An Autonomous Solar-Powered Marine Robotic Observatory for Permanent Monitoring of Large Areas of Shallow Water

González-Reolid, I; Molina, Juan Carlos Molina; Guerrero-González, Antonio; Ortiz, Francisco; Alonso, Diego

doi:10.3390/s18103497

Cited by 14 publications

(20 citation statements)

References 17 publications

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“…The displacement of the vessel under normal operating conditions was approximately 1000 kg, with an average draft of 0.325 m. The ASV was steered by two independent outboard propellers anchored to the transom. Further information on the ASV can be found in [23].…”

Section: Methodsmentioning

confidence: 99%

Underwater Acoustic Impulsive Noise Monitoring in Port Facilities: Case Study of the Port of Cartagena

Enguix

Egea

González

et al. 2019

Sensors

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Recording underwater impulsive noise data is an important aspect of mitigating its environmental impact and improving maritime environmental management systems. This paper describes the method used and results of the spatial monitoring of both the baseline noise level and the impulsive noise sources in the Port of Cartagena. An autonomous vessel was equipped with a smart digital hydrophone with a working frequency range between 10 and 200 kHz and a received voltage response (RVR) of, approximately, −170 dB re 1V/µPa. A GIS map was drawn up with the spatiotemporal distribution of the basal sound pressure levels by coupling the acoustic data with the vessel’s GPS positions to identify the sources of the impulsive noise of interest and their temporal characteristics. The loading of cargo containers was identified as the main source of impulse noise. This study is the first of a series designed to obtain accurate information on underwater noise pollution and its potential impact on biodiversity in the Port of Cartagena.

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Section: Methodsmentioning

confidence: 99%

Underwater Acoustic Impulsive Noise Monitoring in Port Facilities: Case Study of the Port of Cartagena

Enguix

Egea

González

et al. 2019

Sensors

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“…The BUSCAMOS-VIGIA ASV was developed by DAyRA (División de Automatización y Robótica Autónoma) group at the Technical University of Cartagena (UPCT). One of its achievements is described in González-Reolid et al [ 4 ], where we gave the ASV the capability to perform long-term missions to acquire data from multiparameter probes in the Mar Menor (Murcia, Spain) on factors to decide the urgency in inspecting a specific area based on fuzzy logic.…”

Section: Proposed Platform For Surveillance In Marine Protected Areasmentioning

confidence: 99%

“…There are also other issues: mainly water quality, pollution, and the effect on the ecosystem. In a previous work, we proposed an autonomous system consisting of an autonomous solar-powered marine robot with specialized sensing systems [ 4 ], designed to carry out long-term observation missions in shallow water, collecting georeferenced oceanic data to monitor and analyze physical–chemical water parameters.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas

Molina

Salhaoui

Guerrero-González

et al. 2021

Sensors

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The world’s oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected by law due to their unique characteristics, such as being the habitat of endangered marine species. Even with this protection, there are still illegal activities such as poaching or anchoring that threaten the survival of different marine species. In this context, we propose an autonomous surface vehicle (ASV) model system for the surveillance of marine areas by detecting and recognizing vessels through artificial intelligence (AI)-based image recognition services, in search of those carrying out illegal activities. Cloud and edge AI computing technologies were used for computer vision. These technologies have proven to be accurate and reliable in detecting shapes and objects for which they have been trained. Azure edge and cloud vision services offer the best option in terms of accuracy for this task. Due to the lack of 4G and 5G coverage in offshore marine environments, it is necessary to use radio links with a coastal base station to ensure communications, which may result in a high response time due to the high latency involved. The analysis of on-board images may not be sufficiently accurate; therefore, we proposed a smart algorithm for autonomy optimization by selecting the proper AI technology according to the current scenario (SAAO) capable of selecting the best AI source for the current scenario in real time, according to the required recognition accuracy or low latency. The SAAO optimizes the execution, efficiency, risk reduction, and results of each stage of the surveillance mission, taking appropriate decisions by selecting either cloud or edge vision models without human intervention.

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“…Fornai [21] presented the small-size autonomous surface vessel (ASV) able to perform water column monitoring with a bespoke sampling probe (Figure 3). The autonomous solar-powered vessel "BUSCAMOS-RobObs" equipped with side scan sonar, sub-bottom sonar, laser systems, ultrasound sonar, depth metres, a multi-parametric probe and a GPS for collecting georeferenced oceanic data has been tested at the coastal lagoon system of Mar Menor (Spain) [22] (Figure 3). Low-budget and portable autonomous vessels have also been proved to be efficient with the collection of bathymetry and other variables in remote and dangerous coastal areas [23] (Figure 3).…”

Section: Autonomous Underwater Vehicles Rovs and On-water Platformsmentioning

confidence: 99%

“…Characterization of the euphotic and epipelagic zones can be achieved with both autonomous underwater vehicles (AUV) and remotely operated underwater vehicles (ROVs) (Figure 4 (1) ASV equipped with a winch system for autonomous water column sampling [21]; (2) the solarpowered ASV equipped with a large range of sensors is able of self-mooring [22]; (3) the affordable and portable size ASV used in coastal surveys in Greenland [23].…”

Section: Autonomous Underwater Vehicles Rovs and On-water Platformsmentioning

confidence: 99%

Autonomous Systems for the Environmental Characterization of Lagoons

Casado¹,

Palma²,

Leinster³

2020

Lagoon Environments Around the World - A Scientific Perspective

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This chapter reviews the state of the art in robotics and autonomous systems (RAS) for monitoring the environmental characteristics of lagoons, as well as potential future uses of such technologies that could contribute to enhancing current monitoring programmes. Particular emphasis will be given to unmanned aerial vehicles (UAVs), autonomous under water vehicles (AUVs), remotely operated underwater vehicles (ROVs) and (semi-)autonomous boats. Recent technological advances in UAVs, AUVs and ROVs have demonstrated that high-resolution data (e.g. 0.4 cm imagery resolution) can be gathered when bespoke sensors are incorporated within these platforms. This in turn enables the accurate quantification of key metrics within lagoon environments, such as coral morphometries. For example, coral height and width can now be estimated remotely with errors below 12.6 and 14.7 cm, respectively. The chapter will explore how the use of such technologies in combination could improve the understanding of lagoon environments through increased knowledge of the spatial and temporal variations of parameters of interest. Within this context, both advantages and limitations of the proposed approaches will be highlighted and described from operational, logistical, and regulatory considerations. The chapter will be based on recent peer-reviewed research outputs obtained by the authors.

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An Autonomous Solar-Powered Marine Robotic Observatory for Permanent Monitoring of Large Areas of Shallow Water

Cited by 14 publications

References 17 publications

Underwater Acoustic Impulsive Noise Monitoring in Port Facilities: Case Study of the Port of Cartagena

Underwater Acoustic Impulsive Noise Monitoring in Port Facilities: Case Study of the Port of Cartagena

Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas

Autonomous Systems for the Environmental Characterization of Lagoons

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