MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float
At 2000 m depth in the oceans, one can hear biological, seismological, meteorological, and anthropogenic activity. Acoustic monitoring of the oceans at a global scale and over long periods of time could bring important information for various sciences. The Argo project monitors the physical properti...
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doaj-bd1626f825534a7596c91c33121274032020-11-25T03:04:43ZengMDPI AGSensors1424-82202020-10-01206081608110.3390/s20216081MeLa: A Programming Language for a New Multidisciplinary Oceanographic FloatSébastien Bonnieux0Dorian Cazau1Sébastien Mosser2Mireille Blay-Fornarino3Yann Hello4Guust Nolet5Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, IRD, Géoazur, 06560 Valbonne, FranceLab-STICC, UMR 6285, CNRS, ENSTA Bretagne, 29238 Brest, FranceDépartement d’Informatique, Université du Québec à Montréal, Montréal, QC H3C3P8, CanadaUniversité Côte d’Azur, CNRS, I3S, 06900 Valbonne, FranceUniversité Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, IRD, Géoazur, 06560 Valbonne, FranceUniversité Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, IRD, Géoazur, 06560 Valbonne, FranceAt 2000 m depth in the oceans, one can hear biological, seismological, meteorological, and anthropogenic activity. Acoustic monitoring of the oceans at a global scale and over long periods of time could bring important information for various sciences. The Argo project monitors the physical properties of the oceans with autonomous floats, some of which are also equipped with a hydrophone. These have a limited transmission bandwidth requiring acoustic data to be processed on board. However, developing signal processing algorithms for these instruments requires one to be an expert in embedded software. To reduce the need of such expertise, we have developed a programming language, called MeLa. The language hides several aspects of embedded software with specialized programming concepts. It uses models to compute energy consumption, processor usage, and data transmission costs early during the development of applications; this helps to choose a strategy of data processing that has a minimum impact on performances. Simulations on a computer allow for verifying the performance of the algorithms before their deployment on the instrument. We have implemented a seismic P wave detection and a blue whales D call detection algorithm with the MeLa language to show its capabilities. These are the first efforts toward multidisciplinary monitoring of the oceans, which can extend beyond acoustic applications.https://www.mdpi.com/1424-8220/20/21/6081acoustic monitoringoceanographyModel Driven EngineeringModel Based ProgrammingDomain Specific Languageembedded system |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sébastien Bonnieux Dorian Cazau Sébastien Mosser Mireille Blay-Fornarino Yann Hello Guust Nolet |
spellingShingle |
Sébastien Bonnieux Dorian Cazau Sébastien Mosser Mireille Blay-Fornarino Yann Hello Guust Nolet MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float Sensors acoustic monitoring oceanography Model Driven Engineering Model Based Programming Domain Specific Language embedded system |
author_facet |
Sébastien Bonnieux Dorian Cazau Sébastien Mosser Mireille Blay-Fornarino Yann Hello Guust Nolet |
author_sort |
Sébastien Bonnieux |
title |
MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float |
title_short |
MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float |
title_full |
MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float |
title_fullStr |
MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float |
title_full_unstemmed |
MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float |
title_sort |
mela: a programming language for a new multidisciplinary oceanographic float |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-10-01 |
description |
At 2000 m depth in the oceans, one can hear biological, seismological, meteorological, and anthropogenic activity. Acoustic monitoring of the oceans at a global scale and over long periods of time could bring important information for various sciences. The Argo project monitors the physical properties of the oceans with autonomous floats, some of which are also equipped with a hydrophone. These have a limited transmission bandwidth requiring acoustic data to be processed on board. However, developing signal processing algorithms for these instruments requires one to be an expert in embedded software. To reduce the need of such expertise, we have developed a programming language, called MeLa. The language hides several aspects of embedded software with specialized programming concepts. It uses models to compute energy consumption, processor usage, and data transmission costs early during the development of applications; this helps to choose a strategy of data processing that has a minimum impact on performances. Simulations on a computer allow for verifying the performance of the algorithms before their deployment on the instrument. We have implemented a seismic P wave detection and a blue whales D call detection algorithm with the MeLa language to show its capabilities. These are the first efforts toward multidisciplinary monitoring of the oceans, which can extend beyond acoustic applications. |
topic |
acoustic monitoring oceanography Model Driven Engineering Model Based Programming Domain Specific Language embedded system |
url |
https://www.mdpi.com/1424-8220/20/21/6081 |
work_keys_str_mv |
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