• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.777-785
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• 2021

Many utility lines are buried underground to provide various functions of the city. Because historical records are not managed systematically, damage has occurred during excavation. In addition, the demand for an underground facility management system is increasing as the aerial underground project is progressing. By attaching an electronic recognition sensor to an underground facility, such as pipelines, the management history and site conditions can be carefully managed. Therefore, in this study, electronic recognition sensors, such as BLE Beacon, UHF RFID, geomagnetic sensor, and commercial marker, were tested to analyze the strengths, weaknesses, and field applicability through a pilot project. According to the limited research results collected through two pilot projects, the installation depth is most important to demonstrate the performance of the electronic reader. In addition, because it should be used in urban areas, the influence of environmental interference should be minimized, and there should be no performance degradation over time. In the case of the geomagnetic recognizer, the effect of environmental interference was large, and performance degradation occurred over time using the BLE Beacon. In the field situation, where the installation depth can be controlled to less than 40cm, the utility of the battery-free UHF RFID was the best.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.331-337
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• 2022

Raman spectroscopy is an optical technique that can identify molecules in a label-free manner, and is therefore heavily investigated in various areas ranging from biomedical engineering to materials science. Probe-based Raman spectroscopy can perform minimally invasive chemical analysis, and thus has potential as a real-time diagnostic tool during surgery. In this study, Raman experimentation was calibrated by examining the Raman shifts with respect to the concentrations of chemical substances. Raman signal characteristics, targeted for normal mice and cerebral tissues of the 5xFAD dementia mutant model with accumulated amyloid beta plaques, were measured and analyzed to explore the possibility of diagnosis of Alzheimer's disease. The application to the diagnosis of dementia was cross-validated by measuring Raman signals of amyloid beta. The results suggest the potential of Raman spectroscopy as a diagnostic tool that may be useful in various areas of application.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.409-414
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• 2021

In order to acquire an image from a gamma camera, linearity correction must be performed. To this end, digital coordinates are acquired by using a linearity map to accurately specify the location where the scintillator and gamma rays interact. In this study, a method for acquiring undistorted images and digital coordinates was developed using a lookup table and maximum likelihood position estimation without using a linearity map. The proposed method was verified by configuring a small gamma camera through DETECT2000 simulation. A gamma camera was constructed using a GAGG scintillator and a SiPM optical sensor, and a gamma-ray interaction was generated at the center of the scintillator, and a lookup table was prepared using the ratio of the signals obtained from the SiPM. Through the prepared lookup table and the maximum likelihood position estimation, the position of the signal obtained by the gamma-ray interaction was acquired as digital coordinates to compose an image. As a result, the linearity was maintained compared to the generally acquired image, the accuracy of the location where the gamma-ray interaction was generated was excellent, and the distance between the locations was uniform. Since the lookup table obtained through simulation is created using the ratio of the signal, it can be directly used in the experiment, and the position of the signal can be conveniently obtained with digital coordinates with corrected linearity without creating a linearity map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.587-598
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• 2021

This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.101-115
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• 2022

This study compared the performance of LiDAR in detecting objects in rough weather with that in clear weather. An experiment that reproduced rough weather divided the fog visibility into four stages from 200 m to 50 m and controlled the rainfall by dividing it into 20 mm/h and 50 mm/h. The number of points cloud and intensity were used as the performance indicators. The difference in performance was statistically investigated by a T-Test. The result of the study indicates that the performance of LiDAR decreased in the order in situations of 20 mm/h rainfall, fog visibility less than 200 m, 50 mm/h rainfall, fog visibility less than 150 m, fog visibility less than 100 m, and fog visibility less than 50 m. The decreased performance was greater when the measurement distance was greater and when the color was black rather than white. However, in the case of white, there was no difference in performance at a measurement distance of 10 m even at 50 m fog visibility, which is considered the worst situation in this experiment. This no difference in performance was also statistically significant. These performance verification results are expected to be utilized in the manufacture of road facilities in the future that improve the visibility of sensors.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.