• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.11-17
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• 2022

In this study, we address the development of a floating platform system based on a unmanned surface vessel for wide-area sensing and monitoring of hazardous and noxious substances (HNSs). For long endurance, a movable floating platform with no mooring lines was used and modified for HNS sensing and monitoring. The floating platform was equipped with various sensors such as optical and thermal imaging cameras, marine radar, and sensors for detecting HNSs in water and air. Additionally, for experiment validation in real outdoor environments, a portable gas-exposure system (PGS) was built and installed on the monitoring system. The software for carrying out the mission was integrated with the Robot Operating System (ROS) framework. The practical feasibility of the developed system was verified through experimental tests conducted in inland water and real-sea environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.108-117
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• 2011

Seoul metropolitan government has been operating traffic signal control system with the name of COSMOS since 2001. COSMOS uses the degrees of saturation and congestion which are calculated by installing loop detectors. At present, inductive loop detector is generally used for detecting vehicles but it is inconvenient and costly for maintenance since it is buried on the road. In addition, the estimated queue length might be influenced in case of error occurred in measuring speed, because it only uses the speed of vehicles passing by the detector. A traffic signal control algorithm which enables smooth traffic flow at intersection is proposed. The proposed algorithm assigns vehicles to the group of each lane and calculates traffic volume and congestion degree using traffic information of each group using VANETs(Vehicular Ad-hoc Networks) inter-vehicle communication. It does not demand additional devices installation such as cameras, sensors or image processing units. In this paper, the algorithm we suggest is verified for AJWT(Average Junction Waiting Time) and TQL(Total Queue Length) under single intersection model based on GLD(Green Light District) Simulator. And the result is better than Random control method and Best first control method. In case real-time control method with VANETs is generalized, this research that suggests the technology of traffic control in signalized intersections using wireless communication will be highly useful.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.514-517
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• 2003

Oxygen supply is one of the most basic things in human body. Breathing is controlled by the lungs' stationary function and the respiratory center which is in the mesulla oblongata. Nothing but, the external breathing that air movement between the lungs and atmosphere and the internal breathing that cellular air movement between the hemoglobin and a single cell. The adult's number of times of the respirations is about 15∼20 per 1 minute, but it depends ages, exercise, temperature, disease, etc. The important thing in detecting the respiration is that doing it in object person's resting time. Detecting the respiration have to be done without attracting any attention of object person. In present using method is detecting the pulse with catching an object person's wrist and observing the object person's movement. In this paper, we propose the mobile respiration detection diagnostic system using ultrasound sensing method that does not be influenced by the inertia error and the pressure error.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.17-24
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• 2012

As the resources and power on Ad-hoc networks are limited, new data aggregation techniques are required for energy efficiency. The current research on data aggregation techniques is actively in progress, but existing studies don't consider the density of nodes. If nodes are densely placed in a particular area, the information which the sensor nodes placed on those areas detect can be judged as very strong association. But, the energy spent transmitting this information is a waste of energy. In this paper the densely-concentrated node area is designated as Hotspot_Zone in the multi-hop clustering environment using the AMC and a key node is selected in the area. If the request message of data aggregation is transmitted, the key node among the neighboring nodes sends its environmental information to a manager to avoid duplicate sensing information. Therefore, the life of networks can be prolonged due to this.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6597-6601
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• 2013

This study aims at suggesting a evaluation method of water cycle soundness in U-City. The distortion of water cycle soundness induced industrialization and urbanization was quantitatively analyzed. In order to evaluate the soundness of water cycle in U-City the reduction ratio of runoff was evaluated in comparison of before the construction of the water recycling facilities for natural water cycle, the reduction ratio of urban water was evaluated in comparison of before the introduction of the artificial recycling facilities for artificial water cycle.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.789-796
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• 2006

Context-aware is the core in ubiquitous environment of sensor network to support intelligent and contextual adaptation service. The new context information model is demanded to support context-aware applications. The model should not depend on a specified application and be shareable between applications in the same environment. Also, it should support various context representation and complex context-aware. In this paper, we define the context information according to context-aware process. Also we design the knowledge of domain as well as applications using ontologies and rules. The domain spatial ontology and application knowledge are represented using the spatial object model and the rules of expanded ontologies, respectively. The expression of abundant spatial ontology represents the context information about distance between objects and adjacent object as well as the location of the object. The proposed context information model which is able to exhibit various spatial context and recognizes complex spatial context through the existing GIS. This model shows that it can adapt to a large scale outdoor context-aware applications such as air pollution and prevention of disasters as well as various context-aware applications.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.23-34
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• 2012

Space launch vehicles are designed to fly according to the elaborate pre-determined path. However, if a vehicle went out of the planned trajectory or its thrust terminated abnormally, or if a free-fall atmospheric reentry vehicle tracked by a tracking sensor became impossible to be measured, it is required to attempt to track by a another track equipment or estimate its impact point rapidly. In this paper a new algorithm is proposed, named the ITS-EKF combined with the Integrated Track Splitting (ITS) algorithm and the Extended Kalman Filter (EKF) to obtain the location information of a ballistic projectile without thrust, create its track and maintain it in an environment with clutter. For the reentry vehicle, the track performance is to be verified and the impact point is estimated by applying the simulation through ITS-EKF algorithm. To ensure the proposed algorithm's adequacy, by comparing the track performance and impact point distribution by the ITS-EKF with those of ITS-PF combined with ITS and Particle Filter (PF), it is confirmed that the ITS-EKF algorithm can be used an effective real-time On-line impact point prediction.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.16-27
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• 2017

IEEE 802.15.6 standard, a Wireless Body Area Network, aims to transfer not only medical data but also non-medical data, such as physical activity, streaming, multimedia game, living information, and entertainment. Services which transfer those data have very various data rates, intervals and frequencies of continuous access to a medium. Therefore, an efficient anti-collision operations and medium assigning operation have to be carried out when multiple nodes with different data rates are accessing shared medium. IEEE 802.15.6 standard for CSMA/CA medium access control method distributes access to the shared medium, transmits a control packet to avoid collision and checks status of the channel. This method is energy inefficient and causes overhead. These disadvantages conflict with the low power, low cost calculation requirement of wireless body area network, shall minimize such overhead for efficient wireless body area network operations. Therefore, in this paper, we propose a medium access scheduling scheme, which adjusts the time interval for accessing to the shared transmission medium according to the amount of data for generating respective sensor node, and a priority control algorithm, which temporarily adjusts the priority of the sensor node that causes transmission concession due to the data priority until next successful transmission to ensure fairness.