Zeitschriftenartikel zum Thema „Electronic monitoring in fisheries“
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1
Glemarec, Gildas, Lotte Kindt-Larsen, Louise Scherffenberg Lundgaard und Finn Larsen. „Assessing seabird bycatch in gillnet fisheries using electronic monitoring“. Biological Conservation 243 (März 2020): 108461. http://dx.doi.org/10.1016/j.biocon.2020.108461.
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van Helmond, A. T. M., C. Chen und J. J. Poos. „How effective is electronic monitoring in mixed bottom-trawl fisheries?“ ICES Journal of Marine Science 72, Nr. 4 (11.11.2014): 1192–200. http://dx.doi.org/10.1093/icesjms/fsu200.
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Gilman, Eric, Gonzalo Legorburu, Andrew Fedoruk, Craig Heberer, Mark Zimring und Amos Barkai. „Increasing the functionalities and accuracy of fisheries electronic monitoring systems“. Aquatic Conservation: Marine and Freshwater Ecosystems 29, Nr. 6 (10.05.2019): 901–26. http://dx.doi.org/10.1002/aqc.3086.
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Brown, Christopher J., Amelia Desbiens, Max D. Campbell, Edward T. Game, Eric Gilman, Richard J. Hamilton, Craig Heberer, David Itano und Kydd Pollock. „Electronic monitoring for improved accountability in western Pacific tuna longline fisheries“. Marine Policy 132 (Oktober 2021): 104664. http://dx.doi.org/10.1016/j.marpol.2021.104664.
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Helmond, Aloysius T. M., Lars O. Mortensen, Kristian S. Plet‐Hansen, Clara Ulrich, Coby L. Needle, Daniel Oesterwind, Lotte Kindt‐Larsen et al. „Electronic monitoring in fisheries: Lessons from global experiences and future opportunities“. Fish and Fisheries 21, Nr. 1 (14.11.2019): 162–89. http://dx.doi.org/10.1111/faf.12425.
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Gilman, Eric, Vicente De Ramón Castejón, Eparama Loganimoce und Milani Chaloupka. „Capability of a pilot fisheries electronic monitoring system to meet scientific and compliance monitoring objectives“. Marine Policy 113 (März 2020): 103792. http://dx.doi.org/10.1016/j.marpol.2019.103792.
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Ulrich, Clara, Hans Jakob Olesen, Heiðrikur Bergsson, Josefine Egekvist, Kirsten Birch Håkansson, Jørgen Dalskov, Lotte Kindt-Larsen und Marie Storr-Paulsen. „Discarding of cod in the Danish Fully Documented Fisheries trials“. ICES Journal of Marine Science 72, Nr. 6 (15.03.2015): 1848–60. http://dx.doi.org/10.1093/icesjms/fsv028.
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Abstract Denmark was the first nation in Europe to promote the use of Fully Documented Fisheries (FDF) through Remote Electronic Monitoring (REM) and CCTV camera systems, with pilot schemes in place since 2008. In theory, such a scheme could supplement and even potentially replace expensive control and monitoring programmes; and when associated with a catch quota management (CQM) system, incentivize positive changes in fishing patterns in a results-based management approach. New data flows are, however, required to ensure the practical implementation of such a scheme. This paper reviews the quality of the FDF data collected during 2008–2014 and their potential in strengthening information on cod discards. The analyses demonstrate the improved reporting of discards in logbooks and overall discard reductions, but they also show that some uncertainties around the absolute estimates of discard quantities have remained. Regular validation of weight estimation methods and close collaboration between scientific monitoring and control are important to support the use of reported discards as a reliable source of information. We discuss the potential of electronic monitoring in the context of the EU landing obligation.
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Emery, Timothy J., Rocio Noriega, Ashley J. Williams und James Larcombe. „Changes in logbook reporting by commercial fishers following the implementation of electronic monitoring in Australian Commonwealth fisheries“. Marine Policy 104 (Juni 2019): 135–45. http://dx.doi.org/10.1016/j.marpol.2019.01.018.
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Acharya, Debaditya, Moshiur Farazi, Vivien Rolland, Lars Petersson, Uwe Rosebrock, Daniel Smith, Jessica Ford et al. „Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system“. Fisheries Research 272 (April 2024): 106939. http://dx.doi.org/10.1016/j.fishres.2024.106939.
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Latief, Tamana, Farooz Ahmad Bhat1, Tasaduq Hussain Shah, Adnan Abubakr, Bilal Ahmad Bhat und Ashwani Kumar. „Innovative Technologies in Fisheries Sector“. Chronicle of Aquatic Science 10, Nr. 01 (2024): 102–14. http://dx.doi.org/10.61851/coas.v1i10.10.
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The World’s greatest confronting issue is the increment in population and the trouble of feeding them healthy food. Agriculture and fisheries play a crucial role in global fish production on land and within the ocean. But currently the sector is facing numerous issues due to the use of age-old traditional techniques, improper management, environmental pollution and expensive labour costs. Hence this sector has embraced use of automation and technologies to address these challenges. This article looks at how fisheries management has changed as a result of technological improvements. Aquaculture innovations as well as advancements in robotics, autonomous systems, automatic feeding devices, drones, electronic tracking and reporting, acoustic devices, remote sensing and satellite monitoring are all on display. With the help of technology, the production and trading of fisheries can undergo an emerging shift. Technology has also set its way to the fish markets and supply chains. This study focuses on how technology may increase the sustainability, efficacy and transparency of fisheries paving the way for a future in which ethical fishing practices and healthy marine ecosystems coexist.
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Needle, Coby L. „Honeycomb: a spatio-temporal simulation model to evaluate management strategies and assessment methods“. ICES Journal of Marine Science 72, Nr. 1 (29.07.2014): 151–63. http://dx.doi.org/10.1093/icesjms/fsu130.
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Abstract In recent years, scientists providing advice to fisheries managers have been granted access to an increasing range of spatio-temporal data from fishing vessels, using tools such as vessel monitoring systems and electronic observation platforms. This information should allow for the provision of more germane advice on the activity of vessels, and hence the likely impact of management measures which are becoming increasingly spatial in nature. However, the development of appropriate management simulation and assessment models has lagged behind the availability of these new data. This paper presents an accessible spatio-temporal simulation framework (Honeycomb) which features a weekly time-step, multiple stocks and vessels, and economic decision rules and applies this to a case study of a spatial evaluation of a simple closed-area fishery policy. We conclude that the development and utilization of such spatio-temporal simulation models is a key research task for fisheries in which both spatial fisheries data and spatial fisheries management are becoming paramount.
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Bartholomew, David C., Jeffrey C. Mangel, Joanna Alfaro-Shigueto, Sergio Pingo, Astrid Jimenez und Brendan J. Godley. „Remote electronic monitoring as a potential alternative to on-board observers in small-scale fisheries“. Biological Conservation 219 (März 2018): 35–45. http://dx.doi.org/10.1016/j.biocon.2018.01.003.
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Emery, Timothy J., Rocio Noriega, Ashley J. Williams und James Larcombe. „Measuring congruence between electronic monitoring and logbook data in Australian Commonwealth longline and gillnet fisheries“. Ocean & Coastal Management 168 (Februar 2019): 307–21. http://dx.doi.org/10.1016/j.ocecoaman.2018.11.003.
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Pratiwi, Tia Dini, Budy Wiryawan und Tri Wiji Nurani. „Implementation of Tuna Traceability in Ocean Fishing Port of Nizam Zachman Jakarta“. Marine Fisheries : Journal of Marine Fisheries Technology and Management 12, Nr. 1 (31.05.2021): 23–34. http://dx.doi.org/10.29244/jmf.v12i1.32827.
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Nizam Zachman Fishing Port (PPS Nizam Zachman) is one of fishing ports in Indonesia that implemented traceability and has export-destination to the United States and the European Union. However, previous study showed that documents recording and fish handling activities in the fishing port were poorly managed. Objectives of this study were to identify structure of supply chain, formulate obstacle factors of traceability, and recommend implementation actions of traceability. Data were collected through observation and interviews with longline tuna fishermen and tuna processing entrepreneurs. Subsequently, data were analyzed by applying descriptive and GAP analysis. The results showed that supply chain of tuna fisheries at PPS Nizam Zachman was started from fishermen, fish landing center, and ended at tuna processing industries. Regarding traceability implementation, 83% of activities at the Nizam Zachman fishing port met the standard. However, improvement was still required for documentation process at fishermen and processing phase, in addition to tuna handling procedures. Factors that impede traceability include e-logbooks filling, tuna handling at unloading process; 1) No regular checking on temperature at every 2 hours; 2) slow loading and unloading speed; 3) Fish are exposed to the floor during transportation process, no refrigerated vehicles were used during transportation process, and no electronics documentation. Some actions to overcome traceability implementation problems are: 1) evaluating and monitoring the fishermen activities; 2) doing periodic quality control in the field; 3) managing collaborations between the government and NGOs and tuna fisheries industry associations.Keywords: GAP analysis, supply chain, traceability, tuna export, tuna handling
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Neidig, Carole, Max Lee, Genevieve Patrick und Ryan Schloesser. „Employing an innovative underwater camera to improve electronic monitoring in the commercial Gulf of Mexico reef fish fishery“. PLOS ONE 19, Nr. 3 (08.03.2024): e0298588. http://dx.doi.org/10.1371/journal.pone.0298588.
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Vessel electronic monitoring (EM) systems used in fisheries around the world apply a variety of cameras to record catch as it is brought on deck and during fish processing activities. In EM work conducted by the Center for Fisheries Electronic Monitoring at Mote (CFEMM) in the Gulf of Mexico commercial reef fish fishery, there was a need to improve upon current technologies to enhance camera views for accurate species identification of large sharks, particularly those that were released while underwater at the vessel side or underneath the hull. This paper describes how this problem was addressed with the development of the first known EM system integrated underwater camera (UCAM) with a specialized vessel-specific deployment device on a bottom longline reef fish vessel. Data are presented based on blind video reviews from CFEMM trained reviewers of the resulting UCAM video footage compared with video from only the overhead EM cameras from 68 gear retrievals collected from eight fishing trips. Results revealed that the UCAM was a successful tool for capturing clear underwater video footage of released large (>2m) sharks to enable reviewers to improve individual species identification, determination, and fate by 34.4%. This was particularly important for obtaining data on incidental catches of large protected shark species. It also provided clear underwater imagery of the presence of potential predators such as marine mammals close to the vessel, more specifically bottlenose dolphin (Tursiops truncatus) during gear retrieval, which often damaged or removed catch. This information is intended to assist researchers in need of gathering critical data on bycatch in close proximity to a vessel in which conventional overhead EM cameras are limited.
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Jalbert, Kirk, Matthew Cutler, Teal Guetschow und Noa Bruhis. „Surveillance Systems for Sustainable Fisheries: Perceptions on the Adoption of Electronic Monitoring in the Northeast US Multispecies Fishery“. Surveillance & Society 21, Nr. 3 (24.09.2023): 288–303. http://dx.doi.org/10.24908/ss.v21i3.15790.
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Amendment 23 (A23) to the Northeast Multispecies Fisheries Management Plan will remake monitoring systems for the Northeast US commercial groundfish fishery. In addition to substantially increasing monitoring coverage, A23 will provide fishers with the option to utilize electronic monitoring (EM) technologies in place of human at-sea observers. Based on twenty-six interviews with representatives of the fishing industry, nongovernmental organizations, regulatory agencies, EM service providers, and other stakeholder groups, this paper examines how the fishery is planning for the adoption of EM. We focus on the differing perspectives on the value of EM as an appropriate tool for protecting the fishery, and as a tool of surveillance that may transform the lives of fishers. We find that while most stakeholders support the use of EM in the future, mistrust within the industry—based on historical regulatory failures, perceived lack of information on technical feasibility, privacy and data ownership issues, and the unknown long-term costs to vessel owners—poses significant barriers to successful adoption of these technologies. We conclude that these barriers can be overcome by investing in co-management driven EM implementations that draw on the expertise of fishers and increase their autonomy over their vessels and their use of data. This study offers critical insights into the conflicting sociotechnical imaginaries that co-produce spaces of surveillance for natural resource management, as well as provides important findings for the fishery as A23 moves into implementation phases.
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Emery, Timothy J., Rocio Noriega, Ashley J. Williams, James Larcombe, Simon Nicol, Peter Williams, Neville Smith et al. „The use of electronic monitoring within tuna longline fisheries: implications for international data collection, analysis and reporting“. Reviews in Fish Biology and Fisheries 28, Nr. 4 (29.08.2018): 887–907. http://dx.doi.org/10.1007/s11160-018-9533-2.
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Ishii, Kazuo, Eiji Hayashi, Norhisam Bin Misron und Blair Thornton. „Special Issue on Advanced Robotics in Agriculture, Forestry and Fisheries“. Journal of Robotics and Mechatronics 30, Nr. 2 (20.04.2018): 163–64. http://dx.doi.org/10.20965/jrm.2018.p0163.
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The importance of primary industries, agriculture, forestry and fisheries, is obvious and needless to mention, however, the reduction of the working population and the aging problem make the situation of primary industry more sever. To compensate for the issues, the advanced technology in robotics has attracted attentions and expected the contributions in terms of productivity, cost effectiveness, pesticide-less, monitoring of the growth and harvesting, etc. Recently, robotic technologies are gradually being used in primary industry and their application area will expand more in the near future. This special issue’s objectives include collecting recent advances, automation, mechanization, research trends and their applications in agriculture, forestry and fisheries to promote a deeper understanding of major conceptual and technical challenges and facilitate spreading of recent breakthroughs in primary industries, and contribute to the enhancement of the quality of agricultural, forestry and fisheries robots by introducing the state-of-the-art in sensing, mobility, manipulation and related technologies. In this special issue, twelve papers are included. The first paper by Noguchi is the survey paper of the state-of-the-art in the agricultural vehicle type robots and discusses the future scope of agriculture with robotics. The next three papers are on tomato-monitoring system, and Fukui et al. propose a tomato fruit volume estimation method using saliency-based image processing and point cloud and clustering technology, Yoshida et al. do the cutting point identification for tomato-harvesting using a RGBD sensor and evaluate in the real farm experiments, and Fujinaga et al. present an image mosaicking method of tomato yard based on the infrared images and color images of tomato-clusters in the large green house. The fifth paper by Sori et al. reports a paddy weeding robot in wet-rice field to realize the pesticide-free produce of rice, and the sixth paper by Shigeta et al. is about an image processing system to measure cow’s BCS (Body Condition Score) automatically before milking cows and analyzes the two months data by CNN (Convolutional Neural Network). The seventh paper by Inoue et al. reports on an upper-limb power assist robot with a single actuator to reduce the weight and cost. The assist machine supports the shoulder and elbow movements for viticulture operations and upper-limb holding for load transport tasks. In the next paper, Tominaga et al. show an autonomous robotic system to move between the trees without damaging them and to cut the weeds in the forest for the forest industry. The last four papers are for the fishery industry, and Komeyama et al. propose a methods for monitoring the size of fish, red sea bream (RSB) aquaculture by developing a stereo vision system to avoid the risks of physical injury and mental stress to the fish. Nishida et al. report on a hovering type underwater robot to measure seafloor for monitoring marine resources whose sensor can be replaced depending on missions as the open hardware system. Yasukawa et al. propose a vision system for an autonomous underwater robot with a benthos sampling function, especially, sampling-autonomous underwater vehicles (SAUVs) to achieve a new sampling mission. The last paper by Han et al. is for gait planning and simulation analysis of an amphibious quadruped robot in the field of fisheries and aquaculture. We hope that this special issue can contributes to find solutions in primary industries, agriculture, forestry and fisheries.
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Mendo, Tania, Sophie Smout, Theoni Photopoulou und Mark James. „Identifying fishing grounds from vessel tracks: model-based inference for small scale fisheries“. Royal Society Open Science 6, Nr. 10 (Oktober 2019): 191161. http://dx.doi.org/10.1098/rsos.191161.
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Recent technological developments facilitate the collection of location data from fishing vessels at an increasing rate. The development of low-cost electronic systems allows tracking of small-scale fishing vessels, a sector of fishing fleets typically characterized by many, relatively small vessels. The imminent production of large spatial datasets for this previously data-poor sector creates a challenge in terms of data analysis. Several methods have been used to infer the spatial distribution of fishing activities from positional data. Here, we compare five approaches using either vessel speed, or speed and turning angle, to infer fishing activity in the Scottish inshore fleet. We assess the performance of each approach using observational records of true vessel activity. Although results are similar across methods, a trip-based Gaussian mixture model provides the best overall performance and highest computational efficiency for our use-case, allowing accurate estimation of the spatial distribution of active fishing (97% of true area captured). When vessel movement data can be validated, we recommend assessing the performance of different methods. These results illustrate the feasibility of designing a monitoring system to efficiently generate information on fishing grounds, fishing intensity, or monitoring of compliance to regulations at a nationwide scale in near-real-time.
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N. Lanjewar, Gaurav, Shweta A. Sonawane, Digvijay D. Chauhan, Omkar Kode, Hitesh B. Jagane und Saurabh Rawoo. „Navigating the Depths of the Global Marine Fisheries Crisis: A Brief Review“. Chronicle of Aquatic Science 10, Nr. 01 (2024): 43–52. http://dx.doi.org/10.61851/coas.v1i10.04.
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The global fisheries industry faces a critical challenge with annual catches exceeding sustainable levels, leading to overexploitation. Establishing precise global limits is difficult, highlighting the need for immediate action, particularly due to severe overcapacity. Managing fisheries is complicated by uncertainties, requiring safety margins, risk management, and transparent institutional arrangements. Indiscriminate fishing methods like gill nets and traps pose ecological threats, capturing targeted species while endangering non-commercial marine species and disrupting marine ecosystems. Effects of COVID-19 on fisheries include changes in food consumption, supply chain disruptions, and socio-economic instability. Overfishing, driven by increased demand and technological advancements, has depleted fish stocks, impacting ecosystems and food security. Climate change worsens these challenges through ocean acidification, sea level rise, and habitat alterations. Proposed solutions involve restoring fish populations, enhancing carbon storage, and reducing CO2 emissions. Sustainable fisheries management requires recovery measures, improved monitoring, and ecosystem-focused scientific advice, including fishing bans, habitat restoration, and promoting sustainable practices. Immediate comprehensive measures are needed to address overfishing, mitigate climate change impacts, and ensure long-term global fisheries sustainability.
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Tassetti, Anna Nora, Alessandro Galdelli, Jacopo Pulcinella, Adriano Mancini und Luca Bolognini. „Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System“. Sensors 22, Nr. 3 (22.01.2022): 839. http://dx.doi.org/10.3390/s22030839.
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During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative information of industrial fisheries. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they play an important socio-economic and cultural role in European waters and coastal communities and account for most of the total EU fishing fleet. The typically low-technological capacity of these small-scale fishing boats—for which space and power onboard are often limited—as well their reduced operative range encourage the development of efficient, low-cost, and low-burden tracking solutions. In this context, we designed a cost-effective and scalable prototypic architecture to gather and process positional data from small-scale vessels, making use of a LoRaWAN/cellular network. Data collected by our first installation are presented, as well as its preliminary processing. The emergence of a such low-cost and open-source technology coupled to artificial intelligence could open new opportunities for equipping small-scale vessels, collecting their trajectory data, and estimating their fishing effort (information which has historically not been present). It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to inform coastal resource and fisheries management.
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van Helmond, Aloysius T. M., Chun Chen und Jan Jaap Poos. „Using electronic monitoring to record catches of sole (Solea solea) in a bottom trawl fishery“. ICES Journal of Marine Science 74, Nr. 5 (10.01.2017): 1421–27. http://dx.doi.org/10.1093/icesjms/fsw241.
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Electronic monitoring (EM) is often presented as a solution to document all catches through video observations under the EU landing obligation. However, identifying small fish on video in large volumes of catch is challenging. In this study, logbook records were compared with video observations for catches to test efficacy of EM for different size classes of sole (Solea solea) on board bottom trawlers. Comparisons were based on: (i) systematic differences (paired t-test), (ii) linear correlation (Pearson’s r), and (iii) absolute agreement (ICC). Results suggest that EM of small individuals in mixed fisheries is not as effective as it is for large individuals. To improve efficiency for estimating quantities of small fish, additional methods are required to enhance video review. One possible method for enhancing video review is using a protocol where crew arranged the individual fish in front of the cameras. Indeed, this study suggests that such a protocol substantially improves EM of the complete catch. However, the protocol requires an additional three minutes of processing time per haul for a single species. Given the large number of quota species under the landing obligation for this fishery, implementing the protocol thus comes with a cost for the fishing industry; the extra time needed to conduct a simple protocol probably would exceed 12 h per fishing trip.
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Votier, S. C., R. B. Sherley, K. L. Scales, K. Camphuysen und R. A. Phillips. „An overview of the impacts of fishing on seabirds, including identifying future research directions“. ICES Journal of Marine Science 80, Nr. 9 (01.11.2023): 2380–92. http://dx.doi.org/10.1093/icesjms/fsad173.
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Abstract Knowledge of fisheries impacts, past and present, is essential for understanding the ecology and conservation of seabirds, but in a rapidly changing world, knowledge and research directions require updating. In this Introduction and in the articles in this Themed Set “Impacts of fishing on seabirds”, we update our understanding of how fishing impacts seabird communities and identify areas for future research. Despite awareness of the problems and mitigation efforts for >20 years, fisheries still negatively impact seabirds via the effects of bycatch, competition, and discards. Bycatch continues to kill hundreds of thousands of seabirds annually, with negative population-level consequences. Fisheries for forage fish (e.g. anchovy, sandeel, and krill) negatively impact seabirds by competing for the same stocks. Historically, discards supplemented seabird diets, benefitting some species but also increasing bycatch rates and altering seabird community composition. However, declining discard production has led to potentially deleterious diet switches, but reduced bycatch rates. To improve research into these problems, we make the following recommendations: (1) improve data collection on seabird–vessel interaction and bycatch rates, on fishing effort and vessel movements (especially small-scale fleets), and on mitigation compliance, (2) counter the current bias towards temperate and high-latitude ecosystems, larger-bodied species and particular life stages or times of year (e.g. adults during breeding), and (3) advance our currently poor understanding of combined effects of fisheries and other threats (e.g. climate change, offshore renewables). In addition, research is required on under-studied aspects of fishing impacts: consequences for depleted sub-surface predators, impacts of illegal, unreported and unregulated fishing, artisanal and emerging fisheries, such as those targeting mesopelagic fish, have received insufficient research attention. Some of these shortfalls can be overcome with new tools (e.g. electronic monitoring, remote sensing, artificial intelligence, and big data) but quantifying and addressing fishing impacts on seabirds requires greater research investment at appropriate spatio-temporal scales, and more inclusive dialogue from grassroots to national and international levels to improve governance as fishing industries continue to evolve.
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Megantoro, Prisma, Antik Widi Anugrah, Muhammad Hudzaifah Abdillah, Bambang Joko Kustanto, Marwan Fadhilah und Pandi Vigneshwaran. „Smart measurement and monitoring system for aquaculture fisheries with IoT-based telemetry system“. Bulletin of Electrical Engineering and Informatics 13, Nr. 3 (01.06.2024): 1555–65. http://dx.doi.org/10.11591/eei.v13i3.6900.
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The instrumentation design of an online monitoring device for aquaculture media is discussed in this article. The main processor in this internet of things (IoT) real-time telemetry system is an ESP32 board. Temperature, acidity level, conductivity level, dissolved oxygen (DO) level, and degree of oxygen reduction in the water were the aquaculture parameters measured. The ESP32 collects data from each sensor, groups it into a dataset, displays it on the LCD, saves it to the SD card, and then uploads it to the real-time database. In addition, an Android application is being developed for users. This device has been tested to ensure that each measured parameter is accurate and precise. The accuracy test, one of the major results of laboratory scale tests, demonstrates that each parameter has a different measurement error that represents with average error absolute. Six tested sensors/instruments were subjected to the test. Average absolute error for temperature sensor is +0.76%, pH sensor is +1.52%, electrical conductivity (EC) sensor is +10.8%, oxidation reduction potential (ORP) sensor is +14.6%, DO sensor is +9.3%, and total dissolve solids (TDS) sensor is +13.2%. This device is very dependable and convenient for monitoring the condition of aquaculture media in real-time and accurately.
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Kraus, Richard T., Helen Bontrager, Christopher S. Vandergoot und Matthew D. Faust. „Expanding freshwater biologger studies to view fish as environmental sensing platforms“. Marine and Freshwater Research 73, Nr. 1 (2022): 133. http://dx.doi.org/10.1071/mf21046.
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While recording fish habitat use by electronic sensors, biologgers can also be viewed as autonomous environmental monitoring systems with the organism as a vehicle. This dual perspective has provided novel results from marine ecosystems, but has not been applied to freshwater ecosystems. To understand limitations in fresh water, we evaluated miniature depth and temperature recorders as aquatic monitoring systems in a Laurentian Great Lake: Erie. As part of an acoustic telemetry study, biologgers were opportunistically implanted in a subsample of walleye Sander vitreus. Biologgers recorded temperature and depth at half-hour intervals for up to 1 year. Recaptures provided six biologgers for analysis of seasonal temperature patterns and lake stratification, key variables for understanding dimictic lakes. Depth-resolved temperature patterns showed close correspondence with independent weather buoy measurements. Because the buoy was deployed late in the season, biologger data provided improved estimates of the start of stratification, which had important implications for understanding development of hypoxia in the hypolimnion. Drawbacks to biologger data included imprecise knowledge of fish location and reliance on tag recoveries from the fishery. Optimistically, our results show how biologgers could be part of a monitoring approach that integrates limnological surveys with fisheries science.
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Muammar Yuliana, Edy Sutrisno und Asropi. „Factors for The Implementation of Talent Management in the Ministry of Marine Affairs and Fisheries of The Republic of Indonesia“. JMKSP (Jurnal Manajemen, Kepemimpinan, dan Supervisi Pendidikan) 8, Nr. 1 (28.06.2023): 390–404. http://dx.doi.org/10.31851/jmksp.v8i1.12077.
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Implementation of effective talent management at the Ministry of Marine Affairs and Fisheries (MMAF) has an important role in optimizing talent potential and improving organizational performance. This study aims to identify and analyze the factors that influence the implementation of talent management in MMAF focusing on the marine and fisheries sector in Indonesia. The research method used is a qualitative approach by conducting in-depth interviews with high-ranking officials, administrators, and functional officials who are directly involved in managing talent management at the Ministry. The results of the study found that the factors that influence the implementation of talent management in MMAF are (1) top management's commitment to talent management plays an important role in creating an environment that supports effective talent management, (2) clear policies and procedures in talent management facilitate the implementation and monitoring of these programs, (3) structured career development and learning opportunities help motivate employees to work better and stay in the organization and (4) proper rewards and recognition for employee achievements and contributions can increase job satisfaction and talent retention. This research provides recommendations to the Ministry to develop competitive strategies to attract, develop and retain quality talent.
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RAMAKRISHNA, BHARATH, CHEIN-I. CHANG, BRUCE TROU und JERRY HENQEMIHLE. „CHESAPEAKE BAY WATER QUALITY MONITORING USING SATELLITE IMAGERY“. International Journal of High Speed Electronics and Systems 17, Nr. 04 (Dezember 2007): 681–88. http://dx.doi.org/10.1142/s0129156407004886.
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The Chesapeake Bay is a valued ecological, economic, recreational, cultural and scenic resource. The Bay watershed States and the District of Columbia, in conjunction with the EPA Chesapeake Bay Program, have worked and teamed together over the past 20 years to protect and restore the Bay ecosystem. A key component of this effort is water quality and habitat monitoring to assess the impact of management actions and natural processes, and evaluate habitat parameters on living resources such as submerged aquatic vegetation (SAV), oysters, and fisheries. Using aerial and satellite remote sensing imagery has become a practical and effective means of monitoring water quality in a timely manner. Of particular interest in evaluation of water clarity are several initiative measures. Specifically, Secchi-Disk Transparency (SDT) and Chlorophyll a (Chl-a) have been widely accepted as critical indicators of water quality and their reliable estimation using satellite imagery provides a cost effective and speedy means for water quality monitoring. Work done at Water Resources Center, University of Minnesota has demonstrated the feasibility of performing regional assessment of lake water quality using LANDSAT image data. This paper investigates an approach similar to their work but uses a different type of satellite imagery, EO-1 ALI imagery where the SDT and Chl-a are also used as indicators to estimate water quality for the Chesapeake Bay and DC area (Potomac River). In doing so, three major issues are investigated, which are (1) the study site that is an open Bay area, not a self-contained lake; (2) investigation of applicability of equations that are used to specify the SDT and Chl-a to our Bay area study; (3) the use of a different type of satellite imagery for water quality monitoring. This paper develops techniques to address these three issues and presents preliminary experiments which show encouraging results.
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Stanley, Richard D., Howard McElderry, Tameezan Mawani und John Koolman. „The advantages of an audit over a census approach to the review of video imagery in fishery monitoring“. ICES Journal of Marine Science 68, Nr. 8 (09.05.2011): 1621–27. http://dx.doi.org/10.1093/icesjms/fsr058.
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Abstract Stanley, R. D., McElderry, H., Mawani, T., and Koolman, J. 2011. The advantages of an audit over a census approach to the review of video imagery in fishery monitoring. – ICES Journal of Marine Science, 68: 1621–1627. Technology-based fishery monitoring, or electronic monitoring (EM), has emerged as an alternative to human observers and is being applied in a variety of fisheries. The method records sensor and image data from fishing operations, so can be used to provide 100% monitoring of catches and fishing activity. Alternatively, EM can be used to audit catch data self-reported by harvesters. If the random audit indicates that these data are sufficiently accurate, they can provide useful catch estimates with less reviewing time and, hence, cost. The audit approach was adopted in the groundfish hook-and-line fishery in British Columbia, Canada, in 2006, and experience has shown that it can meet operational requirements for accuracy and timeliness. It is also more robust to the impact of equipment malfunction and can provide an independent estimate of total catch. Moreover, because catch estimates are derived from self-reported data rather than “black-box” records, the estimation process is more transparent and intuitive and, hence, more trusted by harvesters. Although cost reduction is always a primary concern, the audit approach offers significant additional benefits that should be considered in the design and implementation of EM programmes.
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Omkar Mahajan. „YOLOv8 based fish detection and classification on fishnet dataset“. Journal of Electrical Systems 20, Nr. 3 (08.05.2024): 1456–64. http://dx.doi.org/10.52783/jes.3552.
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The research examines the marine fishing sector and highlights the urgent need for an electronic monitoring system designed to meet the unique needs of fishermen. The initiative’s motive is emphasized in the paper, which highlights how cutting-edge technology like object detection and tracking could revolutionize the fishing industry when integrated into an electronic monitoring framework. The research proposes an electronic monitoring system based on YOLOv8 (You Only Look Once) as a comprehensive solution to address current issues, such as out-of-date data collection methods and a lack of guiding applications. The review of the literature, which highlights gaps in the current fishing applications, is an important component of the paper. The research is geared towards training an object detection model on the fishnet dataset. The focus is on data processing created by an electronic monitoring system to rectify the current state of the fishing industry’s deficiencies.
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Morris, David J., John K. Pinnegar, David L. Maxwell, Stephen R. Dye, Liam J. Fernand, Stephen Flatman, Oliver J. Williams und Stuart I. Rogers. „Over 10 million seawater temperature records for the United Kingdom Continental Shelf between 1880 and 2014 from 17 Cefas (United Kingdom government) marine data systems“. Earth System Science Data 10, Nr. 1 (09.01.2018): 27–51. http://dx.doi.org/10.5194/essd-10-27-2018.
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Abstract. The datasets described here bring together quality-controlled seawater temperature measurements from over 130 years of departmental government-funded marine science investigations in the UK (United Kingdom). Since before the foundation of a Marine Biological Association fisheries laboratory in 1902 and through subsequent evolutions as the Directorate of Fisheries Research and the current Centre for Environment Fisheries & Aquaculture Science, UK government marine scientists and observers have been collecting seawater temperature data as part of oceanographic, chemical, biological, radiological, and other policy-driven research and observation programmes in UK waters. These datasets start with a few tens of records per year, rise to hundreds from the early 1900s, thousands by 1959, and hundreds of thousands by the 1980s, peaking with > 1 million for some years from 2000 onwards. The data source systems vary from time series at coastal monitoring stations or offshore platforms (buoys), through repeated research cruises or opportunistic sampling from ferry routes, to temperature extracts from CTD (conductivity, temperature, depth) profiles, oceanographic, fishery and plankton tows, and data collected from recreational scuba divers or electronic devices attached to marine animals. The datasets described have not been included in previous seawater temperature collation exercises (e.g. International Comprehensive Ocean–Atmosphere Data Set, Met Office Hadley Centre sea surface temperature data set, the centennial in situ observation-based estimates of sea surface temperatures), although some summary data reside in the British Oceanographic Data Centre (BODC) archive, the Marine Environment Monitoring and Assessment National (MERMAN) database and the International Council for the Exploration of the Sea (ICES) data centre. We envisage the data primarily providing a biologically and ecosystem-relevant context for regional assessments of changing hydrological conditions around the British Isles, although cross-matching with satellite-derived data for surface temperatures at specific times and in specific areas is another area in which the data could be of value (see e.g. Smit et al., 2013). Maps are provided indicating geographical coverage, which is generally within and around the UK Continental Shelf area, but occasionally extends north from Labrador and Greenland to east of Svalbard and southward to the Bay of Biscay. Example potential uses of the data are described using plots of data in four selected groups of four ICES rectangles covering areas of particular fisheries interest. The full dataset enables extensive data synthesis, for example in the southern North Sea where issues of spatial and numerical bias from a data source are explored. The full dataset also facilitates the construction of long-term temperature time series and an examination of changes in the phenology (seasonal timing) of ecosystem processes. This is done for a wide geographic area with an exploration of the limitations of data coverage over long periods. Throughout, we highlight and explore potential issues around the simple combination of data from the diverse and disparate sources collated here. The datasets are available on the Cefas Data Hub (https://www.cefas.co.uk/cefas-data-hub/). The referenced data sources are listed in Sect. 5.
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Vinston Raja, R., K. Ashok Kumar und V. Gokula Krishnan. „Condition based Ensemble Deep Learning and Machine Learning Classification Technique for Integrated Potential Fishing Zone Future Forecasting“. International Journal on Recent and Innovation Trends in Computing and Communication 11, Nr. 2 (10.03.2023): 75–85. http://dx.doi.org/10.17762/ijritcc.v11i2.6131.
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Artificial Intelligence (AI) technologies have become a popular application in order to improve the sustainability of smart fisheries. Although the ultimate objective of AI applications is often described as sustainability, there is yet no proof as to how AI contributes to sustainable fisheries. The proper monitoring of the longitudinal delivery of different human impacts on activities such as fishing is a major concern today in aquatic conservation. The term "potential fishing zone" (PFZ) refers to an anticipated area of any given sea where a variety of fish may congregate for some time. The forecast is made based on factors including the sea surface temperature (SST) and the sea superficial chlorophyll attentiveness. Fishing advisories are a by-product of the identification procedure. Normalization and preliminary processing are applied to these unprocessed data. The gathered attributes, together with financial derivatives and geometric features, are then utilised to make projections about IPFZ's Technique are used to get the final determination (CECT). In this study, we offer a technique for identifying and mapping fishing activity. Experimentations are performed to validate the efficacy of the CECT method in comparison to machine learning (ML) and deep learning (DL) methods across a variety of measurable parameters. Results showed that CECT obtained 94% accuracy, while Convolutional neural network only managed 92% accuracy on 80% training data and 20% testing data.
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Ou, Liguo, Bilin Liu, Xinjun Chen, Qi He, Weiguo Qian und Leilei Zou. „Automated Identification of Morphological Characteristics of Three Thunnus Species Based on Different Machine Learning Algorithms“. Fishes 8, Nr. 4 (29.03.2023): 182. http://dx.doi.org/10.3390/fishes8040182.
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Tuna are economically important fish species. The automated identification of tuna species is of importance in fishery production and resource assessment in that it would facilitate the informed monitoring of tuna fishing vessels and the establishment of electronic observer systems. As morphological characteristics are important for tuna identification, this study aims to verify the performance of the automated identification of three Thunnus species through morphological characteristics based on different machine learning algorithms. Firstly, morphological outlines were visually analyzed using EFT (elliptic Fourier transform) and CNN (convolutional neural network). Then, the EFT feature data and deep feature data of the tuna outline images were extracted, and principal component analysis of the two different morphological characteristics was performed. Finally, different machine learning algorithms were used to analyze the identification performance of tuna of the same genus and different species. The experimental results showed that EFT features had the highest identification accuracy in KNN (K-nearest neighbor), with 90% for T. obesus, 90% for T. albacores, and 85% for T. alalunga. Deep features had the best identification performance in SVM (support vector machine), with 80% for T. obesus, 90% for T. albacores, and 100% for T. alalunga. Deep features were better than EFT features in identification performance. The biodiversity and intergeneric differences among tuna species can be well analyzed using these two different morphological characteristics. Machine learning algorithms open up the way for rapid near-real-time electronic observer systems in these important international fisheries.
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Plet-Hansen, Kristian S., Søren Q. Eliasen, Lars O. Mortensen, Heiðrikur Bergsson, Hans J. Olesen und Clara Ulrich. „Remote electronic monitoring and the landing obligation – some insights into fishers’ and fishery inspectors’ opinions“. Marine Policy 76 (Februar 2017): 98–106. http://dx.doi.org/10.1016/j.marpol.2016.11.028.
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Sung, Wen-Tsai, Indra Griha Tofik Isa und Sung-Jung Hsiao. „Designing Aquaculture Monitoring System Based on Data Fusion through Deep Reinforcement Learning (DRL)“. Electronics 12, Nr. 9 (27.04.2023): 2032. http://dx.doi.org/10.3390/electronics12092032.
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The aquaculture production sector is one of the suppliers of global food consumption needs. Countries that have a large amount of water contribute to the needs of aquaculture production, especially the freshwater fisheries sector. Indonesia is a country that has a large number of large bodies of water and is the top-five producer of aquaculture production. Technology and engineering continue to be developed to improve the quality and quantity of aquaculture production. One aspect that can be observed is how the condition of fish pond water is healthy and supports fish growth. Various studies have been conducted related to the aquaculture monitoring system, but the problem is how effective it is in terms of accuracy of the resulting output, implementation, and costs. In this research, data fusion (DF) and deep reinforcement learning (DRL) were implemented in an aquaculture monitoring system with temperature, turbidity, and pH parameters to produce valid and accurate output. The stage begins with testing sensor accuracy as part of sensor quality validation, then integrating sensors with wireless sensor networks (WSNs) so they can be accessed in real time. The implemented DF is divided into three layers: first, the signal layer consists of WSNs and their components. Second, the feature layer consists of DRL combined with deep learning (DL). Third, the decision layer determines the output of the condition of the fish pond in “normal” or “not normal” conditions. The analysis and testing of this system look at several factors, i.e., (1) the accuracy of the performance of the sensors used; (2) the performance of the models implemented; (3) the comparison of DF-DRL-based systems with rule-based algorithm systems; and (4) the cost effectiveness compared to labor costs. Of these four factors, the DF-DRL-based aquaculture monitoring system has a higher percentage value and is a low-cost alternative for an accurate aquaculture monitoring system.
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Prem Monickaraj, Vigilson, Sterlin Rani Devakadacham, Nithyadevi Shanmugam, Nithya Nandhakumar, Manjunathan Alagarsamy und Kannadhasan Suriyan. „Deep learning and machine learning classification technique for integrated forecasting“. IAES International Journal of Artificial Intelligence (IJ-AI) 13, Nr. 2 (01.06.2024): 1519. http://dx.doi.org/10.11591/ijai.v13.i2.pp1519-1525.
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Smart fisheries are increasingly using artificial intelligence (AI) technologies to increase their sustainability. The potential fishing zone (PFZ) forecasts several fish aggregation zones throughout the duration of the prediction in any sea. The autoregressive integrated moving average (ARIMA) and random forest model are used in the current study to provide a technique for locating viable fishing zones in deep marine seas. A significant amount of data was gathered for the database's creation, including monitoring information for Indian fishing fleets from 2017 to 2019. Using expert label datasets for validation, it was discovered that the model's detection accuracy was 98%. Our method uses salinity and dissolved oxygen, two crucial markers of water quality, to identify suitable fishing zones for the first time. In the current research, a system was created to identify and map the quantity of fishing activity. The tests use a number of parameter measurements to evaluate the contrast-enhanced computed tomography (CECT) approach to machine learning (ML) and deep learning (DL) methodologies. The findings showed that the CECT had a 94% accuracy rate compared to a convolutional neural network's 92% accuracy rate for the 80% training data and 20% testing data.
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Okomba, Nnamdi, Adebimpe Esan, Bolaji Omodunbi, Sobowale Adedayo, Iyoaye Fajimi, Lois Nwobodo und Ujunwa Nduanya. „Development of Microcontroller Based Water Quality Monitoring and Water Level Control Device“. FUOYE Journal of Engineering and Technology 9, Nr. 1 (01.05.2024): 43–48. http://dx.doi.org/10.4314/fuoyejet.v9i1.7.
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Access to clean and safe water is not only a fundamental human right but also a vital requirement for electronics industries, chemicals industries, pharmaceuticals, food and beverage production, fisheries and aquatic farming. This project addresses the pressing issue of water quality monitoring and efficient water usage within the context of these industries. The study's identification of problem areas for water quality can lead to more efficient interventions and solutions to safeguard the environment, and prevent waterborne diseases. This paper presents the design and implementation of microcontroller-based system for monitoring water quality and water level in the thank, the water in the thank is refilled when it goes beyond a set threshold with the aid of an automatic switch control. The system is a hybrid of 3 subsystems: a Water Level Checker, a Water Quality Monitoring System and an Automatic Switch control system. The Water level checker consists of Ultrasonic sensors. The Water Quality Monitoring system consists of pH sensors, TDS (Total Dissolved Solids) sensors and Turbidity sensors. The continuous (Analog) data from the water quality sensors used would be outputted via an LCD (Liquid Crystal Display). The Automatic Switch control system consists of 5v Relay modules and a 12v Pump that would automatically switch ON/OFF depending on the level of water in the tank. The values of EC (Electrical Conductivity) and TDS spike drastically to the introduction of salt from as low as 138 -906 for TDS and 0.34 – 2.04 for EC, signifying increase in water capacity of electrical conductivity. Temperature rise in the afternoon also increases TDS values from 142 for clean water to 920 for the salty water while it ranges from 138 for clean water to 906 for salt water at both morning and evening time. Pumping aspects of the system are triggered when water level in the thank falls below 10% and trips off when water level goes above 95% as programmed in the control unit. The developed system marks a significant achievement in water management and automation technology. integration of quality monitoring sensors has enabled real-time evaluation of water parameters that holds potential for applications in environmental monitoring, ensuring safe drinking water, and safeguarding aquatic ecosystems. The automated switch control mechanism responds dynamically to water levels, enabling the system to trigger actions such as pump activation or filling processes based on predefined thresholds.
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Peplinski, William J., Jesse Roberts, Geoff Klise, Sharon Kramer, Zach Barr, Anna West und Craig Jones. „Marine Energy Environmental Permitting and Compliance Costs“. Energies 14, Nr. 16 (04.08.2021): 4719. http://dx.doi.org/10.3390/en14164719.
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Costs to permit Marine Energy projects are poorly understood. In this paper we examine environmental compliance and permitting costs for 19 projects in the U.S., covering the last 2 decades. Guided discussions were conducted with developers over a 3-year period to obtain historical and ongoing project cost data relative to environmental studies (e.g., baseline or pre-project site characterization as well as post-installation effects monitoring), stakeholder outreach, and mitigation, as well as qualitative experience of the permitting process. Data are organized in categories of technology type, permitted capacity, pre- and post-installation, geographic location, and funding types. We also compare our findings with earlier logic models created for the Department of Energy (i.e., Reference Models). Environmental studies most commonly performed were for Fish and Fisheries, Noise, Marine Habitat/Benthic Studies and Marine Mammals. Studies for tidal projects were more expensive than those performed for wave projects and the range of reported project costs tended to be wider than ranges predicted by logic models. For eight projects reporting full project costs, from project start to FERC or USACE permit, the average amount for environmental permitting compliance was 14.6%.
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Er, Meng Joo, Jie Chen, Yani Zhang und Wenxiao Gao. „Research Challenges, Recent Advances, and Popular Datasets in Deep Learning-Based Underwater Marine Object Detection: A Review“. Sensors 23, Nr. 4 (10.02.2023): 1990. http://dx.doi.org/10.3390/s23041990.
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Underwater marine object detection, as one of the most fundamental techniques in the community of marine science and engineering, has been shown to exhibit tremendous potential for exploring the oceans in recent years. It has been widely applied in practical applications, such as monitoring of underwater ecosystems, exploration of natural resources, management of commercial fisheries, etc. However, due to complexity of the underwater environment, characteristics of marine objects, and limitations imposed by exploration equipment, detection performance in terms of speed, accuracy, and robustness can be dramatically degraded when conventional approaches are used. Deep learning has been found to have significant impact on a variety of applications, including marine engineering. In this context, we offer a review of deep learning-based underwater marine object detection techniques. Underwater object detection can be performed by different sensors, such as acoustic sonar or optical cameras. In this paper, we focus on vision-based object detection due to several significant advantages. To facilitate a thorough understanding of this subject, we organize research challenges of vision-based underwater object detection into four categories: image quality degradation, small object detection, poor generalization, and real-time detection. We review recent advances in underwater marine object detection and highlight advantages and disadvantages of existing solutions for each challenge. In addition, we provide a detailed critical examination of the most extensively used datasets. In addition, we present comparative studies with previous reviews, notably those approaches that leverage artificial intelligence, as well as future trends related to this hot topic.
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Strilets, Viktoriia, Volodymyr Donets, Mykhaylo Ugryumov, Sergii Artiuch, Roman Zelenskyi und Tamara Goncharova. „Agent-oriented data clustering for medical monitoring“. RADIOELECTRONIC AND COMPUTER SYSTEMS, Nr. 1 (23.02.2022): 103–14. http://dx.doi.org/10.32620/reks.2022.1.08.
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Medical data processing is one of the priority machine learning areas. Usually, data obtained in the process of medical patient monitoring are complex and have a different nature. Solving the problem of clustering, classification, or forecasting problem these data requires the creation of new methods or improvement of existing methods to improve the decision accuracy and effectiveness. The classical clustering approaches and the c-means fuzzy clustering method were analyzed. Based on the multiagent systems theory, it is proposed to use in the c-means method the separate rules for selecting elites when forming clusters and selecting the best of them in accordance with the chosen intra-cluster distance measures. The result of solving such a problem is the number of clusters, as well as the number of elements in them. The method quality was tested on Fisher iris data set using three measures of intra-cluster distance: Mahalanobis distance, Mahalanobis distance considering the membership function, and Kullbak-Leibler entropy. The highest accuracy of 98% was obtained for the distance measured by the Kullbak-Leibler entropy. Therefore, this measure was chosen to solve the clustering problem of medical monitoring data for prostate disease. Medical monitoring data were divided into four classes of patient states: “healthy persons”, “non-metastatic patients”, “metastatic patients” and “hormone-resistant patients”. The accuracy of clustering according to medical data was 95,6%. In addition to accuracy, the confusion matrix, ROC- and LF-curves were used to assess the method quality. The minimum value of the ROC-curve was 0.96 for Fisher's irises and 0.95 for medical monitoring data, which characterizes the high quality of the proposed clustering method. The loss function value is also quite small (-0.056 and -0.0176 for each considered data set), which means that the optimal cluster number and the distribution of data over them are obtained. Based on the obtained results analysis, the proposed method can be recommended for use in medical information and diagnostic decision support systems for clustering monitoring data.
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Silvino, Daniella, Jay Goldberg und Katelyn Brendel. „Comparing Clark’s 2017 Category II Electronic Fetal Monitoring Algorithm to Actual Management When Umbilical Cord Arterial pH Was Less Than 7 [ID 2683452]“. Obstetrics & Gynecology 143, Nr. 5S (Mai 2024): 52S. http://dx.doi.org/10.1097/01.aog.0001013668.50446.91.
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INTRODUCTION: Our previously published study reported that, in only 47% of labors resulting in a baby with severe acidemia (defined as umbilical cord arterial pH less than 7), intrapartum electronic fetal monitoring (EFM) was interpreted as concerning, with delivery expedited. We compared Clark’s EFM Category II algorithm to EFM interpretation and actual management of these deliveries. METHODS: Institutional review board approval was obtained. A retrospective cohort study was performed on deliveries with umbilical cord arterial pH less than 7. Two groups were identified in actual management: 1) expedited delivery (urgent/emergent operative vaginal delivery or cesarean section) and 2) nonexpedited delivery. We then reviewed all fetal heart tracings (FHTs) to determine whether the algorithm would have recommended expedited delivery or not. Data were analyzed using chi-squared test for independence and Fisher's exact test. RESULTS: Thirty deliveries were identified with severe fetal acidemia. Forty-seven percent were delivered in expedited fashion. The Clark algorithm recommended expedited delivery in 30%. The algorithm was not applicable to 3 out of 30 deliveries. Of actually expedited deliveries, the algorithm agreed with expediting 75% of the time, 78% of which should have been delivered even earlier. Of actually nonexpedited deliveries, the algorithm would have only expedited 7% of those. CONCLUSION: The Clark 2017 Category II FHT algorithm had a lower sensitivity for predicting severe fetal acidemia and recommending expedited delivery. Although only 47% of babies with severe acidemia were delivered in expedited fashion, the Clark algorithm would only have expedited delivery in 30% overall.
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Patel, Krishna, Chintan Bhatt und Pier Luigi Mazzeo. „Deep Learning-Based Automatic Detection of Ships: An Experimental Study Using Satellite Images“. Journal of Imaging 8, Nr. 7 (28.06.2022): 182. http://dx.doi.org/10.3390/jimaging8070182.
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The remote sensing surveillance of maritime areas represents an essential task for both security and environmental reasons. Recently, learning strategies belonging to the field of machine learning (ML) have become a niche of interest for the community of remote sensing. Specifically, a major challenge is the automatic classification of ships from satellite imagery, which is needed for traffic surveillance systems, the protection of illegal fisheries, control systems of oil discharge, and the monitoring of sea pollution. Deep learning (DL) is a branch of ML that has emerged in the last few years as a result of advancements in digital technology and data availability. DL has shown capacity and efficacy in tackling difficult learning tasks that were previously intractable. Specifically, DL methods, such as convolutional neural networks (CNNs), have been reported to be efficient in image detection and recognition applications. In this paper, we focused on the development of an automatic ship detection (ASD) approach by using DL methods for assessing the Airbus ship dataset (composed of about 40 K satellite images). The paper explores and analyzes the distinct variations of the YOLO algorithm for the detection of ships from satellite images. A comparison of different versions of YOLO algorithms for ship detection, such as YOLOv3, YOLOv4, and YOLOv5, is presented, after training them on a personal computer with a large dataset of satellite images of the Airbus Ship Challenge and Shipsnet. The differences between the algorithms could be observed on the personal computer. We have confirmed that these algorithms can be used for effective ship detection from satellite images. The conclusion drawn from the conducted research is that the YOLOv5 object detection algorithm outperforms the other versions of the YOLO algorithm, i.e., YOLOv4 and YOLOv3 in terms accuracy of 99% for YOLOv5 compared to 98% and 97% respectively for YOLOv4 and YOLOv3.
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Fuada, Syifaul, und Trio Adiono. „Prototyping of e-fisherman web server to support Indonesian fishermen’s activities“. IAES International Journal of Artificial Intelligence (IJ-AI) 12, Nr. 4 (01.12.2023): 1960. http://dx.doi.org/10.11591/ijai.v12.i4.pp1960-1973.
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<p>This paper presents a webserver for Indonesian fishermen, to support fishing activities. This is one of the sub-systems of e-Nelayan (in English: eFisherman) architecture, which was connected to e-Nelayan Apps; it helps to provide interaction between two users, including the administrators and fishermen. Using hypertext preprocessor (PHP) language, the website was developed to function on an Apache web server, with the adaptation of my structured query language (MySQL) framework for the database. This system was subsequently divided into two parts: (1) the front-end, which is responsible for the accessibility of data collection and (2) the back-end, where administrators update or modify crucial information: price, fishing result, illegal activity report, save our ship! (SOS) potential fish zone, and ship tracking. The administrators are unable to update the real-time weather information for the front-end part. The application was found to record the information obtained from the fishermen through the e-Nelayan apps and meteorology, climatology, and geophysical agency (BMKG in Indonesian). This web system is expected to carry out the following functions: to ensure easier interactions between fishermen and administrators, to enable easy update of information, to promote monitoring and recording of results, and to ensure fishermen’s safety.</p>
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Cheng, Lei, Xiyue Tan, Dong Yao, Wenxia Xu, Huaiyu Wu und Yang Chen. „A Fishery Water Quality Monitoring and Prediction Evaluation System for Floating UAV Based on Time Series“. Sensors 21, Nr. 13 (29.06.2021): 4451. http://dx.doi.org/10.3390/s21134451.
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In recent years, fishery has developed rapidly. For the vital interests of the majority of fishermen, this paper makes full use of Internet of Things and air–water amphibious UAV technology to provide an integrated system that can meet the requirements of fishery water quality monitoring and prediction evaluation. To monitor target water quality in real time, the water quality monitoring of the system is mainly completed by a six-rotor floating UAV that carries water quality sensors. The GPRS module is then used to realize remote data transmission. The prediction of water quality transmission data is mainly realized by the algorithm of time series comprehensive analysis. The evaluation rules are determined according to the water quality evaluation standards to evaluate the predicted water quality data. Finally, the feasibility of the system is proved through experiments. The results show that the system can effectively evaluate fishery water quality under different weather conditions. The prediction accuracy of the pH, dissolved oxygen content, and ammonia nitrogen content of fishery water quality can reach 99%, 98%, and 99% on sunny days, and reach 92%, 98%, and 91% on rainy days.
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Ghosh, Somnath, Pramod Kumar Konugurthi, Gowri Shankar Rao Singupurapu, Shivi Patel, Tirupathi Tammanagari, Mallikarjuna Rao Desu, Lalit Krushna Thakar und Ishika Ghara. „On-Board Ship Detection for Medium Resolution Optical Sensors“. Sensors 21, Nr. 9 (28.04.2021): 3062. http://dx.doi.org/10.3390/s21093062.
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In recent years there has been an increased interest in ocean surveillance. The activity includes control and monitoring of illegal fisheries, manmade ocean pollution and illegal sea traffic surveillance, etc. The key problem is how to identify ships and ship-like objects accurately and in a timely manner. In this context, currently, many solutions have been proposed based on high resolution optical and radar remote sensing systems. Most often, these systems suffer from two major limitations viz., limited swath, thereby requiring multiple satellites to cover the region of interest and huge volumes of data being transmitted to ground, even though effective per-pixel information content is minimal. Another limitation is that the existing systems are either simulated on ground or built using the non-space qualified/Commercial Of-The-Shelf (COTS) components. This paper proposes an efficient on-board ship detection system/package connected with medium resolution wide swath optical camera. The methodology adopted has three major components, viz., onboard data processing for improving the radiometric fidelity, followed by a ship detection using modified Constant False Alarm Rate algorithm (CFAR) and a false alarm suppression module to mask false identifications. Finally, the package outputs only the locations of the ships, which is transmitted to the ground. The proposed system reduces the effective volume of data to be transmitted and processed on ground and also significantly cuts down the turnaround time for achieving the end objective. The system is built on radiation hardened Field Programmable Gate Array (FPGA) devices to meet the various engineering constraints such as real-time performance, limited onboard power, radiation hardness, handling of multiple custom interfaces etc. The system is tested with one of the medium resolution Multispectral Visual and Near Infra-Red (MX-VNIR) sensor having a spatial resolution of around 50 m and swath of around 500 Kms, which would be flown with one of the upcoming satellites. The systems performance is also verified on ground with Indian Remote Sensing (IRS) Satellite’s Resourcesat’s Advanced Wide Field Sensor (AWiFS) data and the results are found to be quite encouraging as well as meeting the mission objectives.
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K. Høye, Gudrun, Torkild Eriksen, Bjørn T. Narheim und Terje Waht. „GLOBAL FISHERIES MONITORING FROM SMALL SATELLITES“. Acta Astronautica 52, Nr. 9-12 (Mai 2003): 825–28. http://dx.doi.org/10.1016/s0094-5765(03)00059-6.
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Gauldie, R. W., S. K. Sharma und C. E. Helsley. „LIDAR applications to fisheries monitoring problems“. Canadian Journal of Fisheries and Aquatic Sciences 53, Nr. 6 (01.06.1996): 1459–68. http://dx.doi.org/10.1139/f96-070.
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Jia, Junle, Chun Luo, Zhengyi Hou, Qiqi Xia, Xuanhang Ma, Xiang Pan, Awen Ma und Yuru Zheng. „Fisheries Water Quality Monitoring Improvement System“. Journal of Physics: Conference Series 2632, Nr. 1 (01.11.2023): 012016. http://dx.doi.org/10.1088/1742-6596/2632/1/012016.
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Abstract In this paper, the system of dynamic identification and monitoring of water bodies and intelligent allocation of pharmaceutical discharge is designed. At present, aquaculture technology in our country is relatively traditional, and the water environment-bearing capacity will often be ignored. This paper aims to realize the efficiency of equipment in the multiple stages of aquaculture through the design system, the remote control of motion software device, and strive to combine intelligent equipment and the basic process of aquaculture, so as to make the aquaculture industry gradually upgrade. Through the test, our device can dynamically identify and detect the water body, and ensure the fishery output and water quality at the same time, bringing economic and environmental benefits to a great extent.
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Wiff, Rodrigo, Andrés Flores, Leonardo Peralta, Rodrigo A. Estévez, Santiago Gacitúa und Stefan Gelcich. „Monitoring data poor small-scale estuarine fisheries: a proposal from the striped mullet (Mugil cephalus) fishery in the Rapel River, Chile“. Latin American Journal of Aquatic Research 52, Nr. 3 (30.06.2024): 473–85. http://dx.doi.org/10.3856/vol52-issue3-fulltext-3145.
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Chile has a relatively long history of monitoring and managing large-scale commercial fish stocks. However, many other small-scale fisheries, particularly those operating in estuaries, usually lack basic fisheries and biological information. International experience indicates that a monitoring system designed for large-scale stocks cannot simply be resized to address the complexity, relatively low total economic value, and the large number of actors and supply chains in small-scale fisheries. This article proposes a strategy to monitor data-poor fisheries operating in estuaries. The striped mullet (Mugil cephalus), locally known as “lisa”, in the Rapel River, central Chile, was selected to establish a pilot monitoring program for small-scale fish resources. From May 2022 to May 2023, fisheries information, including fleet description, catch and effort data, and fish biological attributes such as length and weight, were collected and described for the first time in the region. Drawing insights from this case study, we propose developing a generic monitoring system tailored specifically for monitoring fish stocks in estuaries. This conceptualization is based on: i) change agents, who are individuals trained to work with both the social and biological dimensions of each coastal fish stock; ii) experienced fisheries scientists outside government agencies; and iii) local fishers' knowledge to provide constant feedback for adapting temporal and spatial scales for monitoring. This monitoring scheme is cost-effective and can be efficiently replicated in other estuarine fisheries in Chile.
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Sondita, Muhammad Fedi Alfiadi, Nida Mardhiyah Ramdhani und Tri Wiji Nurani. „STRATEGI PENGEMBANGAN PEMANTAUAN KUOTA PENANGKAPAN IKAN UNTUK SUATU WILAYAH PENGELOLAAN PERIKANAN DI INDONESIA“. Marine Fisheries : Journal of Marine Fisheries Technology and Management 13, Nr. 1 (20.06.2022): 15–29. http://dx.doi.org/10.29244/jmf.v13i1.36354.
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Catch quota would be less effective to control fishing activities if fish production is not monitored properly. Limited support and participation of business players in fish monitoring program are contributing factors to the unreliability of fisheries statistics in many places, including Indonesia. To address this challenge, Indonesia fisheries managers may consider experiences of some fisheries management bodies with advanced monitoring system. This study analyzed the process of establishment of a monitoring system developed by Commission for the Conservation of Southern Bluefin Tuna (CCSBT) to direct each affiliated country to monitor its catch quota. The study was conducted in June-November 2020 by conducting interviews and literature review. CCSBT implements a monitoring system called the catch documentation scheme (CDS) to record the captured/cultured/traded southern bluefin tuna (SBT). Its development started from discussions to solve data insufficiency for SBT stock assessment. These discussions promoted engagement of its affiliated countries, business players and fisheries experts. CCSBT is successful in building the capacity of some affiliate countries which implement the CDS under supervision of CCSBT. Such process was effective in building compliance of business players in the affiliate countries. In preparation of new fisheries management regime, Ministry of Marine Affairs and Fisheries may consider adapting this process by positioning CCSBT as a Fisheries Management Authority and affiliate members as provincial fisheries management bodies. Based on the CCSBT's experience, advocacy in public awareness on fisheries crisis and provision of preliminary data are two priority strategies in bringing stakeholders to build an effective fish monitoring program.
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Bennett, Nathan J., Anna Schuhbauer, Daniel Skerritt und Naazia Ebrahim. „Socio-economic monitoring and evaluation in fisheries“. Fisheries Research 239 (Juli 2021): 105934. http://dx.doi.org/10.1016/j.fishres.2021.105934.
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