• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.769-779
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• 2017

As the occurrence of drought is recently on the rise, the reliable drought forecasting is required for developing the drought mitigation and proactive management of water resources. This study developed a probabilistic hydrological drought forecasting method using the Bayesian Networks and drought propagation relationship to estimate future drought with the forecast uncertainty, named as the Propagated Bayesian Networks Drought Forecasting (PBNDF) model. The proposed PBNDF model was composed with 4 nodes of past, current, multi-model ensemble (MME) forecasted information and the drought propagation relationship. Using Palmer Hydrological Drought Index (PHDI), the PBNDF model was applied to forecast the hydrological drought condition at 10 gauging stations in Nakdong River basin. The receiver operating characteristics (ROC) curve analysis was applied to measure the forecast skill of the forecast mean values. The root mean squared error (RMSE) and skill score (SS) were employed to compare the forecast performance with previously developed forecast models (persistence forecast, Bayesian network drought forecast). We found that the forecast skill of PBNDF model showed better performance with low RMSE and high SS of 0.1~0.15. The overall results mean the PBNDF model had good potential in probabilistic drought forecasting.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.33-39
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• 2016

With recent advances in sensor technology, CMOS-based semiconductor devices and networking protocol, the areas for application of wireless sensor networks greatly expanded and diversified. Such diversification of uses for wireless sensor networks creates a multitude of beneficial possibilities for several industries. In the application of wireless sensor networks for monitoring systems' data transmission process from the sensor node to the sink node, transmission through multi-hop paths have been used. Also mobile sink techniques have been applied. However, high energy costs, unbalanced energy consumption of nodes and time gaps between the measured data values and the actual value have created a need for advancement. Therefore, this thesis proposes a new model which alleviates these problems. To reduce the communication costs due to frequent data exchange, a State Prediction Model has been developed to predict the situation of the peripheral node using a geographic autocorrelation of sensor nodes constituting the wireless sensor networks. Also, a Risk Analysis Model has developed to quickly alert the monitoring system of any fatal abnormalities when they occur. Simulation results have shown, in the case of applying the State Prediction Model, errors were smaller than otherwise. When the Risk Analysis Model is applied, the data transfer latency was reduced. The results of this study are expected to be utilized in any efficient communication method for wireless sensor network monitoring systems where all nodes are able to identify their geographic location.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.357-364
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• 2014

The first mission for the IoT based hyper-connectivity communication is developing a device-to-device communication technique in infra-less low-power and lossy networks. In a low-power and lossy wireless network, IoT devices and routers cannot keep the original path toward the destination since they have the limited memory. Different from the previous light-weight routing protocols focusing on the reduction of the control messages, the proposed scheme provides the light-weight IPv6 address auto-configuration, IPv6 neighbor discovery and routing protocol in a IoT capable infra-less wireless networks with the bloom filer and enhanced rank concepts. And for the first time we evaluate our proposed scheme based on the modeling of various probability distributions in the IoT environments with the lossy wireless link. Specifically, the proposed enhanced RPL based light-weight routing protocol improves the robustness with the multi-paths locally established based on the enhanced rank concepts even though lossy wireless links are existed. We showed the improvements of the proposed scheme up to 40% than the RPL based protocol.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.123-132
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• 2012

Gas sensors has been used very differently that depending on following purposes; Automotive (exhaust gas, fuel mixture gas, oxygen, particulates), agriculture / food industry (fresh, stored, CO2, humidity, NH3, nitrogen oxide gas, organic gas, toxic gas emitted from pesticides and insecticides), industrial / medical (chemical gas, hydrogen, oxygen and toxic gases), military (chemical weapon), environmental measurements (CO and other air pollution consisting of sulfur and nitrogen gas), residential (LNG, LPG, butane, indoor air, humidity). The types of industrial toxic substances are known about 700 species and many of these exist in gaseous form under normal conditions. he multi-gas detection sensors will be developed for casualties that detect the most important and find easy three kinds of gases in marine plant; carbon dioxide(CO2), carbon(CO), ammonia(NH3). Package block consists of gas sensing device minor ingredient, rf front end, zigbee chip. Develope interworking technology between the sensor and zigbee chip inside a package. Conduct a performance test through test jig about prototype zigbee sensor module with rf output power and unwanted emission test. This research task available early address when poisonous gas leaked from large industrial site and contribution for workers' safety at the enclosed space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.581-584
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• 2009

Recently, the cameras which used for observation are installed in children protection area and local crime prevention area in order to protect life and property and by its work being recognized and are installed more. Normal cameras have cost problem to observe multiple area and detail, because they can observe only one place. PTZ camera can observe multiple area by moving focus by schedule or remote control, but it can't automatically move the focus of it to the place where event occurred, because it can't recognize the place. In this study, we can monitor multiple area effectively, by installing a wireless sensor node equipped with temperature, lighting, gas and human detection sensor to each area, to monitor many place low-price and actively and to move the focus of PTZ camera to preset position, and send recorded video to the user, when the various sensor data received from wireless sensors in observation area are to be determined abnormal by analyzing. In addition, at night we can record a scene using infrared, but to reduce power consumption of lighting system which are installed to improve resolution, it supplies power to the lighting system when event occurred. So we were able to implement low power green monitoring system.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.220-241
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• 2019

In order to provide theoretical guidance to research in platform strategy, we build the conceptual framework based on the organizational ecology and analyze symbiotic/competitive relationship between platform entities. Platform owner and service provider (i.e. complementors) make symbiotic relationship, where platform owner provide service provider user-base and platform resources such as marketing tools and platform technology, and service provider provide platform owner services which users utilize. In addition to symbiotic relationships, platform owner has competitive relationship with other platform owners, and service provider builds competitive relationship with other service providers. In these relationships, the strategy of platform owner affects service provider and service provider builds a strategy for their own survival and success. This type of interaction makes competitive dynamics in platform. However, previous platform literature focuses on strategies to enhance network effect from the perspective of platform owner. Thus, there is little attention on interaction among the service providers. Using the framework based on community ecology of organizational ecology, we analyze interaction and strategy between platform owner and service provider in the viewpoint of platform openness strategy and platform pricing strategy. This research contributes to the literature of platform strategy by providing a theoretical framework based on organizational ecology to deeply understand the dynamics of platform.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.55-63
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• 2022

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.291-298
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• 2021

In this study, the future of countermobility capability is presented by analyzing the status of the countermobility obstacles focusing on the history of landmines and munitions. The conventional landmine was forbidden globally by the CCW and Ottawa Treaty because it caused civilian damage after the war. Because the inhumanity of those mines had been acknowledged, shatterable mines with a self-destruct (SD) function and M93 "HORNET" anti-tank munition with enhanced sensors have been fielded. In 2016, the Obama administration announced a policy that banned all antipersonnel landmines, leaving a considerable gap in the countermobility capability. To deal with these problems, the developments of "SAVO" and the SLEP program of Volcano mines were conducted. In the sense of a long-term approach, the countermobility obstacles, including mines, were chosen as fundamental forces for Multi-Domain Operations and were improved to Terrain Shaping Obstacles (TSO). TSO has improved sensors and mobility kill capabilities and features an enhanced remote control over each munition on the battlefield through a network established with satellite communication. The combined arms countermobility might be fully capable until 2050 if the TSO program can be completed successfully.