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MeLa: A Programming Language for a New Multidisciplinary Oceanographic Float.

Sébastien Bonnieux1,2, Dorian Cazau3, Sébastien Mosser4

  • 1Université Côte d'Azur, Observatoire de la Côte d'Azur, CNRS, IRD, Géoazur, 06560 Valbonne, France.

Sensors (Basel, Switzerland)
|October 29, 2020
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Summary
This summary is machine-generated.

A new programming language, MeLa, simplifies on-board acoustic data processing for ocean monitoring. This enables multidisciplinary oceanographic research without requiring deep embedded software expertise.

Keywords:
Digital Signal ProcessingDomain Specific LanguageModel Based ProgrammingModel Driven Engineeringacoustic monitoringembedded softwareembedded systemoceanography

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Area of Science:

  • Oceanography
  • Marine acoustics
  • Signal processing

Background:

  • Oceans at 2000m depth exhibit diverse acoustic signals (biological, seismological, anthropogenic).
  • Global-scale, long-term acoustic monitoring offers valuable scientific insights.
  • Autonomous floats (Argo project) with hydrophones require on-board processing due to limited bandwidth.

Purpose of the Study:

  • To develop a programming language simplifying embedded software development for acoustic data processing.
  • To reduce the expertise needed for creating signal processing algorithms on autonomous oceanographic instruments.

Main Methods:

  • Introduction of the MeLa programming language, abstracting embedded software complexities.
  • Integration of models for early estimation of energy, processor, and transmission costs.
  • On-computer simulations for algorithm performance verification before deployment.
  • Implementation of seismic P-wave and blue whale D-call detection algorithms using MeLa.

Main Results:

  • MeLa successfully abstracts embedded software challenges.
  • Performance modeling aids in optimizing data processing strategies.
  • Demonstrated capability through seismic and marine mammal acoustic detection algorithm implementation.

Conclusions:

  • MeLa facilitates multidisciplinary ocean monitoring by lowering the barrier to embedded software development.
  • The language supports efficient algorithm design, minimizing performance impact.
  • This work represents a step towards broader, integrated ocean observation systems.