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The wind energy industry has expanded in recent years. Promotion of the Sustainable Development Goals (SDGs) is expected to further increase the scale of the wind energy industry. Determining the location and quantity of wind turbines is crucial for monitoring the development status of the wind energy industry and evaluating wind energy production. In this study, we propose a method for simultaneously detecting and positioning wind turbines in remote sensing images, namely, Wind Turbine YOLO (WT-YOLO), based on the You Only Look Once version 5 model (YOLOv5). The wind turbine hub, base, and shadow hub are treated as key points in the proposed method. Regression terms are incorporated into the head of the YOLOv5 basic framework to predict the location of these three key points. The base point is utilized to determine the exact position of the wind turbine. A multibackground and multiresolution wind-turbine image dataset is constructed by sampling high-resolution images from Google Earth. The WT-YOLO method outperforms existing methods in both wind turbine detection and positioning on different types of land cover backgrounds and multiresolution images of the constructed dataset. In the spatial resolution range of 0.6 m to 5.4 m, WT-YOLO exhibits enhanced wind-turbine detection, where the average precision (AP) is 5.92 % to 15.43 % higher than that of existing wind-turbine detection methods. Wind-turbine positioning by WT-YOLO has a mean distance error (MDE) that is 16.06 m to 21.59 m lower than that of existing wind-turbine positioning methods. A comparative analysis showed that the shadow and the three key points are effective features for wind-turbine detection. The proposed WT-YOLO model can support detection, positioning and counting for wind turbines worldwide.

Abstract Organic retinomorphic sensors offer the advantage of in‐sensor processing to filter out redundant static backgrounds and are well suited for motion detection. To improve this promising structure, here, the key role of interfacial energetics in promoting charge accumulation to raise the inherent photoresponse of the light‐sensitive capacitor is studied. Specifically, incorporating appropriate interfacial layers around the photoactive layer is crucial to extend the carrier lifetime, as confirmed by intensity‐modulated photovoltage spectroscopy. Compared to its photodiode counterpart, the retinomorphic sensor shows better detectivity and response speed due to the additional insulating layer, which reduces the dark current and the RC time constant. Lastly, three retinomorphic sensors are integrated into a line array to demonstrate the detection of movement speed and direction, showing the potential of retinomorphic designs for efficient motion tracking.

A biomimetic strategy of combining soft actuators with an exoskeleton is applied to create untethered, self‐sustained robots with high load capacity, applicable for transportation in unsupervised environments. The soft actuation components are based on liquid crystal elastomers formed into functionally graded structures by extrusion printing, which enables a high free strain of 45.5%. The robot design includes a self‐sustained oscillation mechanism incorporating a novel, highly elastic spring for energy storage and impulse release. The arthropod‐inspired exoskeleton structures are printed from polycarbonate with high strength to increase the load‐carrying capacity, or to increase moving speed by a lever mechanism that amplifies the stepping distance up to eight times. The robot achieves self‐sustained locomotion, harvesting constant infrared radiation for continual power. Leveraging the strength of the exoskeleton and the high stress of the actuator, the robot transports a load 22 times its body weight. It is capable of climbing up a slope of 40° and moving up to a quarter of its body length per minute with peripheral lever legs. The robot operation does not require external signaling controls or complex electronics, demonstrating the potential of this battery‐free, scalable, environment‐powered design with an unlimited range free from tethering constraints.