• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.308-311
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• 2006

A vibration monitoring is performed on a 1kW class stand alone wind turbine(W/T). When a W/T model is developed, general performance under various wind condition should be verified to introduce the product in the market. Especially, vibration characteristics within operating speed range are very important in the aspect of structural stability as well as generator's electrical efficiency. This paper examines the vibration performance of a home made 1kW W/T Various data of the W/T model are acquired in real time using a remote vibration monitoring system installed in Daekwanryung test site. Vibration stability of the W/T structure is diagnosed based upon the data and the result is used to estimate the applicability of the W/T model.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1505-1515
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• 2016

The age of autonomous vehicles has come according to development of high performance sensing and artificial intelligence technologies. And importance of the vehicle's surrounding environment sensing and observation is increasing accordingly because of its stability and control efficiency. In this paper we propose an integrated platform for efficient networking, analysis and monitoring of multiple sensing data on the vehicle that are equiped with various automotive sensors such as GPS, weather radar, automotive radar, temperature and humidity sensors. From simulation results, we could see that the proposed platform could perform realtime analysis and monitoring of various sensing data that were observed from the vehicle sensors. And we expect that our system can support drivers or autonomous vehicles to recognize optimally various sudden or danger driving environments on the road.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.667-673
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• 2019

We present an orienteering problem with unknown stochastic reward(OPUSR) model for persistent monitoring tasks with unknown event probabilities at each point of interest. Prior studies on orienteering problem for persistent monitoring task assume that rewards and event probabilities are known as a prior. In this paper, we propose a stochastic reward model with unknown event statistics and a path re-planning algorithm based on Bayesian reward inference. Experiments demonstrate the efficiency of our method.

• ETRI Journal
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• v.41 no.4
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• pp.515-527
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• 2019

This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.211-218
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• 2023

Background: Traditional wildlife monitoring has often relied on invasive techniques posing risks to species and demanding substantial resources. To address this, camera traps emerged as non-invasive alternatives, albeit primarily tailored for larger mammals, posing limitations for small mammal research. Thus, the Mostela, an innovative tool designed to overcome these challenges, was introduced to monitor small mammals in South Korea. Results: The Mostela was deployed at two study sites in South Korea, yielding compelling evidence of its efficiency in capturing small mammal species. By analyzing the collected data, we calculated the relative abundance of each species and elucidated their activity patterns. Conclusions: In summary, the Mostela system demonstrates substantial potential for advancing small mammal monitoring, offering valuable insights into diversity, community dynamics, activity patterns, and habitat preferences. Its application extends to the detection of endangered and rare species, further contributing to wildlife conservation efforts in South Korea. Consequently, the Mostela system stands as a valuable addition to the toolkit of conservationists and researchers, fostering ethical and non-invasive research practices while advancing our understanding of small mammal populations and ecosystems.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.445-448
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• 2007

Three boreholes (BE-1, BE-2 and BE-3) were drilled for geothermal resources development in Haengbok (Sejong) city. Monitoring of temperature, electric conductivity (EC) and piezometric head were carried out at each borehole. Temperatures were measured at 10 m depth, it ranges from 13.22$^{\cdot}C$ to 14.4$^{\cdot}C$. EC of BE-1 and BE-3 declined with time because groundwater flowed in boreholes. Barometric efficiency was analysed by piezometric head of groundwater and atmospheric pressure, it ranges from 44.8% to 71.5%. These parameters can be used for a geothermal modeling.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.69-74
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• 2014

With the increasing interest of energy efficiency, several buildings and factories begin to monitor energy usages with a built-in energy management system. However, the built-in energy monitoring system does not reflect the dynamics of buildings and factories energy usage. To overcome the latter, we deploy several sensors to monitor the dynamics of buildings energy usage patterns. In this paper, we are proposing a framework of a sensor based energy monitoring system. Based on our limited experiments, we can monitor power usages by a person, device and time period. As a result, we can plan a better energy usage and improve energy efficiency by the monitored energy usage profile data.

• Smart Structures and Systems
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• v.19 no.3
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• pp.259-268
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• 2017

System identification of structures is one of the important aspects of structural health monitoring. The accuracy and efficiency of identification results is affected severely by measurement noises, especially when the structure system is large, such as bridge structures, and when online system identification is required. In this paper, the least square estimation (LSE) method is used combined with the substructure approach for identifying structural parameters of a cable-stay bridge with large degree of freedoms online. Numerical analysis is carried out by first dividing the bridge structure into smaller substructures and then estimates the parameters of each substructure online using LSE method. Simulation results demonstrate that the proposed approach is capable of identifying structural parameters, however, the accuracy and efficiency of identification results depend highly on the noise sensitivities of loading region, loading pattern as well as element size.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.963-966
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• 1988

This paper describes the development of a prototype expert system, which is designed to analyze loom production efficiency by employing a loom monitoring system. The problem field of the prototype expert system is the loom failure analysis which has a great effect on prouction efficiency, and the characteristic graph in which the loom failure causes are classified and organized, is used in the analysis. The knowledge for characteristic graph is organized, and an effective inference engine- is developed. The developed system is tested and modified using hypothetical loom failure causes, and the feasibility of the expert system application to extend the functions of the loom monitoring system is proved.

• Journal of the Semiconductor & Display Technology
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• v.3 no.2
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• pp.1-4
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• 2004

An experimental study was conducted on the optimal configuration and size of ADFL(Aerodynamic Focusing Lens) which used in modified ISPM(In-Situ Particle Monitoring). The particle counting efficiency has been known as a function of distance and size of ADFL, thus we varied these parameters to find out the optimum values. From a result of experiment, it was found that two lenses and 6mm space between them showed a maximum particle measuring efficiency. To apply this modified ISPM to semiconductor manufacturing field, we need more experiment about the pressure change, flow rate, and input particle size.