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JMSE
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Progress in Sensor Technology for Ocean Sciences
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Progress in Sensor Technology for Ocean Sciences

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 30 August 2025 | Viewed by 2094

Special Issue Editor

Dr. Marc Le Menn

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Guest Editor
Service Hydrographique et Océanographique de la Marine (Shom), CS 92803, 29228 Brest, CEDEX 2, France
Interests: sensors; calibration; uncertainty; best practices; monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ocean is a challenging environment in which to explore. Pressure, currents, oxidation, bacterial deposits, required uncertainties, and various other factors contribute to making technological development and renewal difficult. Additionally, requirements in terms of ocean sampling and data quality are constantly increasing in order to improve the reliability of knowledge and ocean forecasting models.

Against this backdrop of constraints, it is worth taking stock of developments in sensor technology for ocean sciences. “Sensor" is used here in the broadest sense, from the element in contact with the quantity intended to be measured to the entire instrument or system of instruments used to sample ocean basins. In the same way, progress can concern technological developments, as well as data metrology, i.e., data referencing or the estimation of measurement uncertainties.

The field of publication themes opened up by this Issue of JMSE is therefore quite broad, and we look forward to your contributions. If the quality and quantity of the papers selected are sufficient, this collection will be published in book form.

Dr. Marc Le Menn
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor
  • oceanographic instrument
  • instrument network
  • calibration
  • uncertainty

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

21 pages, 5088 KiB  
Article
Assessment of the Representativeness and Uncertainties of CTD Temperature Profiles
by Marc Le Menn, Franck Dumas and Baptiste Calvez
J. Mar. Sci. Eng. 2025, 13(2), 213; https://doi.org/10.3390/jmse13020213 - 23 Jan 2025
Viewed by 701
Abstract
CTD profilers are used as reference instruments to qualify temperature and salinity data. Their metrological specifications can be controlled in a calibration bath, and calibration coefficients can be applied to correct the linearity of sensors and the trueness of measured data with a [...] Read more.
CTD profilers are used as reference instruments to qualify temperature and salinity data. Their metrological specifications can be controlled in a calibration bath, and calibration coefficients can be applied to correct the linearity of sensors and the trueness of measured data with a given uncertainty. However, in ocean areas with thermal gradients, the uncertainty of the measured data is questionable due to the thermal inertia of sensors and the movements of the CTD in relation to the roll or pitch of the boat. In order to evaluate these measurement uncertainties and in order to be able to use the upcast profiles, a double C–T sensor SBE 9 profiler was fixed under a carousel water sampler, the second C–T couple being at the top of the carousel frame. This configuration allows the evaluation of the temperature measurement deviations of recorded profiles. In order to quantify the different sources of instrumental uncertainties, the temperature signal has been modelled accounting for the movements induced by the boat. The result allows one to quantify what can be called the representativeness of CTD’s temperature measurements. This notion is very useful in the data assimilation process. A table quantifying the various sources of uncertainty has been created from profiles obtained during four offshore campaigns. In the future, it could be used to find the representativeness of similar profiles obtained with a single pair of sensors. Ship-based CTD profiles are generally considered as perfect or without uncertainty in data assimilation and in the qualification per comparison of other instruments (XBT, Argo profiles, etc.). Our findings imply that this hypothesis will have to be reconsidered. Full article
(This article belongs to the Special Issue Progress in Sensor Technology for Ocean Sciences)
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17 pages, 6175 KiB  
Article
Multivariate, Automatic Diagnostics Based on Insights into Sensor Technology
by Astrid Marie Skålvik, Ranveig N. Bjørk, Enoc Martínez, Kjell-Eivind Frøysa and Camilla Saetre
J. Mar. Sci. Eng. 2024, 12(12), 2367; https://doi.org/10.3390/jmse12122367 - 23 Dec 2024
Cited by 1 | Viewed by 736
Abstract
With the rapid development of smart sensor technology and the Internet of things, ensuring data accuracy and system reliability is paramount. As the number of sensors increases with demand for high-resolution, high-quality input to decision-making systems, models and digital twins, manual quality control [...] Read more.
With the rapid development of smart sensor technology and the Internet of things, ensuring data accuracy and system reliability is paramount. As the number of sensors increases with demand for high-resolution, high-quality input to decision-making systems, models and digital twins, manual quality control of sensor data is no longer an option. In this paper, we leverage insights into sensor technology, environmental dynamics and the correlation between data from different sensors for automatic diagnostics of a sensor node. We propose a method for combining results of automatic quality control of individual sensors with tests for detecting simultaneous anomalies across sensors. Building on both sensor and application knowledge, we develop a diagnostic logic that can automatically explain and diagnose instead of just labeling the individual sensor data as “good” or “bad”. This approach enables us to provide diagnostics that offer a deeper understanding of the data and their quality and of the health and reliability of the measurement system. Our algorithms are adapted for real time and in situ operation on the sensor node. We demonstrate the diagnostic power of the algorithms on high-resolution measurements of temperature and conductivity from the OBSEA observatory about 50 km south of Barcelona, Spain. Full article
(This article belongs to the Special Issue Progress in Sensor Technology for Ocean Sciences)
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