• Title/Summary/Keyword: multiple sensor network

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Protocol implementation for simultaneous signal continuation acquisition of industrial plant machine condition in wireless sensor networks (산업플랜트 기계상태 동시신호 연속취득을 위한 무선센서 네트워크프로토콜 구현)

  • Lee, Hoo-Rock;Chung, Kyung-Yul;Rhyu, Keel-Soo
    • Journal of Advanced Marine Engineering and Technology
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    • v.39 no.7
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    • pp.760-764
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    • 2015
  • Wireless sensors, installed on machinery, and Time Division Multiple Access (TDMA) transmission make an ideal system for monitoring machine conditions in industrial plants because there is no need for electronic wiring. However, there has not yet been a successful field application of such a system, capable of continuously transmitting data at sample rates greater than 100 Hz. In this research, a TDMA network protocol capable of acquiring data from multiple sensors at sample rates greater than 100 Hz was developed for field application. The protocol was implemented in a single cluster-star topology network, and the system was evaluated based on the node number and transmission distance. Network simulator 2 (ns-2) was used for a real field simulation. Non-TDMA and TDMA protocol cases were compared using four sensor nodes. In the cases of 20-s and 40-s transmission times, there was little difference between the reception rates of the non-TDMA and TDMA systems. However, the difference was much greater when using a 60-s transmission time.

PathGAN: Local path planning with attentive generative adversarial networks

  • Dooseop Choi;Seung-Jun Han;Kyoung-Wook Min;Jeongdan Choi
    • ETRI Journal
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    • v.44 no.6
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    • pp.1004-1019
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    • 2022
  • For autonomous driving without high-definition maps, we present a model capable of generating multiple plausible paths from egocentric images for autonomous vehicles. Our generative model comprises two neural networks: feature extraction network (FEN) and path generation network (PGN). The FEN extracts meaningful features from an egocentric image, whereas the PGN generates multiple paths from the features, given a driving intention and speed. To ensure that the paths generated are plausible and consistent with the intention, we introduce an attentive discriminator and train it with the PGN under a generative adversarial network framework. Furthermore, we devise an interaction model between the positions in the paths and the intentions hidden in the positions and design a novel PGN architecture that reflects the interaction model for improving the accuracy and diversity of the generated paths. Finally, we introduce ETRIDriving, a dataset for autonomous driving, in which the recorded sensor data are labeled with discrete high-level driving actions, and demonstrate the state-of-the-art performance of the proposed model on ETRIDriving in terms of accuracy and diversity.

RRSEB: A Reliable Routing Scheme For Energy-Balancing Using A Self-Adaptive Method In Wireless Sensor Networks

  • Shamsan Saleh, Ahmed M.;Ali, Borhanuddin Mohd.;Mohamad, Hafizal;Rasid, Mohd Fadlee A.;Ismail, Alyani
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.7
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    • pp.1585-1609
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    • 2013
  • Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

Development of an Agricultural Data Middleware to Integrate Multiple Sensor Networks for an Farm Environment Monitoring System

  • Kim, Joonyong;Lee, Chungu;Kwon, Tae-Hyung;Park, Geonhwan;Rhee, Joong-Yong
    • Journal of Biosystems Engineering
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    • v.38 no.1
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    • pp.25-32
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    • 2013
  • Purpose: The objective of this study is to develop a data middleware for u-IT convergence in agricultural environment monitoring, which can support non-standard data interfaces and solve the compatibility problems of heterogenous sensor networks. Methods: Six factors with three different interfaces were chosen as target data among the environmental monitoring factors for crop cultivation. PostgresSQL and PostGIS were used for database and the data middleware was implemented by Python programming language. Based on hierarchical model design and key-value type table design, the data middleware was developed. For evaluation, 2,000 records of each data access interface were prepared. Results: Their execution times of File I/O interface, SQL interface and HTTP interface were 0.00951 s/record, 0.01967 s/record and 0.0401 s/record respectively. And there was no data loss. Conclusions: The data middleware integrated three heterogenous sensor networks with different data access interfaces.

Uniform Sensor-node Request Scheme for the Recovery of Sensing Holes on IoT Network (IoT 네트워크의 센싱홀 복구를 위한 센서 이동 균등 요청 방법)

  • Kim, Moonseong;Park, Sooyeon;Lee, Woochan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.16 no.4
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    • pp.9-17
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    • 2020
  • When IoT sensor nodes are deployed in areas where data collection is challenging, sensors must be relocated if sensing holes occur due to improper placement of sensors or energy depletion, and data collection is impossible. The sensing hole's cluster header transmits a request message for sensor relocation to an adjacent cluster header through a specific relay node. However, since a specific relay node is frequently used, a member sensor located in a specific cluster area adjacent to the sensing hole can continuously receive the movement message. In this paper, we propose a method that avoids the situation in which the sensing hole cluster header monopolizes a specific relay node and allows the cluster header to use multiple relay nodes fairly. Unlike the existing method in which the relay node immediately responds to the request of the header, the method proposed in this paper solves a ping-pong problem and a problem that the request message is concentrated on a specific relay node by applying a method of responding to the request of the header using a timer. OMNeT++ simulator was used to analyze the performance of the proposed method.

Development of Road-Following Controller for Autonomous Vehicle using Relative Similarity Modular Network (상대분할 신경회로망에 의한 자율주행차량 도로추적 제어기의 개발)

  • Ryoo, Young-Jae;Lim, Young-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.5
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    • pp.550-557
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    • 1999
  • This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

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A Study on Real time Multiple Fault Diagnosis Control Methods (실시간 다중고장진단 제어기법에 관한 연구)

  • 배용환;배태용;이석희
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.04b
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    • pp.457-462
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    • 1995
  • This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

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Wearable System for Real-time Monitoring of Multiple Vital Signs (인체 착용형 다중 생체신호 실시간 모니터링 시스템)

  • Lee, Young-Dong;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.249-252
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    • 2008
  • A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

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A High Efficiency Data Compression Scheme Based on Deletion of Bit-plain in Wireless Multimedia Sensor Networks (무선 멀티미디어 센서 네트워크에서 비트-평면 삭제를 통한 고효율 데이터 압축 기법)

  • Park, Junho;Ryu, Eunkyung;Son, Ingook;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.13 no.10
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    • pp.37-45
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    • 2013
  • In recent years, the demands of multimedia data in wireless sensor networks have been significantly increased for the high-quality environment monitoring applications that utilize sensor nodes. However, since the amount of multimedia data is very large, the network lifetime is significantly reduced due to excessive energy consumption on particular nodes. To overcome this problem, in this paper, we propose a high efficiency data compression scheme in wireless multimedia sensor networks. The proposed scheme reduces the packet size by a multiple compression technique that consists of primary compression that deletes the lower priority bits considering characteristics of multimedia data and secondary compression based on Chinese Remainder Theorem. To show the superiority of our scheme, we compare it with the existing compression scheme. Our experimental results show that our proposed scheme reduces the amount of transmitted data by about 55% and increases network lifetime by about 16% over the existing scheme on average.

Low-Cost Flexible Strain Sensor Based on Thick CVD Graphene

  • Chen, Bailiang;Liu, Ying;Wang, Guishan;Cheng, Xianzhe;Liu, Guanjun;Qiu, Jing;Lv, Kehong
    • Nano
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    • v.13 no.11
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    • pp.1850126.1-1850126.10
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    • 2018
  • Flexible strain sensors, as the core member of the family of smart electronic devices, along with reasonable sensing range and sensitivity plus low cost, have rose a huge consumer market and also immense interests in fundamental studies and technological applications, especially in the field of biomimetic robots movement detection and human health condition monitoring. In this paper, we propose a new flexible strain sensor based on thick CVD graphene film and its low-cost fabrication strategy by using the commercial adhesive tape as flexible substrate. The tensile tests in a strain range of ~30% were implemented, and a gage factor of 30 was achieved under high strain condition. The optical microscopic observation with different strains showed the evolution of cracks in graphene film. Together with commonly used platelet overlap theory and percolation network theory for sensor resistance modeling, we established an overlap destructive resistance model to analyze the sensing mechanism of our devices, which fitted the experimental data very well. The finding of difference of fitting parameters in small and large strain ranges revealed the multiple stage feature of graphene crack evolution. The resistance fallback phenomenon due to the viscoelasticity of flexible substrate was analyzed. Our flexible strain sensor with low cost and simple fabrication process exhibits great potential for commercial applications.