• 한국해양공학회지
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• 제24권3호
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• pp.1-10
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• 2010

In this study, hybrid smart sensor nodes were developed for the autonomous structural health monitoring of prestressed concrete (PSC) girders. In order to achieve the objective, the following approaches were implemented. First, we show how two types of smart sensor nodes for the hybrid health monitoring were developed. One was an acceleration-based smart sensor node using an MEMS accelerometer to monitor the overall damage in concrete girders. The other was an impedance-based smart sensor node for monitoring the local damage in prestressing tendons. Second, a hybrid monitoring algorithm using these smart sensor nodes is proposed for the autonomous structural health monitoring of PSC girders. Finally, we show how the performance of the developed system was evaluated using a lab-scaled PSC girder model for which dynamic tests were performed on a series of prestress-loss cases and girder damage cases.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.711-730
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• 2010

This study presents the design of autonomous smart sensor nodes for damage monitoring of tendons and girders in prestressed concrete (PSC) bridges. To achieve the objective, the following approaches are implemented. Firstly, acceleration-based and impedance-based smart sensor nodes are designed for global and local structural health monitoring (SHM). Secondly, global and local SHM methods which are suitable for damage monitoring of tendons and girders in PSC bridges are selected to alarm damage occurrence, to locate damage and to estimate severity of damage. Thirdly, an autonomous SHM scheme is designed for PSC bridges by implementing the selected SHM methods. Operation logics of the SHM methods are programmed based on the concept of the decentralized sensor network. Finally, the performance of the proposed system is experimentally evaluated for a lab-scaled PSC girder model for which a set of damage scenarios are experimentally monitored by the developed smart sensor nodes.

• 한국멀티미디어학회논문지
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• 제17권4호
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• pp.458-465
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• 2014

In this paper, we propose a strategy to distribute the energy consumption over the network. The proposed strategy is based on geographic routing. We use a smart base station that maintains the residual energy and location information of sensor nodes and selects a head node and an anchor node using this information. A head node gathers and aggregates data from the sensor nodes in a target region that interests the user. An anchor node then transmits the data that was forwarded from the head node back to the smart base station. The smart base station extends network lifetime by selecting an optimal head node and an optimal anchor node. We simulate the proposed protocol and compare it with the LEACH protocol in terms of energy consumption, the number of dead nodes, and a distribution map of dead node locations.

• Smart Structures and Systems
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• 제10권3호
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• pp.271-298
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• 2012

Researchers have made significant progress in recent years towards realizing effective structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and distributed, in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low power design and operation are still critically important. This research presents the WiSeMote: a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM deployments. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.193-196
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• 2007

최근 무선 통신 기술과 초소형화 기술의 진보로 지능형 센서 (smart sensor)를 이용한 무선 센서 네트워크의 구축이 가능해 졌으며 무선 센서 네트워크를 우리 생활 전반에 걸친 다양한 분야에 응용하려는 연구가 활발하게 진행되고 있다[1]. 본고에서는 무선 센서 네트워크의 응용분로서 무선센서노드를 활용한 캠퍼스 차량 관리 시스템 구축 방안에 대하여 기술하였다. 이를 위하여 무선센서노드의 전송전력제어 및 개별 노드 인식 방안을 고찰하였으며 실제 적용 시스템의 구성 및 동작 절차를 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• 한국통신학회논문지
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• 제39C권11호
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• pp.1146-1150
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• 2014

최근 스마트선박 기술 관련 연구에 대한 관심이 증가하고 있다. 또한 스마트선박 기술의 발달로 데이터가 sensor node들에 의해 수집되면서 전송횟수의 증가로 인해 network의 과부하를 야기할 수 있다. 따라서 본 논문에서는 스마트선박 내부의 sensor node에 대한 data 전송횟수에 대한 빈도수를 줄이기 위해 data fusion를 이용하여 data를 가공 처리하는 기법을 적용하였다. 스마트선박 내부에서 수집되는 data는 의미 있는 data 가공하여 센터로 전송되어 network의 부하를 줄이고 효율적으로 data를 전송할 수 있는 방안을 제시하였다.

• Smart Structures and Systems
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• 제7권5호
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• pp.393-416
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• 2011

Hybrid acceleration-impedance sensor nodes on Imote2-platform are designed for damage monitoring in steel girder connections. Thus, the feasibility of the sensor nodes is examined about its performance for vibration-based global monitoring and impedance-based local monitoring in the structural systems. To achieve the objective, the following approaches are implemented. First, a damage monitoring scheme is described in parallel with global vibration-based methods and local impedance-based methods. Second, multi-scale sensor nodes that enable combined acceleration-impedance monitoring are described on the design of hardware components and embedded software to operate. Third, the performances of the multi-scale sensor nodes are experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints.

• 스마트미디어저널
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• 제3권1호
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• pp.28-32
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• 2014

It is practical nowadays to automate data recording in order to prevent loss and tampering of records. There are existing technologies that satisfy this needs and one of them is wireless sensor networks (WSN). Wireless body sensor networks (WBSN) are wireless networks and information-processing systems which are deployed to monitor medical condition of patients. In terms of performance, WBSNs are restricted by energy, and communication between nodes. In this paper, we focused in improving the performance of communication to achieve less energy consumption and to save power. The main idea of this paper is to prioritize nodes that exhibit a sudden change of vital signs that could put the patient at risk. Cluster head is the main focus of this study in order to be effective; its main role is to check the sent data of the patient that exceeds threshold then transfer to the sink node. The proposed scheme implemented added a time-based protocol to sleep/wakeup mechanism for the sensor nodes. We seek to achieve a low energy consumption and significant throughput in this study.