• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.177-183
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• 2005

The subject of this paper is research into the application of electrical resistivity monitoring to detecting the water leakage of water utilization facilities. For this purpose, we installed a comprehensive monitoring system consisting of resistivity measurement, inclinometer, piezometer, and water gauge at an embankment. Using this monitoring system, we monitored the various kinds of measurement data and compared the resistivity structures and that of hydrological and engineering data in order to investigate the water leakage and stability of the embankment. The variant images of electrical resistivity at the embankment were provided from the monitoring data and we could accurately locate the portion of which resistivities have sharply changed. Furthermore, we could estimate the stability of the embankment more effectively and quantitatively by jointly interpreting the monitoring data of resistivity, water level, pore water pressure, and subsurface displacement. The monitoring experiments in this study led us to the conclusion that for the efficient maintenance of the water utilization facilities, monitoring the resistivity data and hydrological data would be much more preferable to performing the just one-time measurements.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.3
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• pp.250-260
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• 2013

Objectives: The aim of this study is to analyze the current status of the possession of measurement and analytical instruments among work environment monitoring organizations that have been designated by the Ministry of Employment and Labor (MoEL) in Korea. Methods: Data for measurement and analytical instruments were gathered by inspectors who had been assigned by the Korea Occupational Safety and Health Agency (KOSHA) and MoEL during the evaluation program for designated work environment monitoring service providers in 2012. Data for 11 monitoring instruments and nine analytical instruments were collected from 108 organizations. Basic data such as the type of service provides and the size of employment were also recorded by the inspector. Results: The total number of personal air samplers including high and low flow rates operated in Korea was 5,418, with average of 50.2. Average operation number of noise dosimeters was 35.0, while 3,780 dosimeters were used in 108 work environment monitoring organizations. There were 10,488 monitoring instruments in total. All service providers possessed at least one AAS and GC in their analytical laboratory. Total number of HPLC/MS was five, followed by ICP/MS of seven, with an average of 0.07. Conclusions: Based on the data, domestic work environment monitoring service providers possessed relatively reasonable measurement and analytical instruments. Nearly all instruments had been imported from advanced countries such as USA, UK and Japan. Periodic gathering of data on these instruments may help maintain good workplace monitoring results and the health of workers at the sites.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.651-659
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• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.119-126
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• 2012

Local monitoring is an effective technique in securing data of wireless sensor networks. Existing solutions require high communication cost for detecting false data and this results in a network lifetime being shortened. This paper proposes novel techniques of monitoring based secure data aggregation and filtering false data in wireless sensor networks. The aim is to reduce energy consumption in securing data aggregation. An aggregator and its monitoring node perform data aggregation in a 60o sextant cluster. By checking Message Authentication Codes (MAC), aggregation data will be dropped by a forward aggregator if data aggregated by the aggregator and data monitored by the monitoring node are inconsistent. The simulation shows that the proposed protocol can reduce the amount of average energy consumption about 64% when comparing with the Data Aggregation and Authentication protocol (DAA)[1]. Additionally, the network lifetime of the proposed protocol is 283% longer than that of DAA without any decline in data integrity.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2002-2007
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• 2010

The objective of this study is the developement monitoring measurement using global positioning digital datalogger system for monitoring measurement of railway construction sites. For the replacement of current passive data communication, Global positioning digital datalogger system using active communication is studied for the first time with in a country. Therefore data communication method and analyzing program of automatic measurement data is developed for the global positioning automatic digital datalogger system. The results of this study will be using real time automatic monitoring measurement of railway structures.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.436-452
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• 2008

In this study, the settlement prediction method based on field monitoring data under preloading improvement with ramp loading is developed. Settlement behavior can be predicted with field monitored settlement throughout the entire preloading process including ramp loading followed by constant loading. The developed method is verified by comparing its predicted results with results from physical model tests and field monitoring data.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.253-257
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• 2013

Mobile computers can process large amounts of data at high speeds, and it is feasible and easy to implement a remote monitoring system utilizing mobile computers. Because of their portability and convenience, these computers have been employed in various research areas to develop such monitoring systems. Existing monitoring system is a bit difficult to real time monitoring the scattered offshore facilities. So this paper compensate the existing system by using mobile computers such as a tablet PC-based monitoring system. Also, the scattered offshore facilities can be monitored in real-time through the tablet PC. The developed monitoring system is a fully Internet-based monitoring platform that enables one to monitor and control remote oceanic applications at any time and any place where it is possible to access the Internet. It can be applied to many oceanic applications as well as the unmanned systems and remote monitoring systems on land.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.185-189
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• 2006

Time series analysis is a frequently effective method of constructing model and prediction in data processing of deformation monitoring. The monitoring data sample must to be as more as possible and time intervals are equal roughly so as to construct time series model accurately and achieve reliable prediction. But in the project practice of GPS deformation monitoring, the monitoring data sample can't be obtained too much and time intervals are not equal because of being restricted by all kinds of factors, and it contains many variates in the deformation model moreover. It is very important to study the data processing method for small samples and multi-variates time series in GPS deformation monitoring. A new method of establishing small samples and multi-variates deformation model and prediction model are put forward so as to resolve contradiction of small samples and multi-variates encountered in constructing deformation model and improve formerly data processing method of deformation monitoring. Based on the system theory, a deformation body is regarded as a whole organism; a time-dependence linear system model and a time-dependence bilinear system model are established. The dynamic parameters estimation is derived by means of prediction fit and least information distribution criteria. The final example demonstrates the validity and practice of this method.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.236-251
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• 2020

As remote sensing technologies are evolving, and more satellites are orbited, the demand for using satellite data for disaster monitoring is rapidly increasing. Although natural and social disasters have been monitored using satellite data, constraints on establishing an integrated satellite-based near real-time disaster monitoring system have not been identified yet, and thus a novel framework for establishing such system remains to be presented. This research identifies constraints on establishing satellite data-based near real-time disaster monitoring systems by devising and testing a new conceptual framework of disaster monitoring, and then presents a feasible disaster monitoring system that relies mainly on acquirable satellite data. Implementing near real-time disaster monitoring by satellite remote sensing is constrained by technological and economic factors, and more significantly, it is also limited by interactions between organisations and policy that hamper timely acquiring appropriate satellite data for the purpose, and institutional factors that are related to satellite data analyses. Such constraints could be eased by employing an integrated computing platform, such as Amazon Web Services(AWS), which enables obtaining, storing and analysing satellite data, and by developing a toolkit by which appropriate satellites'sensors that are required for monitoring specific types of disaster, and their orbits, can be analysed. It is anticipated that the findings of this research could be used as meaningful reference when trying to establishing a satellite-based near real-time disaster monitoring system in any country.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.355-360
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• 2022

In this paper, we present design and developing method for EMS(environment monitoring system) of micro data center. This developing EMS monitors operating environment of micro data center and analyze sensing data through IoT(Internet of things) sensors in real time. Firstly we present configuration method of IoT sensing package and design method EMS hardware platform. Secondly we design data collector software for data collection of IoT sensor with different protocol and develop monitoring software of EMS. The data collector software consists of sensor collector module and collector manager module. Also we design EMS software which has micro service architecture structural style and component based business logic.