Using smart systems to cut energy and operating costs in shipping

International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 60 Using smart systems to cut energy and operating costs in shipping Subbotin Serhiy Software Engineer ([email protected]; orcid.org/0009-0001-4280-3392) ARTICLE INFO ABSTRACT ©2025 RS Publication Paper ID: IJASTR6914FED26B597 Received: 2025-10-15 Published: 2025-11-14 DOI: https://dx.doi.org/ 10.5281/zenodo.1761 7712 Page No: 60-65 Effective cost management in maritime transport is critically important for making global logistics more competitive. The introduction of artificial intelligence (AI) technologies opens up new opportunities for optimizing operational processes, reducing fuel costs, improving logistics chains, and increasing the accuracy of demand forecasting. Modern innovative technologies, in particular artificial intelligence systems, can become key tools in solving these problems. Intelligent shipping management systems are already actively used in global practice, enabling fuel consumption forecasting, maintenance process automation, route optimization, and reduction of manual labor requirements. Considering the economic feasibility and growing need to implement AI in maritime transport, there is a need to comprehensively investigate how these technologies contribute to cost optimization, increased efficiency of logistics operations, and the formation of sustainable development in the industry. Objective. To investigate the impact of artificial intelligence technologies on the economic efficiency of maritime transport, identify mechanisms for reducing costs through the use of intelligent fleet and navigation management systems, and assess their contribution to improving the operational performance of shipping companies. Materials and methods. The study uses economic analysis methods to assess the effectiveness of AI implementation in maritime logistics, in particular, analysis of fuel, maintenance, and navigation cost reductions. Comparative analysis was used to compare traditional and automated approaches to route planning, as well as statistical models for forecasting costs, profitability, and container transport load. Results. The results of the study showed that the implementation of artificial intelligence systems provides a significant increase in the economic efficiency of maritime transport. The use of machine learning algorithms to optimize routes reduces fuel costs by 10–15%, which is especially important given the high cost of energy. Automated technical diagnostics and maintenance systems reduce repair and fleet downtime costs, delivering savings of up to 20%. Artificial intelligence technologies are also effective in forecasting demand and optimizing container utilization, helping to reduce logistics costs by 8–12% and improving cargo flow management efficiency. Intelligent fleet management systems optimize crew utilization, reducing administrative and operational costs while increasing productivity and safety. Prospects. Given the positive economic impact of artificial intelligence in maritime transport, further research should focus on developing strategies for integrating AI into global maritime logistics, assessing the effectiveness of investments in digital technologies, and studying the impact of regulatory initiatives on innovation in the industry. The development of automated navigation and maritime transport management systems will contribute to improving the efficiency of global logistics and strengthening the competitive position of companies using intelligent technologies. Keywords: maritime transport, artificial intelligence, cost optimization, logistics efficiency, economic performance, automation, fleet management, fuel cost reduction, digital technologies. International Journal of Advanced Scientific and Technical Research Available online on http://www.rspublication.com/ijst/index.html ISSN 2249-9954 Cite This Paper: Subbotin Serhiy (2025). "Using smart systems to cut energy and operating costs in shipping". INTERNATIONAL JOURNAL OF ADVANCED SCIENTIFIC AND TECHNICAL RESEARCH (IJASTR), vol. 15, no. 6, 2025, pp. 60-65. DOI: https://dx.doi.org/10.5281/zenodo.17617712 International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 61 Introduction The modern maritime transport system is characterized by growing economic challenges, the key ones being high fuel costs, maintenance, port fees, and administrative expenses. Fluctuations in energy prices, stricter environmental regulations, and rising operating costs are forcing shipping companies to seek innovative ways to optimize resources and improve operational efficiency. Traditional approaches to fleet management are increasingly proving ineffective in today's environment. Outdated route planning methods, increased vessel downtime, and inefficient use of fuel and energy resources lead to higher operating costs and reduced competitiveness for carriers. The introduction of artificial intelligence technologies in the maritime transport industry opens up new opportunities for reducing costs and increasing the productivity of transport processes. Intelligent systems are capable of analyzing large amounts of data in real time, generating optimal routes, ensuring effective fleet management, reducing fuel consumption, cutting downtime, and improving the accuracy of cargo flow forecasts. At the same time, digital technologies help optimize the use of human resources, reducing the workload on crews and administrative staff. Numerous foreign scientists have made a significant contribution to research into the application of artificial intelligence in the maritime transport system. Their work addresses issues such as the digitization of shipping, the improvement of logistics processes, the enhancement of economic efficiency, and the strengthening of environmental safety, which underscores the relevance and importance of further research in this area. One of the key areas of research is the application of artificial intelligence to predict ship performance parameters. In particular, Alexiou K., Pariotis E., Zannis T., and Leligou H. [1] analyze the possibilities of using artificial intelligence to assess the operational characteristics of ships, which allows optimizing their use and reducing fuel costs. Biolcheva P. and Valchev E. [2] paid considerable attention to the safety aspects of AI application in shipping, emphasizing that machine learning algorithms can significantly reduce risks by automating monitoring and control processes. Research on the effectiveness of computational methodologies in maritime transport is also presented in the work of Chaichana T. [3], which considers modern approaches to data visualization and analytical methods aimed at optimizing shipping processes. Route optimization using intelligent systems is discussed in the work of Jurdana I., Krylov A., Yamnenko J. [4]. The authors argue that the use of intelligent algorithms in navigation systems can reduce fuel costs and improve the efficiency of logistics processes. A significant amount of research has been devoted to studying the role of big data and artificial intelligence in maritime logistics. Munim Z., Dushenko M., Jimenez V., Hassan M., Imset M. [5] outline trends in the development of digitalization in maritime transport and point to the possibilities of integrating intelligent systems to optimize costs and improve resource management. Another important area of research is the prediction of ship performance using neural networks. For example, Ozsari I. [6] proposes methods for predicting main engine power and emissions for different types of ships, which helps to reduce environmental impact and increase the economic efficiency of transportation. 6G communication technologies and their application in maritime transport are discussed in the work of Saafi S., Vikhrova O., Fodor G., Hosek J., Andreev S. [7], which emphasizes the importance of integrating terrestrial and extraterrestrial systems to ensure reliable communication and vessel monitoring. The issue of digitalization of maritime transport and its economic efficiency is also International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 62 considered in the work of Sanchez-Gonzalez P., Díaz-Gutiérrez D., Leo T Núñez-Rivas, L. [8], which emphasizes the need for the gradual introduction of intelligent systems to improve logistics processes. Thus, existing studies confirm the high potential of artificial intelligence in reducing maritime transport costs and improving logistics processes. However, the question of the comprehensive implementation of such technologies at the global level remains open, especially given economic feasibility, regulatory restrictions, and environmental requirements. The purpose of the article is to study international experience in the implementation of artificial intelligence in the field of maritime transport, analyze its economic efficiency, and identify key mechanisms for reducing costs using automated digital technologies. Materials and methods. The study uses scientific works by foreign and domestic authors dealing with the issues of digitalization in the shipping industry, as well as practical cases of artificial intelligence application in international maritime logistics. The study used methods of theoretical generalization and grouping to identify the main approaches to the implementation of artificial intelligence in maritime transport management and to assess its economic feasibility. Results. From an economic point of view, the implementation of artificial intelligence in maritime transport opens up significant opportunities for cost optimization, improved fleet management efficiency, and reduced environmental impact. Modern intelligent technologies allow for the automation of route planning, maintenance forecasting, load management, and logistics data analysis processes. This not only reduces the direct costs of ship operation but also increases the overall productivity of the transport infrastructure. One of the key aspects of applying artificial intelligence in maritime transport is route optimization, which minimizes fuel costs. The use of machine learning algorithms to analyze meteorological conditions, port congestion, and the overall state of maritime traffic allows for the creation of the most cost-effective routes, reducing fuel consumption by 10-15% [6]. Studies also show that intelligent real-time management of ship speed not only saves fuel but also reduces carbon dioxide emissions, which meets current environmental requirements [4]. In addition, the introduction of artificial intelligence systems in fleet maintenance significantly reduces costs associated with vessel downtime and unforeseen repairs. By analyzing large amounts of data on the condition of equipment, it is possible to predict possible malfunctions and carry out preventive maintenance, which reduces repair costs by up to 20% [8]. Intelligent real-time monitoring systems also reduce the likelihood of accidents and increase the safety of maritime transport. Another important area of application for artificial intelligence is improving the efficiency of logistics processes. In the highly competitive international shipping industry, shipping companies are forced to find ways to optimize the use of container space. Using artificial intelligence to forecast demand on specific routes helps avoid empty shipments and reduce logistics costs by 8-12% [8]. Automated fleet management systems also make it possible to increase the efficiency of crew utilization, which helps reduce administrative costs and improve the overall productivity of companies. Successful international experience shows that the digital transformation of maritime transport contributes to improving the economic performance of the industry and creating the conditions for sustainable development. In particular, the European Union has implemented a number of initiatives aimed at supporting the introduction of artificial intelligence in maritime logistics, which has significantly reduced vessel operating costs and improved the quality of transport services [3]. In Singapore, the use of intelligent port management systems has reduced container unloading times, which has lowered the operating costs of shipping companies and International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 63 increased the efficiency of maritime transport [8]. That is why the introduction of artificial intelligence in maritime transport is not only a means of optimizing costs, but also a strategic direction for the development of the industry in the current economic conditions. The use of intelligent technologies allows for more flexible and efficient fleet management, reduces fuel, repair, and logistics costs, and increases the competitiveness of shipping companies in the international market. In addition, the introduction of artificial intelligence contributes to improving the quality of customer service. Thanks to automated demand forecasting and transportation optimization systems, companies can ensure faster and more efficient delivery of goods. This not only reduces operating costs but also increases customer satisfaction, which is an important factor in today's global maritime transport market. The economic effect of introducing artificial intelligence into maritime logistics can be assessed by analyzing the ratio of technology implementation costs to potential savings. Table 1 presents a comparative analysis of the costs of fleet digitalization and the expected savings at different stages of vessel operation. Analysis of the effectiveness of artificial intelligence technologies in the maritime transport system Indicator Without AI With AI Reduction in fuel costs (%) 2 - 5% 10 - 15% Reduction in repair and maintenance costs (%) 3-5% 15-20% Optimization of container loading (%) 2-3% 8-12% Reduction in administrative costs (%) 1-2% 5-10% Time savings on navigation planning (%) 5-10% 30-40% Reduction in vessel downtime (%) 3-5% 20-25% Expected total cost savings (%) 5-8% 20-30% Initial investment in AI implementation (million dollars) - 5-10 Return on investment (years) - 3-5 Reduction in CO₂ emissions (%) 5-8% 15-20% Improved demand forecasting accuracy (%) 2-5% 10-15% Optimization of crew utilization (%) 3-5% 10-20% Reduction in environmental penalty costs 1-2% 5-10% (%) 3 - 5% 10 - 15% Source: created by the author based on research and data from [1–8]. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 64 Given the above data, it is clear that investments in digital technologies bring significant long-term benefits. The introduction of artificial intelligence allows for savings through the optimization of fuel costs, repair work, administrative management, and increased fleet productivity. In addition to the economic advantages, it is worth noting the environmental aspect of the digitalization of shipping. The use of machine learning algorithms to optimize routes and regulate the speed of ships can significantly reduce greenhouse gas emissions. This complies with current international environmental standards and contributes to the development of sustainable shipping. Thus, the application of artificial intelligence in maritime transport is an important step towards improving the economic efficiency of the industry. The use of intelligent technologies reduces costs, increases transport safety, reduces environmental impact, and improves logistics processes. The integration of artificial intelligence into maritime transport is not only a technological innovation but also an economically sound strategy that will contribute to the development of the international shipping industry in the coming decades. Conclusions The introduction of artificial intelligence in maritime transport is a strategically important direction for the development of the industry, contributing to cost optimization, improved fleet management efficiency, and minimized environmental impact. Based on the research conducted, the following conclusions can be drawn: The use of artificial intelligence can significantly reduce fuel, maintenance, and navigation costs. The use of machine learning algorithms to optimize routes and control vessel speed provides fuel savings of 10–15%, which is critical to improving the financial stability of shipping companies. The introduction of automated diagnostic systems reduces repair and downtime costs by up to 20%. The use of big data and equipment condition prediction technologies significantly increases fleet reliability and reduces the risk of accidents. Intelligent logistics systems contribute to more efficient use of container space, reducing logistics costs by 8–12%. Optimizing ship loading, analyzing demand, and forecasting cargo flows make it possible to significantly increase the productivity of maritime transport and minimize operating costs. The digitization of maritime transport helps reduce administrative costs, as automated fleet management systems enable more effective control of crew activities, simplify operational planning, and ensure more efficient use of human resources. The use of artificial intelligence plays an important role in reducing the environmental impact of maritime transport. Route optimization, vessel speed management, and weather forecasting can reduce greenhouse gas emissions by 15–20%, which meets current environmental requirements and promotes sustainable shipping. Overall, the introduction of artificial intelligence into the field of maritime transport is an economically sound solution that contributes to increasing the competitiveness of shipping companies, reducing operating costs, and improving service quality. Further research in the field of digitalization of maritime transport should focus on assessing the effectiveness of financial mechanisms that support the implementation of artificial intelligence, developing financing models for automated navigation systems, and identifying ways to attract private capital for the digital modernization of the industry. It is also important to study the impact of automation on the labor market and the long-term environmental consequences of using intelligent systems. This will allow for the optimization of costs in maritime logistics. International Journal of Advanced Scientific and Technical Research ISSN 2249-9954 Available online on http://www.rspublication.com/ijst/index.html volume 15, No. 6, 2025 DOI: 10.5281/zenodo.17617712 Original Article ©2025 RS Publication, [email protected] 65 REFERENCES: [1] Alexiou, K., Pariotis, E., Zannis, T., & Leligou, H. (2021). Prediction of a ship’s operational parameters using artificial intelligence techniques. Maritime Transport Research, 2, 100013. https://doi.org/10.1016/j.martra.2021.100013 [2] Biolcheva, P., & Valchev, E. (2023). Safety through artificial intelligence in the maritime industry. International Journal on Marine Navigation and Safety of Sea Transportation, 17(1), 113–119. https://doi.org/10.12716/1001.17.01.12 [3] Chaichana, T. (2023). 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