Search Results (21)

Cyber-physical infrastructures such as hospitals and smart campuses face hybrid threats that target both digital and physical domains. Traditional security solutions separate surveillance from network monitoring, leaving blind spots when attackers combine these vectors. This paper introduces ARGUS, an autonomous robotic platform designed to close this gap by correlating cyber and physical anomalies in real time. ARGUS integrates computer vision for facial and weapon detection with intrusion detection systems (Snort, Suricata) for monitoring malicious network activity. Operating through an edge-first microservice architecture, it ensures low latency and resilience without reliance on cloud services. Our evaluation covered five scenarios—access control, unauthorized entry, weapon detection, port scanning, and denial-of-service attacks—with each repeated ten times under varied conditions such as low light, occlusion, and crowding. Results show face recognition accuracy of 92.7% (500 samples), weapon detection accuracy of 89.3% (450 samples), and intrusion detection latency below one second, with minimal false positives. Audio analysis of high-risk sounds further enhanced situational awareness. Beyond performance, ARGUS addresses GDPR and ISO 27001 compliance and anticipates adversarial robustness. By unifying cyber and physical detection, ARGUS advances beyond state-of-the-art patrol robots, delivering comprehensive situational awareness and a practical path toward resilient, ethical robotic security. Full article

Accurate ship berthing behavior prediction (BBP) is essential for enabling collision warnings and support decision-making. Existing methods based on Automatic Identification System (AIS) data perform well in the task of ship trajectory prediction over long time-series and large scales, but struggle with addressing the fine-grained and highly dynamic changes in berthing scenarios. Therefore, the accuracy of BBP remains a crucial challenge. In this paper, a novel BBP method based on Light Detection and Ranging (LiDAR) data is proposed. To test its feasibility, a comprehensive dataset is established by conducting on-site collection of berthing data at Dalian Port (China) using a shore-based LiDAR system. This dataset comprises equal-interval data from 77 berthing activities involving three large ships. In order to find a straightforward architecture to provide good performance on our dataset, a cascading network model combining convolutional neural network (CNN), a bi-directional gated recurrent unit (BiGRU) and bi-directional long short-term memory (BiLSTM) are developed to serve as the baseline. Experimental results demonstrate that the baseline outperformed other commonly used prediction models and their combinations in terms of prediction accuracy. In summary, our research findings help overcome the limitations of AIS data in berthing scenarios and provide a foundation for predicting complete berthing status, therefore offering practical insights for safer, more efficient, and automated management in smart port systems. Full article

Ports are vital nodes in global trade networks but are also significant contributors to greenhouse gas emissions. Their transition toward sustainable, nearly zero-energy operations require comprehensive and structured strategies. This study proposes a practical and scalable framework to support the energy decarbonization of ports through the phased integration of hybrid renewable energy systems (HRES) and energy storage systems (ESS). Emphasizing a systems-level approach, the framework addresses key aspects such as energy demand assessment, resource potential evaluation, HRES configuration, and ESS sizing, while incorporating load characterization protocols and decision-making thresholds for technology deployment. Special consideration is given to economic performance, particularly the minimization of the Levelized Cost of Energy (LCOE), alongside efforts to meet energy autonomy and operational resilience targets. In parallel, the framework integrates digital tools, including smart grid infrastructure and digital shadow technologies, to enable real-time system monitoring, simulation, and long-term optimization. It also embeds mechanisms for regulatory compliance and continuous adaptation to evolving standards. To validate its applicability, the framework is demonstrated using a representative case study based on a generic port profile. The example illustrates the transition process from conventional energy models to a sustainable port ecosystem, confirming the framework’s potential as a decision-making tool for port authorities, engineers, and policymakers aiming to achieve effective, compliant, and future-proof energy transitions in maritime infrastructure. Full article

Ports play a crucial role in Indonesia’s economy, yet many, particularly smaller ports, lack standardized port performance indicators (PPIs) to assess and improve operational efficiency. Existing studies primarily focus on financial and operational performance, often employing either the balanced scorecard (BSC) or PESTLE analysis in isolation, with limited integration of sustainability concepts, such as smart port and green port frameworks. This study bridges this gap, aiming to develop and validate a comprehensive PPI framework that combines BSC, PESTLE, and circular economy smart and green port principles to create holistic performance assessment tools for ports. The research used a three-round Delphi method, incorporating expert evaluations and consensus from academics, consultants, port authorities, and customers to validate key performance indicators. A total of 127 PPIs were initially identified through a literature review and expert consultations, using strict selection criteria—standard deviation ≤ 1.5, interquartile range (Q3–Q1) ≤ 2.5, and ≥51% expert agreement (ratings 8–10). The final validated framework includes 114 indicators covering financial, operational, environmental, and strategic dimensions. This study provides valuable insights for port authorities to optimize performance and align with global best practices by integrating internal and external factors into a comprehensive model. Full article

The maritime transportation sector is undergoing a profound shift with the emergence of autonomous vessels powered by real-time artificial intelligence (AI) agents. This article investigates the pivotal role of these agents in enhancing the safety, efficiency, and sustainability of autonomous maritime systems. Following a structured literature review, we examine the architecture of real-time AI agents, including sensor integration, communication systems, and computational infrastructure. We distinguish maritime AI agents from conventional systems by emphasizing their specialized functions, real-time processing demands, and resilience in dynamic environments. Key safety mechanisms—such as collision avoidance, anomaly detection, emergency coordination, and fail-safe operations—are analyzed to demonstrate how AI agents contribute to operational reliability. The study also explores regulatory compliance, focusing on emission control, real-time monitoring, and data governance. Implementation challenges, including limited onboard computational power, legal and ethical constraints, and interoperability issues, are addressed with practical solutions such as edge AI and modular architectures. Finally, the article outlines future research directions involving smart port integration, scalable AI models, and emerging technologies like federated and explainable AI. This work highlights the transformative potential of AI agents in advancing autonomous maritime transportation. Full article

Hybrid renewable energy systems (HRESs) are being incorporated and evaluated within seaports to realize efficiencies, reduce dependence on grid electricity, and reduce operating costs. The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). The scenarios were developed based on different levels of renewable energy integration, energy storage utilization, and grid dependency to optimize cost and sustainability while reflecting the actual port energy scenario as the base case. Integrating HRES, ESS, and EMS reduced the port’s levelized cost of energy (LCOE) by up to 54%, with the most optimized system (Scenario 3) achieving a 53% reduction while enhancing energy stability, minimizing grid reliance, and maximizing renewable energy utilization. The findings show that the HRES configuration provides better cost, sustainability, and resiliency than the conventional grid-tied system. The unique proposed EMS takes it a step further, optimizing not just the energy flow but also the cost, making the overall system more efficient—and less costly—for the user. ESS complements energy storage and keeps it functional and reliable while EMS makes it completely functional by devising ways to reduce costs and enhance efficiency. The study presents the technical and economic viability of HRES as an economic and operational smart port infrastructure through its cost-effective integration of renewable energy sources. The results reinforce the move from conventional to sustainable autonomous port energy systems and lay the groundwork for forthcoming studies of DR-enhanced port energy management schemes. While prior studies have explored renewable energy integration within ports, many lack a unified, empirically validated framework that considers HRES, ESS, and EMS within real-world port operations. This research addresses this gap by developing an optimization-driven approach that assesses the techno-economic feasibility of port energy systems while incorporating real-time data and advanced control strategies. This study was conducted to enhance port infrastructure and evaluate the impact of HRES, ESS, and EMS on port sustainability and autonomy. By bridging the gap between theoretical modeling and practical implementation, it offers a scalable and adaptable solution for improving cost efficiency and energy resilience in port operations. Full article

In spite of its strong increase and relevant position in the evolution of international maritime routes, the global livestock trade is still a poorly treated topic in the maritime business domain of research. Aiming to cover this gap, the authors are focused on revealing the livestock logistics technology in intermodal transports, approaching both equipment reliability and operation flow design, applying the business processes modeling method to map the most relevant stages in animals’ port operation, transfer, and maritime transportation. This paper examines the intricate logistics of maritime livestock transportation through a case study on the Port of Midia, administrated by the Constanța Maritime Port Administration, one of Romania’s primary export hubs for livestock operations, using BPM software, seeking to identify the most important deficiencies and alternatives in improving the technical and technological effectiveness. Key findings indicate that improving ramp availability, automating document verification, and implementing RFID-based animal tracking systems could significantly enhance operational efficiency. By integrating workflow models, real-time monitoring, and simulation-based optimization, the study offers a comprehensive framework for streamlining multimodal livestock transportation. The implications extend to policymakers, port authorities, and logistics operators, emphasizing the necessity of digital transformation, regulatory harmonization, and technological integration in livestock maritime transportation. This research contributes to the expansion of intermodal transportation studies, providing practical recommendations for enhancing livestock logistics efficiency while ensuring compliance with European animal welfare regulations. The findings pave the way for further research into AI-driven risk assessments, smart logistics solutions, and sustainable livestock transportation alternatives. Full article

As the digital paradigm stimulates changes in various areas, seaports, which are fundamental to logistics and the global supply chain, are also undergoing a digital revolution, evolving into smart ports. Smart gates are essential components in this transformation, playing a vital role in increasing port efficiency. In the context of smart gates, the aim of this study is to understand how process management can serve as a catalyst for digital transformation, promoting efficiency in traffic flow and logistics. To achieve this objective, the design science research (DSR) methodology was followed, which allowed for the integration of information from several sources of requirement, encompassing both theoretical and practical aspects. The practical component took place at one of Portugal’s largest container terminals, which allowed for the integration of information from various sources. As a result, this study presents the conceptual definition of a smart gate in terms of processes, main technologies, and key performance indicators that will support the monitoring and improvement of future operations. The results provide theoretical and practical contributions: on a practical level, they present a real application of the transformation towards a smart gate, serving as a model for other ports in their digitalization; on a theoretical level, they enrich the literature with a methodology for digitalizing maritime road gates, showing how the use of process management approaches, such as the BPMN, can increase operational efficiency in container terminals. Full article

The cyber–physical systems (CPSs) of various stakeholders from the mobility, logistics, and security sectors are needed to enable smart and secure situational awareness operations in a port environment. The motivation for this research arises from the challenges caused by some unexpected events, such as accidents, in such a multi-stakeholder critical environment. Due to the scale, complexity, and cost and safety challenges, a simulation-based approach was selected as the basis for the study. Prototype-level experimental solutions for dataspaces for secure data sharing and visualization of situational awareness were developed. The secure data-sharing solution relies on the application of verifiable credentials (VCs) to ensure that data consumers have the required access rights to the data/information shared by the data prosumer. A 3D virtual digital twin model is applied for visualizing situational awareness for people in the port. The solutions were evaluated in a simulation-based execution of an accident scenario where a forklift catches fire while loading a docked ship in a port environment. The simulation-based approach and the provided solutions proved to be practical and enabled the smooth study of disaster-type situations. The realized concept of dataspaces is successfully applied here for both daily routine operations and information sharing during accidents in the simulation-based environment. During the evaluation, needs for future research related to perception, comprehension, projection, trust, and security as well as performance and quality of experience were detected. Especially, distributed and secure viewpoints of objects and stakeholders toward real-time situational awareness seem to require further studies. Full article

Colombian port terminals in the Caribbean are being called upon to increase the sustainability of their operations to better fit with the environmental dynamics of their locations. Within this context, the Palermo Sociedad Portuaria (PSP) has taken a proactive stance in identifying the factors contributing to its CO₂ emissions. This study evaluated the CO₂ emissions of the PSP in 2019 and 2020 and, through the implementation of sustainable practices (rock dust spreading, composting and reducing the burning of fossil fuels), examined the mitigation of the port’s carbon footprint (CF) in the year 2022. Based on collaborative management results and efforts, a set of viable mitigation strategies adapted to port operations was formulated. Viability was assessed through monitoring of the practical implementations encompassing initiatives such as fuel reduction, waste composting and the application of rock dust. The introduction of the CARE system in the operational equipment led to a reduction in fuel consumption over five periods—amounting to an overall emission decrease of 1629 metric tons of CO₂ equivalent (ton CO₂ eq). Meanwhile, the strategic composting of waste generated by port activities (including organic waste, hand towels, coffee grounds and landscaping waste) resulted in the potential reduction of 2 metric tons of CO₂ annually. The application of rock dust (10 kg m⁻²) in the available green spaces within the operational areas contributed to a decrease of 0.00080543 ton CO₂ eq over 45 days. The implementation of these three key measures over the course of a year has the potential to prevent the release of 37 ton CO₂ eq, signifying a 2% decrease in overall CF when compared to the base year of 2020. This investigation was rooted in the current operational reality of the port terminal and its correlated activities. The strategies deployed underscore the feasibility of low-cost solutions that can be emulated across port terminals in pursuit of the holistic aspirations encapsulated in the concepts of a “green port” and a “smart port”. Full article

Due to its widespread occurrence in practically all environmental sectors, including the terrestrial, marine, and atmospheric, microplastics (MP) have transitioned from an emerging pollutant to a chronic contaminant. Studies on the prevalence and hazardous effects on marine creatures have been conducted all over the world, but only in coastal environments. Microplastic pollution has emerged as a global concern in marine environments and a danger to animals, predators, and humans because it has been discovered in the marine environment all over the world. This review examines the quantity of MP samples around the world and their colonization by marine microorganisms, as well as the detection, features, origins, and ecological implications of paint fragments and resins in our oceans and ports. These polymers are derived from paints and the fiber reinforced plastic (FRP) matrix used in shipbuilding. Microplastics should be regarded as coming from synthetic polymers found in ship coatings. For assessing microplastic pollution, choosing an appropriate sample technique is essential. Additionally, this review offers an overview of MP investigation methods, concentrating on sampling techniques, laboratory procedures, and the identification of MPs found in seawater, as well as assessing how well they apply to the seaport environment. Because of the widespread discovery of MP pollution, particularly in Africa, Asia, India, South Africa, North America, and Europe, it is clear that monitoring is crucial for determining the efficacy of mitigation efforts to limit the quantity of waste plastic entering the environment, especially through sensors and real-time information transfer systems (e.g., smart digital seawater monitoring). Full article

Integrated technology management in building smart ports or intelligent ports is a crucial concern for global sustainable development, especially when human societies are facing increasing risks from climate change, sea-levels rising, and supply chain disruptions. By mapping the knowledge base of 103 papers on intelligent ports, retrieved in late December 2022 from the Web of Science, this study conducted a roadmapping exercise using knowledge mapping findings, assisted by Bibliometrix, VoSviewer, and customized Python scripts. The three structural (intellectual, social, and conceptual) aspects of knowledge structure reveal the significance of the internet of things (IoT), the fourth industrial revolution (Industry 4.0), digitalization and supply chains, and the need for digital transformation alignment across various stakeholders with Industry 4.0 practices. Furthermore, an even geographical distribution and institutional representation was observed across major continents. The results of the analysis of the conceptual structure demonstrated the existence of several established and emerging clusters of research, namely (1) industry data, IoT, and ICT, (2) industry 4.0, (3) smart airports, (4) automation; and (5) protocol and security. The overall empirical findings revealed the underlying technology and innovation management issues of digital transformation alignment across stakeholders in IoT, Industry 4.0, 5G, Big Data, and AI integrated solutions. In relation to roadmapping, this study proposed a socio-technical transition framework for prototyping ecosystem innovations surrounding smart sustainable ports, focusing on contributing to valuable carbon or greenhouse gas emission data governance, management, and services in global value chains. Full article

In this digital age, sustainable development and competitive advantage of port businesses rely on their capacity to adapt to changing business requirements. Although many previous studies develop a relation between smart port, technology, and sustainable performance, there is an urgent need to address such issues practically among ports, especially in developing countries. Therefore, this research aims at investigating to what extent the Egyptian ports could apply the smart practices and employ technology to achieve and improve sustainable port performance. The Egyptian ports have been selected to serve as an empirical study in this research, assessing their current performance and evaluating their level of readiness and adaptability to smart practices and technology employment. Interviews have been conducted with a group of 10 different stakeholders from government, private sectors, and experts in the field of port management. The interview results showed the main challenges and obstacles that might face the adaptation of technology and sustainable practices in Egyptian ports. This was followed by a focus group with experts in the field to discuss and conclude some procedures that can be adapted to facilitate the implementation of smart practices and technology employment in the Egyptian ports in order to improve their sustainable performance from different perspectives (economic, social, and environmental), deal with the obstacles facing adaptation, and suggest solutions The research adopted ‘content analysis’ for both phases. The research showed the great potential of technology employment to achieve sustainable performance in Egyptian ports while highlighting the main obstacles and challenges that might face the adaptation with suggestions and recommendations to those obstacles in order to adopt the digital transformation towards a sustainable smart port performance. Nevertheless, there are some limitations that could be an open issue to future researchers and practitioners who can benefit from those suggestions to employ technology and adapt sustainable procedures in ports, foster new practical research initiatives to adapt the smart port practices in different countries, and test their impact on port sustainable performance. Full article

The new business environment, and the new era of digital transformation put pressure on the global supply chain and accordingly on ports to cope with such changes; these require ports to be smarter and adapt to the new technological approaches. Smart ports SP express the prevailing trend for the transformation strategies. Although many previous studies discuss smart ports requirements there is no integrated vision provided before to capture different comprehensive elements of smart port and show its impact on sustainably. Therefore, this research aims at developing an integrated smart port index SPI, capturing different elements of SP and linking them to port sustainability performance. The research conducted a systematic literature review to identify all pillars that are required for the smart port adaptation and showed its impact on sustainability with a full-text reading stage that resulted in 48 articles. The paper indicated that few studies of the SPI have been proposed before to improve SP activity in different domains: operations, environment, energy, safety, and security; however, there is a need to address the several key issues related to port operations, and to consider human resources factor as part of the smart port requirement, particularly an integrated index that captures different pillars in SP elements and shows its effect on sustainable performance. The study reveals that SP initiatives around the world have different integration levels. According to this, the smart port index can be considered as the first integrated index linked to sustainability and including human resources; however, there are some limitations that could be an open issue to future researchers and practitioners to foster new practical research initiatives that can rely on this index to adapt the smart port practices in different ports, taking into consideration the human resources aspect and testing their impact on port sustainability. Full article

Cyber security has become increasingly challenging due to the proliferation of the Internet of things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the Internet. However, these devices possess various security flaws resulting from the lack of defense mechanisms and hardware security support, therefore making them vulnerable to cyber attacks. In addition, IoT gateways provide very limited security features to detect such threats, especially the absence of intrusion detection methods powered by deep learning. Indeed, deep learning models require high computational power that exceeds the capacity of these gateways. In this paper, we introduce Realguard, an DNN-based network intrusion detection system (NIDS) directly operated on local gateways to protect IoT devices within the network. The superiority of our proposal is that it can accurately detect multiple cyber attacks in real time with a small computational footprint. This is achieved by a lightweight feature extraction mechanism and an efficient attack detection model powered by deep neural networks. Our evaluations on practical datasets indicate that Realguard could detect ten types of attacks (e.g., port scan, Botnet, and FTP-Patator) in real time with an average accuracy of 99.57%, whereas the best of our competitors is 98.85%. Furthermore, our proposal effectively operates on resource-constraint gateways (Raspberry PI) at a high packet processing rate reported about 10.600 packets per second. Full article