Search Results (24)

Common underwater target recognition systems suffer from low accuracy, high energy consumption, and low levels of automation. This paper introduces an underwater target recognition system based on the Jetson Xavier NX platform, which deploys an improved YOLOv11 recognition algorithm. During operation, the Jetson Xavier NX invokes an industrial camera to capture underwater target images, which are then processed by the improved YOLOv11 network for inference. The recognized information is transmitted via a serial port to an STM32 control board, which adaptively adjusts the lighting system to enhance image clarity based on the target information. Finally, the system controls an actuator to release a buoyant ball with positioning capabilities and communicates with the shore. On the ROUD dataset, the improved YOLOv11 algorithm achieves an accuracy of 87.5%, with a parameter size of 2.58M and a floating-point operation count of 6.3G, outperforming all current models. Compared to the original YOLOv11, the parameter size is reduced by 5% and the floating-point operation count by 0.3G. The improved DD-YOLOv11 also shows good performance on the URPC2020 dataset. After on-site experiments and hardware–software integration tests, all functions operate normally. The system is capable of identifying a specific underwater target with an accuracy rate of over 85%, simultaneously releasing communication buoys and successfully establishing communication with the shore base. This indicates that the underwater target recognition system meets the requirements of being lightweight, high-precision, and highly automated. Full article

An energy harvester scavenging the kinetic energy of fluctuating waves for supplying small sea monitoring buoys is studied and tested. The harvester exploits a magnetic cylinder that rolls on a track due to the pitching motion of the buoy. The electromagnetic coupling between the rolling magnet and pairs of coils placed along the track generates an electromotive force used to supply a DC load through a bridge rectifier. The considered harvester is characterized by low-cost, simplicity, lightness and efficiency. An analytical model of the harvester is presented to investigate its operating conditions and to predict its nonlinear dynamic behavior. The operating mode of the energy harvester named bang-bang is studied in depth as it allows maximizing the extracted power, and analytical equations that characterize the behavior of the harvester in this operating mode are deduced. A prototype of the energy harvester was built and tested in order to identify the model parameters and to validate the theoretical results. Full article

Melt pond is one of the most significant and important features of Arctic sea ice in the summer and can dramatically reduce the albedo of ice, promoting more energy into the upper ocean. The observation of the seasonal evolution of melt pond can improve our fundamental understanding of the role and sensitivity of sea ice in the context of global climate change. In this study, an ice-tethered observation system is developed for melt pond evolution with vision and temperature profile measurements. The system composition, structure of the ice-tethered buoy, freeze-resistant camera, and thermistor chain are analyzed. A sealed shell and electric heating wires are used to increase the temperature to around the camera in low-temperature environments. The ice thickness and depth of melt pond can be inverted using a specific interface recognition algorithm. A low-light image enhancement strategy is proposed to improve the quality of images under the low lighting conditions in polar regions. The proposed system was tested in the second reservoir of Fen River, Yellow River, from 15 January to 27 January 2021. An artificial freshwater pond was used as the location for thermistor chain deployment and observation. The differences in mean square error (MSE), peak signal-to-noise ratio (PSNR), and feature similarity index (FSIM) between the original and enhanced images indicate that the proposed algorithm is suitable for low-light image enhancement. The research on the ice-tethered observation system will provide a new framework and technical support for the seasonal observation for melt pond. Full article

The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectories. A neural network method was developed to predict the position of Argo buoys, improving target tracking and emergency support capabilities. Based on a deep learning framework using a Simple Recurrent Unit (SRU), a new Time–Space Feature Fusion Method based on an Attention Mechanism (TSFFAM) model was constructed. The TSFFAM mechanism can predict the target trajectory more accurately, avoiding the disadvantages of traditional Long Short-Term Memory (LSTM) models, which are time consuming and difficult to train. The TSFFAM model is able to better capture multi-scale ocean factors, leading to more accurate and efficient buoy trajectory predictions. In addition, it aims to shed light on the mechanism of the joint multi-element and multi-scale effects of laminar and surface currents on multi-scale ocean factors, thereby deepening our understanding of the multi-element and multi-scale interactions in different spatio-temporal regimes of the ocean. Experimental verification was conducted in the Pacific Ocean using buoy trajectory data, and the experimental results showed that the buoy trajectory prediction models proposed in this paper can achieve high prediction accuracy, with the TSFFAM model improving the accuracy rate by approximately 20%. This research holds significant practical value for the field of maritime studies, precise rescue operations, and efficient target tracking. Full article

Many progressive aquariums worldwide house various elasmobranch species as part of their commitment to conservation awareness and the long-term well-being of these creatures. These aquariums face the challenge of enabling these natural predators to live harmoniously with other fish without triggering natural predation. This research, conducted at Zoomarine Algarve in Southern Portugal, aimed to investigate the behaviour of three elasmobranch species (Carcharhinus melanopterus (1:1:0), Triaenodon obesus (1:0:0), and Pteroplatytrygon violacea (0:3:0)) when exposed to different feeding mechanisms. The goal was to provide them with opportunities for alternative predatory behaviours beyond their typical feeding techniques and to reduce the likelihood of natural predation. The study took place under controlled conditions within a community habitat. Four feeding methods (pole, short buoy, long buoy, and PVC) were tested during morning, afternoon, and evening periods, using five different prey species. The results shed light on which feeding method aligns best with each species’ distinct physiological standards and predatory tendencies and revealed their prey preferences. All three species interacted with all feeding methods, with P. violacea showing a strong preference for the pole method. T. obesus favoured bony fish, while C. melanopterus showed a preference for cephalopods. P. violacea interacted with all prey types but displayed no marked preference. These various feeding methods and prey options also function as environmental enrichment strategies, enhancing the complexity of the habitat and providing the animals with more choices and control, ultimately promoting their welfare in captivity. Full article

To investigate the diurnal variation in phytoplankton biomass and its regulating factors during the diurnal cycle, we conducted in situ observations in June 2018 at three buoy stations, including Douwei Buoy Station, Minjiang Estuary Buoy Station, and Huangqi Buoy Station on the western side of the Taiwan Strait. The calibration of buoy sensor data, including temperature, salinity, dissolved oxygen, pH, chlorophyll, and phycoerythrin, was conducted simultaneously. In addition, water sampling was conducted to measure chlorophyll a and phycoerythrin concentrations at hourly time intervals. The results showed that the 24 h cumulative chlorophyll a concentration order for the buoys was Minjiang Estuary (10.280 μg/L) > Huangqi (7.411 μg/L) > Douwei (4.124 μg/L). The Minjiang Estuary had a lower nighttime biomass proportion than Douwei and Huangqi. The diurnal variation in phytoplankton was jointly regulated by water masses, tides, and light. There were three response patterns, including the “light trumps tidal influences” pattern at Douwei, the “Low-tide, High-biomass” pattern at Minjiang Estuary, and the “High-tide, High-biomass” pattern at Huangqi. The prediction of algal blooms and hypoxia using buoy monitoring needs to be based on seasonal water mass background and tidal influence. Full article

Storm surges are natural events that influence the dispersion of sediment along coasts, leading to sudden morphological changes in the seabed. From this perspective, we focused our study on the analysis of measurements from a mobile X-band radar system to survey the sea state and the changes in the seabed depth during storm surges. This analysis was supported by additional information from Sentinel 2 satellite images, the Gorgona wave buoy, the San Giovanni alla Vena hydrometric station, and an echosounder survey. The survey period was from 26 to 28 February and 3 March 2020. During these days, the simultaneous occurrence of a storm surge and flooding of the Arno River was monitored. The analysis of the marine X-band radar mobile images determined the formation and dismantling of seabed shapes. An elongated shoal and a bar-like shape are visible on the right side of the Arno River in the radar image of 26 February and at the Arno mouth on that of 28 February, respectively. The radar image of 3 March shows, near the mouth of the Arno, a delta shape probably due to the deposition of sediment favoured by the interaction between the river flow and storm waves. X-band coastal radar is a detection system that improves the effectiveness and reliability of coastal monitoring because it has a high temporal and spatial resolution. It can be considered a valuable warning system to monitor the sea-bed depth changes in strategic sites, such as harbour areas, during sea storms. Moreover, this system, together with a satellite observing system, is a valid tool for shedding light on the environmental drivers that reshape coastal areas. Full article

Different fish species and different growth stages require different amounts of fish pellets. Excessive fish pellets increase the cost of aquaculture, and the leftover fish pellets sink to the bottom of the fish farm. This causes water pollution in the fish farm. Weather changes and providing too many or too little fish pellets affect the growth of the fish. In light of the abovementioned factors, this article uses the artificial intelligence of things (AIoT) precision feeding management system to improve an existing fish feeder. The AIoT precision feeding management system is placed on the water surface of the breeding pond to measure the water surface fluctuations in the area of fish pellet application. The buoy, with s built-in three-axis accelerometer, senses the water surface fluctuations when the fish are foraging. Then, through the wireless transmission module, the data are sent back to the receiver and control device of the fish feeder. When the fish feeder receives the signal, it judges the returned value to adjust the feeding time. Through this system, the intelligent feeding of fish can be achieved by adjusting the amount of fish pellets in order to reduce the cost of aquaculture. Full article

The 40+ years-long sea surface temperature (SST) dataset from 4 km Global Area Coverage (GAC) data of the Advanced Very High-Resolution Radiometers (AVHRR/2s and/3s) flown onboard ten NOAA satellites (N07/09/11/12/14/15/16/17/18/19) has been created under the NOAA AVHRR GAC SST Reanalysis 2 (RAN2) Project. The data were reprocessed with the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) enterprise SST system. Two SST products are reported in the full ~3000 km AVHRR swath: ‘subskin’ (highly sensitive to true skin SST, but debiased with respect to in situ SST) and ‘depth’ (a closer proxy for in situ data, but with reduced sensitivity). The reprocessing methodology aims at close consistency of satellite SSTs with in situ SSTs, in an optimal retrieval domain. Long-term orbital and calibration trends were compensated by daily recalculation of regression coefficients using matchups with drifters and tropical moored buoys (supplemented by ships for N07/09), collected within limited time windows centered at the processed day. The nighttime Sun impingements on the sensor black body were mitigated by correcting the L1b calibration coefficients. The Earth view pixels contaminated with a stray light were excluded. Massive cold SST outliers caused by volcanic aerosols following three major eruptions were filtered out by a modified, more conservative ACSPO clear-sky mask. The RAN2 SSTs are available in three formats: swath L2P (144 10-min granules per 24 h interval) and two 0.02° gridded (uncollated L3U, also 144 granules/24 h; and collated L3C, two global maps per 24 h, one for day and one for the night). This paper evaluates the RAN2 SST dataset, with a focus on the L3C product and compares it with two other available AVHRR GAC L3C SST datasets, NOAA Pathfinder v5.3 and ESA Climate Change Initiative v2.1. Among the three datasets, the RAN2 covers the global ocean more completely and shows reduced regional and temporal biases, improved stability and consistency between different satellites, and in situ SSTs. Full article

In the existing research on the intelligent navigation of ships, navigation route planning often regards light buoys as fixed obstructions. However, due to factors such as water ripples, the position of the buoys keeps periodically changing. If the buoys are set to a fixed range of avoidance areas in the process of ship navigation, it is easy to allow a collision between the ship and the light buoys. Therefore, based on historical motion trajectory data of the buoys, a SARIMA-based time-series prediction model is proposed to estimate the offset position of a given buoy in a specified time. Furthermore, the collision-free path planning approach is presented to dynamically recommend an accurate sailing path. The results of the simulation experiment show that this method can effectively deal with collisions of ships caused by the offset position of the light buoys during the navigation of the large and low-speed autonomous ships. Full article

The ocean has an abundant reserve of wave energy, which is considered to be a clean, widely distributed and inexhaustible resource. Triboelectric nanogenerators (TENGs) have been regarded as a reliable technology for harvesting wave energy due to its robustness and efficiency in scavenging random mechanical energy. In this study, a wave energy harvesting multi-tunnel TENG (MT-TENG) has been proposed, which could be integrated easily with ocean buoys. The MT-TENG consists of polytetrafluoroethylene (PTFE) balls and a multi-tunnel frame, which could convert wave energy into electrical energy. The multi-tunnel design also avoids possible mutual obstruction of the PFTE balls during the movement. Compared with the flat type structure, the multi-tunnel structure could enhance output performance obviously. With an agitation frequency of 2 Hz and vibration amplitude of 130 mm, the MT-TENG has a peak power density of 8.3 W/m³, which is five times that of the flat type structure TENG. By integrating with a life buoy and floating pipe line, the MT-TENG could harvest wave energy to light LEDs continuously, which could provide a new solution for maritime rescue and night offshore oil delivery warning. Full article

In the present work, a spar-buoy scaled model was designed and built through a “Lab-on-Sea” unit, equipped with an energy harvesting system. Such a system is based on deformable bands, which are loyal to the unit, to convert wave motion energy into electricity by means of piezo patch transducers. In a preliminary stage, the scaled model, suitable for tests in a controlled ripples-type wave motion channel, was tested in order to verify the “fixed-point” assumption in pitch and roll motions and, consequently, to optimize energy harvesting. A special type of structure was designed, numerically simulated, and experimentally verified. The proposed solution represents an advantageous compromise between the lightness of the used materials and the amount of recoverable energy. The energy, which was obtained from the piezo patch transducers during the simulations in the laboratory, was found to be enough to self-sustain the feasible on-board sensors and the remote data transmission system. Full article

There has been considerable modelling and wave basin validation of the multi-mode, multi-float, moored wave energy converter M4. The 6 float (2 power take off) (PTO) configuration is considered here with mooring from a buoy with light inextensible cables. Large mean mooring forces and very large peak or snap forces were measured in large waves while the rotational response about the hinges (for power take off in operational conditions) was predominantly linear. Modelling has been extended with elastic mooring cables connected directly to the base of the bow float and to the buoy. The experimental mean force is input to the linear diffraction/radiation model. The device response is effectively unchanged. The peak mooring force and tensions remain large with direct connection to the base of the bow float but are only slightly greater than the mean forces with elastic cables to the buoy, and an elastic hawser provides a further slight reduction. For the largest waves measured, the force was about 10% of the dry weight of the platform. The idealized efficient modelling may inform more detailed design while efficient methods for determining highly nonlinear mean forces remain to be established. Full article

The KM3NeT underwater neutrino telescope comprises thousands of optical modules forming 3D arrays to detect the Cherenkov light produced by particles generated after a neutrino interaction in the medium. The modules are arranged in detection units—vertical structures with 18 modules at different heights, anchored to the seabed and kept vertical by the buoyancy of the optical modules and a top buoy. The optical modules are, thus, subject to movements due to sea currents. For a correct reconstruction of events detected by the telescope, it is necessary to know the relative position and orientation of modules with 10 cm and a few degrees accuracy, respectively. For this, an Acoustic Positioning System with a piezoceramic transducer installed in each module and a long baseline of acoustic transmitters and receivers on the seabed are used. In addition, there is a system of compass and accelerometers inside the optical modules to determine their orientation. A model of mechanical equations is used to reconstruct the shape of the detection unit taking as input the information from the positioning/orientation sensors and using the sea current velocity and direction as free parameters. The mechanical equations take the buoyancy and the drag force of the elements of the detection unit into account. This work describes the full process that is implemented in KM3NeT to monitor the modules and the shape of the detection units from the measured position and orientation data. Full article

Water clarity is the most common indicator of water quality. The purpose of the study was to develop an instrument which can automatically measure water clarity in place of manual measurement by Secchi disk. The instrument is suspended by buoys at the water surface and uses solar energy to measure the light intensity of LED bulbs after passing through a water column; the result is then converted to Secchi depth by using a regression function. Measurement data are stored in a cloud server so that mobile users can access via an Internet connection. Three experiments were conducted to examine the instrument performance: (i) to ensure light intensity of the LED bulbs is strong enough to pass through the water column; (ii) to determine the regression relationship between the measured light intensity of the instrument and Secchi depth; and (iii) to evaluate the coefficient of variation (CV) of the measured water clarity when using our instrument and a conventional Secchi disk. Experiment results show that the measured values of light intensity are stable with the average CV = 5.25%. Moreover, although there are slight differences between the Secchi depth measured by our instrument and those measured by Secchi disk, the measurements by our instrument can efficiently replace the measurements by conventional Secchi disk, which can be affected by weather conditions as well as by human subjectivity. Full article