Impact of IoT System Imperfections and Passenger Errors on Cruise Ship Evacuation Delay.

Cruise ships and other naval vessels include automated Internet of Things (IoT)-based evacuation systems for the passengers and crew to assist them in case of emergencies and accidents. The technical challenges of assisting passengers and crew to safety during emergencies include various aspects such as sensor failures, imperfections in the sound or display systems that are used to direct evacuees, the timely selection of optimum evacuation routes for the evacuees, as well as computation and communication delays that may occur in the IoT infrastructure due to intense activities during an emergency. In addition, during an emergency, the evacuees may be confused or in a panic, and may make mistakes in following the directions offered by the evacuation system. Therefore, the purpose of this work is to analyze the effect of two important aspects that can have an adverse effect on the passengers' evacuation time, namely (a) the computer processing and communication delays, and (b) the errors that may be made by the evacuees in following instructions. The approach we take uses simulation with a representative existing cruise ship model, which dynamically computes the best exit paths for each passenger, with a deadline-driven Adaptive Navigation Strategy (ANS). Our simulation results reveal that delays in the evacuees' reception of instructions can significantly increase the total time needed for passenger evacuation. In contrast, we observe that passenger behavior errors also affect the evacuation duration, but with less effect on the total time needed to evacuate passengers. These findings demonstrate the importance of the design of passenger evacuation systems in a way that takes into account all realistic features of the ship's indoor evacuation environment, including the importance of having high-performance data processing and communication systems that will not result in congestion and communication delays.

Extensive Spread of SARS-CoV-2 Delta Variant among Vaccinated Persons during 7-Day River Cruise, the Netherlands.

We investigated a large outbreak of SARS-CoV-2 infections among passengers and crew members (60 cases in 132 persons) on a cruise ship sailing for 7 days on rivers in the Netherlands. Whole-genome analyses suggested a single or limited number of viral introductions consistent with the epidemiologic course of infections. Although some precautionary measures were taken, no social distancing was exercised, and air circulation and ventilation were suboptimal. The most plausible explanation for introduction of the virus is by persons (crew members and 2 passengers) infected during a previous cruise, in which a case of COVID-19 had occurred. The crew was insufficiently prepared on how to handle the situation, and efforts to contact public health authorities was inadequate. We recommend installing clear handling protocols, direct contacts with public health organizations, training of crew members to recognize outbreaks, and awareness of air quality on river-cruise ships, as is customary for most seafaring cruises.

Implementation of the energy efficiency existing ship index and carbon intensity indicator on domestic ship for marine environmental protection.

The International Maritime Organization has set a goal to achieve a 50% reduction of total annual greenhouse gas emission related to the international shipping by 2050 compared to the 2008 baseline emissions. Malaysia government has taken an initiative to investigate the assessment (cost-effectiveness) of this International Maritime Organization's short-term measure on Malaysian-registered domestic ships although this measure is only for international merchant ship. To achieve this, this paper collected the ship's data from the shipowners from 25 sample ships. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times. Based on cost-efficiency analysis, it creates for the purpose of compliance with the operational carbon intensity indicator. It found that even if it is possible to bring an asset back into service, it may not be possible to do so in a manner that generates a profit or complies with applicable regulations. In these situations, it may be more prudent to scrap the asset rather than run the risk of having it become a stranded asset. This is especially true for older tankers. Alternatives with lengthy payback periods are not desirable for the domestic tanker fleet that is already in operation.

Accidents, diseases and health complaints among seafarers on German-flagged container ships.

BACKGROUND: For seafarers on the high seas health hazards are various and due to the setting also specific. The spectrum of job-related health impairments and accidents is mainly influenced by the maritime characteristics. The aim of this study is to assess the kind of accidents and the frequency of diseases and health complaints among seafarers on German container ships by evaluating medical log books. METHODS: A systematic analysis of 14,628 medical entries from 95 medical log books of 58 container ships under German flag from 1995 to 2015 was performed. This monocentric retrospective and descriptive study used information on accidents, diseases and health complaints among different occupational groups and medical treatment procedures for the analysis and evaluation. RESULTS: The analysis showed that more than one third of all consultations with the Health Officer on board are related to internal (33.7%) and surgical (31.3%) symptoms. Almost twenty percent of consultations were due to respiratory infections (19.6%) and accidents (17.9%). Accidents represented the most frequent reason for unfitness for sea service (31.2%). Based on occupational categories, most injuries occurred among deck crew (22.5%), followed by ratings working in the engine room (18.9%). In 106 cases, telemedical contact with a physician ashore was necessary. In total, 15 seafarers had to be evacuated from the ship for further medical treatment onshore. Medicine/drug application was the most common therapeutic measure on board, accounting for 77% of all consultations. CONCLUSIONS: The high proportion of health complaints and accidents among seafarers shows that there is a need to optimize medical care at sea and accident prevention, e.g. by standardized treatment algorithms or improving the medical training of Health Officers. The development and introduction of a digital patient file to record medical treatments on the vessels could also improve medical documentation on board.

COVID-19 outbreaks among crew on commercial ships at the Port of Rotterdam, the Netherlands, 2020 to 2021.

BackgroundDuring the COVID-19 pandemic, international shipping activity was disrupted as movement of people and goods was restricted. The Port of Rotterdam, the largest port in Europe, remained operational throughout.AimWe describe the burden of COVID-19 among crew on sea-going vessels at the port and recommend improvements in future infectious disease event notification and response at commercial ports.MethodsSuspected COVID-19 cases on sea-going vessels were notified to port authorities and public health (PH) authorities pre-arrival via the Maritime Declaration of Health. We linked data from port and PH information systems between 1 January 2020 and 31 July 2021, derived a notification rate (NR) of COVID-19 events per arrival, and an attack rate (AR) per vessel (confirmed cases). We compared AR by vessel type (workship/tanker/cargo/passenger), during wildtype-, alpha- and delta-dominant calendar periods.ResultsEighty-four COVID-19 events were notified on ships, involving 622 cases. The NR among 45,030 new arrivals was 173 per 100,000 impacting 1% of vessels. Events per week peaked in April 2021 and again in July 2021, when the AR was also highest. Half of all cases were notified on workships, events occurring earlier and more frequently than on other vessels.ConclusionNotification of COVID-19 events on ships occurred infrequently, although case under-ascertainment was likely. Pre-agreed protocols for data-sharing between stakeholders locally and across Europe would facilitate more efficient pandemic response. Public health access to specimens for sequencing and environmental sampling would give greater insight into viral spread on ships.

Formulating Cybersecurity Requirements for Autonomous Ships Using the SQUARE Methodology.

Artificial intelligence (AI) technology is crucial for developing autonomous ships in the maritime industry. Autonomous ships, based on the collected information, recognize the environment without any human intervention and operate themselves using their own judgment. However, ship-to-land connectivity increased, owing to the real-time monitoring and remote control (for unexpected circumstances) from land; this poses a potential cyberthreat to various data collected inside and outside the ships and to the applied AI technology. For the safety of autonomous ships, cybersecurity around AI technology needs to be considered, in addition to the cybersecurity of the ship systems. By identifying various vulnerabilities and via research cases of the ship systems and AI technologies, this study presents possible cyberattack scenarios on the AI technologies applied to autonomous ships. Based on these attack scenarios, cyberthreats and cybersecurity requirements are formulated for autonomous ships by employing the security quality requirements engineering (SQUARE) methodology.

Fire Detection and Notification Method in Ship Areas Using Deep Learning and Computer Vision Approaches.

Fire incidents occurring onboard ships cause significant consequences that result in substantial effects. Fires on ships can have extensive and severe wide-ranging impacts on matters such as the safety of the crew, cargo, the environment, finances, reputation, etc. Therefore, timely detection of fires is essential for quick responses and powerful mitigation. The study in this research paper presents a fire detection technique based on YOLOv7 (You Only Look Once version 7), incorporating improved deep learning algorithms. The YOLOv7 architecture, with an improved E-ELAN (extended efficient layer aggregation network) as its backbone, serves as the basis of our fire detection system. Its enhanced feature fusion technique makes it superior to all its predecessors. To train the model, we collected 4622 images of various ship scenarios and performed data augmentation techniques such as rotation, horizontal and vertical flips, and scaling. Our model, through rigorous evaluation, showcases enhanced capabilities of fire recognition to improve maritime safety. The proposed strategy successfully achieves an accuracy of 93% in detecting fires to minimize catastrophic incidents. Objects having visual similarities to fire may lead to false prediction and detection by the model, but this can be controlled by expanding the dataset. However, our model can be utilized as a real-time fire detector in challenging environments and for small-object detection. Advancements in deep learning models hold the potential to enhance safety measures, and our proposed model in this paper exhibits this potential. Experimental results proved that the proposed method can be used successfully for the protection of ships and in monitoring fires in ship port areas. Finally, we compared the performance of our method with those of recently reported fire-detection approaches employing widely used performance matrices to test the fire classification results achieved.

BATMAN: A Brain-like Approach for Tracking Maritime Activity and Nuance.

As commercial geospatial intelligence data becomes more widely available, algorithms using artificial intelligence need to be created to analyze it. Maritime traffic is annually increasing in volume, and with it the number of anomalous events that might be of interest to law enforcement agencies, governments, and militaries. This work proposes a data fusion pipeline that uses a mixture of artificial intelligence and traditional algorithms to identify ships at sea and classify their behavior. A fusion process of visual spectrum satellite imagery and automatic identification system (AIS) data was used to identify ships. Further, this fused data was further integrated with additional information about the ship's environment to help classify each ship's behavior to a meaningful degree. This type of contextual information included things such as exclusive economic zone boundaries, locations of pipelines and undersea cables, and the local weather. Behaviors such as illegal fishing, trans-shipment, and spoofing are identified by the framework using freely or cheaply accessible data from places such as Google Earth, the United States Coast Guard, etc. The pipeline is the first of its kind to go beyond the typical ship identification process to help aid analysts in identifying tangible behaviors and reducing the human workload.

Prioritizing management of high-risk routes and ports by vessel type to improve marine biosecurity efforts.

The shipping industry constitutes the main vector of marine bioinvasions. Over 90,000 vessels world-wide create a highly complex shipping network that requires appropriate management tools. Here we characterized a novel vessel category, Ultra Large Container Vessels (ULCV), in terms of potential contribution to the dispersal of Non-Indigenous Species (NIS) in comparison to smaller vessels traveling similar routes. Such approach is essential for providing precise information-based risk analysis necessary to enforce biosecurity regulations and reduce the adverse global effects of marine NIS. We used Automatic Identification System (AIS) based websites to extract shipping data that will enable us to test for differences in two vessel behaviors linked to NIS dispersal: port visit durations and voyage sailing times. We then examined the geographic spread of ULCVs and small vessels, quantifying the accumulation of new port visits, countries, and ecoregions for each vessel category. Finally, Higher Order Network (HON) analysis revealed emergent patterns within shipping traffic, species flow, and invasion risk networks of these two categories. Compared to the smaller vessels, ULCVs spent significantly longer time in 20% of the ports and were more geographically constrained, with fewer port visits, countries, and regions. HON analysis revealed that the ULCV shipping species flow and invasion risk networks were more similar to each other than to those of the smaller vessels. However, HON port importance shifts were discernible for both vessel categories, with major shipping hubs not necessarily being major invasion hubs. Overall, compared to smaller vessels, ULCVs behave differently in ways that potentially increase biofouling risk, albeit in a smaller set of ports. Future studies using HON analysis of other dispersal vectors appears critical for prioritizing management of high-risk routes and ports.

Maritime autonomous surface ships: can we learn from unmanned aerial vehicle incidents using the perceptual cycle model?

Interest in Maritime Autonomous Surface Ships (MASS) is increasing as it is predicted that they can bring improved safety, performance and operational capabilities. However, their introduction is associated with a number of enduring Human Factors challenges (e.g. difficulties monitoring automated systems) for human operators, with their 'remoteness' in shore-side control centres exacerbating issues. This paper aims to investigate underlying decision-making processes of operators of uncrewed vehicles using the theoretical foundation of the Perceptual Cycle Model (PCM). A case study of an Unmanned Aerial Vehicle (UAV) accident has been chosen as it bears similarities to the operation of MASS through means of a ground-based control centre. Two PCMs were developed; one to demonstrate what actually happened and one to demonstrate what should have happened. Comparing the models demonstrates the importance of operator situational awareness, clearly defined operator roles, training and interface design in making decisions when operating from remote control centres. Practitioner Summary: To investigate underlying decision-making processes of operators of uncrewed vehicles using the Perceptual Cycle Model, by using an UAV accident case study. The findings showed the importance of operator situational awareness, clearly defined operator roles, training and interface design in making decisions when monitoring uncrewed systems from remote control centres.

Total Methane and CO2 Emissions from Liquefied Natural Gas Carrier Ships: The First Primary Measurements.

Mitigating methane emissions is vital in meeting global climate targets, but there is a lack of understanding of emissions and abatement opportunities to enable this. The natural gas supply chain is a key emission source, where methane emissions from liquefied natural gas (LNG) shipping have until now not been directly measured. This study provides the first measurement and modeling of total methane and CO2 emissions from an LNG carrier on a round trip voyage from the USA to Belgium and back, including loading, laden voyage, unloading, and ballast voyage, measuring emissions from exhaust stacks, vents, and fugitives. Venting and fugitive emissions were extremely low, contributing less than 0.1% of total greenhouse gas emissions. CO2 emissions from fuel usage were also lower than previous estimates due to improved efficiencies in modern engines and ship design. However, methane slip through the engines were higher than those in prior studies, averaging 3.8% across all engines: equating to 0.1% of delivered LNG. Generator engines are not typically included in emissions analyses but were the key cause of methane emissions. Engines exhibited higher methane slip rates at low loads, and optimized operation could reduce slip rates by half. More measurement studies are now needed to better understand fleet emissions and enable cost-effective mitigation strategies.

Possible influence of shipping emissions on metals in size-segregated particulate matter in Guanabara Bay (Rio de Janeiro, Brazil).

In the world of growing maritime fleets, ships powered by fossil fuels are being widely used that are responsible for atmospheric emissions such as particulate matter (PM). When inhaled, these can cause serious injury to the body and affect internal organs, because the particle size is on a tiny scale. The International Convention for the Prevention of Pollution from Ships (MARPOL) regulates the standards for emissions from marine diesel engines. However, although they pose risks to human health and the environment, the metals present in PM are not covered by Brazilian national current legislation. This study is based on the results of sampling of PM in the atmosphere of Guanabara Bay, Rio de Janeiro, Brazil, by means of the MOUDI cascade impactor, followed by acid opening of the collected PM and subsequent chemical analysis by ICP-MS for the determination of Ba, Ca, Cd, Co, Cu, Cr, Fe, Mg, Mn, Ni, Pb, V, and Zn. In coarse particles, the mean values ranged from 0.11 ng m-3 for Ba to 24.9 ng m-3 for Fe; in fine particles, from 0.07 ng m-3 for Co to 25.0 ng m-3 for Fe; and in ultrafine particles, from 0.11 ng m-3 for Ba to 9.71 ng m-3 for Fe. Finally, the nanoparticles (Ba and Ca) were not detected and the maximum value obtained was 5.32 ng m-3 for Mn.

Successful Control of an Onboard COVID-19 Outbreak Using the Cruise Ship as a Quarantine Facility, Western Australia, Australia.

Onboard quarantining has been only partially effective to control outbreaks of coronavirus disease on cruise ships. We describe the successful use of the ship as a quarantine facility during the response to the outbreak on the MS Artania, which docked in Western Australia, Australia. The health-led 14-day quarantine regime was based on established principles of outbreak management and experiences of coronavirus disease outbreaks on cruise ships elsewhere. The attack rate in the crew was 3.3% (28/832) before quarantine commencement and 4.8% (21/441) during quarantine on board. No crew members became symptomatic after completion of quarantine. Infection surveillance involved telephone correspondence, face-to-face visits, and testing for severe acute respiratory syndrome coronavirus 2. No serious health issues were reported, no response staff became infected, and only 1 quarantine breach occurred among crew. Onboard quarantine could offer financial and operational advantages in outbreak response and provide reassurance to the shore-based wider community regarding risk for infection.

Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports.

This study aims to investigate the coronavirus disease (COVID-19) pandemic effects and associated restrictive rules on ship activities and pollutant emissions (CO2, SOX, NOX, PM, CO, CH4) in four major seaports, namely the Ports of Singapore, Long Beach, Los Angeles, and Hamburg. We used 2019 as the baseline year to show the business-as-usual emission and compared with the estimated quantity during the July 2020-July 2021 pandemic period. We also project future ship emissions from August 2021-August 2022 to illustrate two potential port congestion scenarios due to COVID-19. The results show that the ship emissions in all four ports generally increased by an average of 79% because of the prolonged turnaround time in port. Importantly, majority of ship emissions occurred during the extended hoteling time at berth and anchorage areas as longer operational times were needed due to pandemic-related delays, with increases ranging from 27 to 123% in the total emissions across ports. The most affected shipping segments were the container ships and dry bulk carriers which the total emissions of all pollutants increased by an average of 94-142% compared with 2019. Overall, the results of this study provide a comprehensive review of the ship emission outlook amid the pandemic uncertainty.

A Real-Time Collision Avoidance Framework of MASS Based on B-Spline and Optimal Decoupling Control.

Real-time collision-avoidance navigation of autonomous ships is required by many application scenarios, such as carriage of goods by sea, search, and rescue. The collision avoidance algorithm is the core of autonomous navigation for Maritime autonomous surface ships (MASS). In order to realize real-time and free-collision under the condition of multi-ship encounter in an uncertain environment, a real-time collision avoidance framework is proposed using B-spline and optimal decoupling control. This framework takes advantage to handle the uncertain environment with limited sensing MASS which plans dynamically feasible, highly reliable, and safe feasible collision avoidance. First, owing to the collision risk assessment, a B-spline-based collision avoidance trajectory search (BCATS) algorithm is proposed to generate free-collision trajectories effectively. Second, a waypoint-based collision avoidance trajectory optimization is proposed with the path-speed decoupling control. Two benefits, a reduction of control cost and an improvement in the smoothness of the collision avoidance trajectory, are delivered. Finally, we conducted an experiment using the Electronic Chart System (ECS). The results reveal the robustness and real-time collision avoidance trajectory planned by the proposed collision avoidance system.

Habitability in Berthing Compartments and Well-Being of Sailors Working on U.S. Navy Surface Ships.

OBJECTIVE: The study had two objectives: (a) to assess the prevalence of sleep-related habitability concerns in the berthing compartments of U.S. Navy surface ships and (b) to assess whether habitability issues in berthing compartments affected the sleep and well-being of crew members. BACKGROUND: The importance of habitability for human well-being is recognized. Little is known, however, about the association between habitability factors in the sleeping/berthing compartments and sailor well-being in operational conditions. METHOD: Fit-for-duty sailors (N = 1,269; from six ships) participated in this naturalistic and longitudinal study. Sailors reported habitability factors affecting their sleep and completed four standardized questionnaires to assess daytime sleepiness, insomnia, sleep quality, and mood. Sleep was assessed through wrist-worn actigraphy and activity logs. RESULTS: Noise, ambient temperature, poor bedding conditions, and ambient light were the most frequently reported factors of concern. Compared to their peers with fewer complaints, sailors with more habitability-related complaints were more likely to have elevated daytime sleepiness (by 23%) and to report insomnia symptoms (145%) and lower sleep quality (21%). Sailors who reported more habitability-related issues also tended to sleep longer. Individuals with more complaints about habitability also tended to report worse mood (total mood disturbance, tension/anxiety, depression, fatigue, and confusion/bewilderment). CONCLUSION: Habitability-related complaints are associated with sailor well-being and sleep. Future studies should expound on the various detrimental factors that degrade conditions in berthing compartments and negatively impact crew well-being. APPLICATION: Habitability in berthing compartments of surface ships is associated with sailors' daytime sleepiness, insomnia severity, mood, and sleep attributes. Ship designers should take these findings into consideration and investigate viable and cost-effective methods to mitigate the problems we identified.

Underground and Over the Sea: More Community Prophylactics in Europe, 1100-1600.

Public health historians have repeatedly shown that the theory, policy, and practice of group prophylactics far predate their alleged birth in industrial modernity, and regularly draw on Galenic principles. While the revision overall has been successful, its main focus on European cities entails a major risk, since city dwellers were a minority even in Europe's most urbanised regions. At the same time, cities continue to be perceived and presented as typically European, which stymies transregional and comparative studies based at least in part on non- or extra-urban groups. Thus, any plan to both offer an accurate picture of public health's deeper past and fundamentally challenge a narrative of civilizational progress wedded to Euro-American modernity ("stagism") would benefit from looking beyond cities and their unique health challenges. The present article begins to do so by focusing on two ubiquitous groups, often operating outside cities and facing specific risks: miners and shipmates. Evidence for these communities' preventative interventions and the extent to which they drew on humoral theory is rich yet uneven for Europe between the thirteenth and sixteenth centuries. Methodological questions raised by this unevenness can be addressed by connecting different scales of evidence, as this article demonstrates. Furthermore, neither mining nor maritime trade was typically European, thus building a broader base for transregional studies and comparisons.

Study on Visual Detection Algorithm of Sea Surface Targets Based on Improved YOLOv3.

Countries around the world have paid increasing attention to the issue of marine security, and sea target detection is a key task to ensure marine safety. Therefore, it is of great significance to propose an efficient and accurate sea-surface target detection algorithm. The anchor-setting method of the traditional YOLO v3 only uses the degree of overlap between the anchor and the ground-truth box as the standard. As a result, the information of some feature maps cannot be used, and the required accuracy of target detection is hard to achieve in a complex sea environment. Therefore, two new anchor-setting methods for the visual detection of sea targets were proposed in this paper: the average method and the select-all method. In addition, cross PANet, a feature fusion structure for cross-feature maps was developed and was used to obtain a better baseline cross YOLO v3, where different anchor-setting methods were combined with a focal loss for experimental comparison in the datasets of sea buoys and existing sea ships, SeaBuoys and SeaShips, respectively. The results showed that the method proposed in this paper could significantly improve the accuracy of YOLO v3 in detecting sea-surface targets, and the highest value of mAP in the two datasets is 98.37% and 90.58%, respectively.

An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning.

Deep reinforcement learning (DRL) has excellent performance in continuous control problems and it is widely used in path planning and other fields. An autonomous path planning model based on DRL is proposed to realize the intelligent path planning of unmanned ships in the unknown environment. The model utilizes the deep deterministic policy gradient (DDPG) algorithm, through the continuous interaction with the environment and the use of historical experience data; the agent learns the optimal action strategy in a simulation environment. The navigation rules and the ship's encounter situation are transformed into a navigation restricted area, so as to achieve the purpose of planned path safety in order to ensure the validity and accuracy of the model. Ship data provided by ship automatic identification system (AIS) are used to train this path planning model. Subsequently, the improved DRL is obtained by combining DDPG with the artificial potential field. Finally, the path planning model is integrated into the electronic chart platform for experiments. Through the establishment of comparative experiments, the results show that the improved model can achieve autonomous path planning, and it has good convergence speed and stability.

Nonuniformly-Rotating Ship Refocusing in SAR Imagery Based on the Bilinear Extended Fractional Fourier Transform.

Nonuniformly-rotating ship refocusing is very significant in the marine surveillance of satellite synthetic aperture radar (SAR). The majority of ship imaging algorithms is based on the inverse SAR (ISAR) technique. On the basis of the ISAR technique, several parameter estimation algorithms were proposed for nonuniformly rotating ships. But these algorithms still have problems on cross-terms and noise suppression. In this paper, a refocusing algorithm for nonuniformly rotating ships based on the bilinear extended fractional Fourier transform (BEFRFT) is proposed. The ship signal in a range bin can be modeled as a multicomponent cubic phase signal (CPS) after motion compensation. BEFRFT is a bilinear extension of fractional Fourier transform (FRFT), which can estimate the chirp rates and quadratic chirp rates of CPSs. Furthermore, BEFRFT has excellent performances on cross-terms and noise suppression. The results of simulated data and Gaofen-3 data verify the effectiveness of BEFRFT.