• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.637-650
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• 2014

Geospatial research on emergency response in multi-level micro-spatial environments (e.g., multi-story buildings) that aims at understanding and analyzing human movements at the micro level has increased considerably since 9/11. Past research has shown that reducing the time rescuers needed to reach a disaster site within a building (e.g., a particular room) can have a significant impact on evacuation and rescue outcomes in this kind of disaster situations. With the purpose developing emergency response systems that are capable of using complex real-time geospatial information to generate fast-changing scenarios, this study develops a Spatiotemporal Optimal Route Algorithm (SORA) for guiding rescuers to move quickly from various entrances of a building to the disaster site (room) within the building. It identifies the optimal route and building evacuation bottlenecks within the network in real-time emergency situations. It is integrated with a Ubiquitous Sensor Network (USN) based tracking system in order to monitor dynamic geospatial entities, including the dynamic capacities and flow rates of hallways per time period. Because of the limited scope of this study, the simulated data were used to implement the SORA and evaluate its effectiveness for performing 3D topological analysis. The study shows that capabilities to take into account detailed dynamic geospatial data about emergency situations, including changes in evacuation status over time, are essential for emergency response systems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1003-1008
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• 2012

The paper presents an Experimental Vehicle Model (EVM), that utilizes the kinematic characteristics of suspensions from SPMD test data. The relative displacement and orientation of a wheel with respect to the body are represented as a function of the vertical displacement of the wheel. The equations of motion of the vehicle are formulated in terms of local coordinates that do not require coordinate transformation, which improves the efficiency of dynamic analysis. The EOM was modularized for each suspension model, and a $6{\times}6$ vehicle model was obtained by combining six suspensions. The analysis results were compared with ADAMS to verify the accuracy of the EVM. This study also verifies the feasibility of real-time simulation with the developed EVM. For a vehicle simulation for 1 ms, the real simulation time required within 20% of the prescribed time. This result shows that the EVM meets the real-time simulation requirements.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.6
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• pp.1-9
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• 2009

Watershed topographical data is essential for the management for water resources and watershed management in terms of hydrology analysis. Collecting watershed topographical and meteorological data is the first step for simulating hydrological models and calculating hydrological components. This study describes a specialized Web-based Geographic Information Systems, Soil Water Assessment Tool model data generation system, which was developed to support SWAT model operation using Web-GIS capability for map browsing, online watershed delineation and topographical and meteorological data extraction. This system tested its operability extracting watershed topographical and meteorological data in real time and the extracted spatial and weather data were seamlessly imported to ArcSWAT system demonstrating its usability. The Web-GIS would be useful to users who are willing to operate SWAT models for the various watershed management purposes in terms of spatial and weather preparing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.355-362
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• 2009

In real-time communication services, delay constraints are among the most important QoS (Quality of Service) factors. In particular, it is difficult to guarantee the delay requirement over wireless channels, since they exhibit dynamic time-varying behavior and even severe burst-errors during periods of deep fading. Channel throughput may be increased, but at the cost of the additional delays when ARQ (Automatic Repeat Request) schemes are used. For real-time communication services, it is very essential to predict data deliverability. This paper derives the delay distribution and the successful delivery probability within a given delay budget using a priori channel model and a posteriori information from the perspective of queueing theory. The Gilbert-Elliot burst-noise channel is employed as an a Priori channel model, where a two-state Markov-modulated Bernoulli process $(MMBP_2)$ is used. for a posteriori information, the channel parameters, the queue-length and the initial channel state are assumed to be given. The numerical derivation is verified and analyzed via Monte Carlo simulations. This numerical derivation is then applied to a rate control scheme for real-time video transmission, where an optimal encoding rate is determined based on the future channel capacity and the distortion of the reconstructed pictures.

• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• Smart Structures and Systems
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• v.25 no.1
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• pp.23-35
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• 2020

It is important to take into account the thermal behavior in assessing the structural condition of bridges. An effective method of studying the temperature effect of long-span bridges is numerical simulation based on the solar radiation models. This study aims to develop a time-varying solar radiation model which can consider the real-time weather changes, such as a cloud cover. A statistical analysis of the long-term monitoring data is first performed, especially on the temperature data between the south and north anchors of the bridge, to confirm that temperature difference can be used to describe real-time weather changes. Second, a defect in the traditional solar radiation model is detected in the temperature field simulation, whereby the value of the turbidity coefficient t_u is subjective and cannot be used to describe the weather changes in real-time. Therefore, a new solar radiation model with modified turbidity coefficient γ is first established on the temperature difference between the south and north anchors. Third, the temperature data of several days are selected for model validation, with the results showing that the simulated temperature distribution is in good agreement with the measured temperature, while the calculated results by the traditional model had minor errors because the turbidity coefficient t_u is uncertainty. In addition, the vertical and transverse temperature gradient of a typical cross-section and the temperature distribution of the tower are also studied.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.11-18
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• 2017

The cycle time of construction equipment for earthwork operations has a significant impact on project productivity. Elements that directly impact a haul vehicle's cycle time must be identified in order to accurately quantify the haul cycle time and implement strategies to decrease it. The objective of this research is to scientifically identify and quantify variables that have a significant impact on the cycle time of a dump truck used for earthwork. Real-time location data collected by GPS devices deployed in an active earthwork moving construction site was analyzed using statistical regression. External data including environmental components and haul road conditions were also collected periodically throughout the study duration. Several statistical analyses including a variance analysis and regression analysis were completed on the dump truck location data. Collected data was categorized by stage of the dump truck cycle. Results indicate that a dump truck's enter idle time, exit idle time, moving speed and driver visibility can significantly impact the dump truck cycle time. The contribution of this research is the identification and analysis of statistically significant correlations of variables within the cycle time.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.75-80
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• 2018

In this paper, we propose heterogeneous lifelog mining model in health big-data platform. It is an ontology-based mining model for collecting user's lifelog in real-time and providing healthcare services. The proposed method distributes heterogeneous lifelog data and processes it in real time in a cloud computing environment. The knowledge base is reconstructed by an upper ontology method suitable for the environment constructed based on the heterogeneous ontology. The restructured knowledge base generates inference rules using Jena 4.0 inference engines, and provides real-time healthcare services by rule-based inference methods. Lifelog mining constructs an analysis of hidden relationships and a predictive model for time-series bio-signal. This enables real-time healthcare services that realize preventive health services to detect changes in the users' bio-signal by exploring negative or positive correlations that are not included in the relationships or inference rules. The performance evaluation shows that the proposed heterogeneous lifelog mining model method is superior to other models with an accuracy of 0.734, a precision of 0.752.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.111-117
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• 2019

In this paper, we propose a mobile remicon quality management system to enable inspection and correspondence with a smart phone in the field check of remicon. We also proposed a real-time slump data processing part to digitize field inspection and XML formats for data exchange with the server. We used the smart phone to transmit real-time image about field inspection of remicon and judged the error at the same time. By doing this, we shared the situation of the remicon products in the field and the head office. Based on the actual results, the development technology is used to determine whether the product is abnormal or not, and to provide appropriate information to the company and the site. Based on the analysis of raw material quality data, it is possible to present real time optimal blending ratio according to raw material import with raw material management data, which is the biggest problem of the ready mixed concrete industry.

• Membrane and Water Treatment
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• v.14 no.4
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• pp.155-162
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• 2023

Global climate change and urbanization have various demerits, such as water pollution, flood damage, and deterioration of water circulation. Thus, attention is drawn to Nature-based Solution (NbS) that solve environmental problems in ways that imitate nature. Among the NbS, urban wetlands are facilities that perform functions, such as removing pollutants from a city, improving water circulation, and providing ecological habitats, by strengthening original natural wetland pillars. Frequent monitoring and maintenance are essential for urban wetlands to maintain their performance; therefore, there is a need to apply the Internet of Things (IoT) technology to wetland monitoring. Therefore, in this study, we attempted to develop a real-time wetland monitoring device and interface. Temperature, water temperature, humidity, soil humidity, PM1, PM2.5, and PM10 were measured, and the measurements were taken at 10-minute intervals for three days in both indoor and wetland. Sensors suitable for conditions that needed to be measured and an Arduino MEGA 2560 were connected to enable sensing, and communication modules were connected to transmit data to real-time databases. The transmitted data were displayed on a developed web page. The data measured to verify the monitoring device were compared with data from the Korea meteorological administration and the Korea environment corporation, and the output and upward or downward trend were similar. Moreover, findings from a related patent search indicated that there are a minimal number of instances where information and communication technology (ICT) has been applied in wetland contexts. Hence, it is essential to consider further research, development, and implementation of ICT to address this gap. The results of this study could be the basis for time-series data analysis research using automation, machine learning, or deep learning in urban wetland maintenance.