• Title/Summary/Keyword: Sensors

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Assessment of Validity and Reliability of Plantar Pressure in Smart Insole (스마트 인솔의 족저압 측정 결과에 대한 타당도 및 신뢰도 평가)

  • Kang, Ho Won;An, Yae Lynn;Kim, Dae-Yoo;Lee, Dong-Oh;Park, Gil Young;Lee, Dong Yeon
    • Journal of Korean Foot and Ankle Society
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    • v.26 no.3
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    • pp.130-135
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    • 2022
  • Purpose: Smart insoles are wearable devices that are inserted into shoes. Smart insoles with built-in pressure and acceleration sensors can measure the plantar pressure, stride length, and walking speed. This study evaluated the validity and reliability of the plantar pressure measurements of smart insoles during walking on flat ground. Materials and Methods: Twenty one subjects were included in this study. After wearing smart insoles, I-SOL® (Gilon, Seongnam, Korea), the subjects walked a 10 m corridor six times at a rate of 100 steps/min, and the middle three steps, free from direction changes, were chosen for data analysis. The same protocol was repeated after wearing Pedar-X (Novel Corporation, Munich, Germany), an insoletype plantar pressure measurement equipment with proven validity. The average maximum pressure (Ppeak, kPa) and the time at which Ppeak appeared (Ptime, %stride) were calculated for each device. The validity of smart insoles was evaluated by using the interclass correlation coefficient (ICC) of Ppeak and Ptime between the two instruments, and Cronbach's alpha was obtained from the Ppeak values to evaluate the reliability. Results: The ICC of Ppeak was 0.651 (good) in the hallux, 0.744 (good) in the medial forefoot, 0.839 (excellent) in the lateral forefoot, and 0.854 (excellent) in the hindfoot. The ICC of Ptime showed 0.868 (excellent) in the hallux, 0.892 (excellent) in the medial forefoot, 0.721 (good) in the lateral forefoot, and 0.832 (excellent) in the hindfoot. All ICC values showed good or excellent results. The Cronbach's alpha of Ppeak measured in the smart insoles was 0.990 in the hallux, 0.961 in the medial forefoot, 0.973 in the lateral forefoot, and 0.995 in the hindfoot; all indicated excellent reliability in all areas. Conclusion: The plantar pressure measurements of smart insoles during walking on a flat ground showed validity compared to Pedar-X, and high reliability after repeated measurements.

A Study on the Feasibility of Lead(II) Iodide and Gd2O2S:Tb Overlapping Sensors in Gamma Source Conditions using FLUKA Simulation (FLUKA 전산 모사를 통한 감마선원 조건에서의 요오드화납(II)과 Gd2O2S:Tb가 결합된 센서의 적용가능성 연구)

  • Yang, Seung-Woo;Park, Yoon-Hee;Park, Ji-Koon;Heo, Ye-Ji
    • Journal of the Korean Society of Radiology
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    • v.16 no.4
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    • pp.381-386
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    • 2022
  • Non-Destruction Test (NDT) is a method to check internal defects without destroying the product. Among them, radiographic testing (RT) uses high-energy radiation, so it is very important to prevent radiation exposure of workers. Therefore, in this study, in this study, a radiation sensor structure that improves radiation detection performance compared to the existing PbI2 and can immediately detect accidents in RT was presented. For evaluation, the conversion efficiency was analyzed in the gamma ray source through FLUKA simulation. PbI2 with overlapping Gd2O2S:Tb presented in this study showed a higher radiation sensitivity from 1.22 to 3.22 times than that of non-overlapping PbI2. This indicates that the presented sensor is suitable for use as a radiation sensor for source detection in RT.

A Study on Road Traffic Volume Survey Using Vehicle Specification DB (자동차 제원 DB를 활용한 도로교통량 조사방안 연구)

  • Ji min Kim;Dong seob Oh
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.2
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    • pp.93-104
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    • 2023
  • Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

Anomaly Detections Model of Aviation System by CNN (합성곱 신경망(CNN)을 활용한 항공 시스템의 이상 탐지 모델 연구)

  • Hyun-Jae Im;Tae-Rim Kim;Jong-Gyu Song;Bum-Su Kim
    • Journal of Aerospace System Engineering
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    • v.17 no.4
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    • pp.67-74
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    • 2023
  • Recently, Urban Aircraft Mobility (UAM) has been attracting attention as a transportation system of the future, and small drones also play a role in various industries. The failure of various types of aviation systems can lead to crashes, which can result in significant property damage or loss of life. In the defense industry, where aviation systems are widely used, the failure of aviation systems can lead to mission failure. Therefore, this study proposes an anomaly detection model using deep learning technology to detect anomalies in aviation systems to improve the reliability of development and production, and prevent accidents during operation. As training and evaluating data sets, current data from aviation systems in an extremely low-temperature environment was utilized, and a deep learning network was implemented using the convolutional neural network, which is a deep learning technique that is commonly used for image recognition. In an extremely low-temperature environment, various types of failure occurred in the system's internal sensors and components, and singular points in current data were observed. As a result of training and evaluating the model using current data in the case of system failure and normal, it was confirmed that the abnormality was detected with a recall of 98 % or more.

Development of an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model (앙상블 기반의 악취 농도 다지역 통합 예측 모델 개발)

  • Seong-Ju Cho;Woo-seok Choi;Sang-hyun Choi
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.383-400
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    • 2023
  • Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

An Efficient Routing Scheme based on Link Quality and Load Balancing for Wireless Sensor Networks (무선 센서 네트워크에서 링크 상태 및 트래픽 분산 정보를 이용한 효과적인 라우팅 방법)

  • Kim, Sun-Myeng;Yang, Yeon-Mo
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.11-19
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    • 2010
  • ZigBee is a standard for wireless personal area networks(WPANs) based on the IEEE 802.15.4 standard. It has been developed for low cost and low power consumption. There are two alternative routing schemes that have been proposed for the ZigBee standard: Ad-hoc On-Demand Distance Vector(AODV) and tree routing. The tree routing forwards packets from sensors to a sink node based on the parent-child relationships established by the IEEE 802.15.4 MAC topology formation procedure. In order to join the network, a sensor node chooses an existing node with the strongest RSSI(Received signal strength indicator) signal as a parent node. Therefore, some nodes carry a large amount of traffic load and exhaust their energy rapidly. To overcome this problem, we introduce a new metric based on link quality and traffic load for load balancing. Instead of the strength of RSSI, the proposed scheme uses the new metric to choose a parent node during the topology formation procedure. Extensive simulation results using TOSSIM(TinyOS mote SIMulator) show that the CFR scheme outperforms well in comparison to the conventional tree routing scheme.

A Study on Transport Robot for Autonomous Driving to a Destination Based on QR Code in an Indoor Environment (실내 환경에서 QR 코드 기반 목적지 자율주행을 위한 운반 로봇에 관한 연구)

  • Se-Jun Park
    • Journal of Platform Technology
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    • v.11 no.2
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    • pp.26-38
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    • 2023
  • This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

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Inferring Pedestrian Level of Service for Pathways through Electrodermal Activity Monitoring

  • Lee, Heejung;Hwang, Sungjoo
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1247-1248
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    • 2022
  • Due to rapid urbanization and population growth, it has become crucial to analyze the various volumes and characteristics of pedestrian pathways to understand the capacity and level of service (LOS) for pathways to promote a better walking environment. Different indicators have been developed to measure pedestrian volume. The pedestrian level of service (PLOS), tailored to analyze pedestrian pathways based on the concept of the LOS in transportation in the Highway Capacity Manual, has been widely used. PLOS is a measurement concept used to assess the quality of pedestrian facilities, from grade A (best condition) to grade F (worst condition), based on the flow rate, average speed, occupied space, and other parameters. Since the original PLOS approach has been criticized for producing idealistic results, several modified versions of PLOS have also been developed. One of these modified versions is perceived PLOS, which measures the LOS for pathways by considering pedestrians' awareness levels. However, this method relies on survey-based measurements, making it difficult to continuously deploy the technique to all the pathways. To measure PLOS more quantitatively and continuously, researchers have adopted computer vision technologies to automatically assess pedestrian flows and PLOS from CCTV videos. However, there are drawbacks even with this method because CCTVs cannot be installed everywhere, e.g., in alleyways. Recently, a technique to monitor bio-signals, such as electrodermal activity (EDA), through wearable sensors that can measure physiological responses to external stimuli (e.g., when another pedestrian passes), has gained popularity. It has the potential to continuously measure perceived PLOS. In their previous experiment, the authors of this study found that there were many significant EDA responses in crowded places when other pedestrians acting as external stimuli passed by. Therefore, we hypothesized that the EDA responses would be significantly higher in places where relatively more dynamic objects pass, i.e., in crowded areas with low PLOS levels (e.g., level F). To this end, the authors conducted an experiment to confirm the validity of EDA in inferring the perceived PLOS. The EDA of the subjects was measured and analyzed while watching both the real-world and virtually created videos with different pedestrian volumes in a laboratory environment. The results showed the possibility of inferring the amount of pedestrian volume on the pathways by measuring the physiological reactions of pedestrians. Through further validation, the research outcome is expected to be used for EDA-based continuous measurement of perceived PLOS at the alley level, which will facilitate modifying the existing walking environments, e.g., constructing pathways with appropriate effective width based on pedestrian volume. Future research will examine the validity of the integrated use of EDA and acceleration signals to increase the accuracy of inferring the perceived PLOS by capturing both physiological and behavioral reactions when walking in a crowded area.

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In-situ Calibration of Membrane Type Dissolved Oxygen Sensor for CTD (CTD용 박막형 용존산소 센서의 현장 교정)

  • DONG-JIN KANG;YESEUL KIM
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.28 no.1
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    • pp.41-50
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    • 2023
  • Dissolved oxygen sensors have characteristics in which data drift occurs over time. Therefore, in-situ calibration of the dissolved oxygen sensor is essential to accurately measure the concentration of dissolved oxygen in seawater. In order to provide a method for in-situ calibration, appropriate number of samples for calibration, and laboratory calibration interval of the dissolved oxygen sensor, the dissolved oxygen sensor values were compared with the measured values by titration on a total of 133 samples from three different cruises in the Indian Ocean, Pacific Ocean, and East Sea over a period of about one year. As a result, it is preferable to calibrate the sensor value using the correlation of a straight line obtained by directly comparing the final concentration value given by the sensor and the measured value. For the accurate calibration, at least 30 samples must be used to enable in-situ calibration within an accuracy range of about 1%. In addition, it is recommended that a laboratory calibration should perform within 1 year for the membrane type dissolved oxygen sensor for CTD to achieve a performance of 70% or more.

Design and Implementation of a Data-Driven Defect and Linearity Assessment Monitoring System for Electric Power Steering (전동식 파워 스티어링을 위한 데이터 기반 결함 및 선형성 평가 모니터링 시스템의 설계 구현)

  • Lawal Alabe Wale;Kimleang Kea;Youngsun Han;Tea-Kyung Kim
    • Journal of Internet of Things and Convergence
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    • v.9 no.2
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    • pp.61-69
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    • 2023
  • In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.