• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4341-4348
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• 2012

This paper presents a web-based real-time monitoring system for a photobioreactor using an WiFi wireless network. An WiFi interface can support high speed data transfer, up to 11Mbps and it can be compatible with commercial wireless LAN environment. Thus, the proposed cell culture based on WiFi network can be easily applied to the reconfigurable system and real-time monitoring system. In this paper, we integrate the commercial WiFi module to the various bio-sensors and sensor control board to configure the wireless network. After we evaluate application S/W for monitoring the environment within incubator, we verify the proposed sensor networks for a cell culture system and its monitoring system. This result can be applicable for various bio-applications that require the network configuration and real-time monitoring system.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1221-1226
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• 2015

This paper proposes a multiple switch mode power supply (SMPS) system based on the wireless network which controls variable load. The system enables power supply of up to 600W using 200W SMPS as a unit module and provides a controlling function of output power based on variable load and a monitoring function based on wireless network. The controlling function for output power measures the variation of output power and facilitates efficient power supply by controlling output power based on the measured variation value. The monitoring function guarantees a stable power supply by observing the multiple SMPS system in real time via wireless network. The performance of the proposed system was examined by various experiments. In addition, it was verified through standardized test of Korea Testing Certification. The results were given and discussed.

• Journal of information and communication convergence engineering
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• v.4 no.2
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• pp.67-70
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• 2006

A distributed healthcare monitoring system prototype for clinical and trauma patients was developed, using wireless sensor network node. The proposed system aimed to measure various vital physiological health parameters like ECG and body temperature of patients and elderly persons, and transfer his/her health status wirelessly in Ad-hoc network to remote base station which was connected to doctor's PDA/PC or to a hospital's main Server using wireless sensor node. The system also aims to save the cost of healthcare facility for patients and the operating power of the system because sensor network is deployed widely and the distance from sensor to base station was shorter than in general centralized system. The wireless data communication will follow IEEE 802.15.4 frequency communication with ad-hoc routing thus enabling every motes attached to patients, to form a wireless data network to send data to base-station, providing mobility and convenience to the users in home environment.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.69-75
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• 2002

In this paper, we propose the realtime network traffic monitoring system usin SNMP that can supported network and system operation, management, expansion, and design using network analysis and diagnosis to a network administrator. The proposed system consists of two parts: analysis server for collection and analysis of the network information, and supports real-time monitoring of network traffic, and client system shows user a graphical data that analyzed a returned result from the server. This system implements web-based technology using Java and contributes to enhance the effectiveness of network administrator's management.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.159-173
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• 2015

This paper presents a study on the Internet of Things based low-power wireless sensor networks for remote monitoring of wildlife ecosystem due to climate change. Especially, it is targeting the wild vegetation communities ecological monitoring. First, we performed a pre-test and analysis for selecting the appropriate frequency for the sensor network to collect and deliver information reliably in harsh propagation environment of the forest area, and selected for sensors for monitoring wild vegetation communities on the basis of considerations for selecting the best sensor. In addition, we have presented the platform concept and hierarchical function structures for effectively monitoring, analyzing and predicting of ecosystem changes, to apply the Internet of Things in the ecological monitoring area. Based on this, this paper presents the system architecture and design of the Internet of Things based low-power wireless sensor networks for monitoring the ecosystem of the wild vegetation communities. Finally, we constructed and operated the test-bed applied to real wild trees, using the developed prototype based on the design.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.50-60
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• 2007

The endeavor of this paper focuses on designing a monitoring system to provide a cost-effective solution on quality assurance for construction projects. The construction site monitoring system integrates a long-range wireless network, network cameras, and a web-based collaborative platform. The users of the system could obtain the most updated status of construction sites, such as behaviors of workers, project progress, and site events anywhere with Internet connectivity. It was carefully configured in order to maintain the reliability under the reactive conditions of the construction sites. This paper reports the architecture of the monitoring system and reviews the related technologies. The system has been implemented and tested on a construction site and promising results were obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.545-550
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• 2004

Recent natural disasters like flooding and slope collapse have shown the need for natural risk management system, as they endanger directly public health and cause severe damages on the national economy. In order to improve the efficiency of risk management systems, this management system based on AANN(Auto-Associative Neural Network)is proposed in this paper. AANN can be effectively used for identification of abnormal data and data compression. The proposed AANN-based risk management system collects and stores measurement data from sensors and transmits them to remote server for web-monitoring. Generally, it is desirable to transmit the compressed data instead of raw data in normal state. However, if dangerous situation happens, rapid tramission of measurement data should be required. These requirements are easily satisfied by using AANN. In order to verify the feasibilities of the proposed system, The AANN-based risk management system is applied to slope collapse monitoring system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.838-844
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• 2012

This paper proposes the effective monitoring method for marine engine system, which is implemented based upon Controller Area Network (CAN). As the marine engine monitoring system requires various kind of information, a lot of sensor nodes are distributed to several places. The CAN supports huge numbers of message IDs for the sensor nodes and provides a stable communication channel in a wide area such as a 12,000 TEU container ship. Since the CAN is priority-based communication system, some of hard real-time messages like alarm messages which are time-critical to the operation of the vessel cannot be communicated within the dead-time. Therefore it is desirable to distinguish the bandwidth of the CAN for static state messages and transition-state messages not to be harmful to the engine operations. Using the features of message arbitration ability of the CAN, it is proposed in this paper that the bandwidth allocation is dynamically adjusted to cope with the increment of input signal to improve the performance of monitoring system. Effectiveness and validity of the proposed scheme have been demonstrated through real experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.1-8
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• 2004

In this paper, we propose neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, ART2 neural network is used for fault isolation. The performance and effectiveness of the proposed ART2 neural network based fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.