• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.325-336
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• 2023

With the development of autonomous driving technology, the number of external contact sensors mounted on vehicles is increasing, and the importance is also rising. The vehicular ultrasonic sensor uses the LIN protocol in the form of a bus topology and reports a status message about its surroundings through the vehicle's internal network. Since ultrasonic sensors are vulnerable to various threats due to poor security protocols, physical testing on actual vehicle is needed. Therefore, this paper developed a LIN-CAN co-analysis testbed with a jig for location-specific distance test to examine the operational relation between LIN and CAN caused by ultrasonic sensors.

• Smart Structures and Systems
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• v.31 no.6
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• pp.561-571
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• 2023

Ensuring the safety of a structure necessitates that repairs are carried out based on accurate inspections and records of damage information. Traditional methods of recording damage rely on individual paper-based documents, making it challenging for inspectors to accurately record damage locations and track chronological changes. Recent research has suggested the adoption of building information modeling (BIM) to record detailed damage information; however, localizing damages on a BIM model can be time-consuming. To overcome this limitation, this study proposes a method to automatically localize damages on a BIM model in real-time, utilizing consecutive images and measurements from an inertial measurement unit in close proximity to damages. The proposed method employs a visual-inertial odometry algorithm to estimate the camera pose, detect damages, and compute the damage location in the coordinate of a prebuilt BIM model. The feasibility and effectiveness of the proposed method were validated through an experiment conducted on a campus building. Results revealed that the proposed method successfully localized damages on the BIM model in real-time, with a root mean square error of 6.6 cm.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.21-27
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• 2013

Construction safety is a predominant hindrance in in-situ workflow and considered an unresolved issue. Current methods used for safety optimization and prediction, with limited exceptions, are paper-based, thus error prone, as well as time and cost ineffective. In an attempt to exploit the potential of BIM for safety, the objective of the proposed methodology is to automatically predict hazardous on-site conditions related to the route that the dozers follow during the different phases of the project. For that purpose, safety routes used by construction equipment from an origin to multiple destinations are computed using video cameras and their cycle times are calculated. The cycle times and factors; including weather and light conditions, are considered to be independent and identically distributed random variables (iid); and simulated using the Arena software. The simulation clock is set to 100 to observe the minor changes occurring due to external parameters. The validation of this technology explores the capabilities of BIM combined with simulation for enhancing productivity and improving safety conditions a-priori. Preliminary results of 262 measurements indicate that the proposed methodology has the potential to predict with 87% the location of exclusion zones. Also, the cycle time is estimated with an accuracy of 89%.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.87-94
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• 2023

This study analyzed and identified various causes of caustic alarms of 163 fire detectors that occurred from January 2019 to December 2021 at domestic semiconductor manufacturing plants equipped with about 30,000 fire detectors, and proposed a new non-fire prevention cause investigation plan by applying the NFPA 921 scientific methodology. The results of the study are as follows. First, in terms of necessary recognition and problem definition, an analog detector and an integrated monitoring system were proposed to quickly determine the location and installation space information of the fire detector. Second, in order to prevent speculative causes and errors in various analyses in terms of data analysis and hypothesis establishment, non-fire reports were classified into five by factor and defined, and the causes of occurrence by factor were classified and proposed. Finally, in terms of hypothesis verification and final hypothesis selection, a non-fire prevention improvement termination process and a final hypothesis verification sheet were proposed to prevent the cause from causing re-error.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.1
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.71-78
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• 2024

In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.3
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• pp.331-339
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• 2024

Reliable and precise indoor localization is crucial for personal navigation, emergency rescue, and monitoring workers indoors. To use this technology in different applications, it is important to make it less dependent on infrastructure and to keep the error as small as possible. Fingerprinting stands out as a popular choice for indoor positioning because it leverages existing infrastructure and works with just a smartphone. However, its accuracy heavily relies on the quality of that infrastructure. For instance, having too few access points or beacons can greatly reduce its effectiveness. To reduce dependence on RF infrastructure, we have developed surface correlation (SC) using accumulated Received Signal Strength Indicator (RSSI) signals This approach constructs a user mask for radio map comparisons using an accumulated RSSI vector and the trajectory of the user, which is estimated through PDR. The location with the highest correlation is considered as the user's position after comparison. Through a simulation, the performance of short RSSI vector-based technology and SC is analyzed, and future directions for the development of SC are discussed.

• Journal of Ocean Engineering and Technology
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• v.38 no.4
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• pp.174-186
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• 2024

In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical characteristics of beaches. To address this, we designed scenarios at Chuam Beach to evaluate how factors such as the distance from the camera to GCPs, the number of GCPs, and the height of each point affect the DLT method. Accuracy was assessed by calculating the root mean square error of the distance errors between the actual GCP coordinates and the image coordinates for each setting. This analysis aims to propose an optimal GCP placement method. Our results show that placing GCPs within 200 m of the camera ensures high accuracy with few points, whereas positioning them at strategic heights enhances shoreline extraction. However, since only fixed cameras were used in this study, factors like varying heights, orientations, and resolutions could not be considered. Based on data from a single location, we propose an optimal method for GCP placement that takes into account distance, number, and height using the DLT method.

• Journal of Biomedical Engineering Research
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• v.22 no.5
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• pp.459-468
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• 2001

The Average Coordinate Referenee System (ACRS) method is developed to reduce experimental errors in human locomotion analysis. Experimentally measured kinematic data is used to conduct analysis in human modeling, and the model accuracy is directly related to the accuracy of the data. However. the accuracy is questionable due to skin movement. deformation of skeletal structure while in motion and limitations of commercial motion analysis system . In this study. the ACRS method is applied to an optically-tracked segment marker system. although it can be applied to many of the others as well. In the ACRS method, each marker can be treated independently. as the origin of a local coordinate system for its body segment. Errors, inherent in the experimental process. result in different values for the recovered Euler angles at each origin. By employing knowledge of an initial, calibrated segment reference frame, the Euler angles at each marker location can be averaged. minimizing the effect of the skin extension and rotation. Using the developed ACRS methodology the error is reduced when compared to the general Euler angle method commonly applied in motion analysis. If there is no error exist in the experimental gait data. the separation and Penetration distance of the femoraltibial joint using absolute coordinate system is supposed to be zero during one gait cycle. The separation and Penetration distance was ranged up to 18 mm using general Euler angle method and 12 mm using the developed ACRS.