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Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Environmental Sensing".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 13710

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Prof. Dr. Zbigniew Otremba

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Guest Editor

Department of Physics, Gdynia Maritime University, 81-225 Gdynia, Poland
Interests: physics; oceanology; oils; environment protection; ocean optics; environmental impact assessment; environmental pollution; environmental management; environmental monitoring; water analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Emilia Baszanowska

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Guest Editor

Department of Physics, Gdynia Maritime University, 81-225 Gdynia, Poland
Interests: atomic physics; oceanography

Special Issue Information

Dear Colleagues,

Anthropogenic pressure, combined with fluctuations in the global climate, affects the functioning of the marine environment. It is important to take care of its health, and the related durability of its productivity. Information about the changes of biological, physical and chemical parameters of marine areas resulting from their use is highly desirable. The possibility of early detection of alien substances and energies in water masses is also important. To meet such needs requires the improvement of sensors for environmental parameters changes, the creation of theoretical foundations for the functioning of sensors, as well as the automation of collecting, processing, and sharing information from sensor systems for use in national and global environmental management. In this Special Issue, original research articles and reviews are welcome.

Potential topics include, but are not limited to:

Materials dedicated to the construction of marine sensors;
Transmission of the signal from underwater sensors;
Autonomic sensors;
Sensing the sea surface dynamics;
Sensors for solar radiation in the seawater column;
Intelligent sensors for marine applications;
Machine learning in the development of sensor signals;
Sensing and identifying sound sources;
Multi-sensor data processing;
Spatially integrated sensing.

Prof. Dr. Zbigniew Otremba
Dr. Emilia Baszanowska
Guest Editors

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Keywords

ocean health
weather parameters
climate change
detecting of marine pollution
marine large scale constructions
alien energies and substances

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Related Special Issue

Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection—Second Edition in Sensors (1 article)

Published Papers (11 papers)

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Research

19 pages, 5364 KiB

Open AccessArticle

Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels

by Jeremy Karst, Robert McGurrin, Kimberly Gavin, Joseph Luttrell, William Rippy, Robert Coniglione, Jason McKenna and Ralf Riedel

Sensors 2025, 25(6), 1930; https://doi.org/10.3390/s25061930 - 20 Mar 2025

Viewed by 681

Abstract

Acoustic target recognition has always played a central role in marine sensing. Traditional signal processing techniques that have been used for target recognition have shown limitations in accuracy, particularly with commodity hardware. To address such limitations, we present the results of our experiments to assess the capabilities of AI-enabled acoustic buoys using OpenEar™, a commercial, off-the-shelf, software-defined hydrophone sensor, for detecting and tracking fast-moving vessels. We used a triangular sparse sensor network to investigate techniques necessary to estimate the detection, classification, localization, and tracking of boats transiting through the network. Emphasis was placed on evaluating the sensor’s operational detection range and feasibility of onboard AI for cloud-based data fusion. Results indicated effectiveness for enhancing maritime domain awareness and gaining insight into illegal, unreported, and unregulated activities. Additionally, this study provides a framework for scaling autonomous sensor networks to support persistent maritime surveillance. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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18 pages, 35678 KiB

Open AccessArticle

Novelty Recognition: Fish Species Classification via Open-Set Recognition

by Manuel Córdova, Ricardo da Silva Torres, Aloysius van Helmond and Gert Kootstra

Sensors 2025, 25(5), 1570; https://doi.org/10.3390/s25051570 - 4 Mar 2025

Viewed by 721

Abstract

To support the sustainable use of marine resources, regulations have been proposed to reduce fish discards focusing on the registration of all listed species. To comply with such regulations, computer vision methods have been developed. Nevertheless, current approaches are constrained by their closed-set nature, where they are designed only to recognize fish species that were present during training. In the real world, however, samples of unknown fish species may appear in different fishing regions or seasons, requiring fish classification to be treated as an open-set problem. This work focuses on the assessment of open-set recognition to automate the registration process of fish. The state-of-the-art Multiple Gaussian Prototype Learning (MGPL) was compared with the simple yet powerful Open-Set Nearest Neighbor (OSNN) and the Probability of Inclusion Support Vector Machine (PISVM). For the experiments, the Fish Detection and Weight Estimation dataset, containing images of 2216 fish instances from nine species, was used. Experimental results demonstrated that OSNN and PISVM outperformed MGPL in both recognizing known and unknown species. OSNN achieved the best results when classifying samples as either one of the known species or as an unknown species with an F1-macro of

0.79 \pm 0.05

and an AUROC score of

0.92 \pm 0.01

surpassing PISVM by

0.05

and

0.03

, respectively. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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19 pages, 13268 KiB

Open AccessArticle

Modeling and Performance Analysis of Uplink Laser Transmission Across Sea Surfaces: A Channel Characterization Study

by Hong Gao, Tinglu Zhang, Ruiman Yuan, Lianbo Hu and Shuguo Chen

Sensors 2025, 25(4), 1239; https://doi.org/10.3390/s25041239 - 18 Feb 2025

Viewed by 429

Abstract

Variable marine environmental conditions, particularly at the sea surface, present considerable challenges to cross-media laser transmission. This study simulates uplink laser transmission through a seawater–sea surface–air channel via ray tracing and Monte Carlo methods, with an emphasis on the impacts of the sea surface channel. A spatial model of the sea surface is introduced, which uses a wave spectrum and fast Fourier transform technology, and the results are compared against those of a classical statistical model. The validity and applicability of six representative wind wave spectra are assessed for their effectiveness in characterizing the optical sea surface. Among these spectra, the Elfouhaily spectrum, which is refined for low-wind conditions, can most accurately represent the optical properties of the sea surface. The simulations reveal that the spatial model captures power fluctuations due to dynamic sea surface changes. At shorter underwater transmission distances, the spatial model may induce considerable drift, thereby degrading power estimates, where the difference is about 0.9 dB compared with the statistical model. Deeper underwater transmissions can mitigate beam distortions, resulting in a decrease in normalized peak power from −114 dB to −157 dB. Additionally, the laser centroid distribution tends to be elliptical because of the distribution of the sea surface azimuth. These findings underscore the importance of incorporating spatiotemporal dynamics in modeling sea surfaces and provide insights for optimizing underwater air laser transmission links in complex marine environments. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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20 pages, 7487 KiB

Open AccessArticle

Towards the Measurement of Sea-Ice Thickness Using a Time-Domain Inductive Measurement System

by Danny Hills, Becan Lawless, Rauan Khangerey, Jeremy Wilkinson and Liam A. Marsh

Sensors 2025, 25(2), 510; https://doi.org/10.3390/s25020510 - 16 Jan 2025

Viewed by 1023

Abstract

Frequency-domain electromagnetic induction (EMI) is routinely used to detect the presence of seawater due to the inherent electrical conductivity of the seawater. This approach is used to infer sea-ice thickness (SIT). A time-domain EMI sensor is presented, which demonstrates the potential for correlating the spectroscopic properties of the received signal with the distance to the sea surface. This is a novel approach to SIT measurement, which differs from existing methods in that it uses measurements from 10 kHz to 93 kHz rather than a single frequency. The sensor was tested at a tidal pool containing seawater and measured to have a conductivity of 57.3 mS/cm. Measurements were performed at a range of heights between 0.2 m and 1.9 m above the sea surface and for inclinations from 0° to 45°. These measurements were correlated with Finite Element Modeling (FEM) simulations performed in COMSOL. The measured and simulated datasets are presented along with a proposed form of post-processing, which establishes a correlation between the distance to the sea surface and the measured EMI response. This forms a proxy measurement for the absolute distance from the EMI sensor to the sea surface. Because the air gap between the sensor and the seawater is indicative of the properties of sea ice, this study demonstrates a novel approach to non-destructive measurement of sea-ice thickness. The measurements show that this distance to the sea surface can be estimated to within approximately 10% of the known value from 0.2–1.5 m and 15% from 1.5 to 1.9 m. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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11 pages, 8257 KiB

Open AccessArticle

Fibre Optic Method for Detecting Oil Fluorescence in Marine Sediments

by Emilia Baszanowska, Zbigniew Otremba and Maria Kubacka

Sensors 2025, 25(1), 173; https://doi.org/10.3390/s25010173 - 31 Dec 2024

Viewed by 553

Abstract

The aim of this study is to verify the possibility of detecting oil in the bottom sediment using a fibre optic system. The presence of oil is assessed on excitation–emission spectra obtained from spectral fluorescence signals of the sediment sample. A factory spectrofluorometer coupled with an experimental fibre optic measurement system was used. During the determination of spectra, the fibre optic system is set at a 45° angle to the sediment surface and placed above its surface. The light exciting the fluorescence and the light emitted by the sediment are transmitted in a combined bundle of fibre optic threads. The analysis of excitation–emission spectra of sediments contaminated with oil shows variability of the shapes of fluorescence spectra depending on the type and degree of oil contamination, which indicates the feasibility of the sensor design for detecting oil in the sediment in situ. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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24 pages, 27231 KiB

Open AccessArticle

Bentayga-I: Development of a Low-Cost and Open-Source Multispectral CubeSat for Marine Environment Monitoring and Prevention

by Adrián Rodríguez-Molina, Alejandro Santana, Felipe Machado, Yubal Barrios, Emma Hernández-Suárez, Ámbar Pérez-García, María Díaz, Raúl Santana, Antonio J. Sánchez and José F. López

Sensors 2024, 24(23), 7648; https://doi.org/10.3390/s24237648 - 29 Nov 2024

Viewed by 1323

Abstract

CubeSats have emerged as a promising alternative to satellite missions for studying remote areas where satellite data are scarce and insufficient, such as coastal and marine environments. However, their standard size and weight limitations make integrating remote sensing optical instruments challenging. This work presents the development of Bentayga-I, a CubeSat designed to validate PANDORA, a self-made, lightweight, cost-effective multispectral camera with interchangeable spectral optical filters, in near-space conditions. Its four selected spectral bands are relevant for ocean studies. Alongside the camera, Bentayga-I integrates a power system for short-time operation capacity; a thermal subsystem to maintain battery function; environmental sensors to monitor the CubeSat’s internal and external conditions; and a communication subsystem to transmit acquired data to a ground station. The first helium balloon launch with B2Space proved that Bentayga-I electronics worked correctly in near-space environments. During this launch, the spectral capabilities of PANDORA alongside the spectrum were validated using a hyperspectral camera. Its scientific applicability was also tested by capturing images of coastal areas. A second launch is planned to further validate the multispectral camera in a real-world scenario. The integration of Bentayga-I and PANDORA presents promising results for future low-cost CubeSats missions. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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15 pages, 7389 KiB

Open AccessArticle

A Modular Smart Ocean Observatory for Development of Sensors, Underwater Communication and Surveillance of Environmental Parameters

by Øivind Bergh, Jean-Baptiste Danre, Kjetil Stensland, Keila Lima, Ngoc-Thanh Nguyen, Rogardt Heldal, Lars-Michael Kristensen, Tosin Daniel Oyetoyan, Inger Graves, Camilla Sætre, Astrid Marie Skålvik, Beatrice Tomasi, Bård Henriksen, Marie Bueie Holstad, Paul van Walree, Edmary Altamiranda, Erik Bjerke, Thor Storm Husøy, Ingvar Henne, Henning Wehde and Jan Erik Stiansen Show full author list Hide full author list

Sensors 2024, 24(20), 6530; https://doi.org/10.3390/s24206530 - 10 Oct 2024

Viewed by 2203

Abstract

The rapid growth of marine industries has emphasized the focus on environmental impacts for all industries, as well as the influence of key environmental parameters on, for instance, offshore wind or aquaculture performance, animal welfare and structural integrity of different constructions. Development of automatized sensors together with efficient communication and information systems will enhance surveillance and monitoring of environmental processes and impact. We have developed a modular Smart Ocean observatory, in this case connected to a large-scale marine aquaculture research facility. The first sensor rigs have been operational since May 2022, transmitting environmental data in near real-time. Key components are Acoustic Doppler Current Profilers (ADCPs) for measuring directional wave and current parameters, and CTDs for redundant measurement of depth, temperature, conductivity and oxygen. Communication is through 4G network or cable. However, a key purpose of the observatory is also to facilitate experiments with acoustic wireless underwater communication, which are ongoing. The aim is to expand the system(s) with demersal independent sensor nodes communicating through an “Internet of Underwater Things (IoUT)”, covering larger areas in the coastal zone, as well as open waters, of benefit to all ocean industries. The observatory also hosts experiments for sensor development, biofouling control and strategies for sensor self-validation and diagnostics. The close interactions between the experiments and the infrastructure development allow a holistic approach towards environmental monitoring across sectors and industries, plus to reduce the carbon footprint of ocean observation. This work is intended to lay a basis for sophisticated use of smart sensors with communication systems in long-term autonomous operation in remote as well as nearshore locations. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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16 pages, 3514 KiB

Open AccessArticle

Comparative Analysis of Meteorological versus In Situ Variables in Ship Thermal Simulations

by Elena Arce, Andrés Suárez-García, José Antonio López-Vázquez and Rosa Devesa-Rey

Sensors 2024, 24(8), 2454; https://doi.org/10.3390/s24082454 - 11 Apr 2024

Viewed by 1031

Abstract

Thermal simulations have become increasingly popular in assessing energy efficiency and predicting thermal behaviors in various structures. Calibration of these simulations is essential for accurate predictions. A crucial aspect of this calibration involves investigating the influence of meteorological variables. This study aims to explore the impact of meteorological variables on thermal simulations, particularly focusing on ships. Using TRNSYS (TRaNsient System Simulation) software (v17), renowned for its capability to model complex energy systems within buildings, the significance of incorporating meteorological data into thermal simulations was analyzed. The investigation centered on a patrol vessel stationed in a port in Galicia, northwest Spain. To ensure accuracy, we not only utilized the vessel’s dimensions but also conducted in situ temperature measurements onboard. Furthermore, a dedicated weather station was installed to capture real-time meteorological data. Data from multiple sources, including Meteonorm and MeteoGalicia, were collected for comparative analysis. By juxtaposing simulations based on meteorological variables against those relying solely on in situ measurements, we sought to discern the relative merits of each approach in enhancing the fidelity of thermal simulations. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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17 pages, 3481 KiB

Open AccessArticle

Monitoring Bioindication of Plankton through the Analysis of the Fourier Spectra of the Underwater Digital Holographic Sensor Data

by Victor Dyomin, Alexandra Davydova, Nikolay Kirillov, Oksana Kondratova, Yuri Morgalev, Sergey Morgalev, Tamara Morgaleva and Igor Polovtsev

Sensors 2024, 24(7), 2370; https://doi.org/10.3390/s24072370 - 8 Apr 2024

Cited by 3 | Viewed by 1143

Abstract

The study presents a bioindication complex and a technology of the experiment based on a submersible digital holographic camera with advanced monitoring capabilities for the study of plankton and its behavioral characteristics in situ. Additional mechanical and software options expand the capabilities of the digital holographic camera, thus making it possible to adapt the depth of the holographing scene to the parameters of the plankton habitat, perform automatic registration of the “zero” frame and automatic calibration, and carry out natural experiments with plankton photostimulation. The paper considers the results of a long-term digital holographic experiment on the biotesting of the water area in Arctic latitudes. It shows additional possibilities arising during the spectral processing of long time series of plankton parameters obtained during monitoring measurements by a submersible digital holographic camera. In particular, information on the rhythmic components of the ecosystem and behavioral characteristics of plankton, which can be used as a marker of the ecosystem well-being disturbance, is thus obtained. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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10 pages, 7482 KiB

Open AccessCommunication

A Global Seawater Density Distribution Model Using a Convolutional Neural Network

by Qin Liu, Liyan Li, Yan Zhou, Shiwen Zhang, Yuliang Liu and Xinwei Wang

Sensors 2024, 24(6), 1972; https://doi.org/10.3390/s24061972 - 20 Mar 2024

Cited by 1 | Viewed by 1783

Abstract

Seawater density is an important physical property in oceanography that affects the accuracy of calculations such as gravity fields and tidal potentials and the calibration of acoustic and optical oceanographic sensors. In related studies, constant density values are frequently used, which can introduce significant errors. Therefore, this study employs a basic convolutional neural network model to construct a comprehensive model showing the seawater density distribution across the globe. The model takes into account depth, latitude, longitude, and month as inputs. Numerous real seawater datasets were used to train the model, and it has been shown that the model has an absolute mean error and root mean square error of less than 1 kg/m³ in 99% of the test set samples. The model effectively demonstrates the influence of input parameters on the distribution of seawater density. In this paper, we present a newly developed global model for distributing seawater density which is both comprehensive and accurate, surpassing previous models. The utilization of the model presented in this paper for estimating seawater density can minimize errors in theoretical ocean models and serve as a foundation for designing and analyzing ocean exploration systems. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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13 pages, 1929 KiB

Open AccessArticle

Practical Considerations for Laser-Induced Graphene Pressure Sensors Used in Marine Applications

by Tessa Van Volkenburg, Daniel Ayoub, Andrea Alemán Reyes, Zhiyong Xia and Leslie Hamilton

Sensors 2023, 23(22), 9044; https://doi.org/10.3390/s23229044 - 8 Nov 2023

Cited by 1 | Viewed by 1661

Abstract

Small, low-power, and inexpensive marine depth sensors are of interest for a myriad of applications from maritime security to environmental monitoring. Recently, laser-induced graphene (LIG) piezoresistive pressure sensors have been proposed given their rapid fabrication and large dynamic range. In this work, the practicality of LIG integration into fieldable deep ocean (1 km) depth sensors in bulk is explored. Initially, a design of experiments (DOEs) approach evaluated laser engraver fabrication parameters such as line length, line width, laser speed, and laser power on resultant resistances of LIG traces. Next, uniaxial compression and thermal testing at relevant ocean pressures up to 10.3 MPa and temperatures between 0 and 25 °C evaluated the piezoresistive response of replicate sensors and determined the individual characterization of each, which is necessary. Additionally, bare LIG sensors showed larger resistance changes with temperature (ΔR ≈ 30 kΩ) than pressure (ΔR ≈ 1–15 kΩ), indicating that conformal coatings are required to both thermally insulate and electrically isolate traces from surrounding seawater. Sensors encapsulated with two dip-coated layers of 5 wt% polydimethylsiloxane (PDMS) silicone and submerged in water baths from 0 to 25 °C showed significant thermal dampening (ΔR ≈ 0.3 kΩ), indicating a path forward for the continued development of LIG/PDMS composite structures. This work presents both the promises and limitations of LIG piezoresistive depth sensors and recommends further research to validate this platform for global deployment. Full article

(This article belongs to the Special Issue Sensor Technologies for Ocean Environments: Impact Assessment, Monitoring and Protection)

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