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.

This paper proposes a highly integrated triboelectric‐electromagnetic wave energy harvester (TEWEH) that can efficiently collect wide‐frequency wave energy and realize a self‐powered marine buoy. The innovative design of a permanent magnet‐polytetrafluoroethylene (PM‐PTFE) ball ensures high integration between the magnetic material forming the electromagnetic generator (EMG) and the dielectric material forming the triboelectric nanogenerator (TENG). In the condition of swinging (1 Hz and ±30°), the output of the TENG component can reach 230.25 V, 1.34 µA, and the average output of the EMG is 2.30 V, 10.43 mA. Remarkably, even at an extremely low frequency (0.2 Hz), the TEWEH maintains exceptional output. The output power density of the TENG component and EMG component reach 13.77 W m−3 and 148.24 W m−3, respectively, which are much higher than in previous work. The TEWEH can quickly charge the 330 µF capacitor to a certain voltage, and then light up navigation mark lights and power thermometers. A sealed TEWEH with circuits works as a self‐powered marine buoy that can transmit actual marine ambient temperatures to land. In conclusion, the TEWEH has broad application prospects in the field of wave energy harvesting and the self‐powered marine Internet of Things.

China is a central actor in Latin America. Between 2002 and 2020, total trade between the regions grew by almost eighteen times, from $18 billion to $318 billion. China is the main trading partner of Brazil, Chile, Peru, and Uruguay and the second-largest trading partner of several other countries. It has free trade agreements with Chile, Costa Rica, and Peru and in 2022 is negotiating one with Ecuador. Furthermore, between 2005 and 2020, Chinese banks gave more than $137 billion in loans to the region. Most of Latin America has joined China's Belt and Road Initiative (BRI), a global strategy centered on developing infrastructure projects around the world. Since the outbreak of COVID-19,

No abstract

The rational assessment of regional energy distribution provides a scientific basis for the selection and siting of power generation units. This study, which focused on the Bohai Sea, set 31 research coordinate points in the Bohai sea for assessing the potential/trends of wave energy flux (WEF). We applied a point-to-point time series prediction method which modelled the different geographical coordinate points separately. Subsequently, we evaluated the performance of three traditional machine learning methods and three automated machine learning methods. To estimate WEF, the best model was applied to each research coordinate points, respectively. Then, the WEF was calculated and predicted based on the data of MWP, SWH, and water depth. The results indicate that, for all coordinates in the Bohai Sea, the H2O-AutoML algorithm is superior to the other five algorithms. Gradient boosting machine (GBM), extreme gradient boosting (XGBoost), and stacked ensemble models yielded the best performance out of the H2O algorithms. The significant wave height (SWH), the mean wave period (MWP), and the WEF in the Bohai Sea tended to be concentrated in the center of the sea and dispersed in the nearshore areas. In the year 2000, 2010, 2020, and 2030, the maximum annual average WEF at each research coordinate in the Bohai Sea is around 1.5 kW/m, with a higher flux in autumn and winter. In summary, the results provide ocean parameter characterization for the design and deployment of wave energy harvesting devices. Moreover, the automated machine learning introduced herein has potential for use in more applications in ocean engineering.