Website Design for Locating Tuna Fishing Spot Using Naïve Bayes and SVM Based on VMS Data on Indonesian Sea

Hery, Hery; Lukas, Samuel; Yugopuspito, Pujianto; Murwantara, I Made; Krisnadi, Dion

doi:10.1109/isriti51436.2020.9315338

Cited by 3 publications

(10 citation statements)

References 5 publications

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“…The outcomes showed that the principal factors influencing net primary output and sea surface temperature were the main factors that drive the spatiotemporal potential distribution of the study site's fishing grounds [40]. However, in looking for more information, Hery et al [33] suggested that chlorophyll content, SST, and other environmental features should be considered in future developments in this particular research. It shows that environmental parameters are the most important factors that influenced the potential fishing zone and are the subject of the most potential research according to these features.…”

Section: Vessel Monitoring Systemmentioning

confidence: 93%

“…Additionally, data frequency can be changed to suit regulatory requirements. Fishing boats equipped with VMS transmitters will always be linked to the regulator's central monitor, allowing for continuous global monitoring [33]. Several researchers used the VMS as stated in [33] and [34]- [37].…”

Section: Vessel Monitoring Systemmentioning

confidence: 99%

“…Fishing boats equipped with VMS transmitters will always be linked to the regulator's central monitor, allowing for continuous global monitoring [33]. Several researchers used the VMS as stated in [33] and [34]- [37]. The purpose of study [34] is to examine how fishing vessel activities can be tracked from space using trajectory data from the VMS.…”

Section: Vessel Monitoring Systemmentioning

confidence: 99%

“…According to Sheykhmousa et al [58], of the 251 relevant papers in the database that had been reviewed, 68% of the database applied SVM in the various studies regarding remote sensing respectively. Hery et al [33] proposed the study to employ two machine learning techniques: naive Bayes and support vector machine. With an accuracy rate of 74.8%, the classifier analyzed 24,150 artificially tagged images featuring 15 common fish species in Taiwanese waters [59].…”

Section: Support Vector Machinementioning

confidence: 99%

See 3 more Smart Citations

A review on features and methods of potential fishing zone

Ya’acob,

Nik Dzulkefli,

Abdul Aziz

et al. 2024

IJECE

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This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.

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Section: Vessel Monitoring Systemmentioning

confidence: 93%

Section: Vessel Monitoring Systemmentioning

confidence: 99%

Section: Vessel Monitoring Systemmentioning

confidence: 99%

Section: Support Vector Machinementioning

confidence: 99%

See 2 more Smart Citations

A review on features and methods of potential fishing zone

Ya’acob,

Nik Dzulkefli,

Abdul Aziz

et al. 2024

IJECE

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“…The steps taken by the authorities are now based only on the data observed from the Vessel Monitoring System (VMS) and also the Geographical Information System (GIS) [11]. VMS is used to control fishing activities as well as shipping traffic in a country's waters [1][2][3][4][5][6][7]. However, the use of VMS is limited to registered vessels only.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Controlling Marine Activity Using Iot System

Talib

Thanakodi

Noor

et al. 2021

MJCS

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Marine activities at sea are very popular with the people of the world. Various marine activities such as swimming, boating, fishing and even shipping are often done on the coast and sea. However, loose control and monitoring cause various problems such as accidents, marine life threats and even pollution. The current method uses a vessel monitoring system (VMS) as well as a geographic information system (GIS). This method of course uses high costs because the information obtained is international. There are also barriers to obtaining sensitive information. This makes it difficult for local authorities to obtain uniform information on centralized water activities. This study proposes a smart and centralized system of control and monitoring of water activities. The novelty of this study is to recognise and detect a foreign object on the surface of the sea. In addition, this study made a virtual barrier between safe and dangerous zone. This system can control all marine activities with the use of mobile equipment installed on the body of the user or even the vessel used. The system will control and monitor all activities centrally. In the event of an emergency or violation of the law, this system will deliver an immediate message to the authorities. The system is evaluated based on user distribution and control environment. System performance audit shows that this system method successfully controls and monitors water activity within 1 kilometre from the coast

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Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System

2023

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The amount of data in the maritime domain is rapidly increasing due to the increase in devices that can collect marine information, such as sensors, buoys, ships, and satellites. Maritime data is growing at an unprecedented rate, with terabytes of marine data being collected every month and petabytes of data already being made public. Heterogeneous marine data collected through various devices can be used in various fields such as environmental protection, defect prediction, transportation route optimization, and energy efficiency. However, it is difficult to manage vessel related data due to high heterogeneity of such marine big data. Additionally, due to the high heterogeneity of these data sources and some of the challenges associated with big data, such applications are still underdeveloped and fragmented. In this paper, we propose the Vessel Data Lakehouse architecture consisting of the Vessel Data Lake layer that can handle marine big data, the Vessel Data Warehouse layer that supports marine big data processing and AI, and the Vessel Application Services layer that supports marine application services. Our proposed a Vessel Data Lakehouse that can efficiently manage heterogeneous vessel related data. It can be integrated and managed at low cost by structuring various types of heterogeneous data using an open source-based big data framework. In addition, various types of vessel big data stored in the Data Lakehouse can be directly utilized in various types of vessel analysis services. In this paper, we present an actual use case of a vessel analysis service in a Vessel Data Lakehouse by using AIS data in Busan area.

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Website Design for Locating Tuna Fishing Spot Using Naïve Bayes and SVM Based on VMS Data on Indonesian Sea

Cited by 3 publications

References 5 publications

A review on features and methods of potential fishing zone

A review on features and methods of potential fishing zone

Monitoring and Controlling Marine Activity Using Iot System

Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System

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