• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1328-1336
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• 2012

Compared to terrestrial RF communications, underwater acoustic communications have several limitations such as limited bandwidth, high level of fading effects, and a large underwater propagation delay. In this paper, in order to tackle those limitations of underwater communications and to make it possible to form a large underwater monitoring systems, we propose a hierarchical underwater network architecture, which consists of underwater sensors, clusterheads, underwater/surface sink nodes, autonomous underwater vehicles (AUVs). In the proposed architecture, for the maximization of packet delivery ratio and the minimization of underwater sensor's energy consumption, a hybrid routing protocol is used. More specifically, cluster members use Tree based routing to transmit sensing data to clusterheads. AUVs on optimal trajectory movements collect the aggregated data from clusterhead and finally forward the data to the sink node. Also, in order to minimize the maximum travel distance of AUVs, an Integer Linear Programming based algorithm is employed. Performance analysis through simulations shows that the proposed architecture can achieve a higher data delivery ratio and lower energy consumption than existing routing schemes such as gradient based routing and geographical forwarding. Start after striking space key 2 times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.655-662
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• 2007

Monitoring systems used at present to operate HVAC(Heating, Ventilation and Air Conditioning) optimally do not have a function that enables to detect faults properly when there are faults of such as operating plants or performance falling, so they are unable to manage faults rapidly and operate optimally. In this paper, we have developed a classified rule-based fault detection system which can be inclusively used in HVAC system of a building by installation of sensor which is composed of HVAC system and required low costs compare to the model based fault detection system which can be used only in a special building or system. In order to experiment this algorithm, it was applied to HVAC system which is installed inside EC(Environment Chamber), verified its own practical effect, and confirmed its own applicability to the related field in the future.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.292-305
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• 2009

Wireless sensor networks have a lot of application areas such as industrial process control, machine and resource management, environment and habitat monitoring. One of the main objects of using wireless sensor networks in these areas is the event detection. To detect events at a user's request, we need a join processing between sensor data and the predicates of the events. If there are too many predicates of events compared with a node's capacity, it is impossible to store them in a node and to do an in-network join with the generated sensor data This paper proposes a predicate-merge based in-network join approach to efficiently detect multiple events, considering the limited capacity of a sensor node and many predicates of events. It reduces the number of the original predicates of events by substituting some pairs of original predicates with some merged predicates. We create an estimation model of a message transmission cost and apply it to the selection algorithm of targets for merged predicates. The experiments validate the cost estimation model and show the superior performance of the proposed approach compared with the existing approaches.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.4
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• pp.331-335
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• 2020

In this study, through the accumulated technologies such as real-time monitoring of power consumption using power line communication (PLC) method, power control, and automatic blocking of standby power, to commercialize them, we developed the hardware design, algorithm, protocol and module along with data transmission using PLC. We conducted the study to develop advanced products. We also proposed cloud-based smart outlet products with a novel type of outlet. These products can measure the internal power consumption through the H/W modules and the modules that control the power of household appliances connected to the smart outlets and smart plugs. Subsequently, they transmit the measurements to the energy saving system server via a communication module. This system can control the terminal device connected to the Gateway (G/W) server through a mobile phone. This will allow the customer to check the power consumption of the building at any given time, to turn the terminal on/off, and to maximize the energy efficiency during the construction of new apartments or multi-family housing in an area.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.1
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• pp.35-43
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• 2020

Turbidity has various effects on the water quality and ecosystem of a river. High turbidity during floods increases the operation cost of a drinking water supply system. Thus, the management of turbidity is essential for providing safe water to the public. There have been various efforts to estimate turbidity in river systems for proper management and early warning of high turbidity in the water supply process. Advanced data analysis technology using machine learning has been increasingly used in water quality management processes. Artificial neural networks(ANNs) is one of the first algorithms applied, where the overfitting of a model to observed data and vanishing gradient in the backpropagation process limit the wide application of ANNs in practice. In recent years, deep learning, which overcomes the limitations of ANNs, has been applied in water quality management. LSTM(Long-Short Term Memory) is one of novel deep learning algorithms that is widely used in the analysis of time series data. In this study, LSTM is used for the prediction of high turbidity(>30 NTU) in a river from the relationship of turbidity to discharge, which enables early warning of high turbidity in a drinking water supply system. The model showed 0.98, 0.99, 0.98 and 0.99 for precision, recall, F1-score and accuracy respectively, for the prediction of high turbidity in a river with 2 hour frequency data. The sensitivity of the model to the observation intervals of data is also compared with time periods of 2 hour, 8 hour, 1 day and 2 days. The model shows higher precision with shorter observation intervals, which underscores the importance of collecting high frequency data for better management of water resources in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4529-4536
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• 2010

This paper develops an interconnection test devices for photovoltaic(PV) systems composed of distribution system simulator, PV systems simulator and control and monitoring systems using the LabVIEW S/W, and simulates the customer voltage characteristics considering the 3 parameters on the introduction capacity for PV systems, system configuration and load factor. This paper also proposes a new calculation algorithm for voltage profile to make a comparison between calculation values and test device values. The results show that the test results for the normal operation characteristics of PV systems is very practical and effective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3100-3106
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• 2014

This paper develops power measurement system with multiple sensor input channels (voltage-8 channels and current-10 channels) that simultaneously can monitor power components for both supply and load side of power system. The hardware implementation of the proposed system is based on TMS320C42 DSP and signal processing program algorithm to calculate power components use the definition of IEEE Standard 1459-2010 related power quality. The performance of the developed system is tested by using standard ac power source device, and the test results showed that accuracy of the developed system is less than 0.2 %. Also, field test of the proposed system in the three-phase and four-wire power system was implemented. Simultaneous multiple channel measurement and analysis of power components in commercial and industrial electrical power system using the proposed system will be necessary to reduce power quality problems.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.205-214
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• 2010

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic classification becomes important for the effective use of network resources. In this paper, we present an application traffic classification method based on fixed IP-port information. A fixed IP-port is a {IP address, port number, transport protocol}triple dedicated to only one application, which is automatically collected from the behavior analysis of individual applications. We can classify the Internet traffic more accurately and quickly by simple packet header matching to the collected fixed IP-port information. Therefore, we can construct a lightweight, fast, and accurate real-time traffic classification system than other classification method. In this paper we propose a novel algorithm to extract the fixed IP-port information and the system architecture. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.