• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.6
• /
• pp.1849-1876
• /
• 2022

Wireless Sensor Network (WSN) is considered as an integral part of the Internet of Things (IoT) for collecting real-time data from the site having many applications in industry 4.0 and smart cities. The task of nodes is to sense the environment and send the relevant information over the internet. Though this task seems very straightforward but it is vulnerable to certain issues like energy consumption, delay, throughput, etc. To efficiently address these issues, this work develops a cross-layer model for the optimization between MAC and the Network layer of the OSI model for WSN. A high value of duty cycle for nodes is selected to control the delay and further enhances data transmission reliability. A node measurement prediction system based on the Kalman filter has been introduced, which uses the constraint based on covariance value to decide the scheduling scheme of the nodes. The concept of duty cycle for node scheduling is employed with a greedy data forwarding scheme. The proposed Duty Cycle-based Greedy Routing (DCGR) scheme aims to minimize the hop count, thereby mitigating the energy consumption rate. The proposed algorithm is tested using a real-world wastewater treatment dataset. The proposed method marks an 87.5% increase in the energy efficiency and reduction in the network latency by 61% when validated with other similar pre-existing schemes.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.827-838
• /
• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.53-62
• /
• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.858-861
• /
• 2011

Smart Society로 나아가는 핵심으로 손꼽히는 모바일의 급속한 확산은 교육, 교통, 경제뿐만 아니라 건강에도 큰 영향을 미치고 있다. 그동안 발전이 미진했던 u-Health 기술 및 시장 역시 모바일로 인해 새로운 서비스 모델을 제시함으로써 발전하고 있다. 본 논문은 제안하는 시스템은 u-Health 서비스 중 sensor를 이용하여 원격지 환자의 생체정보를 수집하고, 실시간으로 병원의 클라우드 서버에 전송하는 시스템에서 사용자 검증에 대하여 연구하였다. 여기서 사용자란 클라우드 서버에 접속하는 의사를 말하며, 환자의 생체정보를 보기 위하여 시스템 접속함에 있어 공인인증서나 기타 인증 시스템과 비교해 간편하고, 네트워크 트래픽이 적은 사용자 검증 시스템을 목표로 한다. 그리하여 QRcode를 3개 생성하고, 각 클라우드 서버에 분산 분배 후 서로 섞음으로써 기존의 QRcode와 전혀 다른 인증용 QRcode를 생성할 수 있었다. 이것을 3차원 인덱스를 통해 원본 사용자 QRcode와 대조함으로 사용자 검증 과정을 수행시킴으로써 절차를 간소화하고 네트워크 트래픽을 약 15% 감소시킬 수 있었다.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.221-222
• /
• 2023

The purpose of this study is to analyze the applicability and limitations of SPOT robots in the construction industry. The SPOT robot, which is being introduced to construction sites for smart construction with the progress of the 4th industrial revolution, is shaped like a four-legged dog and is equipped with various sensors for data collection and autonomous driving. In this study, hardware and software were analyzed, such as the size of the SPOT robot, mobility on slopes and heights, operating environment, and software functions that can collect data with a sensor weighing up to 14 kg. In addition, while the SPOT robot operates in a construction environment, performance such as stability, accuracy, signal connection distance, and obstacle avoidance are evaluated, and the applicability and limitations of the SPOT robot in the construction industry are analyzed. Based on this analysis, the purpose of this study is to evaluate when and how SPOT robots can be effectively used at construction sites, identify limitations, and derive contributions and improvements for the construction industry.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.4
• /
• pp.523-531
• /
• 2011

Many of the wells which were constructed to use ground water resource are abandoned and not managed efficiently after its use. And a variety of heavy metals and organic compounds are released from the abandoned wells and this can cause ground water pollution. Therefore in this paper implemented to monitor locational information drill holes and underground water sensing information on real time basis using u-GIS environment to combined ubiquitous sensor node and GIS technology to improve these problems. In addition, this system suggests using system by UML 2.0 by analyzing variety requirement of user and between system internal modules interaction and data flow. It provides graphical user interfaces (GUI) to system users to monitor water-well related property information and its managements for each water-well at remote site by variety platform by GIS map and web environment and mobile device based on smart phone.

• Smart Structures and Systems
• /
• v.7 no.2
• /
• pp.83-102
• /
• 2011

As a testbed for various structural health monitoring (SHM) technologies, a super-tall structure - the 610 m-tall Guangzhou Television and Sightseeing Tower (GTST) in southern China - is currently under construction. This study aims to explore state-of-the-art wireless sensing technologies for monitoring the ambient vibration of such a super-tall structure during construction. The very nature of wireless sensing frees the system from the need for extensive cabling and renders the system suitable for use on construction sites where conditions continuously change. On the other hand, unique technical hurdles exist when deploying wireless sensors in real-life structural monitoring applications. For example, the low-frequency and low-amplitude ambient vibration of the GTST poses significant challenges to sensor signal conditioning and digitization. Reliable wireless transmission over long distances is another technical challenge when utilized in such a super-tall structure. In this study, wireless sensing measurements are conducted at multiple heights of the GTST tower. Data transmission between a wireless sensing device installed at the upper levels of the tower and a base station located at the ground level (a distance that exceeds 443 m) is implemented. To verify the quality of the wireless measurements, the wireless data is compared with data collected by a conventional cable-based monitoring system. This preliminary study demonstrates that wireless sensing technologies have the capability of monitoring the low-amplitude and low-frequency ambient vibration of a super-tall and slender structure like the GTST.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.5
• /
• pp.113-118
• /
• 2021

The study is to provide safety to the occupants from smoke generated by fire occurring at midnight, and to provide a method for providing evacuation safety for a certain period of time even if the occupants are not aware of the fire. The goal of this study is to occur in small accommodation (floor area less than 1,000m²)It is to design a system that can provide ASET for more than 1 hour even if the occupant does not recognize the fire in late-night fire. The basic structure of the smoke-control system applicable to accommodation facilities was designed, and the expected effect was suggested when applied to small-scale domestic accommodation facilities through evacuation scenarios in accommodation facilities to which the system was applied.

• Journal of Information Technology Services
• /
• v.21 no.2
• /
• pp.97-107
• /
• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1275-1282
• /
• 2022

In this study, real-time character navigation using AR lens developed by Nreal is developed. Real-time character navigation is not possible with general marker-based AR because NPC characters must guide while moving in an unspecified space. To replace this, a markerless AR system was developed using Digital Twin technology. Existing markerless AR is operated based on hardware such as GPS, gyroscope, and magnetic sensor, so location accuracy is low and processing time in the system is long, resulting in low reliability in real-time AR environment. In order to solve this problem, using the SLAM technique to construct a space into a 3D object and to construct a markerless AR based on point location, AR can be implemented without any hardware intervention in a real-time AR environment. This real-time AR environment configuration made it possible to implement a navigation system using characters in tourist attractions such as Suncheon Bay Garden and Suncheon Drama Filming Site.