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Special Issue "Selected Papers from the 2020 IMEKO TC-19 International Workshop on Metrology for the Sea"

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

Deadline for manuscript submissions: closed (20 March 2021).

Special Issue Editors

Prof. Dr. Giorgio Budillon
E-Mail Website
Guest Editor
University of Naples "Parthenope"
Interests: ocean's stratification; circulation and mixing; sea-air-ice interactions
Prof. Dr. Salvatore Gaglione
E-Mail Website
Guest Editor
Department of Science and Technology, University of Naples Parthenope, Centro Direzionale-Isola C4, 80143 Napoli, Italy
Interests: Geomatic; Navigation; Satellite positioning; Survey; UAV applications
Special Issues and Collections in MDPI journals
Prof. Dr. Roberta Ivaldi
E-Mail
Guest Editor
Italian Hydrographic Institute, Italian Navy, Italy

Special Issue Information

Dear Colleagues,

The 2020 IMEKO TC-19 International Workshop on Metrology for the Sea (http://www.metrosea.org/home) will be held in Naples, Italy, 5–7 October 2020.

MetroSea aims to gather people who work in developing instrumentation and measurement methods for the sea. Particular attention is paid to new technology for sea environment monitoring, metrology-assisted production in the sea industry, ship component measurement, sensors and associated signal conditioning for the sea, and calibration methods for electronic testing and measurement for marine applications.

Topics:

  • Electronic instrumentation for the sea;
  • Automatic test equipment for the sea;
  • Sensors and sensor sensing systems for sea applications;
  • Wireless sensor networks for marine applications;
  • Monitoring systems for the sea;
  • Metrology for navigation and precise positioning;
  • Measurements for submarine obstacle detection;
  • Underwater vehicles for exploration;
  • Pollution detection for reclamation;
  • Submarine infrastructure maintenance and reliability;
  • Signal and image processing;
  • Metrology and quality assurance for submarine soldering;
  • Weather forecasting and nowcasting for maritime navigation;
  • Measures for marine biology;
  • Measures for marine geology;
  • Measures for Oceanography.

Authors of papers related to sensors presented at the workshop are invited to submit extended versions of their work to this Special Issue for publication.

Prof. Dr. Giorgio Budillon
Prof. Dr. Salvatore Gaglione
Prof. Dr. Roberta Ivaldi
Guest Editors

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 papers will be 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. Sensors is an international peer-reviewed open access semimonthly 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 2200 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.

Published Papers (8 papers)

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Research

Article
A Triggering Mechanism for Cyber-Attacks in Naval Sensors and Systems
Sensors 2021, 21(9), 3195; https://doi.org/10.3390/s21093195 - 04 May 2021
Viewed by 536
Abstract
In the maritime sector, the integration of radar systems, Automatic Identification System (AIS) and Electronic Chart Display and Information System (ECDIS) through digital technologies enables several benefits to maritime operations, but also make ships prone to cyberattacks. In this context, this work investigates [...] Read more.
In the maritime sector, the integration of radar systems, Automatic Identification System (AIS) and Electronic Chart Display and Information System (ECDIS) through digital technologies enables several benefits to maritime operations, but also make ships prone to cyberattacks. In this context, this work investigates the feasibility of an attacker using a radar system or AIS as open door to remotely send commands to a cyber threat hosted on a ship, even if the ship’s systems are air gapped—i.e., are not connected to other networks. The received commands are intended to trigger a cyber threat located in the ship. Although the literature covers several analyzes on cyber risks and vulnerabilities in naval systems, it lacks exploiting mechanisms capable of acknowledging attack commands received through radar and AIS. To this end, this work proposes a triggering mechanism that uses a template matching technique to detect specific patterns transmitted by the attacker to the ship’s radar or AIS. The results show the effectiveness of the proposed technique as a tool to acknowledge the received attack commands and activate a malicious code previously installed on the ship. In the case of attacks on a radar system, the accuracy achieved by the proposed method is 0.90. In the case of attacks on an AIS/ECDIS setup it presents an accuracy of 0.93. In both cases the proposed mechanism maintains the due safety against accidental attack activations. Full article
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Article
Semi-Automated Data Processing and Semi-Supervised Machine Learning for the Detection and Classification of Water-Column Fish Schools and Gas Seeps with a Multibeam Echosounder
Sensors 2021, 21(9), 2999; https://doi.org/10.3390/s21092999 - 24 Apr 2021
Viewed by 725
Abstract
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and time-consuming, or affected by low [...] Read more.
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and time-consuming, or affected by low efficiency and high false detection rates if automated. This research describes a comprehensive and reproducible workflow that improves efficiency and reliability of target detection and classification, by calculating metrics for target cross-sections using a commercial software before feeding into a feature-based semi-supervised machine learning framework. The method is tested with data collected from an uncalibrated multibeam echosounder around an offshore gas platform in the Adriatic Sea. It resulted in more-efficient target detection, and, although uncertainties regarding user labelled training data need to be underlined, an accuracy of 98% in target classification was reached by using a final pre-trained stacking ensemble model. Full article
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Article
Investigation on Spectrum Estimation Methods for Bimodal Sea State Conditions
Sensors 2021, 21(9), 2995; https://doi.org/10.3390/s21092995 - 24 Apr 2021
Viewed by 341
Abstract
The reliable monitoring of sea state parameters is a key factor for weather forecasting, as well as for ensuring the safety and navigation of ships. In the current analysis, two spectrum estimation techniques, based on the Welch and Thomson methods, were applied to [...] Read more.
The reliable monitoring of sea state parameters is a key factor for weather forecasting, as well as for ensuring the safety and navigation of ships. In the current analysis, two spectrum estimation techniques, based on the Welch and Thomson methods, were applied to a set of random wave signals generated from a theoretical wave spectrum obtained by combining wind sea and swell components with the same prevailing direction but different combinations of significant wave heights, peak periods, and peak enhancement factors. A wide benchmark study was performed to systematically apply and compare the two spectrum estimation methods. In this respect, different combinations of wind sea spectra, corresponding to four grades of the Douglas Scale, were combined with three swell spectra corresponding to different swell categories. The main aim of the benchmark study was to systematically investigate the effectiveness of the Welch and Thomson methods in terms of spectrum restitution and the assessment of sea state parameters. The spectrum estimation methods were applied to random wave signals with different durations, namely 600 s (short) and 3600 s (long), to investigate how the record length affected the assembled sea state parameters, which, in turn, were assessed by the nonlinear least square method. Finally, based on the main outcomes of the benchmark study, some suggestions are provided to select the most suitable spectrum reconstruction method and increase the effectiveness of the assembled sea state parameters. Full article
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Article
A Synergic Integration of AIS Data and SAR Imagery to Monitor Fisheries and Detect Suspicious Activities
Sensors 2021, 21(8), 2756; https://doi.org/10.3390/s21082756 - 13 Apr 2021
Viewed by 557
Abstract
Maritime traffic and fishing activities have accelerated considerably over the last decade, with a consequent impact on the environment and marine resources. Meanwhile, a growing number of ship-reporting technologies and remote-sensing systems are generating an overwhelming amount of spatio-temporal and geographically distributed data [...] Read more.
Maritime traffic and fishing activities have accelerated considerably over the last decade, with a consequent impact on the environment and marine resources. Meanwhile, a growing number of ship-reporting technologies and remote-sensing systems are generating an overwhelming amount of spatio-temporal and geographically distributed data related to large-scale vessels and their movements. Individual technologies have distinct limitations but, when combined, can provide a better view of what is happening at sea, lead to effectively monitor fishing activities, and help tackle the investigations of suspicious behaviors in close proximity of managed areas. The paper integrates non-cooperative Synthetic Aperture Radar (SAR) Sentinel-1 images and cooperative Automatic Identification System (AIS) data, by proposing two types of associations: (i) point-to-point and (ii) point-to-line. They allow the fusion of ship positions and highlight “suspicious” AIS data gaps in close proximity of managed areas that can be further investigated only once the vessel—and the gear it adopts—is known. This is addressed by a machine-learning approach based on the Fast Fourier Transform that classifies single sea trips. The approach is tested on a case study in the central Adriatic Sea, automatically reporting AIS-SAR associations and seeking ships that are not broadcasting their positions (intentionally or not). Results allow the discrimination of collaborative and non-collaborative ships, playing a key role in detecting potential suspect behaviors especially in close proximity of managed areas. Full article
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Article
Observation Quality Assessment and Performance of GNSS Standalone Positioning with Code Pseudoranges of Dual-Frequency Android Smartphones
Sensors 2021, 21(6), 2125; https://doi.org/10.3390/s21062125 - 18 Mar 2021
Cited by 3 | Viewed by 556
Abstract
The new generation of Android smartphones is equipped with GNSS chips capable of tracking multi-frequency and multi-constellation data. In this work, we evaluate the positioning performance and analyze the quality of observations collected by three recent smartphones, namely Xiaomi Mi 8, Xiaomi Mi [...] Read more.
The new generation of Android smartphones is equipped with GNSS chips capable of tracking multi-frequency and multi-constellation data. In this work, we evaluate the positioning performance and analyze the quality of observations collected by three recent smartphones, namely Xiaomi Mi 8, Xiaomi Mi 9, and Huawei P30 pro that take advantage of such chips. The analysis of the GNSS observation quality implies that the commonly employed elevation-dependent function is not optimal for smartphone GNSS observation weighting and suggests an application of the C/N0-dependent one. Regarding smartphone code signals on L5 and E5a frequency bands, we found that they are characterized with noticeably lower noise as compared to E1 and L1 ones. The single point positioning results confirm an improvement in the performance when the weights are a function of the C/N0-rather than those dependent on the satellite elevation and that a smartphone positioning with E5a code observations significantly outperforms that with E1 signals. The latter is expressed by a drop of the horizontal RMS from 8.44 m to 3.17 m for Galileo E1 and E5a solutions of Xiaomi Mi 9 P30, respectively. The best positioning accuracy of multi-GNSS single-frequency (L1/E1/B1/G1) solution was obtained by Huawei P30 with a horizontal RMS of 3.24 m. Xiaomi Mi 8 and Xiaomi Mi 9 show a horizontal RMS error of 4.14 m and 4.90 m, respectively. Full article
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Article
Design and Performance Evaluation of a “Fixed-Point” Spar Buoy Equipped with a Piezoelectric Energy Harvesting Unit for Floating Near-Shore Applications
Sensors 2021, 21(5), 1912; https://doi.org/10.3390/s21051912 - 09 Mar 2021
Viewed by 562
Abstract
In the present work, a spar-buoy scaled model was designed and built through a “Lab-on-Sea” unit, equipped with an energy harvesting system. Such a system is based on deformable bands, which are loyal to the unit, to convert wave motion energy into electricity [...] Read more.
In the present work, a spar-buoy scaled model was designed and built through a “Lab-on-Sea” unit, equipped with an energy harvesting system. Such a system is based on deformable bands, which are loyal to the unit, to convert wave motion energy into electricity by means of piezo patch transducers. In a preliminary stage, the scaled model, suitable for tests in a controlled ripples-type wave motion channel, was tested in order to verify the “fixed-point” assumption in pitch and roll motions and, consequently, to optimize energy harvesting. A special type of structure was designed, numerically simulated, and experimentally verified. The proposed solution represents an advantageous compromise between the lightness of the used materials and the amount of recoverable energy. The energy, which was obtained from the piezo patch transducers during the simulations in the laboratory, was found to be enough to self-sustain the feasible on-board sensors and the remote data transmission system. Full article
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Article
Preliminary Study for AUV: Longitudinal Stabilization Method Based on Takagi-Sugeno Fuzzy Inference System
Sensors 2021, 21(5), 1866; https://doi.org/10.3390/s21051866 - 07 Mar 2021
Viewed by 510
Abstract
The paper shows the steps for the preliminary studies of an AUV for shallow water: the first part illustrates the vehicle architecture and the philosophy that permeates the various design choices. In the second part illustrates an innovative method for increasing longitudinal stability [...] Read more.
The paper shows the steps for the preliminary studies of an AUV for shallow water: the first part illustrates the vehicle architecture and the philosophy that permeates the various design choices. In the second part illustrates an innovative method for increasing longitudinal stability based on Takagi-Sugeno (T-S) Fuzzy Inference System: it saves a lot of computational time and, by simplifying the calculation, it is also suitable for remarkably simple computers such as Arduino. in the third part is simulated the behavior of the AUV: thanks to the data taken from the previous hydrodynamic simulation, we can establish the behavior of its longitudinal stability and the computational savings due to the T-S method. Full article
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Article
DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation
Sensors 2021, 21(4), 1526; https://doi.org/10.3390/s21041526 - 22 Feb 2021
Viewed by 620
Abstract
One of the main issues for the navigation of underwater robots consists in accurate vehicle positioning, which heavily depends on the orientation estimation phase. The systems employed to this end are affected by different noise typologies, mainly related to the sensors and to [...] Read more.
One of the main issues for the navigation of underwater robots consists in accurate vehicle positioning, which heavily depends on the orientation estimation phase. The systems employed to this end are affected by different noise typologies, mainly related to the sensors and to the irregular noise of the underwater environment. Filtering algorithms can reduce their effect if opportunely configured, but this process usually requires fine techniques and time. This paper presents DANAE++, an improved denoising autoencoder based on DANAE (deep Denoising AutoeNcoder for Attitude Estimation), which is able to recover Kalman Filter (KF) IMU/AHRS orientation estimations from any kind of noise, independently of its nature. This deep learning-based architecture already proved to be robust and reliable, but in its enhanced implementation significant improvements are obtained in terms of both results and performance. In fact, DANAE++ is able to denoise the three angles describing the attitude at the same time, and that is verified also using the estimations provided by an extended KF. Further tests could make this method suitable for real-time applications in navigation tasks. Full article
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