• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.62-66
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• 2014

This study aims to implement the emergency monitoring robot system which predicts the current state of the patients without visiting the medical institutions by measuring the basic health status of the user's blood pressure, heartbeat, and basic health status of body temperature in the disaster emergency situation based on the Smart Grid. By arranging a large number of sensor(blood pressure, heartbeat, body temperature sensor) and measuring the bio signs, so the attached wireless XBee sensor can be stored in DB of robot, and it aims to draw the current state of the patients by analysis of stored bio data. Among 300 data obtained from the sensor, 1st data to 100th data were used for learning, and from 101st data to 300th data were used for assessment. 12 results were different among the total 300 assessment data, so it shows about 96% accuracy.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.25-33
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• 2021

Energy-harvesting wireless sensor networks(EH-WSNs) can collect energy from the environment and overcome the technical limitations of existing power. Since the transmission distance in a wireless sensor network is limited, the data are delivered to the destination node through multi-hop routing. In EH-WSNs, the routing protocol should consider the power situations of nodes, which is determined by the remaining power and energy-harvesting rate. In addition, in applications such as environmental monitoring, when there are urgent data, the routing protocol should be able to transmit it stably and quickly. This paper proposes an adaptive routing protocol that satisfies different requirements of normal and urgent data. To extend network lifetime, the proposed routing protocol reduces power imbalance for normal data and also minimizes transmission latency by controlling the transmission power for urgent data. Simulation results show that the proposed adaptive routing can improve network lifetime by mitigating the power imbalance and greatly reduce the transmission delay of urgent data.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.115-122
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• 2017

In this paper, we propose an adaptive data aggregation and compression scheme for wireless sensor networks with energy-harvesting nodes, which increases the amount of data arrived at the sink node by efficient use of the harvested energy. In energy-harvesting wireless sensor networks, sensor nodes can have more than necessary energy because they harvest energy from environments continuously. In the proposed scheme, when a node judges that there is surplus energy by estimating its residual energy, the node compresses and transmits the aggregated data so far. Conversely, if the residual energy is estimated to be depleted, the node turns off its transceiver and collects only its own sensory data to reduce its energy consumption. As a result, this scheme increases the amount of data collected at the sink node by preventing the blackout of relay nodes and facilitating data transmission. Through simulation, we show that the proposed scheme suppresses the occurrence of blackout nodes and collect the largest amount of data at the sink node compared to previous schemes.

• The KIPS Transactions:PartC
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• v.17C no.5
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• pp.433-440
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• 2010

Energy efficiency, low latency and scalability for wireless sensor networks are important requirements, especially, the wireless sensor network consist of a large number of sensor nodes should be minimized energy consumption of each node to extend network lifetime with limited battery power. An efficient algorithm and energy management technology for minimizing the energy consumption at each sensor node is also required to improve transfer rate. Thus, this paper propose no-overlap multi-pass protocol provides for sensor data transmission in the wireless sensor network environment. The proposed scheme should minimize network overhead through reduced a sensor data translation use to searched multi-path and added the multi-path in routing table. Proposed routing protocol may minimize the energy consumption at each node, thus prolong the lifetime of the sensor network regardless of where the sink node is located outside or inside the received signal strength range. To verify propriety proposed scheme constructs sensor networks adapt to current model using the real data and evaluate consumption of total energy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.341-351
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• 2008

Communication in wireless sensor networks comprising a plurality of sensor nodes located in an ad hoc environment is unidirectional in that data gathered by sensor nodes are transmitted to a sink node and not vice versa. In those networks, it is not possible for a server or a gateway to send commands to the sensor nodes to determine whether some previously received data are valid when the data indicate unusual conditions, which makes it difficult to make appropriate reactions to the unusual situations. This paper proposes and implements a TDMA-based sensor network communication protocol named BiWSLP(Bidirectional Wireless Sensor Line Protocol) supporting bidirectional communication capability. The BiWSLP is an extension of the WSLP, a unidirectional sensor network communication protocol based on the TDMA protocol. To test the feasibility of the proposed BiWSLP, we construct a virtual bridge management system capable of sending commands to sensor nodes as well as collecting data from the sensor nodes. Based on the test results of the virtual bridge management system, we show the applicability and advantages of the BiWSLP in terms of energy efficiency and bidirectional communication capability.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.668-671
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• 2004

This paper proposes a new method of sensor fusion of an ultrasonic sensor and a vision sensor at the sensor level. In general vision system, the vision system finds edges of objects. And in general ultrasonic system, the ultrasonic system finds absolute distance between robot and object. So, the method integrates data of two different types. The system makes perfect output for robot control in the end. But this paper does not propose only integrating a different kind of data but also fusion information which receives from different kind of sensors. This method has advantages which can simply embody algorithm and can control robot on real time.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.523-529
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• 2009

Smart sensor is known as intelligent sensor, it is different with other conventional sensors in the case of intelligent system embedded on it. Smart sensor has many benefits e.g. low-cost in usage, self-decision and self-diagnosis abilities. This sensor consists of perception element(sensing element), signal processing and technology of communication. In this work, a bridge and structure of smart sensor has been investigated to be capable to condition monitoring routine. This investigation involves low power consumption, software programming, fast data acquisition ability, and authoritativeness warranty. Moreover, this work also develops smart sensor to be capable to perform high sampling rate, high resolution of ADC, high memory capacity, and good communication for data transfer. The result shows that the developed smart sensor is promising to be applied to various industrial fields.

• The Journal of Information Technology
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• v.12 no.3
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• pp.1-6
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• 2009

This paper has focused on the development of an educational sensor network (ESN) based on wireless sensor networks(WSN) and pervasive monitoring systems for students' activity during scientific experiments. A number of WSN systems have been proposed with integrated wireless transmission, mounted sensor boards and local processing. However, there is no trail to employ WSN on the educational field. In this paper, to facilitate research and development using wireless sensor network and multi-sensor data fusion, the educational sensor network (ESN) hardware development platform is presented. The ESN project is conducted over one semester time period (Spring Semesters). It involves approximately twenty middle school students who enrolled a gifted program in Kongju National University. Though under prepared, these students are in general highly motivated to learning specially when presented with the ESN project. An ESN project such as this is expected to provide an excellent means for teaching and learning scientific and mathematical principles.

• International Journal of Contents
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• v.11 no.2
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• pp.31-36
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• 2015

Recent years have seen a significant increase in demand for multimedia data over wireless sensor networks for monitoring applications that utilize sensor nodes to collect multimedia data, including sound and video. However, the multimedia streams generate a very large amount of data. When data transmission schemes for traditional wireless sensor networks are applied in wireless multimedia sensor networks, the network lifetime significantly decreases due to the excessive energy consumption of specific nodes. In this paper, we propose a data compression scheme that implements the Chinese remainder theorem to a wireless multimedia sensor network. The proposed scheme uses the Chinese Remainder Theorem (CRT) to compress and split multimedia data, and it then transmits the bit-pattern packets of the remainder to the base station. As a result, the amount of multimedia data that is transmitted is reduced. The superiority of our proposed scheme is demonstrated by comparing its performance to that of an existing scheme. The results of our experiment indicate that our proposed scheme significantly increased the compression ratio and reduced the compression operation in comparison to those of existing compression schemes.