Search Results (8)

The need for real-time and scalable oceanographic monitoring has become crucial for coastal management, marine traffic control and environmental sustainability. This study investigates the integration of sensor technology into marine cables to enable real-time monitoring, focusing on tidal cycles and wave characteristics. A 2000 m cable demonstrator was deployed off the coast of Portugal, featuring three active repeater nodes equipped with pressure sensors at varying depths. The goal was to estimate hourly wave periods using fast Fourier transform and calculate significant wave height via a custom peak detection algorithm. The results showed strong coherence with tidal depth variations, with wave period estimates closely aligning with forecasts. The wave height estimations exhibited a clear relationship with tidal cycles, which demonstrates the system’s sensitivity to coastal hydrodynamics, a factor that numerical models designed for open waters often fail to capture. The study also highlights challenges in deep-water monitoring, such as signal attenuation and the need for high sampling rates. Overall, this research emphasises the scalability of sensor-integrated smart marine cables, offering a transformative opportunity to expand oceanographic monitoring capabilities. The findings open the door for future real-time ocean monitoring systems that can deliver valuable insights for coastal management, environmental monitoring and scientific research. Full article

Carbon (C) in gaseous form is a component of several greenhouse gases emitted during the combustion of fossil fuels. C movement between the atmosphere, land (biosphere and lithosphere), and ocean (hydrosphere) alters the total amount in each pool. Human activities accelerate C movement into the atmosphere, causing increases in temperature. This shift from terrestrial and oceanic C pools to the atmosphere causes an increase in the intensity, frequency, and duration of catastrophic climate disturbances. Although society hears and reads about C emissions, there is a lack of understanding of its importance and the need to decrease it in the atmospheric pool to avoid exacerbating climate change. Forests and biochar are two biological methods to retain C in the terrestrial pool for a long time and at a very low cost. However, forest harvesting, the use of woody biomass as a source of renewable C for different applications, and the relationship with decreasing C emissions have created a highly controversial topic among governments, the scientific community, society in general, and social groups. The main objective of this review is to highlight the importance of C, forests, and biochar, including the benefits of C sequestration to decrease the impacts of climate change and promote sustainable forests and healthy soils in the future. The main findings show strong evidence that climate-smart forest management practices are an efficient option for managing C and increasing C stocks. This review suggests that forest management mitigation actions are another efficient C management approach with high potential. The findings show that biochar is a climate-smart tool that contributes to climate change mitigation by increasing soil carbon sequestration and reducing soil GHG emissions, including other associated benefits. Full article

Monitoring of aquatic ecosystems has been historically accomplished by intensive campaigns of direct measurements (by probes and other boat instruments) and indirect extensive methods such as aero-photogrammetry and satellite detection. These measurements characterized the research in the last century, with significant but limited improvements within those technological boundaries. The newest advances in the field of smart devices and increased networking capabilities provided by emerging tools, such as the Internet of Things (IoT), offer increasing opportunities to provide accurate and precise measurements over larger areas. These perspectives also correspond to an increasing need to promptly respond to frequent catastrophic impacts produced by drilling stations and intense transportation activities of dangerous materials over ocean routes. The shape of coastal ecosystems continuously varies due to increasing anthropic activities and climatic changes, aside from touristic activities, industrial impacts, and conservation practices. Smart buoy networks (SBNs), autonomous underwater vehicles (AUVs), and multi-sensor microsystems (MSMs) such as smart cable water (SCW) are able to learn specific patterns of ecological conditions, along with electronic “noses”, permitting them to set innovative low-cost monitoring stations reacting in real time to the signals of marine environments by autonomously adapting their monitoring programs and eventually sending alarm messages to prompt human intervention. These opportunities, according to multimodal scenarios, are dramatically changing both the coastal monitoring operations and the investigations over large oceanic areas by yielding huge amounts of information and partially computing them in order to provide intelligent responses. However, the major effects of these tools on the management of marine environments are still to be realized, and they are likely to become evident in the next decade. In this review, we examined from an ecological perspective the most striking innovations applied by various research groups around the world and analyzed their advantages and limits to depict scenarios of monitoring activities made possible for the next decade. Full article

This paper presents a new holistic approach that combines solutions for the future power systems. It describes clearly how solar energy is definitely the best outlet for a clean and sustainable planet, either due to their use in both vertical (V) or horizontal (H) forms such as: hydroelectric V&H, wind V&H, thermo-oceanic V&H, water movement sea V&H (tides and waves), solar thermoelectric, PV, and surface geothermal energy. New points of view and simple formulas are suggested to calculate the best characteristic intensity, storage means and frequency for specific places and how to manage the most well-known renewable sources of energy. Future renewables-based power system requires a huge amount of flexibility from different type and size of controllable energy resources. These flexible energy resources can be used in an aggregated manner to provide different ancillary services for the distribution and transmission network. In addition, flexible energy resources and renewable generation can be utilized in different kinds of energy communities and smart cities to benefit all stakeholders and society at the same time with future-proof market structures, new business models and management schemes enabling increased utilization of flexible energy resources. Many of the flexible energy resources and renewable-based generation units are also inverter-interfaced and therefore the authors present future power converter systems for energy sources as well as the latest age of multilevel converters. Full article

As oceans cover the majority of the earth’s surface, it becomes inevitable in extending the concepts of Internet of Things (IoT) to ocean bodies, thereby tiling the way for a new drift in the digital world, the Internet of Underwater Things (IoUT). The primary objective of IoUT is the creation of a network of several smart interconnected undersea things, to digitally link water bodies by using devices such as autonomous underwater vehicles. Since the traditional ideas of IoT cannot be merely expanded to underwater, due to the difference in environmental characteristics, this puts forward a variety of challenges for scientists to work with IoUT, and one such challenge is the network management with IoUT. This paper gives an overview on (1) underwater network management systems (U-NMS) using acoustic communication in IoUT; (2) the challenges and benefits and use cases of U-NMS; (3) fault, configuration, accounting, performance, security and constrained management (FCAPSC) functionalities of U-NMS and (4) a comparison between network management system in IoT and U-NMS system in IoUT. Additionally, this paper shows the prototype design and implementation setup of U-NMS in a laboratory environment, using lightweight machine to machine (LWM2M) and acoustic communication technology for IoUT. This paper will contribute much to the profit of researchers and industry players in uncovering the critical areas of the Internet of Underwater Things. Full article

A smart grid employs information and communications technology to improve the efficiency, reliability, economics, and sustainability of electricity production and distribution. The convergent and complex nature of a smart grid and the multifarious connection between its individual technology components, as well as competition between private companies, which will exert substantial influences on the future smart grid business, make a strategic approach necessary from the beginning of research and development (R&D) planning with collaborations among various research groups and from national, industry, company, and detailed technological levels. However, the strategic, technological, business environmental, and regulatory barriers between various stakeholders with collaborative or sometimes conflictive interests need to be clarified for a breakthrough in the smart grid field. A strategic R&D planning process was developed in this study to accomplish the complicated tasks, which comprises five steps: (i) background research of smart grid industry; (ii) selection of R&D target; (iii) societal, technological, economical, environmental, and political (STEEP) analysis to obtain a macro-level perspective and insight for achieving the selected R&D target; (iv) patent analysis to explore capabilities of the R&D target and to select the entry direction for smart grid industry; and, (v) nine windows and scenario planning analyses to develop a method and process in establishing a future strategic R&D plan. This R&D planning process was further applied to the case of a Korean company holding technological capabilities in the sustainable smart grid domain, as well as in the sustainable electric vehicle charging system, a global consumer market of smart grid. Four plausible scenarios were produced by varying key change agents for the results of this process, such as technology and growth rates, policies and government subsidies, and system standards of the smart grid charging system: Scenario 1, ‘The Stabilized Settlement of the Smart Grid Industry’; Scenario 2, ‘The Short-lived Blue Ocean of the Smart Grid Industry’; Scenario 3, ‘The Questionable Market of the Smart Grid’; and, Scenario 4, ‘The Stalemate of the Smart Grid Industry’. The R&D plan suggestions were arranged for each scenario and detailed ways to cope with dissonant situations were also implied for the company. In sum, in this case study, a future strategic R&D plan was suggested in regard to the electric vehicle charging technology business, which includes smart grid communication system, battery charging duration, service infrastructure, public charge station system, platform and module, wireless charging, data management system, and electric system solution. The strategic R&D planning process of this study can be applicable in various technologies and business fields, because of no inherent dependency on particular subject, like electric vehicle charging technology based on smart grid. Full article

In recent years, with the development of the marine industry, the ship navigation environment has become more complicated. Some artificial intelligence technologies, such as computer vision, can recognize, track and count sailing ships to ensure maritime security and facilitate management for Smart Ocean systems. Aiming at the scaling problem and boundary effect problem of traditional correlation filtering methods, we propose a self-selective correlation filtering method based on box regression (BRCF). The proposed method mainly includes: (1) A self-selective model with a negative samples mining method which effectively reduces the boundary effect in strengthening the classification ability of the classifier at the same time; (2) a bounding box regression method combined with a key points matching method for the scale prediction, leading to a fast and efficient calculation. The experimental results show that the proposed method can effectively deal with the problem of ship size changes and background interference. The success rates and precisions were over 8 % higher than Discriminative Scale Space Tracking (DSST) on the marine traffic dataset of our laboratory. In terms of processing speed, the proposed method is higher than DSST by nearly 22 frames per second (FPS). Full article

Nowadays, two-factor data security protection has become a research hotspot in smart ocean management. With the increasing popularity of smart ocean management, how to achieve the two-factor protection of public data resources in smart ocean management is a serious problem to be tackled. Furthermore, how to achieve both security and revocation is also a challenge for two-factor protection. In this paper, we propose a two-factor-based protection scheme with factor revocation in smart ocean management. The proposed scheme allows data owners (DOs) to send encrypted messages to users through a shipboard server (SS). The DOs are required to formulate access policy and perform attribute-based encryption on messages. In order to decrypt, the users need to possess two factors. The first factor is the user’s secret key. The second factor is security equipment, which is a sensor card in smart ocean system. The ciphertext can be decrypted if and only if the user gathers the key and the security equipment at the same time. What is more, once the security equipment is lost, the equipment can be revoked and a new one is redistributed to the users. The theoretical analysis and experiment results indeed indicate the security, efficiency, and practicality of our scheme. Full article