• 제목/요약/키워드: smart monitoring

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임베디드 시스템 기반 오버헤드 빈 내부 상황 실시간 식별 시스템 개발 (Development of the Embedded System-based Real-time Internal Status Identification System for Overhead Bin)

  • 김재은;임혜정;조성욱
    • 항공우주시스템공학회지
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    • 제17권2호
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    • pp.111-119
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    • 2023
  • 본 논문에서 제안하는 스토리지 박스의 내부 상황에 대한 실시간 식별 시스템은 오버헤드 빈의 내부 보관 상태, 무게 정보 및 무게 중심 계산 값을 시각화하는 시스템이다. 제안된 시스템은 로드 셀과 스위치 어레이를 사용하여 각 측정값을 동기화하고 시각적 센서를 통해 의미 있고 필요한 정보를 제공한다. 이 시스템은 C 언어 기반 임베디드 시스템으로 구축되며 1) 내부 가용공간 파악, 2) 무게중심 계산, 3) 실시간 시각 정보 제공이 주요 기능이다. 이러한 기능을 통해 스마트 오버헤드 빈을 개발하고, 향후 화물 적재 자동화 시스템 개발에 기여할 수 있는 실시간 화물 적재 모니터링 기술을 개발하였다.

An Adaptive Tuned Heave Plate (ATHP) for suppressing heave motion of floating platforms

  • Ruisheng Ma;Kaiming Bi;Haoran Zuo
    • Smart Structures and Systems
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    • 제31권3호
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    • pp.283-299
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    • 2023
  • Structural stability of floating platforms has long since been a crucial issue in the field of marine engineering. Excessive motions would not only deteriorate the operating conditions but also seriously impact the safety, service life, and production efficiency. In recent decades, several control devices have been proposed to reduce unwanted motions, and an attractive one is the tuned heave plate (THP). However, the THP system may reduce or even lose its effectiveness when it is mistuned due to the shift of dominant wave frequency. In the present study, a novel adaptive tuned heave plate (ATHP) is proposed based on inerter by adjusting its inertance, which allows to overcome the limitation of the conventional THP and realize adaptations to the dominant wave frequencies in real time. Specifically, the analytical model of a representative semisubmersible platform (SSP) equipped with an ATHP is created, and the equations of motion are formulated accordingly. Two optimization strategies (i.e., J1 and J2 optimizations) are developed to determine the optimum design parameters of ATHP. The control effectiveness of the optimized ATHP is then examined in the frequency domain by comparing to those without control and controlled by the conventional THP. Moreover, parametric analyses are systematically performed to evaluate the influences of the pre-specified frequency ratio, damping ratio, heave plate sizes, peak periods and wave heights on the performance of ATHP. Furthermore, a Simulink model is also developed to examine the control performance of ATHP in the time domain. It is demonstrated that the proposed ATHP could adaptively adjust the optimum inertance-to-mass ratio by tracking the dominant wave frequencies in real time, and the proposed system shows better control performance than the conventional THP.

Precision Agriculture using Internet of Thing with Artificial Intelligence: A Systematic Literature Review

  • Noureen Fatima;Kainat Fareed Memon;Zahid Hussain Khand;Sana Gul;Manisha Kumari;Ghulam Mujtaba Sheikh
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.155-164
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    • 2023
  • Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

Pipeline defect detection with depth identification using PZT array and time-reversal method

  • Yang Xu;Mingzhang Luo;Guofeng Du
    • Smart Structures and Systems
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    • 제32권4호
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    • pp.253-266
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    • 2023
  • The time-reversal method is employed to improve the ability of pipeline defect detection, and a new approach of identifying the pipeline defect depth is proposed in this research. When the L(0,2) mode ultrasonic guided wave excited through a lead zirconate titinate (PZT) transduce array propagates along the pipeline with a defect, it will interact with the defect and be partially converted to flexural F(n, m) modes and longitudinal L(0,1) mode. Using a receiving PZT array attached axisymmetrically around the pipeline, the L(0,2) reflection signal as well as the mode conversion signals at the defect are obtained. An appropriate rectangle window is used to intercept the L(0,2) reflection signal and the mode conversion signals from the obtained direct detection signals. The intercepted signals are time reversed and re-excited in the pipeline again, result in the guided wave energy focusing on the pipeline defect, the L(0,2) reflection and the L(0,1) mode conversion signals being enhanced to a higher level, especially for the small defect in the early crack stage. Besides the L(0,2) reflection signal, the L(0,1) mode conversion signal also contains useful pipeline defect information. It is possible to identify the pipeline defect depth by monitoring the variation trend of L(0,2) and L(0,1) reflection coefficients. The finite element method (FEM) simulation and experiment results are given in the paper, the enhancement of pipeline defect reflection signals by time-reversal method is obvious, and the way to identify pipeline defect depth is demonstrated to be effective.

PEI가 코팅된 CVD 그래핀의 저항 온도 계수 측정 (Measurements of the Temperature Coefficient of Resistance of CVD-Grown Graphene Coated with PEI)

  • 임수묵;석지원
    • Composites Research
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    • 제36권5호
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    • pp.342-348
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    • 2023
  • 최근 웨어러블 소자를 이용한 신체와 주변 온도의 실시간 모니터링에 대한 수요가 급격히 증가하고 있다. 그래핀 기반 써미스터가 고성능 유연 온도 센서로 개발되어 왔다. 본 연구에서는 단일층 그래핀의 온도 측정 성능을 개선하기 위하여 표면에 polyethylenimine(PEI)를 코팅하여 저항 온도 계수(TCR)를 조절하였다. 화학기상증착법(CVD)에 의해 합성한 단일층 그래핀은 습식 전사 공정을 통해 원하는 기판에 전사되었다. PEI에 의한 계면 도핑을 유도하기 위하여, 소수성의 그래핀 표면을 산소 플라즈마 처리를 통해 결함을 최소화하면서 친수성으로 제어하였다. PEI 도핑 효과를 전계효과트랜지스터(FET)를 이용하여 확인하였다. PEI 도핑에 의해서 CVD 그래핀의 TCR 값이 30~50℃의 온도 범위에서 -0.49(±0.03)%/K로 향상된 것을 확인하였다.

인공지능 기반 컨테이너 적재 안전관리 시스템 연구 (Research on Artificial Intelligence Based Shipping Container Loading Safety Management System)

  • 김상우;오세영;서용욱;연정흠;조희정;윤주상
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제12권9호
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    • pp.273-282
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    • 2023
  • 최근 스마트항만을 구축하기 위해 ICT 기술이 적용된 물류 자동화, 항만 운영 자동화 등 다양한 기술이 개발 중이다. 하지만 항만 안전과 안전사고를 예방하기 위한 기술 개발은 부족한 상황이다. 이에 본 논문에서는 항만 내 컨테이너 적재 공간에서 발생할 수 있는 안전사고를 예방하기 위한 인공지능 기반 컨테이너 적재 안전관리 시스템을 제안한다. 이 시스템은 인공지능 기반 컨테이너 안전사고 위험도 분류 및 저장 기능과 실시간 안전사고 모니터링 기능으로 구성되어 있다. 이 시스템은 실시간으로 현장의 사고 위험도를 모니터링하며 이를 통해 컨테이너 붕괴사고를 예방할 수 있다. 제안된 시스템은 프로토타입으로 개발되어 직접 항만에 적용하여 시스템을 평가하였다.

근활성도(EMG) 측정 전극 레이어 설계에 따른 성능 및 안정성 평가 (Performance and Stability Evaluation of Muscle Activation (EMG) Measurement Electrodes According to Layer Design)

  • 구본학;이동희;김주용
    • 감성과학
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    • 제26권4호
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    • pp.41-50
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    • 2023
  • 본 연구는 EMG(electromyography) 텍스타일 전극 개발을 목적으로 레이어 수의 디자인 및 원단을 다르게 하여 성능 및 신호 획득 안정성을 평가한다. 레이징 및 프레스 공정을 통하여 텍스타일 전극을 제조하며 Layer-0, Layer-1, Layer-2로 레이어 유무 및 수에 따른 결과를 분석했다. 이에 레이어 유무에 따라서는 근활성 측정에 영향을, 수가 많을수록 높은 성능이 나타남을 확인할 수 있었다. Layer-2 구조로 통일하여 5가지의 원단(네오프렌, 스판덱스 쿠션, 폴리에스테르 100%, 나일론 스판덱스, 광목 캔버스)으로 전극을 제조해 실험해 보았다. 성능적인 면에서, 원단의 중량이 높은 나일론 스판덱스가 높은 성능을 보였으며, 스판쿠션 텍스타일 전극이 근활성도 수득에 높은 안정성을 보였다. 이에 위 연구는 레이어에 따른 성능 연관성과 전극-피부사이의 닿는 면적 간의 관계 등을 고찰하여 슬리브 전체의 의복압을 늘리는 대신 특정 센서 측정 부위에만 높은 압력을 가함으로 차후 연구에서 레이어의 수 및 물성에 따른 전극의 공학적 설계 가능성을 제시한 의의가 있다.

Time-varying characteristics analysis of vehicle-bridge interaction system using an accurate time-frequency method

  • Tian-Li Huang;Lei Tang;Chen-Lu Zhan;Xu-Qiang Shang;Ning-Bo Wang;Wei-Xin Ren
    • Smart Structures and Systems
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    • 제33권2호
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    • pp.145-163
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    • 2024
  • The evaluation of dynamic characteristics of bridges under operational traffic loads is a crucial aspect of bridge structural health monitoring. In the vehicle-bridge interaction (VBI) system, the vibration responses of bridge exhibit time-varying characteristics. To address this issue, an accurate time-frequency analysis method that combines the autoregressive power spectrum based empirical wavelet transform (AR-EWT) and local maximum synchrosqueezing transform (LMSST) is proposed to identify the time-varying instantaneous frequencies (IFs) of the bridge in the VBI system. The AR-EWT method decomposes the vibration response of the bridge into mono-component signals. Then, LMSST is employed to identify the IFs of each mono-component signal. The AR-EWT combined with the LMSST method (AR-EWT+LMSST) can resolve the problem that LMSST cannot effectively identify the multi-component signals with weak amplitude components. The proposed AR-EWT+LMSST method is compared with some advanced time-frequency analysis techniques such as synchrosqueezing transform (SST), synchroextracting transform (SET), and LMSST. The results demonstrate that the proposed AR-EWT+LMSST method can improve the accuracy of identified IFs. The effectiveness and applicability of the proposed method are validated through a multi-component signal, a VBI numerical model with a four-degree-of-freedom half-car, and a VBI model experiment. The effect of vehicle characteristics, vehicle speed, and road surface roughness on the identified IFs of bridge are investigated.

Enhancing Transparency and Trust in Agrifood Supply Chains through Novel Blockchain-based Architecture

  • Sakthivel V;Prakash Periyaswamy;Jae-Woo Lee;Prabu P
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권7호
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    • pp.1968-1985
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    • 2024
  • At present, the world is witnessing a rapid change in all the fields of human civilization business interests and goals of all the sectors are changing very fast. Global changes are taking place quickly in all fields - manufacturing, service, agriculture, and external sectors. There are plenty of hurdles in the emerging technologies in agriculture in the modern days. While adopting such technologies as transparency and trust issues among stakeholders, there arises a pressurized necessity on food suppliers because it has to create sustainable systems not only addressing demand-supply disparities but also ensuring food authenticity. Recent studies have attempted to explore the potential of technologies like blockchain and practices for smart and sustainable agriculture. Besides, this well-researched work investigates how a scientific cum technological blockchain architecture addresses supply chain challenges in Precision Agriculture to take up challenges related to transparency traceability, and security. A robust registration phase, efficient authentication mechanisms, and optimized data management strategies are the key components of the proposed architecture. Through secured key exchange mechanisms and encryption techniques, client's identities are verified with inevitable complexity. The confluence of IoT and blockchain technologies that set up modern farms amplify control within supply chain networks. The practical manifestation of the researchers' novel blockchain architecture that has been executed on the Hyperledger network, exposes a clear validation using corroboration of concept. Through exhaustive experimental analyses that encompass, transaction confirmation time and scalability metrics, the proposed architecture not only demonstrates efficiency but also underscores its usability to meet the demands of contemporary Precision Agriculture systems. However, the scholarly paper based upon a comprehensive overview resolves a solution as a fruitful and impactful contribution to blockchain applications in agriculture supply chains.

Nonlinear intelligent control systems subjected to earthquakes by fuzzy tracking theory

  • Z.Y. Chen;Y.M. Meng;Ruei-Yuan Wang;Timothy Chen
    • Smart Structures and Systems
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    • 제33권4호
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    • pp.291-300
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    • 2024
  • Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.