Port Environment Research Articles

A dataset of drone-captured, segmented images for oil spill detection in port environments

The high incidence of oil spills in port areas poses a serious threat to the environment, prompting the need for efficient detection mechanisms. Utilizing automated drones for this purpose can significantly improve the speed and accuracy of oil spill detection. Such advancements not only expedite cleanup operations, reducing environmental harm but also enhance polluter accountability, potentially deterring future incidents. Currently, there’s a scarcity of datasets employing RGB images for oil spill detection in maritime settings. This paper presents a unique, annotated dataset aimed at addressing this gap, leveraging a neural network for analysis on both desktop and edge computing platforms. The dataset, captured via drone, comprises 1268 images categorized into oil, water, and other, with a convolutional neural network trained using an Unet model architecture achieving an F1 score of 0.71 for oil detection. This underscores the dataset’s practicality for real-world applications, offering crucial resources for environmental conservation in port environments.

What is hidden under our pontoons? Abundance and distribution of filter feeders (bivalves and tunicates) in the port area revealed. Artificial intelligence: an interesting analysis tool?

Urbanization is particularly prevalent along the coast, causing a considerable change in the ecology of the habitats found there. Ports, docks and all the structures linked to this anthropization modify the coastal environment by providing new niches, but also new constraints. Thus, ports are ecosystems in their own right, although they are rarely studied as such. In Europe’s largest marina (La Rochelle, France), among the multitude of organisms inhabiting it, four taxa seem particularly interesting to study: Mytilidae, Ostreïdae, Pectinidae and ascidiacea. Because these taxa, which belong to the bivalve and tunicate groups, are the stewards of the health of the port environment both as bio-indicators and as engineering species. The establishment of a systematic and regular census allows us to study the evolution of their populations and to determine what influences their distribution. To have as less impact as possible on the fauna studied, the census was carried out by underwater photography. The study shows that the populations are partly conditioned by the hydrodynamics of the environment and by the anthropic activity which is carried out there. Indeed, this study, which was carried out in a particular context (before and after the COVID-19 health crisis), shows the importance of anthropic pressure, particularly on the bivalve communities. A large amount of data is needed to understand what precisely governs bivalve and tunicate populations. Therefore, an innovative method, using artificial intelligence to automate the analyses, was tested in this study. This promising method should facilitate the census by reducing the analysis time.

Optimizing municipal solid waste management in industrial ports: A case study of source separation implementation

ABSTRACT With the acceleration of industrialization and population growth, there has been a notable surge in municipal solid waste (MSW) production globally. This necessitates the development of efficient waste management strategies that align with sustainable economic, environmental, and social goals. Implementing sorting and source separation policies serves as foundational steps toward optimizing material flow and resource utilization. In industrial areas, waste generation around a primary source may improve policy implementation and participation. Given the unique strategic context of port environments, Bahregan Port in Iran was selected as a case study to evaluate the proposed methodology. Three integrated scenarios were formulated and prioritized using the ELECTRE-I model: currently practiced collection method, and segregated collection followed by source separation of MSW into two or three groups. The analysis identified the third scenario as the most effective approach. Remarkably, when evaluating the results under optimistic and pessimistic conditions, the ranking of preferences remained consistent across scenarios in the optimal state. Under pessimistic conditions, all scenarios received identical scores, indicating significant uncertainty in criteria weights. Furthermore, sensitivity analysis revealed that criteria such as the raw material sources protection, emissions in the waste separation sector, and greenhouse gas emissions were highly influential. Interestingly, criteria with the highest weighting did not always dictate the final scenario selection. External factors, such as expert opinions on specific criteria, played a pivotal role in scenario prioritization. This research serves as a foundational study for source separation initiatives, offering practical and technically viable strategies to enhance environmental sustainability within industrial settings. Implications Statement Rising industrialization and population growth have led to increased municipal solid waste (MSW) production worldwide. To address this, efficient waste management strategies are essential, focusing on sustainability and resource optimization through sorting and source separation policies. By prioritizing the scenario of segregated collection followed by source separation – industrial areas can optimize material flow and resource utilization. The study highlights the influence of criteria like raw material protection, emissions, and greenhouse gases, making this research foundational for enhancing environmental sustainability in industrial settings. This study provides practical strategies for enhancing environmental sustainability in industrial settings through source separation initiatives.

Vessel Trajectory Prediction at Inner Harbor Based on Deep Learning Using AIS Data

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.

Digital twins for resource optimization in multi-purpose ports: A design approach for data-driven decision making

Abstract Multi-purpose ports’ ef/icient and sustainable operation relies on seamless coordination and decision-making among multiple organizations. This paper underscores the critical importance of forecasting resource and infrastructure utilization for informed operational, tactical, and strategic decision-making. The proposed approach draws on digital twin technology to enable collaborative decision-making by modeling complex port environments to enable shared situational awareness among stakeholders. Illustrated through a collaborative project involving the RISE Research Institutes of Sweden, National University of Singapore, Grieg Connect, Umeå University, Kvarken Ports Umeå, and INAB, we propose a digital twin design to empower the port as a decision-maker in multi-organizational settings to proactively plan and optimize its utilization of present and future resources.

Digital twin-driven safety management and decision support approach for port operations and logistics

Ports are of great significance in processing cargo containers and facilitating global marine logistics. Nevertheless, the susceptibility of the container shipping network for hazardous cargo is likely to intensify in the event of a significant disruption at a major port, such as adverse weather conditions, inadequate management practices, or unforeseen catastrophes. Such situations require the deployment of port protection emergency response and prevention in advance. This study proposes a digital twin (DT) model that employs extensive and trajectory data within containers to comprehensively analyze the occurrence of hazardous cargo failures within the port storage process. The virtual models of physical entities in the port are created through a data-driven approach, and the behavior of these entities in a port environment with big data is then simulated. A combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) algorithm is employed to provide predictions for the service layer of the DT system. The predicted correlation coefficients of temperature and humidity in the container reach 0.9855 and 0.9181, respectively. The developed system driven by DT models integrated with a CNN and the LSTM algorithm can more effectively assist the safety manager in achieving prevention in port operations. This study enables marine authorities and decision-makers to optimize emergency procedures, thereby reducing the probability of accidents in port operations and logistics.

A Simulation-Based Study on Securing Data Sharing for Situational Awareness in a Port Accident Case

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.

Epidemiological and Clinical Profile of Work-related Dermatoses in the Artisanal Fishing Ports of Conakry, Guinea: A Cross-sectional Study

Objective: Was to describe the epidemiological and clinical profile of dermatoses in workers in artisanal fishing ports in Conakry. Materials and Methods: The study was a cross-sectional and descriptive in nature, lasting 17 months. Workers with active or remitting dermatosis were included. A multidisciplinary medical observation (occupational physicians and dermatologists) was made of each worker. Results: The study focused on 396 workers in artisanal fishing ports who had dermatosis in artisanal fishing ports in Conakry with an average age of 39 years and a male predominance of 72.5%. Fishermen represented the most affected professionals with 65.6%. Erythema and keratosis were the dominant dermatological lesions, 45.9% and 35.3% respectively. Traumatic dermatoses were encountered in 90.9% with an involvement of the hands of 70.7% and the feet of 26.5%. Among the etiologies identified on the lesions, the bite of the jaw dominated with 51.9%. Almost all (99%) of the workers of the artisanal fishing ports had no qualified professional training in the matter against 44.9% who used gloves and 16.2%, helmets. Conclusion: Dermatoses in the artisanal port environment are urgent as a significant health problem among workers. The establishment of a research orientation plan focused on working conditions and medical surveillance will allow a better understanding of safety and health issues in this area.

Port environmental path planning based on key obstacles

This paper proposes an improved hybrid algorithm for automated guided vehicles (AGVs) in port environments based on the concept of key obstacles for the JPS and DWA algorithms. Given the complexity of the port environment and the abundance of obstacles, the traditional heuristic function of the JPS algorithm is improved by adding the key obstacle heuristic function. Simultaneously, improvements are made to the evaluation function of the traditional DWA algorithm, where the braking distance is segmented into key obstacle distance and non-key obstacle distance, utilizing the concept of key obstacles. Simulation experiments are conducted using Matlab to demonstrate the effectiveness of the improved algorithm. Moreover, the performance of the hybrid algorithm is compared with five mainstream algorithms in a real simulated port environment, and the final results show the significant enhancement of this paper’s algorithm in several key performance metrics. Thus, this study provides a feasible strategy for improved path planning efficiency for AGV in the port environment.

Scaling-up 5G adoption in smart ports: barriers and enablers

ABSTRACT As the fifth generation of mobile communication technology, 5G is predicted to be a significant focus for investment by the logistics industry in the coming years. One area where it is expected to have a significant impact is ports, enabling further digitization and the development of Smart Ports. The aim of this paper is to investigate the barriers and enablers to 5G adoption, focusing on the UK port industry. Data has been collected from nine senior representatives from the UK port sector as well as two technology providers. Potential use cases are identified, along with barriers and enablers to their adoption. These including building a business case with appropriate use cases, the trade-off between legacy systems and 5G capability, technology maturity, skill development within the workforce, and the role of government in supporting innovation. This work contributes by giving insights into the challenges when introducing 5G within the port environment. Research of 5G applications in logistics currently focuses more on the technological applications rather than the business implications from adoption.

Volcano tsunamis and their effects on moored vessel safety: the 2022 Tonga event

Abstract. The explosion of the Hunga Tonga–Hunga Ha'apai volcano on 15 January 2022 (Tonga 2022) was the origin of a volcano-meteorological tsunami (VMT) recorded worldwide. At a distance exceeding 10 000 km from the volcano and 15 h after its eruption, the moorings of a ship in the port of La Pampilla, Callao (Peru), failed, releasing over 11 000 barrels of crude oil. This study delves into the profound implications of the Tonga 2022 event, investigating whether it could have led to the breaking of the mooring system. We conducted a comprehensive analysis of this significant event, examining the frequency content of the time series recorded at tide gauges, DART (Deep-ocean Assessment and Reporting of Tsunamis) buoys, and barometers in the southern Pacific Ocean. Our findings revealed that the maximum energy of the spectra corresponds to the 120 min wave period off the coast of Peru, with the arrival time of these waves coinciding with the time of the accident in the port. We used a Boussinesq model to simulate the propagation of the volcano-meteorological tsunami from the source to the port in Peru to study the impact of those waves on the mooring system. We used the synthetic tsunami recorded in the port as input for the model that simulates mooring line loads based on the ship's degrees of freedom. The results suggest that the 120 min wave triggered by the VMT could significantly increase mooring stresses due to the resulting hydrodynamic effects, exceeding the minimum breaking load (MBL). We conclude that the propagation of the long wave period generated by the VMT caused overstresses in moored lines that triggered accidents in port environments. This event showed the need to prepare tsunami early warning systems and port authorities for detecting and managing VMTs induced by atmospheric acoustic waves. The work provides new insights into the far-reaching impacts of the Tonga 2022 tsunami.

Composition and Distribution of Bacteria, Pathogens, and Antibiotic Resistance Genes at Shanghai Port, China

As one of the biggest ports, the aquatic ecology of Shanghai Port has a significant impact on the health of surrounding residents and aquatic animals. Therefore, this study explored the composition and distribution of bacteria, pathogens, and ARGs at Shanghai Ports by high-throughput sequencing. The results showed that the bacterial community was dominated by the Proteobacteria at the phylum level. With the refinement of classification level, the main composition of bacteria in different samples shows significant differences. In contrast, there was no significant difference in the composition and distribution of pathogens among the samples. It indicates that pathogens and ARGs have steady community composition at Shanghai Port. Pseudomonas aeruginosa and Salmonella enterica could be regarded as candidate indicator pathogens. macB, tetA (58), and evgS were the main ARGs, and they showed a close relationship with Mycobacterium tuberculosis, Magnaporthe oryzae, Streptococcus pneumonia, Xanthomonas oryzae, and Vibrio cholerae in different sites and layers. This may lead to the transfer of ARGs between different pathogens, resulting in more threatening pathogens. The results showed that the pathogens and ARGs present posed a risk of transmission and were potentially harmful to residents in the environment. They can spread to any other ports in the world through the transmission of ballast water, posing a threat to humans and local ecology. In order to keep human health, it is necessary to pay more attention to the water environment of ports and increase the monitoring. Furthermore, it is essential to strengthen the supervision of external source pollution input due to the special features of the port.

Assessing Critical Entities: Risk Management for IoT Devices in Ports

Integrating Internet of Things (IoT) devices into port operations has brought substantial improvements in efficiency, automation, and connectivity. However, this technological advancement has also introduced new operational risks, particularly in terms of cybersecurity vulnerabilities and potential disruptions. The primary objective of this scientific article is to comprehensively analyze and identify the primary security threats and vulnerabilities that IoT devices face when deployed in port environments. This includes examining potential risks, such as unauthorized access, cyberattacks, malware, etc., that could disrupt critical port operations and compromise sensitive information. This research aims to assess the critical entities associated with IoT devices in port environments and develop a comprehensive risk-management framework tailored to these settings. It also aims to explore and propose strategic measures and best practices to mitigate these risks. For this research, a risk-management framework grounded in the principles of ORM, which includes risk avoidance, reduction, sharing, and retention strategies, was developed. The primary outcome of this research is the development of a comprehensive risk-management framework specifically tailored for IoT devices in port environments, utilizing Operational Risk-Management (ORM) methodology. This framework will systematically identify and categorize critical vulnerabilities and potential threats for IoT devices. By addressing these objectives, the article seeks to provide actionable insights and guidelines that can be adopted by port authorities and stakeholders to safeguard their IoT infrastructure and maintain operational stability in the face of emerging threats.

Improved YOLOv5 Network for High-Precision Three-Dimensional Positioning and Attitude Measurement of Container Spreaders in Automated Quayside Cranes.

For automated quayside container cranes, accurate measurement of the three-dimensional positioning and attitude of the container spreader is crucial for the safe and efficient transfer of containers. This paper proposes a high-precision measurement method for the spreader's three-dimensional position and rotational angles based on a single vertically mounted fixed-focus visual camera. Firstly, an image preprocessing method is proposed for complex port environments. The improved YOLOv5 network, enhanced with an attention mechanism, increases the detection accuracy of the spreader's keypoints and the container lock holes. Combined with image morphological processing methods, the three-dimensional position and rotational angle changes of the spreader are measured. Compared to traditional detection methods, the single-camera-based method for three-dimensional positioning and attitude measurement of the spreader employed in this paper achieves higher detection accuracy for spreader keypoints and lock holes in experiments and improves the operational speed of single operations in actual tests, making it a feasible measurement approach.

European ports transition to carbon-neutral energy: A multiple regression analysis

This paper focuses on sustainable initiatives in the maritime industry, specifically energy transition in EU ports. Our research aims to apply the stakeholder theory in port contexts, to examine the influence of different actors on the adoption of carbon–neutral energy generation technologies, from a port-employee perspective. To that aim, the proposed conceptual model is empirically tested through a survey among port employees, following the identification of applicable technologies via a literature review. Specifically, six types of energy generation technologies that advance the goal of carbon neutrality are identified, and likewise, following the stakeholder theory approach, we identified six categories of relevant stakeholders, perceived as external or internal. By means of a multiple regression analysis, we assess the influence of stakeholders identified regarding the carbon–neutral generation technologies. The results corroborate the suitability of the stakeholder approach for assessing port environments. The findings suggest the existence of different perceptions among port employees regarding the various technologies, while stakeholder influence can be either positive or negative depending on the type of technology. Among the stakeholders involved, customers and competitors appear as most influential. The main contribution of our results derive of tackling the differences in perception of carbon neutrality within the European Ports, and the carbon–neutral technologies in ports contributing towards carbon neutrality. By providing a more thorough understanding regarding the influence of diverse stakeholders in promoting carbon neutral energy generation technologies, this study can serve as a guideline for future research and be of value for practitioners in the field.

SOLUCIONES BASADAS EN INTELIGENCIA ARTIFICIAL PARA EL DESARROLLO DE NEGOCIOS EN ENTORNOS PORTUARIOS

Artificial intelligence (AI) is transforming numerous sectors, including the port industry. This article addresses how AI-based solutions can revolutionize business development in port environments, providing significant competitive advantages. The state of the art reveals that ports face increasing challenges in terms of operational efficiency, resource optimization, and competitiveness. In this context, AI emerges as a powerful tool capable of analyzing large volumes of data and making informed decisions.The content of the article is structured into several key sections. First, it explores the competitive advantages offered by AI in the port sector, such as resource optimization, strategic decision-making, improved security, environmental sustainability, and customer experience. Specific applications such as predictive analytics, process automation, and route optimization are discussed. Case studies of ports that have successfully implemented AI technologies, such as the Port of Rotterdam, the Port of Hamburg, and the Port of Singapore, are presented to illustrate the benefits obtained and the challenges overcome.The development of the research focuses on the algorithms and analysis techniques used, including machine learning, neural networks, and natural language processing. Various applications in the port sector are analyzed, from facility pre-design and space optimization to Capex and Opex estimations and business generation capacity. AI is also used to improve operational efficiency and optimize investments and costs.The conclusions emphasize that, although the adoption of AI presents challenges, such as the need for advanced technological infrastructure and continuous staff training, the potential benefits are significant. AI enables ports to improve operational efficiency, reduce costs, increase security and sustainability, and offer better services to customers. Finally, recommendations for the successful implementation of AI solutions are proposed, emphasizing the importance of detailed strategic planning, collaboration with technology partners, and adequate staff training.article is to provide an extensive comparison of some of them, showing their similarities and also their regulatory differences, as well as possible gaps and inconsistencies.

Considerations on Prevention of Pollution from Ships in a Seaport

Negative effects on the port environment can originate from ports’ hinterland, ports’ activities and operations, and from ships. According to the available literature and long-lasting experience of numerous ports presented in different sources, pollution from ships belongs to the group of environmental priorities in ports. After a theoretical introduction where the importance of ports, their development, and the challenges/risks faced by ports (with special attention to environmental risks) are analyzed, an overview of the literature from the domain of prevention of pollution from ships is presented. Based on the standard structure of the PDCA (Plan, Do, Check, Act) management cycle, in this paper, a process model of the management (sub)system of prevention of pollution from ships in a port is proposed. Key demands related to the modeled (sub)system and bases which directly determine those demands are made concrete through an analysis of a case study: the Port of Bar (Montenegro). A categorization of domains of risks of pollution from ships in the analyzed port is conducted using the Analytic Hierarchy Process (AHP) method: considerations are based on a three-level hierarchy model: “0”—goal; level “1”—criterion; and level “2”—choice. The results of the analyses show that a domain with the highest rank of risk of pollution from ships is variant (alternative) M1: unloading oil/oil derivatives from ships to tanks (and vice versa), with a composite weight of 0.5365 (53.65%). The results of considerations presented in this paper can be used in a process of optimization of the (sub)system of prevention of pollution from ships in a multipurpose port as well as a reliable base for further research in this domain.

A Systematic understanding of the risk development process for port authority

Ports play a crucial role in the maritime transportation system but are also vulnerable to various risks. In the current complex and uncertain global market, characterized by factors such as the COVID-19 pandemic, the Russia-Ukraine War, climate change, and geopolitics, the development and operation of ports face increasing uncertainties and challenges. These factors have had a significant impact on maritime security worldwide. Previous studies on port risks have primarily focused on the operational phase of ports, lacking a comprehensive view of the whole lifecycle. Little effort has been made to explore the developmental process of risk events within the port environment, leading to a failure to distinguish the causes and results of risks from the risk events. In this study, a meta-case analysis method is employed to examine 208 port cases from 51 countries worldwide, revealing the developmental process of risk events across different phase of port. The innovative findings highlight the periodic pattern of port risks, the critical path of risk development, the unequal distribution of risk initiators and recipients, as well as the co-occurrence effects of various causes. The study provides insights into rethinking port risks and management strategies. It aims to assist international port authorities and researchers in developing a systematic understanding and management approach for risks throughout the whole lifecycle of ports.

Corrosion Rate Analysis of Steel Metal Material Against Seawater Intake Time at Port of Tanjung Emas Semarang

This research analyzes the corrosion rate of metal materials consisting of iron, aluminum and copper used in infrastructure materials supporting port operations at the Tanjung Emas port, Semarang, based on the time of sea air sampling. Ports as the main infrastructure in supporting sea transportation have an important and strategic role for economic growth, trade and industry. To support these activities, it is necessary to build supporting infrastructure, most of which is made of metal materials such as steel, aluminum and copper, which are very easily damaged due to corrosion, especially as the port environment is a corrosive environment due to contamination with sea air. With the problem of infrastructure damage due to corrosion, the method used in this writing is a qualitative descriptive method by collecting data in the form of literature studies and observations at the Tanjung Emas port, Semarang. From the research carried out, it is known that the sea water media that has the highest corrosion rate is sea water taken in the afternoon. It is hoped that the results of this calculation will enable maritime industry players in the port environment to predict the useful life of steel, aluminum and copper metal equipment used to support port operational activities and to estimate the age and type of maintenance that will be carried out so that it does not cause more severe damage.

Modelling the governance of European medium-sized port-cities

The paper presents a model designed to analyse port governance. It considers that thestakeholders ability to adopt cooperative behaviors constitutes the key element to portdevelopment. Its focus is on medium-sized European ports and fifteen cases were studied. Eachterritory was first subject to a qualitative survey and analysis of the contents of local stakeholdersdiscourse (over 80 interviews conducted). The material is rich, allowing for the comparisonbetween two or even three ports, yet the delicate nature of the relations brought to light addsconsiderable complexity to the comparison within a larger ensemble. The paper, therefore,proposes a semi-automatic treatment which helps to mitigate this difficulty by means of acomputer model based on graph theory. It involves a modelling system based on the relationsbetween the entities of the system. In this context, the relations between stakeholders wereanalysed in order to create typologies and eventually envisage some standard models ofgovernance. In order to territorialize the subject, six typical cases out of fifteen were used: LeHavre, Nantes-Saint Nazaire, Dunkirk (France), Gdynia (Poland), Klaipėda (Lituania), Hamina-Kotka (Finland).All these port environments modelled according to a single format (i.e. a graph) led to theapplication of a certain number of metrics which enables them to be compared. Two mainmetrics were presented in the framework of this paper for illustrative purposes: “Density” and“S_metric”. These metrics originating in graph theory, coupled with other indicators (distributionof degrees and number of hubs per port), allowed to measure the relationships' intensity and thedistribution of these intensities among the stakeholders, and to identify the main stakeholders orconversely the least influential.