• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.11-21
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• 2022

We have investigated the optimal design of an aperiodic optical phased array (OPA) for use in light detection and ranging applications. Three optimization algorithms - particle-swarm optimization (PSO), a genetic algorithm (GA), and a pattern-search algorithm (PSA) - were employed to obtain the optimal arrangement of optical antennas comprising an OPA. The optimization was performed to obtain the minimal side-lobe level (SLL) of an aperiodic OPA at each steering angle, using the three optimization algorithms. It was found that PSO and GA exhibited similar results for the SLL of the optimized OPA, while the SLL obtained by PSA showed somewhat different features from those obtained by PSO and GA. For an OPA optimized at a steering angle <45°, the SLL value averaged over all steering angles increased as the angle of optimization decreased. However, when the angle of optimization was larger than 45°, low average SLL values of <13 dB were obtained for all three optimization algorithms. This implies that an OPA with high signal quality can be obtained when the arrangement of the optical antennas is optimized at a large steering angle.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.23-29
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• 2023

For given the importance of elementary school students developing the ability to solve problems using artificial intelligence (AI), problem-solving abilities should be developed using AI along with education to develop problem-solving abilities. Such students need a form that allows them to understand the concepts and principles of AI and to be easily educated in a fun way to understand basic understanding of how AI works. To this end, this study planned an 8-hour AI convergence program and operated based on self-driving cars, demonstrating that it was effective in improving elementary school students' problem-solving abilities, creativity, and AI understanding. As a result of operating the camp, students' understanding of AI was 3.56 (standard deviation 0.85), 4.00 (standard deviation 0.71), and t-value was -5.412 (p<0.001), indicating statistically improved understanding of AI, and high satisfaction and interest of students. In the future, it will be necessary to develop an educational program that allows elementary school students to devise their own ideas and create products to which AI models can be applied.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.335-343
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• 2024

Real-time target signal processing techniques for FMCW LiDAR are described in this paper. FMCW LiDAR is gaining attention as the next-generation LiDAR for self-driving cars because of its detection robustness even in adverse environmental conditions such as rain, snow and fog etc. in addition to its long range measurement capability. The hardware architecture which is required for high-speed data acquisition, data transfer, and parallel signal processing for frequency-domain signal processing is described in this article. Fourier transformation of the acquired time-domain signal is implemented on FPGA in real time. The paper also details the C-FAR algorithm for ensuring robust target detection from the transformed target spectrum. This paper elaborates on enhancing frequency measurement resolution from the target spectrum and converting them into range and velocity data. The 3D image was generated and displayed using the 2D scanner position and target distance data. Real-time target signal processing and high-resolution image acquisition capability of FMCW LiDAR by using the proposed parallel signal processing algorithms based on FPGA architecture are verified in this paper.

• Journal of Adhesion and Interface
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• v.24 no.3
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• pp.95-99
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• 2023

In this study, LiDAR-detectable black materials are synthesized by coating and reduction of titanium dioxide onto plate-type natural mica, which evaluated practical LiDAR verification. In detail, black TiO₂@Mica materials are fabricated by utilizing a sol-gel reaction to coat titanium dioxide onto natural mica, followed by reduction using sodium tetrahydridoborate. Subsequently, Black TiO₂@Mica materials are dispersed in hydrophilic transparent varnish and sprayed onto the glass substrate to assess applicability as paints. As a result, Black TiO₂@Mica-based paints exhibit true blackness (L^*=12.1) and a higher NIR reflectance (30.2 R%). In addition, it was confirmed that as-synthesized Black TiO₂@Mica materials are successfully recognized by a LiDAR sensor. This phenomenon is attributed to Fresnel's reflection law, in which light reflection occurs at the interface between natural mica and titanium dioxide with different refractive indices. In this regard, the findings of the study are expected to contribute to the potential utilization of LiDAR-detectable materials in various fields such as autonomous vehicles, robotics, and drones.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.1
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• pp.39-47
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• 2024

In this study, LiDAR-detective black material is synthesized by recycling silicon sludge (SS) that is generated from semiconductor manufacturing process, and its recognition is confirmed using two types of LiDAR sensors (MEMS and Rotating LiDAR). In detail, metal impurities on the surface of SS is removed, followed by coating of titanium dioxide (TiO₂) and subsequent chemical reduction to obtain SS-derived black TiO₂ (SS/bTiO₂) material. As-prepared SS/bTiO₂ is mixed with transparent paint to prepare hydrophilic black paints and applied to a glass substrate using a spray gun. SS/bTiO₂-based paint shows similar blackness (L^*=15.7) compared to commercial carbon black-based paint, and remarkable NIR reflectance (26.5R%, 905nm). Furthermore, MEMS and Rotating LiDAR have successfully detected the SS/bTiO₂-based paint. This is attributed to the occurrence of high reflection of light at the interface between the black TiO₂ and the silicon sludge according to the Fresnel's reflection principle. Hence, the new application field to effectively recycle silicon sludge generated in the semiconductor manufacturing process has been presented.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.54-69
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• 2021

In 2020, civilized society's overall lifestyle showed a distinct change from consumable analog media, such as paper, to digital media with the increased penetration of cloud computing, and from wired media to wireless media. Based on these social changes, this work examines whether the use of computer media in the field of landscape architecture is appropriately applied. This study will give directions for new computer media classes in landscape architectural education in the 4th Industrial Revolution era. Landscape architecture is a field that directly proposes the realization of a positive lifestyle and the creation of a living environment and is closely connected with social change. However, there is no clear evidence that landscape architectural education is making any visible change, while the digital infrastructure of the 4th Industrial Revolution, such as Artificial Intelligence (AI), Big Data, autonomous vehicles, cloud networks, and the Internet of Things, is changing the contemporary society in terms of technology, culture, and economy among other aspects. Therefore, it is necessary to review the current state of the use of computer technology and media in landscape architectural education, and also to examine the alternative direction of the curriculum for the new digital era. First, the basis for discussion was made by studying the trends of computational design in modern landscape architecture. Next, the changes and current status of computer media classes in domestic and overseas landscape education were analyzed based on prior research and curriculum. As a result, the number and the types of computer media classes increased significantly between the study in 1994 and the current situation in 2020 in the foreign landscape department, whereas there were no obvious changes in the domestic landscape department. This shows that the domestic landscape education is passively coping with the changes in the digital era. Lastly, based on the discussions, this study examined alternatives to the new curriculum that landscape architecture department should pursue in a new degital world.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.815-825
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• 2017

Visibility of lane marking is impaired at night or in the rain, which thereby threatens traffic safety. Recently, various studies and technologies have been developed to improve lane marking visibility, such as the extension of lane marking life expectancy (up to 1.5 times), improvement of lane marking equipment productivity, improvement of lane marking visibility by applying phosphorescent material mixed paint. Cost-benefit analysis was performed with considering various benefit items that can be expected. About 45% of traffic accidents would be prevented by improving lane marking visibility. Additionally, accident reduction benefit and traffic congestion reduction benefit were calculated as much as 246 billion KRW per year and 12 billion KRW per year, respectively, by reducing repaint cycle due to enhanced durability. 45 billion KRW per year is expected to reduced with improved lane detection performance of autonomous vehicle. Meanwhile, total increased cost when introducing phosphorescent material mixed paint to 91,195km of nationwide road is identified as 1922 billion KRW per year. However, economic feasibility could not be secured with 0.16 of cost-benefit ratio when applied to the road network as a whole. In case of "Accident Hot Spot" analyzing section window (400m), one or more fatality or two or more injured (one or more injured in case of less than 2 lanes per direction) per year were caused by pavement marking related accident, economic feasibility was secured. In detail, 3.91 of cost-benefit ratio is estimated with comparison of the installation cost for 5,697 of accident hot spot and accident reduction benefit. Some limitations and future research agenda have also been discussed.