• International journal of advanced smart convergence
• /
• 제7권4호
• /
• pp.174-184
• /
• 2018

The efficiency and safety of social-overhead capital (SOC) public infrastructures have become an eminent social concern. In this regard, a continuous structural health monitoring has been widely implemented to oversee the robustness of such public infrastructures for the safety of the public. This paper deals with the analysis of a distributed mobility management (DMM) support for wireless sensor network (WSN) based information transmission system. The partial DMM support separates the data and control plane infrastructures, wherein, the control plane is managed by a particular mobility management network entity, while the data plane is distributed by the mobility anchors. The system will be able to optimize the information transmission for a wireless structural health monitoring of SOC public infrastructures specifically designed for bridges, and thus, guarantees the safety of public commuters.

• 반도체디스플레이기술학회지
• /
• 제18권3호
• /
• pp.122-126
• /
• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• 한국전자통신학회논문지
• /
• 제6권6호
• /
• pp.987-991
• /
• 2011

본 논문에서는 인체의 운동 변화를 홈 네트워크 방식으로 측정하고 확인할 수 있는 헬스 케어 시스템을 구현하였다. 제안되는 시스템은 트레드밀 운동 또는 사이클 운동 자세에서, 그 운동의 변화에 따라 신호 전달 장치를 통하여 실시간으로 전달되는 생체 신호를 데이터 획득 장치를 통하여 얻고, 그 데이터를 분석 장치에서 논리적으로 분석하여 자세에 대한 평가를 할 수 있도록 구성하였다. 측정파라미터의 항목을 혈압(Blood Pressure), 온도(Temperature), 낙상(Fall Index), 무게분포도(WDI), 체질량지수(BMI) 등으로 함으로서 측정값을 통하여 신체적 변화정도를 확인하고, 신체의 상태를 평가할 수 있도록 감시 체제를 구성하였다.

• 한국멀티미디어학회논문지
• /
• 제19권12호
• /
• pp.1981-1991
• /
• 2016

In recent, the advancement of wearable devices and wireless body area networking technologies motivate researchers to pay attention to remote healthcare system for monitoring patients health and disease progression effectively. However, in order to implement a practical remote healthcare system, we must consider the security and privacy of patient's personal health information transmitted to healthcare servers through the network. Hence, in this paper, we propose a secure health data transmission protocol in remote healthcare monitoring system to protect patient's health information and prevent privacy from eavesdropping on the network. To achieve our security goals, we design an efficient secure protocol based on the identity-based cryptography with key evolution technique, and then confirm the superiority and the efficiency of the proposed protocol as compared with the existing protocol of Yang et al.

• 한국전자통신학회논문지
• /
• 제8권5호
• /
• pp.791-796
• /
• 2013

뇌파 건강관리 시스템의 태동은 산업과 연구분야에서 요즘 중요한 쟁점으로 여겨지고 있다. 실시간으로 간질병이나 뇌경색의 환자들의 의료응급서비스를 지원하기 위해서는 EEG신호 감지가 필수적이다. 이러한 시스템을 위하여 효과적인 네트워크를 지원하는 것이 필수적이기 때문에 센서노드 기반의 무선통신 토폴로지를 제안하며 시뮬레이트한다. 마지막으로 이러한 네트워크의 효과적인 토폴로지를 위하여 옵넷 시뮬레이터의 결과를 평가한다.

• 한국대기환경학회지
• /
• 제23권5호
• /
• pp.526-538
• /
• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• 센서학회지
• /
• 제21권5호
• /
• pp.352-358
• /
• 2012

A sensor network system can be an efficient tool for healthcare telemetry for multiple users due to its power efficiency. One drawback is its limited data size. This paper proposed a real-time application of data compression/decompression method in u-Health monitoring system in order to improve the network efficiency. Our high priority was given to maintain a high quality of signal reconstruction since it is important to receive undistorted waveform. Our method consisted of down sampling coding and differential Huffman coding. Down sampling was applied based on the Nyquist-Shannon sampling theorem and signal amplitude was taken into account to increase compression rate in the differential Huffman coding. Our method was successfully tested in a ZigBee and WLAN dual network. Electrocardiogram (ECG) had an average compression ratio of 3.99 : 1 with 0.24% percentage root mean square difference (PRD). Photoplethysmogram (PPG) showed an average CR of 37.99 : 1 with 0.16% PRD. Our method produced an outstanding PRD compared to other previous reports.

• Smart Structures and Systems
• /
• 제29권1호
• /
• 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.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1997년도 추계학술대회
• /
• pp.228-231
• /
• 1997

In this paper, we designed an ART(Adaptive Resonance Theory) network based on LPC(Linear Prediction Coefficient) for classification of PVB (Premature Ventricular Beat: PVC, LBBB, RBBB). The procedure of proposed system consists of the error calculation, feature generation and processing of the ART network. The error is calculated after processing by linear prediction algorithm and the features of ART network or classification are obtained from the binary ata determined by threshold method. In conclusion, ART network has good performance in classification of PVB.

• Journal of Information Technology Applications and Management
• /
• 제25권4호
• /
• pp.185-196
• /
• 2018

This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.