Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Munim, Ziaul Haque; Dushenko, Mariia; Jimenez, Veronica Jaramillo; Shakil, Mohammad Hassan; Imset, Marius

doi:10.1080/03088839.2020.1788731

Cited by 246 publications

(152 citation statements)

References 63 publications

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“…However, the existing digital publishing theories have many defects in dealing with such problems and lack effective means to solve them. erefore, it is necessary to draw on new theories to conduct research on such problems and provide theoretical support for the healthy development of digital publishing enterprises [4].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Information Fusion Algorithm for Big Data in Digital Publishing Industry Chain

He¹

2021

Complexity

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This paper studies the information of big data in the digital publishing industry chain and adopts advanced algorithms for its fusion calculation. The basic theory of digital publishing ecological chain is dissected, the construction requirements, construction methods, and construction paths of digital publishing ecological chain are analysed, and feasible construction measures are proposed. It also defines the connotation of the fusion of knowledge services between publishing institutions and libraries in the digital era; then analyses the characteristics and principles of the fusion of knowledge services between publishing institutions and libraries in the digital era; and finally sorts out the theoretical foundations such as synergy theory, information integration service theory, and game theory. Meanwhile, this paper also studies the flow of digital publishing resources and empirically analyses the eco-efficiency of digital publishing eco-chain by using metabolic network analysis, population analysis, and life cycle analysis, and it finds the eco-efficiency problems of the existing e-book eco-chain from its analysis. Finally, the imbalance in the digital publishing ecological chain and its hazards are analysed, and specific regulation and optimization measures are proposed. The research in this paper makes up for the deficiencies of related studies and can well solve the problems that exist in the previous and provide theoretical support for the healthy development of digital publishing enterprises.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Information Fusion Algorithm for Big Data in Digital Publishing Industry Chain

He¹

2021

Complexity

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“…Ziaul Haque et al [23] shown a bibliometric research on large data and Artificial Intelligence (AI) technologies was examined for 279 studies in maritime industry performed by 842 scholars in 214 university outlets. The bibliographic information was obtained from the science web by researchers and analysed via the R software Bibliometric process.…”

Section: Organizational Risk Assessment Of Cybersecurity Using Aimentioning

confidence: 99%

The future of Artificial Intelligence in Cybersecurity: A Comprehensive Survey

Tao¹,

Akhtar²,

Zhang³

2021

EAI Endorsed Transactions on Creative Technologies

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AI in Cybersecurity Market scheme helps organizations in observance, detecting, reporting, and countering cyber threats to keep up information confidentiality. The increasing awareness among folks, advancements in info technology, up-gradation of intelligence and police work solutions, and increasing volume of knowledge gathered from numerous sources have demanded the utilization of reliable and improved cybersecurity solutions all told industries. The increase in the incidence and quality of cyber-attacks is driving AI-enabled cyber systems. Increasing incidents of huge cyber-attacks globally have created awareness among organizations for securing their information. The motive behind these cyber-criminals are political competition, competitors move for gain and harming the name of others, international information theft, and radical nonsecular cluster interest. Most cyber-attacks are for gain. In this review we have presented some previous studies related to Cybersecurity which involves AI.

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“…Finally, In maritime shipping from distinct points of view, AI and big data were employed to attain better energy efficiency [66]. A large number of papers concentrated on ship speed optimization [44][52]; while some emphasized vessel crane control [67], and route planning [68].…”

Section: ) Fleet Optimizationmentioning

confidence: 99%

A Comprehensive Review on Big Data-Based Potential Applications in Marine Shipping Management

Bui¹,

Nguyen²

2021

Int. J. Adv. Sci. Eng. Inf. Technol.

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Shipping is becoming a spearhead economic sector in sea countries. Over 90% of goods and raw materials are transported globally by marine shipping. However, the requests from the advanced transport ship generations include much more modern facilities, larger cargo space, faster moving, and flexible controlling cargo from inland with a shorter time. As a result, the demand for digitalization of maritime is increasing in a flexible virtual environment and under pressure to reduce costs. Big Data plays an extremely important role in marine shipping. Big Data helps determine what is traditional and non-traditional data to reap profits. Shipping companies often collect extremely large amounts of data from various sources such as frequent reports from ships, sensors, GPS devices, RFID tags, and traffic management systems. This way can boost forecasting and/or avoiding risks as well as saving the cost of transport. This article focuses on assessing the challenges and opportunities of Big data in marine shipping before comprehensively analyzing its applications in maritime transport including online vessel decision support, vessel performance optimization, fleet operation optimization, and predictive analysis. This review has gathered, provided, and highlighted the rich ways and vast opportunities to improve big data-driven shipping processes and operations of the shipping industry. The results achieved can provide a good direction for authorities and shipping companies to formulate and implement effective policies to cope with the growing pressures of a highly competitive shipping market.

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Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Cited by 246 publications

References 63 publications

[Retracted] Information Fusion Algorithm for Big Data in Digital Publishing Industry Chain

[Retracted] Information Fusion Algorithm for Big Data in Digital Publishing Industry Chain

The future of Artificial Intelligence in Cybersecurity: A Comprehensive Survey

A Comprehensive Review on Big Data-Based Potential Applications in Marine Shipping Management

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