Cargo Monitoring Research Articles

Digital Transformation in the Maritime Industry; Opportunities and Challenges for Indonesia

Digital transformation is reshaping industries worldwide, including the maritime sector, by integrating advanced technologies to improve efficiency, safety, and sustainability. In the context of Indonesia, a country with a vast archipelago and significant maritime activities, digital transformation offers substantial opportunities but also presents distinct challenges. This paper explores the multifaceted impacts of digital transformation on Indonesia's maritime industry, examining both the opportunities and challenges that arise from this technological shift. Opportunities in the maritime sector include enhanced operational efficiency, improved safety, and better environmental management. Technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence (AI), and blockchain are pivotal in optimizing logistics, predictive maintenance, and real-time monitoring of vessels and cargo. These advancements can lead to reduced operational costs, minimized human errors, and lower environmental footprints. For Indonesia, leveraging these technologies could significantly boost its competitiveness in global shipping, enhance port operations, and support the sustainable management of its extensive marine resources. However, the journey towards digital transformation in Indonesia’s maritime industry is fraught with challenges. Key issues include inadequate digital infrastructure, limited technological expertise, and regulatory hurdles. The uneven distribution of digital infrastructure across Indonesia's archipelago hampers the consistent application of advanced technologies. Additionally, the maritime workforce requires upskilling to handle new digital tools effectively, necessitating substantial investment in education and training. Regulatory frameworks also need to evolve to address data security, privacy concerns, and the integration of international standards, ensuring a seamless transition to digital operations.

New Technology in Marine Logistics Warehouse Management

The marine logistics industry faces challenges in improving efficiency, reducing operational costs, and supporting environmental sustainability. One crucial aspect that can be optimized is warehouse management, which is responsible for the storage, handling, and distribution of cargo. This research aims to explore the application of new technologies such as the Internet of Things (IoT), artificial intelligence (AI), robotics, automation, and green technologies in marine logisticswarehousemanagement. Themethodology used includes a comprehensive literature review, in-depth interviews with industry experts, and analysis of case studies of new technology implementation in marine logistics companies. The results revealed significant opportunities and benefits from the implementation of new technologies, such as improved visibility and real-time monitoring of cargo, optimization of cargo storage and handling, increased productivity and safety, and reduced operational carbon footprint. However, challenges such as initial investment costs, data security, system interoperability, and human resource training needs must be overcome. This research presents a comprehensive implementation strategy, including cost-benefit analysis, development of industry standards, implementation of strict security protocols, and collaboration between industry, government, and standardization bodies.A conceptual framework is developed to provide practical guidance for the marine logistics industry to effectively implement new technologies and optimize their benefits. By adopting new technologies appropriately, the marine logistics industry can improve its competitiveness and global supply chain performance, and support environmental sustainability.

The Effect of Regional Electronic Cargo Tracking Systems on Cargo Safety at the Kenya Revenue Authority

The Regional Electronic Cargo Tracking System (RECTS) was adopted by the Kenya Revenue Authority (KRA) to enhance cargo security and boost revenue collection. RECTS is aimed at addressing inefficiencies in vendor-operated Electronic Cargo Tracking Systems (ECTs) whose geo-fence routes can be manipulated, making it challenging to determine the exact location of the cargo. Their failure to send alerts on seal tampering and diversions has resulted in a substantial loss of revenue. This study sought to assess the impact of RECTS on cargo security with a focus on KRA customs operations. The study addressed the impact of RECTS cargo tracking on cargo security, the impact of RECTS cargo monitoring on cargo security, and the measurement of the impact of RECTS real-time response on cargo security at KRA. The research adopted a descriptive research design. The target population for this study was the 140 Rapid Response Units (RRU) and the Cargo Monitoring Unit (CMU) staff working at the five designated RRU stations along the Northern Corridor. Stratified simple random sampling was used to select 104 KRA staff to participate in the study. The primary data was collected by means of a self-administered questionnaire provided to the staff working at the five designated stations. Secondary data was collected from the records of the Cargo Monitoring Unit on incidents of theft, tampering and damage of cargo. The data was analysed using SPSS to compute descriptive and inferential statistics. The study established that the independent variables of cargo tracking, cargo monitoring and real-time response, significantly influence the dependent variable as they account for an 82.90 per cent variation in cargo security. The results of a multiple regression analysis established that cargo tracking has a positive and significant effect on cargo security (β1=0.873, p=0.000); that cargo monitoring has a positive and significant effect cargo security (β2=0.175, p=0.015); and that real-time response has a positive and significant effect cargo security (β3=0.222, P=0.000). The findings of the study revealed that cargo tracking enhances the security of the cargo by deterring cases of cargo diversion and by providing the exact location of the stolen, damaged or tampered cargo enabling the Rapid Response Unit to locate the cargo and resolve the situation immediately. Cargo monitoring enhances cargo security by providing real-time alerts in respect of cargo seal tampering which minimises the tampering that previously occurred during changeover of seals at border points. Additionally, real-time response enhances the security of cargo by reducing the time taken by the Rapid Response Unit to respond to and resolve cases of theft, tampering and cargo accidents during transit.

Review of Reliability Assessment Methods of Drone Swarm (Fleet) and a New Importance Evaluation Based Method of Drone Swarm Structure Analysis

Drones, or UAVs, are developed very intensively. There are many effective applications of drones for problems of monitoring, searching, detection, communication, delivery, and transportation of cargo in various sectors of the economy. The reliability of drones in the resolution of these problems should play a principal role. Therefore, studies encompassing reliability analysis of drones and swarms (fleets) of drones are important. As shown in this paper, the analysis of drone reliability and its components is considered in studies often. Reliability analysis of drone swarms is investigated less often, despite the fact that many applications cannot be performed by a single drone and require the involvement of several drones. In this paper, a systematic review of the reliability analysis of drone swarms is proposed. Based on this review, a new method for the analysis and quantification of the topological aspects of drone swarms is considered. In particular, this method allows for the computing of swarm availability and importance measures. Importance measures in reliability analysis are used for system maintenance and to indicate the components (drones) whose fault has the most impact on the system failure. Structural and Birnbaum importance measures are introduced for drone swarms’ components. These indices are defined for the following topologies: a homogenous irredundant drone fleet, a homogenous hot stable redundant drone fleet, a heterogeneous irredundant drone fleet, and a heterogeneous hot stable redundant drone fleet.

DW-TRAC – СЕРВИС ОТСЛЕЖИВАНИЯ И МОНИТОРИНГА ОПАСНЫХ ОТХОДОВ

To improve the efficiency and security of transportation of hazardous waste is implemented by service DW-TRAC, has a number of undoubted advantages, among which are the tracking and monitoring of cargo

Deep Learning-Assisted Triboelectric Smart Mats for Personnel Comprehensive Monitoring toward Maritime Safety.

Monitoring the crew of a ship can be performed by combining sensors and artificial intelligence methods to process sensing data. In this study, we developed a deep learning (DL)-assisted minimalist structure triboelectric smart mat system for obtaining abundant crew information without the privacy concerns of taking video. The smart mat system is fabricated using a conductive sponge with different filling rates and a fluorinated ethylene propylene membrane. The proposed dual-channel measurement method improves the stability of the generated signal. Comprehensive crew and cargo monitoring, including personnel and status identification, as well as positioning and counting functions are realized by the DL-assisted triboelectric smart mat system according to the analysis of instant sensory data. Real-time monitoring of crews through fixed and mobile devices improves the ability and efficiency of handling emergencies. The smart mat system provides privacy concerns and an effective way to build ship Internet of Things and ensure personnel safety.

Ergot in Canadian cereals – relevance, occurrence, and current status

Ergot is a fungal disease that occurs on cereals and grasses, including rye, oat, wheat, and barley. The ergot pathogen, Claviceps purpurea, infects the floret, and as infection progresses, it replaces individual kernels, appearing on the head as darkly coloured fungal bodies called sclerotia. Ergot is a grain-grading factor in Canada and can affect grain quality and value, as well as safety due to production of ergot alkaloids. Testing of durum fortified with ergot sclerotia showed that the presence of sclerotia resulted in black specks in semolina and pasta, but had no impact on milling performance or end-product quality. Surveillance performed as part of the Canadian Grain Commission’s annual Harvest Sample and Cargo Monitoring Programs provided insights into ergot incidence and severity in different grains, growing locations, and years, as well as the presence of ergot alkaloids. Analysis of more than 230 000 Harvest Sample Program grain samples from western Canada across 25 years showed the highest ergot incidence and severity occurred in rye, followed by bread and durum wheat, and then barley and oats. Ergot incidence and severity varied annually, but only incidence increased over time. Analyses of bulk grain shipments indicated that the presence of ergot alkaloids reflected the disease incidence observed in the harvest samples (median ergot alkaloid concentrations in wheat and durum > oats and barley). Data on ergot alkaloids from the Cargo Monitoring Program also showed that the Canadian bulk grain-handling system mitigated the variability in annual ergot incidence and severity observed in harvest samples.

Detecting Moving Trucks on Roads Using Sentinel-2 Data

In most countries, freight is predominantly transported by road cargo trucks. We present a new satellite remote sensing method for detecting moving trucks on roads using Sentinel-2 data. The method exploits a temporal sensing offset of the Sentinel-2 multispectral instrument, causing spatially and spectrally distorted signatures of moving objects. A random forest classifier was trained (overall accuracy: 84%) on visual-near-infrared-spectra of 2500 globally labelled targets. Based on the classification, the target objects were extracted using a developed recursive neighbourhood search. The speed and the heading of the objects were approximated. Detections were validated by employing 350 globally labelled target boxes (mean F1 score: 0.74). The lowest F1 score was achieved in Kenya (0.36), the highest in Poland (0.88). Furthermore, validated at 26 traffic count stations in Germany on in sum 390 dates, the truck detections correlate spatio-temporally with station figures (Pearson r-value: 0.82, RMSE: 43.7). Absolute counts were underestimated on 81% of the dates. The detection performance may differ by season and road condition. Hence, the method is only suitable for approximating the relative truck traffic abundance rather than providing accurate absolute counts. However, existing road cargo monitoring methods that rely on traffic count stations or very high resolution remote sensing data have limited global availability. The proposed moving truck detection method could fill this gap, particularly where other information on road cargo traffic are sparse by employing globally and freely available Sentinel-2 data. It is inferior to the accuracy and the temporal detail of station counts, but superior in terms of spatial coverage.

Key Benefits of Cloud-Based Internet of Vehicle (IoV)-Enabled Fleet Weight Management System

The fleet industry is flourishing at extreme levels with a wide acceptance of IoV-powered methods in various verticals. Fuel consumption, tire pressure readings, driver’s driving habits, cargo monitoring, load measurement, and many other applications have now become possible in the fleet sector with the implementation of IoV and cloud based applications. Most of the industries heavily rely on transportation to carry loads and other different industrial products. The overall cost of vehicle maintenance involves a significant portionof total operating costs. Vehicle weight plays a major role in transporting goods from one place to the other. Many places have stringent rules regarding load transportation that only a certain amount of weight is allowed through a particular passage or road. This could result in heavy fines if all the regulations are not met and create unwanted expenses. It also creates unnecessary delays in product deliveries, which hampers the reputation of businesses. Hence, a smart solution can be integrated with the fleet sector to avoid extra costs during transit. In this paper, we will highlight the key benefits of IoV-based fleet weight management smart solution for fleet sector

Research and Design of the Architecture of the Marine Logistics Information Platform Based on Big Data

Zhang, N. and Zheng, K., 2020. Research and design of the architecture of the marine logistics information platform based on big data. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 628–632. Coconut Creek (Florida), ISSN 0749-0208.Using Internet of Things (IoTs) and cloud computing technologies in the era of big data to design a highly shared marine logistics information platform is the basis for realizing the information, efficiency, and intelligence of its logistics process. This research integrated big data thinking and sharing concepts into shared logistics, designed the architecture of a highly shared marine logistics information platform, and proposed an implementation method and application model for the architecture. The platform design introduces artificial intelligence and IoT technologies based on GPS, general packet radio service, and automatic identification system. The platform realizes real-time positioning and monitoring of land and sea cargo, which greatly improves the efficiency of marine logistics management.

Monte Carlo and experimental analysis of a novel directional rotating scatter mask gamma detection system

Abstract For such diverse applications as on-site radiation monitoring, treaty or material verification, cargo monitoring during transport, and orphan source location a radioactive source localization system is of great use. The Rotating Scatter Mask (RSM) detection system, a rapid scatter mask retrofit to a conventional radiation detector, provides a low-cost, large field of view and energy range solution to this problem. This work demonstrates successful experimental operation of a prototype system to identify source direction which was modeled using a library of signals simulated using GEANT and a novel algorithm, validated by comparing results with MCNP and experiment.

SOFTWARE OPTIMIZATION TECHNOLOGY OF AIRCRAFT COMPOSITION IN OPERATIONAL PLANNING IN THE AEROSPACE SEARCH AND RESCUE SYSTEM

The article considers the software of optimization technology allowing to enhance the work of the aerospace search and rescue system in terms of making decisions on the use of aircraft. Due to the fact that at the moment the scientifically based principles of making operational decisions for optimal distribution and attraction of aircraft to search and rescue are not completely developed, especially with the use of automated processes, such decisions are made on the basis of the personal experience of the head of search and rescue (HSR). The article provides an analysis of domestic developments in the field of information and technical support for search and rescue (SAR), an algorithm for decision-making based on factors influencing the choice of search and rescue forces and assets. Software implemented on the visual programming tool Visual Basic for Applications is presented; it provides the mathematical model of the aircraft optimization for: the minimum expenditure of funds based on the theory of linear programming, the minimum examination time of given area and the probability of failure-free operation with a forecast of meteorological conditions for three days. The results of calculations are presented in the form of recommendations with graph-analytic explanations for each block of optimization to reflect the full "picture" of the forecasted search and rescue operation (SAR). The realized integrated approach in the software is able to provide unified recommendations for the RPFS not only during operational planning, but also in the organization of transport tasks, monitoring and delivery of humanitarian cargo. This allows the governing bodies to give the best recommendations (on the basis of the "efficiency-quality-economical efficiency" principle) and, if necessary, to formulate scientifically based offers on the use of forces and assets in the aerospace search and rescue system

Study on Developing a System with IP Functionality to Monitor the Status of Containers in Maritime Logistics

There has been increasing demand from consignors and shipping companies for real-time monitoring of maritime cargo due to increases in fresh, dangerous, and high-value cargo. Although larger carriers have developed and integrated their own systems for such real-time monitoring services, small- and medium-sized shippers are struggling with the heavy costs and workforce associated with such capability. This study introduces a system that can do real-time monitoring of the location of shipping containers and their internal status by using IP-RFID that in cludes IP functionality. This system is composed of a tag, a smart point, and a service platform. The monitoring tags are attached to regular containers to track the opening and closing of the doors, the internal temperature, and humidity. The tags then send the data to the smart point where the GPS information is added. The data packet is then finally transmitted to the service platform for location tracking. In particular, as the tags in this system have IP functionality like Multicast, they are capable of communicating with the users and also allow users to control them. In order to provide such functionality, the smart points can serve as a gateway between the service platform and the tag. By managing the tag’s connection information and the status of transmission at the smart point, the service platform can directly communicate with tags connected to the respective smart point. This technology could be applied in a diverse range of maritime and non-maritime areas including warehouse management. As for maritime logistics, it also often goes through ground, port, and air transportation phases. Further studies should monitor the actual performance of this equipment across the various phases of maritime logistics to empirically test the systems proposed herein.

Tracking and tracing tobacco products in Kenya

This report evaluates the effectiveness of various measures to control the size of illicit cigarette trade in Kenya. It is based on a literature review, a review of conference proceedings/materials, online searches, and analyses of data from the National Statistical Office of Kenya, ERC, and Euromonitor. I used both published and grey literature, official government reports, and online news articles.In response to the presence of illicit cigarettes in the market in the early 2000s, Kenya adopted numerous measures to reduce tobacco tax evasion, with varying degrees of success. The latest solution involving a tracking and tracing system accompanied by electronic cargo monitoring of export seems to be the most effective, as it reduced the size of the illicit cigarette market and increased tax revenue. In addition, it seems to be more resistant to tampering.The experience of Kenya highlights the importance of consistency and comprehensiveness of the system addressing tax evasion, because piecemeal measures have only short-term effects.

The impact of cargo monitoring systems usage on intermodal transport risk and costs

The research was carried out to verify the impact of using systems to monitor cargo location and parameters in the transportation chain. Three variants of cases were examined - a reference variant (without cargo monitoring systems), variant I (positioning systems), and variant II (monitoring cargo location and parameters). It was possible to assess the benefits of application of the monitoring systems of loading units in road transport. The transport chain was divided into separate processes. For each of them, the possible risk appearance was specified with percentage probability. On this basis, the simulation of transport cases was performed using Excel software. For the simulation results analysis, the statistical software 'MiniTab 17' and 'Statgraphic Centurion XVI' was used. Risk identification on each link of the supply chain allows taking actions in order to reduce costs, which is essential to the effective functioning of the company and increasing the level of customer service.

An IoT-based cargo monitoring system for enhancing operational effectiveness under a cold chain environment

Differing from managing a general supply chain, handling environmentally sensitive products (ESPs) requires the use of specific refrigeration systems to control the designated range of storage conditions, such as temperature, humidity, and lighting level in a cold chain environment. In general, third-party logistics (3PL) companies are authorized to handle ESPs, who therefore need to have a good cargo monitoring system in the cold chain environment, without which the functional quality is difficult to control and manage. This may result in product deterioration and even inventory obsolescence of the ESPs due to the lack of such systems, so there is a need to develop an effective cargo monitoring system to prevent such situations. This article proposes an Internet of Things-based cargo monitoring system (IoT-CMS) to monitor any environmental changes of ESPs in order to ensure their functional quality throughout the entire cold chain operational environment. Operational efficiency, maintenance strategy, environmental change, and electricity consumption are considered in real-life cold chain operations. Through applying (i) a wireless sensor network to collect real-time product information, together with (ii) fuzzy logic and case-based reasoning techniques to suggest appropriate storage conditions for various ESPs, effective storage guidance can be established. Through conducting the case study in a 3PL company in Hong Kong, the performance in customer satisfaction, obsolescence rate, and inventory visibility after adoption of IoT-CMS is evaluated. It is found that the functional quality of ESPs can be effectively assured, and the overall customer satisfaction is increased.

The impact of cargo monitoring systems usage on intermodal transport risk and costs

The research was carried out to verify the impact of using systems to monitor cargo location and parameters in the transportation chain. Three variants of cases were examined - a reference variant (without cargo monitoring systems), variant I (positioning systems), and variant II (monitoring cargo location and parameters). It was possible to assess the benefits of application of the monitoring systems of loading units in road transport. The transport chain was divided into separate processes. For each of them, the possible risk appearance was specified with percentage probability. On this basis, the simulation of transport cases was performed using Excel software. For the simulation results analysis, the statistical software 'MiniTab 17' and 'Statgraphic Centurion XVI' was used. Risk identification on each link of the supply chain allows taking actions in order to reduce costs, which is essential to the effective functioning of the company and increasing the level of customer service.

Model and Algorithm Design for Cargo Shipping Safety Based on Fuzzy- Precise Bayesian Network

The shippers have the requests for the accessibility and economics of logistics on the premise of cargo safety, and the cargo shipping safety is an important part of logistics safety. Thus, it is quite essential to monitor the cargo shipping safety. The data is difficult to obtain in the research for cargo shipping safety, thus it cannot cover all states of influencing factors during modeling process of Bayesian network. In order to solve this problem, the computation process of Bayesian network was improved in this paper, and the Fuzzy-precise Bayesian network was obtained. The Fuzzy-precise Bayesian network was applied to monitor cargo shipping safety. According to the multi-field coupling theory, the index system influencing the cargo shipping safety was established, the GeNIe software was used to conduct the inference of Bayesian network. The inference model was utilized for conducting the safety monitoring of specific cargo on a bulk cargo ship of a company in Hainan province, and the effectiveness and availability of this model was examined. This paper provides guidance for safety production of enterprises' cargo shipping

Ubiquitous Containerized Cargo Monitoring System Development based on Wireless Sensor Network Technology

Due to globalization, global trade is strongly growing nowadays. The use of containers has significantly increased and bringing the change on the shape of the world economy. Thus, monitoring every single container is a big challenge for port industries. Furthermore, rapid development in embedded computing systems has led to the emergence of Wireless Sensor Network (WSN) technology which enabled us to envision the intelligent containers. This represents the next evolutionary development in logistics industry to increase the efficiency, productivity, security of containerized cargo shipping. In this paper, we present a comprehensive containerized cargo monitoring system based on WSNs. We incorporated tilt/motion sensor to improve the network convergence time of container networks. Moreover, we periodically switch the nodes into sleeping mode to save energy and extend the lifetime of the network. Based on the technical implementation on a real container vessel, we strongly believed that our design which employed WSN technology is viable to be implemented in container logistics to improve port services and provide safe transport of containerized cargo.

Transportation Security SensorNet: a service‐oriented architecture for cargo monitoring

PurposeSecurity and accountability within the transportation industry are vital because cargo theft could amount to as much as $60 billion per year. Since goods are often handled by many different parties, it must be possible to tightly monitor the location of cargo and handovers. Tracking trade is difficult to manage in different formats and legacy applications Web services and open standards overcome these problems with uniform interfaces and common data formats. This allows consistent reporting, monitoring and analysis at each step. The purpose of this paper is to examine Transportation Security SensorNet (TSSN), the goal being to promote the use of open standards and specifications in combination with web services to provide cargo monitoring capabilities.Design/methodology/approachThis paper describes a system architecture for the TSSN targeted for cargo monitoring. The paper discusses cargo security and reviews related literature and approaches. The paper then describes the proposed solution of developing a service‐oriented architecture (SOA) for cargo monitoring and its individual components.FindingsWeb services in a mobile sensor network environment have been seen as slow and producing significant overhead. The authors demonstrate that with proper architecture and design the performance requirements of the targeted scenario can be satisfied with web services; the TSSN then allows sensor networks to be utilized in a standardized and open way through web services.Originality/valueThe integration of SOA, open geospatial consortium (OGC) specifications and sensor networks is complex and difficult. As described in related works, most systems and research focus either on the combination of SOA and OGC specifications or on OGC standards and sensor networks. The TSSN shows that all three can be combined and that this combination provides cargo security and monitoring capabilities to the transportation and other industries that have not existed before.