployed in offshore aquaculture infrastructures. The target sensor node is based on a commercial ultra-low-power microcontroller. The proposed fundamental frequency identification algorithm only requires the use of an integer arithmetic unit. Our approach exploits the mathematical properties of the finite impulse response (FIR) filtering in the integer domain. The design and implementation of the presented algorithm are discussed in detail in terms of FIR tuning/coefficient selection, memory usage and variable domain for its mathematical formulation aimed at reducing the computational effort required. The approach is validated using a shallow water current model and real-world raw data from an offshore aquaculture infrastructure. The extracted frequencies have a maximum error below a 4%. MDPI 2023-07-20 /pmc/articles/PMC10383303/ /pubmed/37514843 http://dx.doi.org/10.3390/s23146549 Text en © 2023 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
Montiel-Caminos, Juan
Hernandez-Gonzalez, Nieves G.
Sosa, Javier
Montiel-Nelson, Juan A.
Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title_full Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title_fullStr Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title_full_unstemmed Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title_short Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents
title_sort integer arithmetic algorithm for fundamental frequency identification of oceanic currents
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383303/
https://www.ncbi.nlm.nih.gov/pubmed/37514843
http://dx.doi.org/10.3390/s23146549
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