• Title/Summary/Keyword: intelligent electronic monitoring system

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Intelligent Electronic Nose System for Detection of VOCs in Exhaled Breath

  • Byun, Hyung-Gi;Yu, Joon-Bu
    • Journal of Sensor Science and Technology
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    • v.28 no.1
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    • pp.7-12
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    • 2019
  • Significant progress has been made recently in detection of highly sensitive volatile organic compounds (VOCs) using chemical sensors. Combined with the progress in design of micro sensors array and electronic nose systems, these advances enable new applications for detection of extremely low concentrations of breath-related VOCs. State of the art detection technology in turn enables commercial sensor systems for health care applications, with high detection sensitivity and small size, weight and power consumption characteristics. We have been developing an intelligent electronic nose system for detection of VOCs for healthcare breath analysis applications. This paper reviews our contribution to monitoring of respiratory diseases and to diabetic monitoring using an intelligent electronic nose system for detection of low concentration VOCs using breath analysis techniques.

Intelligent Diagnosis System for an Electronic Weighting Machine (전자 저울을 위한 지능형 고장 진단 시스템)

  • 김종원;김영구;조현찬;서화일;김두용;이병수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.78-82
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    • 2001
  • Electronic Weighting Machine is used an electronic scale which has many trouble because of broken load cells. In this paper, we propose an intelligent Diagnosis System will for an electronic weighting machine using fuzzy logic. It's purpose be detect of the load cell's trouble. The electronic circuit of system, which call 'junction box', will be connected resistances in a series at circuit of Wheatstone Bridge for monitoring the condition of load cells.

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Observer-Based On-Line Overload Monitoring System of PMSM (상태관측기를 이용한 PMSM의 On-Line 과부하 모니터링 시스템)

  • Jang, Ki-Chan;Suh, Suhk-Hoon;Woo, Kwang-Joon
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.268-271
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    • 2001
  • This paper presents observer-based on-line overload monitoring scheme for a PMSM(Permanent Magnet Synchronous Motor) drive system. Proposed scheme is to monitor overload status of motor drive system at remote place. The drive system is previously installed on main system and has no communication function. Proposed scheme consists of intelligent sensing head and monitoring part. Intelligent sensing head acquire motor 3-Phase currents and transmit data to monitoring part over serial communication interface. Monitoring part estimates motor speed using state observer. By comparing estimated speed with reference speed, we can detect motor fault. In this scheme observed information must coded and transmitted over a digital communication channel with finite capacity. We consider communication constraint as time delay and we design discrete-time observer. The proposed scheme is tested on the actual drive system.

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A study on Introducing Intelligent Electronic Monitoring System through the Analysis of the Electronic Supervision (전자감독제도의 실태분석을 통한 지능형 전자발찌 도입 방안)

  • Cha, Minkyu;Kim, Donghee;Kim, Taehwan;Kwak, Daekyung
    • Journal of the Society of Disaster Information
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    • v.10 no.3
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    • pp.374-387
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    • 2014
  • Since the sexual violence crime has a high probability of repeated crime, the electronic monitoring system has been introduced as a measure to it. And this system allows the police to know the location of former criminal around the clock through the electronic device, the former criminal has the psychological/mental oppression which can restrain the intention of crime to a degree. However, there is a limit in blocking criminals with strong will from repeated crime. The next-generation intelligent electronic anklet currently under study collects and analyzes the change bio-data in real time through the location information of electronic monitoring target and attached sensor. This study is aimed to predict the symptom of crime occurrence in advance based on this and block the crime intention in advance or stop the ongoing crime before it is expanded.

Electric Load Signature Analysis for Home Energy Monitoring System

  • Lu-Lulu, Lu-Lulu;Park, Sung-Wook;Wang, Bo-Hyeun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.3
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    • pp.193-197
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    • 2012
  • This paper focuses on identifying which appliance is currently operating by analyzing electrical load signature for home energy monitoring system. The identification framework is comprised of three steps. Firstly, specific appliance features, or signatures, were chosen, which are DC (Duty Cycle), SO (Slope of On-state), VO (Variance of On-state), and ZC (Zero Crossing) by reviewing observations of appliances from 13 houses for 3 days. Five appliances of electrical rice cooker, kimchi-refrigerator, PC, refrigerator, and TV were chosen for the identification with high penetration rate and total operation-time in Korea. Secondly, K-NN and Naive Bayesian classifiers, which are commonly used in many applications, are employed to estimate from which appliance the signatures are obtained. Lastly, one of candidates is selected as final identification result by majority voting. The proposed identification frame showed identification success rate of 94.23%.

The Embedded Remote Monitoring Diagnosis for Integration Vessel System (디지털 선박 추진 시스템을 위한 임베디드 원격 모니터링 진단)

  • Park, Se-Hyun;Noh, Seok-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.11
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    • pp.2708-2716
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    • 2013
  • This paper presents implementation of embedded remote monitoring diagnosis system which has effective wireless channel structure and communication protocols with user-friendly UI for intelligent digital vessel. Developed system contains integrated vessel monitoring system, server, exclusive mobile terminal and smart phone. We designed an effective dual structure communication channel and simple but effective communication protocol on the monitoring system. Failures of the wireless communication are minimized and the wrong wireless communication channel is immediately replaced. In addition, we developed an effective embedded Linux UI for LCD. The implemented wireless monitoring system was tested and verified on digital vessel.

Intelligent Diagnosis System for an Electronic Weighting Machine (전자 저울을 위한 지능형 고장 진단 시스템)

  • 김종원;김영구;조현찬;서화일;김두영;이병수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.807-810
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    • 2001
  • Election Weighting Machine is used an electronic scale which has many trouble because of broken load cells. In this paper, we propose an Intelligent Diagnosis System will for an electronic weighting machine using fuzzy logic. It s purpose be detect of the load cell s trouble. The electronic circuit of system, which call junction box , will be connected resistance in a series at circuit of Wheatstone Bridge for monitoring the condition of load cells.

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Smart Home Network System Using the Broadband Power Line Communication(BPLC) (광대역 전력선 통신을 이용한 스마트 홈 네트워크 구성에 관한 연구)

  • Yang Hyun-Chang;Sim Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.87-90
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    • 2005
  • The Intelligent Home provides convenient and comfortable living environment by performing automatic control, heating and air-conditioning, ventilation, home appliances control, home robot control, energy management, visitor management security management, internet, heath state monitoring, etc. through wired/ wireless network and device in the household. Along with the presentation of the features of economical broadband power line communication in the network configuration for new and old houses, its improvement method is proposed.

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Design of a MEMS sensor array for dam subsidence monitoring based on dual-sensor cooperative measurements

  • Tao, Tao;Yang, Jianfeng;Wei, Wei;Wozniak, Marcin;Scherer, Rafal;Damasevicius, Robertas
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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    • pp.3554-3570
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    • 2021
  • With the rapid development of the Chinese water project, the safety monitoring of dams is urgently needed. Many drawbacks exist in dams, such as high monitoring costs, a limited equipment service life, long-term monitoring difficulties. MEMS sensors have the advantages of low cost, high precision, easy installation, and simplicity, so they have broad application prospects in engineering measurements. This paper designs intelligent monitoring based on the collaborative measurement of dual MEMS sensors. The system first determines the endpoint coordinates of the sensor array by the coordinate transformation relationship in the monitoring system and then obtains the dam settlement according to the endpoint coordinates. Next, this paper proposes a dual-MEMS sensor collaborative measurement algorithm that builds a mathematical model of the dual-sensor measurement. The monitoring system realizes mutual compensation between sensor measurement data by calculating the motion constraint matrix between the two sensors. Compared with the single-sensor measurement, the dual-sensor measurement algorithm is more accurate and can improve the reliability of long-term monitoring data. Finally, the experimental results show that the dam subsidence monitoring system proposed in this paper fully meets the engineering monitoring accuracy needs, and the dual-sensor collaborative measurement system is more stable than the single-sensor monitoring system.

Deep Local Multi-level Feature Aggregation Based High-speed Train Image Matching

  • Li, Jun;Li, Xiang;Wei, Yifei;Wang, Xiaojun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.5
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    • pp.1597-1610
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    • 2022
  • At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.