• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5115-5122
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• 2013

This paper has studied about the development and application of landslide collapse prediction real-time monitoring system based on USN to detect and measure the collapse of landslide. The rainfall measuring sensor, gap water pressure sensor, indicator displacement measuring sensor, index inclination sensor, water content sensor and image analysis sensor are selected and these are applied on the test bed. Each sensor's operation and performance for reliability verification is tested by the instrument which is installed in the field. As the result, u-IT based real-time landslide monitoring system which is developed by this research for landslide collapse detection could minimize life and property damages because it makes advance evacuation with collapse risk pre-estimate through real-time monitoring on roadside cut and bedrock slopes. This system is based on the results of this study demonstrate the effect escarpment plan are spread throughout.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.17 no.2
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• pp.33-37
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• 2011

Real time control logic of microbial shelf life of a perishable food, seasoned pork meat has been formulated which exploits monitoring of $CO_2$ concentration of the package. The potential of the proposed logic was examined for storage at dynamic temperature conditions. The start of increase in $CO_2$ production rate from the food or rate of package $CO_2$ concentration change was found to coincide with the point of microbial quality limit and could be used as an index of microbial shelf life determination. This also corresponded to lag time of $CO_2$ concentration change or time for the $CO_2$ concentration to reach a certain value. The application potential of the proposed logic was confirmed for a sensor system to measure on real time and transmit the $CO_2$ concentration wireless to the computer system.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.327-333
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• 2022

Wireless Sensor Networks (WSNs) plays an important role in our everyday life. WSN is distributed in all the places. Nowadays WSN devices are developing our world as smart and easy to access and user-friendly. The sensor is connected to all the resources based on the uses of devices and the environment [1]. In WSN, Quality of Service is based on time synchronization and scheduling. Scheduling is important in WSN. The schedule is based on time synchronization. Min-Max data size scheduling is used in this proposed work. It is used to reduce the Delay & Energy. In this proposed work, Two-hop neighboring node is used to reduce energy consumption. Data Scheduling is used to identify the shortest path and transmit the data based on weightage. The data size is identified by three size of measurement Min, Max and Medium. The data transmission is based on time, energy, delivery, etc., the data are sent through the first level shortest path, then the data size medium, the second level shortest path is used to send the data, then the data size is small, it should be sent through the third level shortest path.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.412-415
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• 2011

본 논문에서는 정적 무선 센서 네트워크상의 클러스터링 기법인 EECS(Energy Efficient Clustering Scheme)의 노드와 Base Station간의 거리를 고려한 head 선출 과정에 노드의 이동성 및 미래 위치 예측을 융합하여 확장한 새로운 동적환경상의 클러스터링 기법 EECS-M(Energy Efficient Clustering Scheme in Mobile wireless sensor networks)을 제안한다. 실험을 통하여 EECS-M이 동적 환경상의 LEACH-M, WCA 및 정적 환경상의 EECS, LEACH 클러스터링 알고리즘들에 비해 life time 및 life time 대비 네트워크의 잔여 에너지 측면에서 성능향상을 가진다는 것을 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.427-429
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• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.99-111
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• 2009

In wireless sensor networks, various schemes have been proposed to store and process sensed data efficiently. A Data-Centric Storage(DCS) scheme assigns distributed data regions to sensors and stores sensed data to the sensor which is responsible for the data region overlapping the data. The DCS schemes have been proposed to reduce the communication cost for transmitting data and process exact queries and range queries efficiently. Recently, KDDCS that readjusts the distributed data regions dynamically to sensors based on K-D tree was proposed to overcome the storage hot-spots. However, the existing DCS schemes including KDDCS suffer from Query Hot-Spots that are formed if the query regions are not uniformly distributed. As a result, it causes reducing the life time of the sensor network. In this paper, we propose a new DCS scheme, called TPDCS(Time-Parameterized DCS), that avoids the problems of storage hot-spots and query hot-spots. To decentralize the skewed. data and queries, the data regions are assigned by a time dimension as well as data dimensions in our proposed scheme. Therefore, TPDCS extends the life time of sensor networks. It is shown through various experiments that our scheme outperform the existing schemes.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.265-270
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• 2019

The technology to locate an individual has enabled various services, its utilization has increased. There were constraints such as the use of separate expensive equipment or the installation of specific devices on a facility, with most of the location technology studies focusing on the accuracy of location verification. These constraints can result in accuracy within a few tens of centimeters, but they are not technology that can be applied to a user's location in real-time in daily life. Therefore, this paper aims to track the locations of smartphones only using the basic components of smartphones. Based on smartphone sensor data, localization accuracy that can be used for verification of the users' locations is aimed at. Accelerometers, Wifi radio maps, and GPS sensor information are utilized to implement it. In forging the radio map, signal maps were built at each vertex based on the graph data structure This approach reduces traditional map-building efforts at the offline phase. Accelerometer data were made to determine the user's moving status, and the collected sensor data were fused using particle filters. Experiments have shown that the average user's location error is about 3.7 meters, which makes it reasonable for providing location-based services in everyday life.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.493-501
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• 2014

Coverage completeness is an important indicator for quality of service in wireless sensor networks (WSN). Due to limited energy and diverse working conditions, the sensor nodes have different lifetimes which often cause network holes. Most of the existing methods expose large limitation and one-sidedness because they generally consider only one aspect, either coverage rate or energy issue. This paper presents a novel method for coverage hole detection with residual energy in randomly deployed wireless sensor networks. By calculating the life expectancy of working nodes through residual energy, we make a trade-off between network repair cost and energy waste. The working nodes with short lifetime are screened out according to a proper ratio. After that, the locations of coverage holes can be determined by calculating the joint coverage probability and the evaluation criteria. Simulation result shows that compared to those traditional algorithms without consideration of energy problem, our method can effectively maintain the coverage quality of repaired WSN while enhancing the life span of WSN at the same time.

• Journal of Biomedical Engineering Research
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• v.39 no.6
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• pp.278-283
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• 2018

Nowdays, many people suffer from the neck pain due to forward head posture(FHP) and text neck(TN). To assess the severity of the FHP and TN the craniovertebral angle(CVA) is used in clinincs. However, it is difficult to monitor the neck posture using the CVA in daily life. We propose a new method using the cervical flexion angle(CFA) obtained from a wearable sensor to monitor neck posture in daily life. 15 participants were requested to pose FHP and TN. The CFA from the wearable sensor was compared with the CVA observed from a 3D motion camera system to analyze their correlation. The determination coefficients between CFA and CVA were 0.80 in TN and 0.57 in FHP, and 0.69 in TN and FHP. From the monitoring the neck posture while using laptop computer for 20 minutes, this wearable sensor can estimate the CVA with the mean squared error of 2.1 degree.