Bo Liu^1,2, Li Feng^1,*, Yufeng Chen³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 845-862, 2024, DOI:10.32604/cmes.2024.047695

Abstract This paper focuses on the effective utilization of data augmentation techniques for 3D lidar point clouds to enhance the performance of neural network models. These point clouds, which represent spatial information through a collection of 3D coordinates, have found wide-ranging applications. Data augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization capabilities. Much of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point clouds. However, there has been a lack of focus on making the most of the numerous existing… More >

Chen Gu^1,*, Caiyu Wang¹, Mengjiao Du², Kan Yi², Bihong Zhu¹, Hao Wang², Shu Dai¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09776

Abstract Site measurement is essential to the meteorological and oceanographic parameters of offshore wind farms. A floating lidar measurement buoy was deployed at a Qingzhou VI wind farm where is 45-80 km away from Guangdong coast. The field observation including wind and wave data start from March, 2021.The lidar wind data is compared and calibrated with the fixed wind tower data for three months, the accuracy meets the standard of stadge3 carbon trust. In this study, all these data are used to recalibrate for the met-ocean model to relies extreme conditions, such as Typhoon Kompasu(2118) and Typhoon Chaba(2203) in recent years.… More >

Tareq Alhmiedat^1,2,*, Ashraf M. Marei^1,2, Saleh Albelwi^1,2, Anas Bushnag², Wassim Messoudi², Abdelrahman Osman Elfaki^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2321-2344, 2023, DOI:10.32604/cmes.2023.025641

Abstract Agricultural projects in different parts of the world depend on underground water wells. Recently, there have been many unfortunate incidents in which children have died in abandoned underground wells. Providing topographical information for these wells is a prerequisite to protecting people from the dangers of falling into them, especially since most of these wells become buried over time. Many solutions have been developed recently, most with the aim of exploring these well areas. However, these systems suffer from several limitations, including high complexity, large size, or inefficiency. This paper focuses on the development of a smart exploration unit that is… More >

Dahyeon Kim¹, Jiyoung Min¹, Yongwoo Song¹, Chulsu Kim², Junho Ahn^1,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2315-2331, 2023, DOI:10.32604/iasc.2023.034394

Abstract Existing firefighting robots are focused on simple storage or fire suppression outside buildings rather than detection or recognition. Utilizing a large number of robots using expensive equipment is challenging. This study aims to increase the efficiency of search and rescue operations and the safety of firefighters by detecting and identifying the disaster site by recognizing collapsed areas, obstacles, and rescuers on-site. A fusion algorithm combining a camera and three-dimension light detection and ranging (3D LiDAR) is proposed to detect and localize the interiors of disaster sites. The algorithm detects obstacles by analyzing floor segmentation and edge patterns using a mask… More >

Dahyeon Kim, Junho Ahn^*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1657-1671, 2023, DOI:10.32604/cmc.2023.029216

Abstract When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire, they use old architectural drawings or a simple monitoring method involving a video device attached to a robot. However, using these methods, the disaster situation inside a building at risk of collapse is difficult to detect and identify. Therefore, we investigate the generation of digital maps for a disaster site to accurately analyze internal situations. In this study, a robot combined with a low-cost camera and two-dimensional light detection and ranging (2D-lidar) traverses across a floor to estimate the location… More >

Zhengshu Zhou^1,*, Shunya Yamada², Yousuke Watanabe², Hiroaki Takada^1,2

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2109-2127, 2023, DOI:10.32604/csse.2023.029005

Abstract Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians’ sudden appearance in the vehicle’s path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision… More >

Qinghai Li¹, Ziyi Zhao², Hao Wu^1,*, Xiaoyu Li^3,*, Qinsheng Zhu¹, Shan Yang⁴

Journal of Quantum Computing, Vol.3, No.1, pp. 35-43, 2021, DOI:10.32604/jqc.2021.016634

Abstract In the detection process of classic radars such as radar/lidar, the detection performance will be weakened due to the presence of background noise and loss. The quantum illumination protocol can use the spatial correlation between photon pairs to improve image quality and enhance radar detection performance, even in the presence of loss and noise. Based on this quantum illumination LIDAR, a theoretic scheme is developed for the detection and tracking of moving targets, and the trajectory of the object is analyzed. Illuminated by the quantum light source as Spontaneous Parametric Down-Conversion (SPDC), an opaque target can be identified from the… More >

Uuganbayar Gankhuyag, Ji-Hyeong Han^*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 133-152, 2021, DOI:10.32604/iasc.2021.015227

Abstract The automated reconstruction of building information modeling (BIM) objects from unstructured point cloud data for indoor as-built modeling is still a challenging task and the subject of much ongoing research. The most important part of the process is to detect the wall geometry clearly. A popular method is first to segment and classify point clouds, after which the identified segments should be clustered according to their corresponding objects, such as walls and clutter. To perform this process, a major problem is low-quality point clouds that are noisy, cluttered and that contain missing parts in the data. Moreover, the size of… More >

Cang Peng¹, Yu Zhenglin²

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 827-835, 2019, DOI:10.31209/2019.100000086

Abstract The assembly error of the supporting component in Mobile Lidar has an inevitable influence on the positioning accuracy and the system error. In this paper, we applied the multi-body system kinematics principle and the homogeneous coordinate transformation to infer the final pointing error formula which influences the three-axis error model of the Mobile Lidar. The influence of each error item on the positioning accuracy (pointing accuracy) of radar system is analyzed by computer simulation, and the motion law between each axis of radar supporting component is discussed, which has laid the base for researching the positioning accuracy of Mobile Lidar. More >