• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.31-40
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• 2020

The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on "UAV technology/industry trends" was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was "remote sensing technology/data analysis". In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.

• Smart Structures and Systems
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• v.29 no.1
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• pp.53-62
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• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1204-1227
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• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.1-17
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• 2012

The Smartphone, one of essential mobile devices widely used recently, can be very effectively applied to capture knowledge on the spot by jointly applying the pervasive functionality of cloud computing. The process of knowledge capturing can be also effectively automated if the topic of knowledge is automatically identified. Therefore, this paper suggests an interdisciplinary approach to automatically acquire knowledge on the spot by combining technologies of text mining-based topic identification and cloud computing-based Smartphone. The Smartphone is used not only as the recorder to record knowledge possessor's dialogue which plays the role of the knowledge source, but also as the sensor to collect knowledge possessor's context data which characterize specific situations surrounding him or her. The support vector machine, one of well-known outperforming text mining algorithms, is applied to extract the topic of knowledge. By relating the topic and context data, a business rule can be formulated, and by aggregating the rule, the topic, context data, and the dictated dialogue, a set of knowledge is automatically acquired.

• Spatial Information Research
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• v.22 no.4
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• pp.11-20
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• 2014

This study aims to provide information about the research-trends in the area of Geospatial Information using text-mining methods. We derived the National R&D Reports and papers from NDSL(National Discovery for Science Leaders) site. And then we preprocessed their key-words and classified those in separable sectors. We investigated the appearance rates and changes of key-words for R&D reports and papers. As a result, we conformed that the researches concerning applications are increasing, while the researches dealing with systems are decreasing. Especially, with in the framework of the keyword, '3D-GIS', 'sensor' and 'service' xcept ITS are emerging. It could be helpful to investigate research items later.

• Journal of the Korean GEO-environmental Society
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• v.14 no.4
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• pp.47-52
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• 2013

In Korea, the number of mining operations are getting smaller. But buried accidents are on the increase every year. For this reason, it is important to safety management in construction process, especially the worker's safety. In the field of construction needs utilization of integration system according to purpose of utilization, particularly in underground construction sites utilizing is emphasized even more. The current element technologies of location tracking, sensors and wireless communication possible to utilize but it is still difficult to utilization of integration system in construction field because a study is not complete on commercialization and availability. In this study, for real time 3-dimensional management of ubiquitous construction site in ground and underground, measure data using MEMS sensor, EDM and DGPS in 2 test site. Also results were analysed by MATLAB. As a result, error is verification less than 3 meter that possible to distinguish with the naked eye and construct direction of study based on result of former.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.433-436
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• 2006

유비쿼터스는 간단히 말해서 많은 센서 들로 이루어진 무선 센서 네트워크이며 해양 환경 감시 서비스는 해양에 센서들을 설치함으로써 유비쿼터스 환경을 구축하고 해양 환경 변화를 감시한다. 센서 노드들로부터 수온, 기온, 염도 등을 센서 데이터들이 측정이 되며 이러한 데이터를 기반으로 유용한 지식을 탐사해낸다. 그러나 기존의 데이터 마이닝 기법은 이력 데이터에 대해서 마이닝 기법을 적용하지만 센서 데이터들은 아주 빠른 속도로 대량으로 유입이 되기 때문에 기존의 데이터 마이닝 기법은 적용이 불가능하게 된다. 그러므로 센서 데이터에 맞는 새로운 센서 데이터 마이닝 기법이 필요하다. 본 논문에서는 센싱된 센서 데이터들을 기반으로 해양 환경 감시 서비스에 제공할 수 있는 센서 마이닝 기법들을 제안한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.28-34
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• 2010

In this paper, we proposes a emergency medical information system for predicting emergency situation by using the body's vital signs. Main research of existing emergency system has focused on body sensor networks. The problem of these studies have a delay of the emergency first aid since occurring of an emergency situation send a message of emergency situation to user. In the serious situation, patients of these problem can lead to death. To solve this problem, it need to the prediction of emergency situation for doing quickly the First Aid with identify signs of a pre-emergency situations until an emergency occurs. In this paper, the sensor network technology, the security technology, the internet information retrieval techniques, data mining technology, and medical information are studied for the convergence of medical information systems of the prediction of emergency situations.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.6
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• pp.421-428
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• 2015

An important trend in the sustainment of military aircraft is the transition from preventative maintenance to condition based maintenance (CBM). For CBM, it is essential that the actual system condition can be measured and the measured condition can be reliably extrapolated to a convenient moment in the future in order to facilitate the planning process while maintaining flight safety. Much research effort is currently being made for the development of technologies that enable CBM, including structural health monitoring (SHM) systems. Great progress has already been made in sensors, sensor networks, data acquisition, models and algorithms, data fusion/mining techniques, etc. However, the transition of these technologies into service is very slow. This is because business cases are difficult to define and the certification of the SHM systems is very challenging. This paper describes a possibility for fielding a SHM system on legacy military aircraft with a minimum amount of certification issues and with a good prospect of a positive return on investment. For appropriate areas in the airframe the application of SHM will reconcile the fail-safety and slow crack growth damage tolerance approaches that can be used for safeguarding the continuing airworthiness of these areas, combining the benefits of both approaches and eliminating the drawbacks.