• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.923-926
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• 2010

A sensor network system processes user queries using the recent field data collected by each sensor node. To process user queries, the system propagates the queries to the specific sensor nodes which have the relevant data and aggregates the results of the queries. However, if continuous queries are processed by the existing scheme, the system has the problem where the queries are propagated repeatedly. In this paper, we propose the query processing scheme to process the continuous queries over the sensor streaming data. To do this, each sensor node builds its own query index on its node. And, we present the scheme to deal with the unexpected data rising on the sensor node.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1003-1006
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• 2004

In this paper have developed a system for monitoring and processing the real time sensor data in remote site through network. For realizing this system, measurement equipment and protocol are used to transmit the measurement data to remote server and to process measurement data. In server part, the received data from remote site sensor is converted to text or graphic charts for user. The measurement device in sensor part receives the sensor data form sensor and store the received data to its internal memory for transmitting data to server part through Internet. Also the measurement device can receive data form server. The temperature sensor is connected to the measurement device located in laboratory and the measurement device measures temperature of laboratory which can be confirmed by user through Internet. We have developed a server programworking on the Linux to store measurement data from measurement device to server memory. The program is use for SNMP(Simple Network Management Protocol) to exchange data with measurement device. Also the program changes the measurement data into text and graphic charts for user display. The program is use apache PHP program for user display and inquiry. The real time temperature measurement system can be apply for many parts of industry and living.

• Smart Structures and Systems
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• v.17 no.4
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.58-67
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• 2010

Data-centric storage schemes(DCS) are one of representative researches that efficiently store and manage sensor readings in sensor nodes in the sensor networks. In DCS, a sensor sends the sensed data to a specific node in order to store them. However, it has a problem that sensor nodes consume a lot of energy for transmitting their readings to remote sensor node. In this paper, we propose a novel sensor data compression algorithm to reduce communication costs for DCS. The proposed algorithm establishes a safe region and transmits the sensed data only when current measurement is out of the safe region, As a result, the proposed algorithm extends network life time and reduces data transmission. It is shown through performance evaluation that our proposed algorithm reduces energy consumption by about 60% over the conventional algorithm.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.276-279
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• 2005

As the Ubiquitous generation approaches, the importance of the sensor data processing is growing. The data approximation scheme, one of the data processing methods, can be the key of sensor data processing, for it is related not only to the lifetime of sensors but also to the size of the storage. In this paper, we propose the Harmonic Wavelet transform which can minimize the relative error for given sensor data. Harmonic Wavelets use the harmonic mean as a representative which is the minimum point of the maximum relative error between two data values. In addition, Harmonic Wavelets retain the relative errors as wavelet coefficients so we can select proper wavelet coefficients that reduce the relative error more easily. We also adapt the greedy algorithm for local optimization to reduce the time complexity. Experimental results show the performance and the scalability of Harmonic Wavelets for sensor data.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.63-68
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• 2008

In now days, Ubiquitous technology grow up, so the variety service are developed. Sensor networks purpose is collection information about environment and geographic. But sensor network has limit in power, cost and so on. There is much restriction. Some sensor networks purpose is monitoring environment. And there is some relation in sensing data. Sensor nodes sense information by periods. First sensing data correlate with next sensing data. At this point, this paper suggest power saving method. Some data are same, the other data are similar.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.581-587
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• 2011

A wireless sensor network needs to consist of multi-sensors in order to infer a high level of information on circumstances. Data fusion, in turn, is required to utilize the data collected from multi-sensors for the inference of information on circumstances. The current paper, based on Dempster-Shafter's evidence theory, proposes data fusion in a wireless sensor network with different weights assigned to different sensors. The frequency of events per sensor is the crucial element in calculating different weights of the data of circumstances that each sensor collects. Data fusion utilizing these different weights turns out to show remarkable difference in reliability, which makes it much easier to infer information on circumstances.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.54-62
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• 2017

Currently, falling to industrial field workers is causing serious injuries. Therefore, many researchers are actively studying the fall by using acceleration sensor, gyro sensor, pressure sensor and image information.Also, as the spread of smartphones becomes common, techniques for determining the fall by using an acceleration sensor built in a smartphone are being studied. The proposed method has complexity due to fusion of various sensor data and it is still insufficient to develop practical application. Therefore, in this paper, we use acceleration sensor module built in smartphone to collect acceleration data, propose a simple falling algorithm based on accelerometer sensor data after normalization and preprocessing, and implement an Android based app.

• Special Issue of the Society of Naval Architects of Korea
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• 2008.09a
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• pp.33-37
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• 2008

The evidence of the Cargo tank volume is very important between Buyer and Seller for agreement each other for LNG Ship. CTS(Custody Transfer System) Radar type level gauging sensor to be measured for cargo volume. The data of Trim & List sensor to be compensated for measuring data which is original data of the CTS sensor. The latest days, the Buyer would have posed a problem both the location and the accuracy of trim/list sensor specially neared final stage of the ship's delivery. So, we would like to report the introducing to the trim/list sensor and the confirmation of actual location for the trim/list sensor.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.