There is a consensus on the need to reduce the emissions of carbon compounds. The increase in global greenhouse gas (GHG) emissions in the maritime industry poses a serious challenge to environmental sustainability, climate change, and the operating costs of ships. This article shows how hybrid versus diesel propulsion technology for ships can help reduce carbon dioxide (CO₂) emissions and fuel consumption, and how these changes can be achieved. The need to reduce exhaust emissions and the increasing need for the shipping industry to seek alternative fuels means that existing regulations for marine engines and engine emissions are being updated almost constantly and new regulations are being formulated. The cost implications of the new regulations may lead to an increase in emissions as engines with lower fuel consumption are chosen, i.e., larger marine engines. Alternative approaches are needed to reduce CO₂ emissions and fuel consumption, which could ultimately lead to hybrid propulsion for ships. This paper examines the current state of greenhouse gas emissions in shipping by analyzing the CO₂ emissions and operating costs of two ships of the same type with similar technical and technological characteristics and different propulsion systems to gain insight into the problem. This paper compares the reductions in CO₂ emissions, fuel consumption, and fuel costs for two suction hopper dredgers with standard diesel and hybrid propulsion. The technical characteristics, CO₂ emissions, fuel consumption, and price of the two ships were analyzed to determine the advantages and disadvantages of each propulsion system. The novelty of this study is that two suction hopper dredgers from the same company with similar technical–technological characteristics but different propulsion systems were used for the case study and a mathematical procedure for calculating CO₂ and other greenhouse gasses was presented in comparison, all to determine to what extent and in what way the hybrid propulsion system of a ship can contribute to reductions in CO₂ emissions and fuel costs at the ship and company levels compared to a standard diesel propulsion system. This comparative analysis shows how much lower CO₂ emissions, fuel consumption, and fuel cost savings can be expected when using a hybrid propulsion system compared to a standard diesel propulsion system. Finally, a conclusion is drawn on the efficiency and environmental compatibility of the two systems.

E-learning has become a widespread form of education as it allows the users a relatively easy access to needed information. E-learning has also been present in maritime affairs, although not so ubiquitous as in other economy sectors. Sea-borne shipping is one of the most stringently controlled industries, with a number of complex regulations and standards. This paper analyses learning methodologies and discusses the economic justification of implementing e-learning systems at global level, with an emphasis on the growing e-learning industry, corporate segment of e-learning, massive open online course market, and the importance of the micro-learning concept. In addition, this study analyses the present systems of seafarers’ education and the potentials, strengths and shortcomings of the conventional learning, e-learning and m-learning. Moreover, the recent application of e-learning in maritime affairs and the need of further research of the e-learning impacts in maritime affairs are examined. Finally, the presented information and discussion result in the logic matrix analysis and the SWOT analysis of e-learning, aiming to define the strengths, weaknesses, logic of action, goals and potentials of the implementation of e-learning in maritime affairs. Keywords: E-learning, education of seafarers, STCW Convention, IMO.

The essence of this work is to explore the potential of shore-side power as a sustainable and efficient solution for mitigating greenhouse gas emissions from passenger ships during their berthing periods in ports. Cruise ships—including both cruise liners and ferries—are significant contributors to port-based emissions because they rely on onboard auxiliary engines to generate power while docked. This practice results in the continuous release of greenhouse gases, such as carbon dioxide, and other pollutants, including nitrogen oxides and sulfur oxides, which contribute to environmental degradation and pose public health concerns in port cities. The objective of this study is to highlight the critical role of shore-side power in decarbonizing the maritime industry and in helping achieve global climate targets. By addressing environmental, technical, and economic aspects, the research aims to provide a comprehensive framework for decision-makers, port authorities, and shipping companies to adopt this technology as a key measure for reducing emissions from cruise ships. Furthermore, this study investigates the multifaceted impacts of shore-side electricity—focusing on its long-term environmental, economic, and social implications—by analyzing case studies from ports that have successfully implemented this technology and by examining the barriers to its broader adoption. Ultimately, this research seeks to provide actionable insights for policymakers, port authorities, and shipping companies.

Shipping in complex marine environments requires a balance between navigational safety, minimising travel time and optimising logistics management, which is particularly challenging in areas with geometric obstructions and Offshore Wind Farms (OWFs). This study focuses on the maritime route networks in the Croatian ports of Pula and Rijeka, including the main access routes to OWFs and zones characterised by multiple navigational challenges. The aim of the research is to develop an empirically based and practically applicable framework for the optimisation of sea routes that combines analytical precision with operational efficiency. The parallel application of Dijkstra and A* algorithms enables a comparative analysis between deterministic and heuristic approaches in terms of reducing navigation risk, optimising route costs and ensuring fast logistical access to OWFs. The applied methods include the analysis of real and simulated route networks, the evaluation of statistical route parameters and the visualisation of the results for the evaluation of logistical and operational efficiency. Adaptive heuristic modifications of the A* algorithm, combined with the parallel implementation of Dijkstra’s algorithm, enable dynamic route planning that takes into account real-world conditions, including variations in wind speed and direction. The results obtained provide a comprehensive framework for safe, efficient and logistically optimised navigation in complex marine environments, with direct applications in the maintenance, inspection and operational management of OWFs.

This study investigates the application of different neural network (NN) models in assessing the risk of the detention of offshore vessels during port state control (PSC) inspections. The focus is on the use of different NN models (“nnet”, “mlp”, “neuralnet”, “rsnns”) to identify the main risk factors based on historical data on vessels and their inspections. The main objective of this research is to improve maritime safety and the efficiency of inspection procedures by applying techniques that can more accurately predict the probability of detention of the offshore vessels. These models make it possible to analyse complex patterns in the data, such as the relationships between the country of inspection, flag, memorandum, age, tonnage and previous deficiencies, and the risk of detention. Understanding these patterns is crucial for inspection teams’ proactive action as it helps direct resources to potentially high-risk vessels. Implementing these models into PSC processes helps to optimise resource allocation, reduce unnecessary costs, and increase the reliability of decision-making processes. NN models significantly help in recognising non-linear patterns and provide high accuracy in risk prediction. The study also includes a comparative analysis of the elements that determine the accuracy, sensitivity, and other performance aspects of the models to determine the most appropriate approach for practical implementation. The results emphasise the importance of applying artificial intelligence (AI) in various aspects of modern maritime safety management. This research opens up new opportunities for the development of intelligent support systems that not only increase safety but also improve the efficiency of inspection processes on a global scale.

Computerized maintenance management systems (CMMSs) are software packages that support or organize the maintenance tasks of assets or equipment. They are found in the background of any ship maintenance operation and are an important part of maintenance planning, spare parts supply, record keeping, etc. In the marine market, there are a number of CMMSs that are competing fiercely to program a better and more modern program that will capture the market, which has been accompanied by published analyses and scientific papers. At the same time, the quality of the data entered into CMMS databases is questionable, a fact that has been ignored in practice and scientific circles; until recently, there were no published analyses and there was no way to measure the quality of the data entered. This article presents two proposals for improving the quality of CMMS databases and calculates their potential benefits. By implementing the first proposal, the evaluation methodology for the ship’s Planned Maintenance System database, between 10% and 15% of databases will have significant financial or safety benefits. This measure will also have an impact on more than 40% of the other databases that can also be improved. The second proposal will have a smaller impact of only 4%. The overall benefit of these proposals is to improve more than 60% of the databases and will result in a significant increase in safety or financial savings.