• 센서학회지
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• 제32권6호
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• pp.475-480
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• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.371-374
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• 2009

본 논문은 대한민국 해군의 차세대호위함인 FFX(Fast Frigate eXperimental)에 장착/운용되는 LAS(Line Array Sensor, 예인배열형센서)로부터 A,B,C 그룹 수중음향신호의 시리얼 데이터를 입력받아 약속된 Protocol로 Packing하여, 고속 데이터통신과 Optic-fiber채널 장거리 전송이 가능한 SFM(Serial FPDP Module)을 통해 신호처리단으로 실시간 전송하는 센서데이터입출력처리보드의 설계/제작 및 시험에 관해 논한다. VME 6U크기의 한정된 보드 공간을 고려하여 Freescale사의 PowerPC계열인 MPC8265 CPU와, FIFO등의 외부디바이스를 줄이고 자체시뮬레이션 데이터생성등을 위해 Altera사의 CycloneIII 계열 FPGA등을 사용하여 설계하고, 실시간 데이터 전송을 보장하며 각종 Device Driver, Peripheral Controller등의 Library를 제공하는 RTOS인 VxWorks를 Porting하여 소프트웨어를 개발하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.353-355
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• 2018

The aim of this paper is Although a large amount of sensor data is generated in the manufacturing process of a manufacturing company and the necessity of utilizing sensor data is felt, there is a real difficulty in collecting a large amount of sensor data and introducing analysis / service. Using W3C Web document standard format, XML based technology, it collects data to provide production status and equipment status information, and researches middleware for sensor data processing that user can analyze.

• 인터넷정보학회논문지
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• 제10권4호
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• pp.35-44
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• 2009

데이터 스트림이란 새로운 개념과 기존의 단순 데이터 사이에 존재하는 개념적 차이를 극복하기 위해서는 많은 연구가 필요하다. 대표적인 예로써 센서 네크워크에서의 데이터 스트림 처리를 들 수 있는 데, 이를 위해서는 대역폭이나 에너지, 메모리와 같은 자원적 한계에서 부터 연속 질의를 포함하는 질의처리의 특수성까지 고려해야 할 대상이 광범위하다. 본 논문에서는 데이터 스트림 처리에서의 물리적 제약사항에 해당하는 한정된 메모리 문제를 해결하기 위해 PCA 기법을 기반으로 하는 데이터 스트림 축소 방안을 제안하다. PCA는 상호 관련된 다수의 변수들을 관련이 없는 적은 수의 변수로 변환해준다. 본 논문에서는 질의 처리 엔진의 협력을 가정하고서 센서 네크워크의 스트림 데이터 처리를 위해 PCA 기법을 적용하며, 다른 센서로부터 얻어진 많은 측정값 사이에 시공간적 관련성을 이용한다. 최종적으로 그러한 데이터 처리를 위한 프레임워크를 제시하고 다양한 실험을 통하여 기법의 성능을 분석한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.870-872
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• 2007

Sensor networks have been widely applied for data collection. Due to the energy limitation of the sensor nodes and the most energy consuming data transmission, we should allocate as much work as possible to the sensors, such as data compression and aggregation, to reduce data transmission and save energy. Querying extreme values is a general query type in wireless sensor networks. In this paper, we propose a novel querying method called Two-Level Filter (TLF) for querying extreme values in wireless sensor networks. We first divide the whole sensor network into domains using the Distributed Data Aggregation Model (DDAM). The sensor nodes report their data to the cluster heads using push method. The advantages of two-level filter lie in two aspects. When querying extreme values, the number of pull operations has the lower boundary. And the query results are less affected by the topology changes of the wireless sensor network. Through this method, the sensors preprocess the data to share the burden of the base station and it combines push and pull to be more energy efficient.

• 정보처리학회논문지C
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• 제14C권1호
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• pp.105-114
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• 2007

센서네트워크 환경에서 이동객체의 위치추적방법은 추적방법론에 따라 데이터의 수신과 위치추적의 정확성에 문제가 있었으며, 이러한 위치데이터는 오로지 위치 추적만을 위한 데이터이었기에 주변의 환경 데이터를 활용하여 상황에 맞는 정보판단 또는 모니터링에 한계가 있었다. 이러한 한계를 극복하기 위한 방법으로 상황인식(context aware)을 종종 활용하는데, 본 문은 자기센서를 기반으로 측정된 자성체(magnetic line tracer)의 자성데이터 위치 추적 및 제어에 관한 데이터처리에 상창인식을 활용한 방법을 제안하였다. 제안된 방법은 센서네트워크 노드의 자기센서의 자성데이터 측정과 주변 환경정보 데이터를 이용하였고, 이러한 데이터를 상황인식 데이터베이스의 엔트리로 구성함으로써 추후 행동정보 추론 및 제어할 수 있다. 아울러 제안된 방법의 타당성을 검증하기 위하여 센서네트워크 환경을 만족하는 테스트베드를 구축하였으며, 이를 이용한 라인트레이서의 위치 추적과 경로탐색의 결과를 도출하였으며, 도출된 데이터를 근거로 하여 주변 환경정보 데이터베이스 엔트리 및 상황인식에 따른 라인트레이서의 방향제어에 미치는 영향을 분석하였다.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.625-628
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• 2011

Dynamic sensor network(DSN) technology which is based on swarming flight type air node offers analyzed and acquired information on target data gathered by air nodes in rotation flight or 3 dimension array flight. Efficient operation of dynamic sensor network based on air node is possible when problems of processing time, data transmission reliability, power consumption and intermittent connectivity are solved. Delay tolerant network (DTN) can be a desirable alternative to solve those problems. DTN using store-and-forward message switching technology is a solution to intermittent network connectivity, long and variable delay time, asymmetric data rates, and high error rates. However, all processes are performed at the bundle layer, so high power consumption, long processing time, and repeated reliability technique occur. DSN based on swarming flight type air node need to adopt store-and-forward message switching technique of DTN, the cancelation scheme of repeated reliability technique, fast processing time with simplified layer composition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4908-4928
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• 2017

Recent research into wireless sensor network (WSN)-related technology that senses various data has recognized the need for spatio-temporal queries for searching necessary data from wireless sensor nodes. Answers to the queries are transmitted from sensor nodes, and for the efficient transmission of the sensed data to the application server, research on index processing methods that increase accuracy while reducing the energy consumption in the node and minimizing query delays has been conducted extensively. Previous research has emphasized the importance of accuracy and energy efficiency of the sensor node's routing process. In this study, we propose an itinerary-based R-tree (IR-tree) to solve the existing problems of spatial query processing methods such as efficient processing and expansion of the query to the spatio-temporal domain.

• International journal of advanced smart convergence
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• 제6권3호
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• 제어로봇시스템학회논문지
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• 제14권7호
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• pp.720-725
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• 2008

This paper proposes a system architecture for USN with a service robot to provide more active assisted living services for elderly persons by monitoring their mental and physical well-being with USN environments at home, hospital, or silver town. Sensors embedded in USN are used to detect preventive measures for chronic disease. Logged data are transferred to main controller of a service robot via wireless channel in which the analysis of data is performed. For the purpose of handling emergency situations, it needs real-time processing on gathering variety sensor data, routing algorithms for sensor nodes to a moving sink node and processing of logged data. This paper realized multi-hop sensor network to detect user movements with biometric data transmission and performed algorithms on Xenomai, a real-time embedded Linux. To leverage active sensing, a mobile robot is used of which task was implemented with a priority to process urgent data came from the sink-node. This software architecture is anticipated to integrate sensing, communication and computing with real-time manner. In order to verify the usefulness of a proposed system, the performance of data transferring and processing on a real-time OS with non real-time OS is also evaluated.