Search Results (43)

Agricultural mechanization and advanced technology have developed significantly in the coffee industry. However, there are still requirements for human laborers to operate, monitor crop health care, and manage production. The integration of advanced technology can significantly enhance the production efficiency and management practices of agricultural enterprises. This paper aims to address these gaps by proposing and implementing a computer vision-based attendance tracking system on mobile platforms that are suitable for the requirements and limitations of agricultural enterprises. First, the face detection process involves interpreting and locating facial structure. Next, the model transforms a photographic image of a human face into digital data based on the unique features and facial structure. We utilize the InsightFace model with the buffalo_l variant, as well as ArcFace with a ResNet backbone, as a facial recognition algorithm. After capturing a facial image, the system conducts a matching process against the existing database to verify identity. Finally, we implement a mobile application prototype on both iOS and Android platforms, ensuring accessibility for farm workers. As a result, our system achieved 95.2% accuracy on the query set, with an average processing time of <200 ms per image (including face detection, embedding extraction, and database matching). The system performs real-time attendance monitoring, automatically recording the entry and exit times of farm workers using facial recognition technology, and enables quick registration of new workers. Our work is expected to enhance transparency and fairness in the human management process, focusing on the coffee farm use case. Full article

Digitalization has resulted in ships being equipped with more computerized systems. Even though this transformation has improved navigational safety and operational efficiency, it has also raised cyber security concerns significantly. To address such concerns, this study proposes a national Maritime Cyber Security Operations Center (M-SOC) concept, aiming at protecting vessels against cyber-attacks. The proposed concept was developed by following a SOC-related guideline published by MITRE. Subsequently, the initial draft was evaluated through the Focus Group technique. Thematic Data Analysis was employed to analyze feedback from domain experts. By considering expert input, the draft concept was improved. Consequently, the 11-element recommendation presented in the study contributes to the development of a center capable of detecting and responding to cyber threats targeting ships within a designated sea zone. The operation of M-SOCs is expected to enhance the cyber resilience of the maritime ecosystem at the national level. Full article

With the development and widespread application of information technology, cybersecurity has become a focal point in all industry sectors. The maritime sector is no exception, with both physical and cyber threats. This survey first highlights, from a system engineering and information technology perspective, the specific architectures of on-vessel and in-port systems, as well as the communication equipment connecting them. Subsequently, cyber attacks in maritime and port domains and their potential consequences are described from various angles. Examples of real cases of cyber attacks are also reported. An overview of current key techniques used in vulnerability analysis, attack detection, and security protection is proposed before discussing cybersecurity issues in the maritime and port sectors from the particular perspective of discrete event systems. Various systems used in maritime and port domains are modeled as automata or Petri nets. Some analysis, detection, and protection approaches are then proposed to illustrate the potential of discrete event systems in this domain. Full article

Equivalent energy consumption minimization methods of energy management systems have been implemented as a rule-based strategy to enhance electric propulsion system efficiency. This study compares the efficiencies of different systems by applying variable- and constant-speed generators with battery hybrid systems, measuring fuel consumption. In the same scenario, the variable-speed operation showed a notable improvement of 10.36% compared to the conventional system. However, in the verification of hybrid system efficiency, onshore charged energy cannot be considered a reduction in fuel consumption. Instead, when converting onshore energy usage into equivalent fuel consumption for comparative analysis, both hybrid constant- and variable-speed operation modes achieved efficiency enhancements ranging from 5.5% to 9.79% compared to the conventional, nonequivalent constant-speed operation mode. Conversely, the nonequivalent variable-speed operation mode demonstrated an efficiency that was 5.41% higher than that of the hybrid constant-speed operation mode. In contrast, the battery-integrated variable-speed operation mode indicated a system efficiency approximately equal to that of the nonequivalent variable-speed operation mode. For vessels with load profiles characterized by prolonged periods of idling or low-load operations, a battery-integrated hybrid system could be a practical solution. This study demonstrates the necessity of analyzing load profiles, even when aiming for the optimal operational set points of the generator engine. Full article

With the growing integration of digital technologies on modern vessels, ranging from satellite links and mobile networks to onboard Wi-Fi, the exposure of maritime systems to cyber threats has become a pressing concern. Wireless networks on ships, although essential for operations and crew welfare, often lack sufficient protection and are frequently overlooked in broader cybersecurity strategies. This article explores vulnerabilities linked to Man-in-the-Middle attacks and rogue access points, particularly in port areas where attackers may exploit signal range and proximity. A simulation carried out in a public setting near the Port of Rijeka demonstrated how standard crew devices could be lured into connecting to a counterfeit Wi-Fi network, resulting in traffic interception and potential data leaks. Although practical limitations, such as signal attenuation and distance, reduce the feasibility of such intrusions at sea, the risk remains significant while in port. Insecure configurations and common user behaviors were identified as key enablers. The article outlines a series of countermeasures aligned with international guidelines ranging from segmentation and encryption to crew training and intrusion detection. Addressing these wireless vulnerabilities is essential for building resilience and ensuring that digital transformation efforts in the maritime sector do not come at the expense of security. Full article

The global shipping industry facilitates the movement of approximately 80% of goods across the world but accounts for nearly 3% of total greenhouse gas (GHG) emissions every year, and other pollutants. One challenge in reducing shipping emissions is understanding and quantifying emission characteristics. A detailed method for calculating shipping emissions should be applied when preparing exhaust gas inventory. This research focused on quantifying CO₂, NO_x, and SO_x emissions from tankers, containers, bulk carriers, and general cargo in the Republic of Korea using spatio-temporal analysis and maritime big data. Using the bottom-up approach, this study calculates vessel emissions from the ship engines while considering the fuel type and operation mode. It leveraged the Geographic Information System (GIS) to generate spatial distribution maps of vessel exhausts. The research revealed variability in emissions according to ship types, sizes, and operational modes. CO₂ emissions were dominant, totaling 10.5 million tons, NO_x 179,355.2 tons, and SO_x 32,505.1 tons. Tankers accounted for about 43.3%, containers 33.1%, bulk carriers 17.3%, and general cargo 6.3%. Further, emissions in hoteling and cruising were more significant than during maneuvering and reduced speed zones (RSZs). This study contributes to emission databases, providing a basis for the establishment of targeted emission control policies. Full article

The maritime industry plays a key role in the global supply chain. Advanced digital technologies bring significant economic benefits to ports and shipowners, but at the same time increase the risks of cyber threats and attacks. This article aims to provide guidelines and examples of good practice that will help in the effective implementation of cyber risk assessment, cyber resilience and cyber sustainability, which are the products of increasingly pronounced challenges. The interconnection of ports requires operators to achieve and maintain a baseline level of cybersecurity to ensure security across the entire port ecosystem. The development of new technologies in areas such as the Internet of Things, cloud computing, artificial intelligence, etc., contributes to the fact that monitoring and control systems in the maritime industry are becoming increasingly exposed to cyber threats and various forms of cyberattacks. The connection of vessels with systems on land in real time presents a necessary element in meeting the intended goals in the digital transformation of the maritime sector. This results in increasingly frequent work on specific software solutions within the maritime sector. With the adoption of new operational technologies (OT) and information technologies (IT), the desire for more efficient supply chains and operations of shipping in general has been realized, but at the same time the level of cybersecurity has decreased. The research results aim to encourage port operators and shippers to develop a series of good practices in order to develop an appropriate level of cybersecurity, resilience, and sustainability. Full article

The transition to environmentally sustainable maritime operations has gained urgency with the International Maritime Organization’s (IMO) 2023 GHG reduction strategy, aiming for net-zero emissions by 2050. While alternative fuels like LNG and methanol serve as transitional solutions, lithium-ion battery energy storage systems (ESSs) offer a viable low-emission alternative. However, safety concerns such as thermal runaway, overcharging, and internal faults pose significant risks to marine battery systems. This study presents an AI-based fault prediction algorithm to enhance the safety and reliability of lithium-ion battery systems used in electric propulsion ships. The research employs a Long Short-Term Memory (LSTM)-based predictive model, integrating electrochemical impedance spectroscopy (EIS) data and voltage deviation analyses to identify failure patterns. Bayesian optimization is applied to fine-tune hyperparameters, ensuring high predictive accuracy. Additionally, a recursive multi-step prediction model is developed to anticipate long-term battery performance trends. The proposed algorithm effectively detects voltage deviations and pre-emptively predicts battery failures, mitigating fire hazards and ensuring operational stability. The findings support the development of safer and more reliable energy storage solutions, contributing to the broader adoption of electric propulsion in maritime applications. Full article

The increasing reliance on digital and automated systems in the maritime industry has introduced significant cybersecurity risks to ship operations. While prior research has examined cyber risk management, systematic modeling of attack scenarios remains limited. This study addresses this gap by employing attack trees to systematically analyze potential cyberattack pathways against modern ships. Drawing insights from the literature and interviews with 10 experts, this research identifies key vulnerabilities in navigation, operational, and communication systems. The study outlines 20 attack scenarios across three primary objectives: crashing, capsizing, and immobilizing a ship. Expert validation emphasizes the real-world feasibility of these threats, with cyberattack scenarios involving crashing and immobilization deemed the most plausible, while capsizing was considered unlikely due to robust ship designs. The findings highlight the importance of strengthening network security, implementing redundancy measures, and enhancing crew training to mitigate cyber risks.in Expert feedback helped validate these insights, underscoring their relevance to real-world maritime operations. This research presents a systematic threat modeling framework that supports effective risk assessment and cybersecurity strategy development, offering a valuable contribution to the advancement of maritime cybersecurity practices. Full article

In the maritime industry, the adoption of hybrid electric propulsion systems aims to enhance energy efficiency and environmental sustainability. However, this study originates from the fundamental question: ‘Are hybrid systems truly environmentally friendly?’ Ensuring optimal system performance requires accurate load analysis and an effective energy management system. Existing studies have limitations in addressing real-time load variability, long-term load patterns, and scalability across different operational conditions. To address these, this study proposes a standard load analyzer based on main engine power output data to conduct performance analysis. Using MATLAB/Simulink simulations and Excel VBA-based methods, the system evaluates key performance factors under various operational load conditions. Cross-validation between MATLAB and Excel ensured high accuracy, with a relative error rate below 0.01%. The results showed consistent performance indicators, offering reliable insights across vessel types and scenarios. The system’s lightweight design and rapid data acquisition enable effective energy management optimization. However, it has limitations in performing detailed analyses for life cycle assessment, operating expenditures, and capital expenditures. Future advancements in data consolidation and analytical methods will help the tool evolve into a comprehensive tool for multi-dimensional performance evaluation, addressing economic, environmental, and technical aspects. Full article

Hydrogen is a promising environmentally friendly fuel with the potential for zero-carbon emissions, particularly in maritime applications. However, owing to its wide flammability range (4–75%), significant safety concerns persist. In confined spaces, hydrogen leaks can lead to explosions, posing a risk to both lives and assets. This study conducts a numerical analysis to investigate hydrogen flow within hydrogen storage rooms aboard ships, with the goal of developing efficient ventilation strategies. Through simulations performed using ANSYS-CFX, this research evaluates hydrogen diffusion, stratification, and ventilation performance. A vertex angle of 120° at the ceiling demonstrated superior ventilation efficiency compared to that at 177°, while air inlets positioned on side-wall floors or mid-sections proved more effective than those located near the ceiling. The most efficient ventilation occurred at a velocity of 1.82 m/s, achieving 20 air exchanges per hour. These findings provide valuable insights for the design of safer hydrogen vessel operations. Full article

In this study, a ship-route prediction model based on a long short-term memory network using port-to-port trajectory data is presented. Data from a traditional automatic identification system—often used for ship-route prediction—are limited by uneven sampling intervals and noise. To address these issues, equal-interval data collected every 10 s from a target ship, which is a liner container vessel, were employed. Our study focuses on predicting the entire trajectory between the Gunsan and Busan ports. The root mean square error (RMSE), mean absolute error (MAE), and average distance $\overline{d}$ between two trajectories were used as the key evaluation metrics. The analysis yielded excellent predictive performance, with the values RMSE = 0.000999, MAE = 0.000672, and $\overline{d}$ = 0.101 km. This study thus provides a foundation for predicting complete port-to-port routes and offers practical insights for managing vessel operations. Accurate route prediction contributes to reducing port congestion, improving fuel efficiency, and lowering carbon emissions. Full article

The maritime industry is constantly evolving and posing new challenges, especially with increasing digitalization, which has raised concerns about cyber-attacks on maritime supply chain agents. Although scholars have proposed various methods and classification models to counter these cyber threats, a comprehensive cyber-attack taxonomy for maritime supply chain actors based on a systematic literature review is still lacking. This review aims to provide a clear picture of common cyber-attacks and develop a taxonomy for their categorization. In addition, it outlines best practices derived from academic research in maritime cybersecurity using PRISMA principles for a systematic literature review, which identified 110 relevant journal papers. This study highlights that distributed denial of service (DDoS) attacks and malware are top concerns for all maritime supply chain stakeholders. In particular, shipping companies are urged to prioritize defenses against hijacking, spoofing, and jamming. The report identifies 18 practices to combat cyber-attacks, categorized into information security management solutions, information security policies, and cybersecurity awareness and training. Finally, this paper explores how emerging technologies can address cyber-attacks in the maritime supply chain network (MSCN). While Industry 4.0 technologies are highlighted as significant trends in the literature, this study aims to equip MSCN stakeholders with the knowledge to effectively leverage a broader range of emerging technologies. In doing so, it provides forward-looking solutions to prevent and mitigate cyber-attacks, emphasizing that Industry 4.0 is part of a larger landscape of technological innovation. Full article

The maritime industry’s increasing integration of IT/OT systems into vessel operations has significantly elevated its exposure to cyber–physical threats, making the development of effective cyber risk management strategies a necessity. This paper provides an outlook of the current landscape of cyber security threats and vulnerabilities for the maritime sector and vessels. An outline of the relevant governmental and industry directives, standards, and guidelines for cyber security in maritime vessels is given. Considering maritime vessels as critical elements of the maritime critical infrastructure sector, a number of relevant cyber–physical security assessment methods are presented. Bridging cyber–physical security, process safety, and security, API SRA (American Petroleum Institute Security Risk Analysis) and BTA (Bow-Tie Analysis) are presented as the most applicable cyber–physical security assessment methods for complex maritime vessels, such as an offshore oil and gas drillship. The scenario of a cyber-attack on the Dynamic Positioning (DP) system of a drillship is presented with the use of API SRA and BTA. The difficulties in the implementation of NIST CSF v2.0 and IACS UR E26 and UR E27 in the maritime sector are also discussed. The need for intensified research on and the formulation of bespoke cyber security measures to mitigate the evolving cyber threats within the maritime domain is highlighted. The need for the allocation of training and resources for the reinforcement of the capacity of a maritime vessel’s crew in the mitigation of cyber threats and safe maritime operations is emphasized. Full article

This study aims to improve vessel trajectory prediction in the inner harbor of Busan Port using Automatic Identification System (AIS) data and deep-learning techniques. The research addresses the challenge of irregular AIS data intervals through linear interpolation and focuses on enhancing the accuracy of predictions in complex port environments. Recurrent neural network (RNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU), and Bidirectional GRU models were developed, with LSTM delivering the highest performance. The primary scientific question of this study is how to reliably predict vessel trajectories under varying conditions in inner harbors. The results demonstrate that the proposed method not only improves the precision of predictions but also identifies critical areas where Vessel Traffic Service Operators (VTSOs) can better manage vessel movements. These findings contribute to safer and more efficient vessel traffic management in ports with high traffic density and complex navigational challenges. Full article