• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.227-232
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• 2011

The QRS complex in ECG analysis is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. This paper presents the preprocessor method to detect R-peak, RR interval, and HRV in wireless sensor node. The derivative of the electrocardiogram is efficiency of preprocessing method for resource hungry wireless sensor node with low computation. We have implemented R-peak and RR interval detection application based on dECG for wireless sensor node. The sensor node only transfers meaning parameter of ECG. Thus, implementation of sensor node can save power, reduce traffic, and eliminate congestion in a WSN.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.285-289
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• 2012

In a coastal area, all of the vessels are always exposed to the potential risk, taking into the maritime accident statistics account over the last decades. To manage vessels underway safety, the characteristics of ship movements in a fairway should be recognized by VTS system or VTS operators. The IMO has already mandated the shipboard carriage of AIS since 2004, as stated in SOLAS Chapter V Regulation 19. As a result, the static and dynamic information of AIS data has been collected for vessel traffic management in the coastal areas and used for VTS. This research proposes a simple algorithm of recognizing potentially risky ships by observing their trajectories on the fairway. The static and dynamic information of AIS data are collected and the curvature for the ship trajectory is surveyed. The proposed algorithm finds out the irregularity of ship movement. The algorithm effectively monitors the change of navigation pattern from the curvature analysis of ship trajectory. Our method improves VTS functions in an intelligent way by analyzing the navigation pattern of vessels underway.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1116-1125
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• 1997

In this paper, the modified UPC(Usage Parameter Control) algorithm is proposed. The proposed UPC algorithm is based on Leakey Bucket algorithm and adds the characteristics of the jumping window algorithm for monitoring the average bit rate. The proposed algorithm let a cell, which is tagged by Leaky Bucket algorithm, pass through the network, if the network does not violate the average bit rate. The measuring method of window mechanism like jumping window. This paper supposes On/Off traffic source model of rthe performance evaluation and analysis of the proposed algorithm. Therefore, as simulation results, the proposed algorithm acquires more reduced results of the cell loss rate and bucket size than the Leaky Bucket algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.259-264
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• 2014

IEEE 802.15.4 has been emerging as the popular choice for various monitoring and control applications. In this paper, a fault management system for DC power-lines has been designed using IEEE 802.15.4, in order to monitor DC power-lines in real time, and to rapidly detect faults and shut off the line where such faults occur. Numbers were allocated for each node and unslotted CSMA-CA method of IEEE 802.15.4 was used, the performance of which was analyzed by a simulation. For such purpose, a total of 60 bits of the control data consisting of 16 bits of the current, 16 bits of the amplitude, 28 bits of the terminal state data were sent out, and the packet transfer rate and the transmission delay time of the fault management system for DC power-lines were measured and analyzed. When the traffic load was 330 packets per second or lower, the average delay time was shown to be shorter than 0.02 seconds, and when the traffic load was 260 packets per second or lower, the packet transfer rate was shown to be 99.99% or higher. Therefore, it was confirmed that the stringent condition of US Department of Energy (DOE) could be satisfied if the traffic load was 260 packets per second or lower, The results of this study can be utilized as basic data for the establishment of the fault management system for DC power-lines using IEEE 802.15.4.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.123-138
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• 2018

To sustainably monitor air pollution in Seoul, the number of Air Pollution Monitoring Station has been gradually increased by Korea's Ministry of Environment. Although particulate matters(PM), one of the pollutants measured at the stations, have an significant influence on human body, the concentration of PM in Korea came in second among 35 OECD member countries. In this study, using the data of PM concentration from the stations, distribution maps of PM10 and PM2.5 concentrations over Seoul were generated, and spatial factors potentially related to PM distribution were investigated. Based on a circumscribed hexagon about a circle in radius of 500 meters created as a basic unit, Seoul was sectionalized and PM concentration map was generated using the interpolation technique of 'inverse distance weighting'. The distributions of PM concentrations were investigated with commuting time by administrative district and the outcome was related with land-use type and volume of traffic. Results from this analysis indicated distribution pattern of PM10 concentration was different from that of PM2.5 by administrative district and time. The distribution of PM concentration was strongly related to not only the size of business and trafficked areas among the land-use type, but also the existence of urban green. Further analysis of the relationship between the PM concentration and detailed land-use and urban green maps can be helpful to identify spatial factors which have an impact on the PM concentration on the regional scale.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.794-804
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• 2018

Various applications running in computers exchange information in the form of packets through the network. Most packets are formatted into UDP/IP or TCP/IP standard. Network management administrators of enterprises and organizations should be able to monitor and manage packets transmitted over the network for Internet traffic measurement & monitoring, network security, and so on. The goal of this paper is to analyze the performance of several algorithms which closely examine and analyze payloads in a DPI(Deep Packet Inspection) system. The main procedure of packet payload analysis is to quickly search for a specific pattern in a payload. In this paper, we introduce several algorithms which detect a specific pattern in payloads, analyze the performance of them from three perspectives, and suggest an application method suitable for requirements of a given DPI system.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.347-349
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• 2009

Air quality of indoor space environment is affected by various pollutants like as particles and chemical stuffs. The indoor air pollution affects directly the human respiration organs to cause consequently unpleasant mental status. The $CO_2$ concentration level is one of the harmful components of air pollutants. Major factor to increase the $CO_2$ concentration level is the people's breath amount in indoor. The car exhaust gas diffused from the around road also has strong affect on $CO_2$ concentration. There are some other reasons to affect the $CO_2$ concentration change, such as, real-time change of the population movement, closeness to the indoor air flow inlet window and changes in road car traffic amount. A remote monitoring system to measure environmental indoor air pollution concerning on the $CO_2$ concentration was studied and installed realized set-up model. Zigbee network configuration was applied for this system and the $CO_2$ concentration data were collected through USN network. A software program was developed to assure systematic analysis and to display real-time data on web pages. For the experimental test various condition was set up, like as, window opening, stopping air condition operation and adjusting fan heater work, etc. The analysis result showed the relation of various environmental conditions to $CO_2$ concentration changes. The causes to increase $CO_2$ concentration were experimentally defined as windows closing, the stopping air condition system, fan heater operation. To keep the $CO_2$ concentration under the legally required ppm level in public access indoor space, the developed remote measurement system will be usefully applied.

• Smart Structures and Systems
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• v.33 no.2
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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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.153-172
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• 2018

Overloading of Commercial vehicles have been an important area of transportation as one of the main causes of pavement damage, bridge collapse, severe traffic accident, etc. In this study, we analyzed the effects of overweight prevention by analyzing overweight driving patterns and using weight sensors. First, we analyzed relevant literatures of overweight and surveyed the commercial weight sensors. Then we chose the typical type of overweight vehicles based of overweight enforcement data analysis. MEMs inclinometer weight sensor were installed to 10 test vehicles and data was collected by weight sensors and gps in real time. As a result of gross vehicle weight and axle weight analysis, it was found weight sensor could decrease overweight rate. However, since the number of samples of test vehicles is insufficient to represent the whole commercial vehicle, further studies are deemed possible through the extension test.