• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.27-38
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• 2017

This Paper Presents a Method for Stitching a Large Number of Images Recorded by a Large Number of Individual Users Through a Cellular Phone Camera at a Venue. In Contrast to 360 Camera Solutions that Use Existing Fixed Rigs, these Conditions must Address New Challenges Such as Time Synchronization, Repeated Transformation Matrix Calculations, and Camera Sensor Mismatch Correction. In this Paper, we Solve this Problem by Updating the Transformation Matrix Using Time Synchronization Method Using Audio, Sensor Mismatch Removal by Color Transfer Method, and Global Operation Stabilization Algorithm. Experimental Results Show that the Proposed Algorithm Shows better Performance in Terms of Computation Speed and Subjective Image Quality than that of Screen Stitching.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.725-731
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• 2013

In This paper, through simulation, proposes a system which makes it possible for freely moving multiple agents with ultrasonic receivers to estimate their own position by themselves using the ultrasonic signals sequentially emitted from multiple ultrasonic transmitters. This system possesses an advantage that there is no limit in the number of agents existing in the space covered by more than three transmitters fixed at proper locations. Hence, the proposed system can be utilized effectively in position tracking control of multiple robotic agents system and motion capturing system.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1779-1780
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• 2006

오늘날 대부분의 감시 시스템은 유선에 의한 계측 시스템을 사용하고 있다. 하지만, 유선 감시 시스템은 흩어져 있는 많은 지점의 데이터를 측정하기 어렵고, 초기 설치시나 변경 시에 많은 비용이 소요된다. 우리나라에는 다수의 통신 기지국이 설치되어 있어, 무선 통신망의 구축이 잘 되어 있기 때문에 무선 통신망을 계측 시스템에 적용할 경우 이용하기 용이하고 계측 된 데이터를 송수신시 소모되는 비용 또한 저렴하다. 때문에, 넓게 분포되어 있는 지점의 데이터 측정에는 무선 통신망을 이용하는 것이 유선 계측 시스템의 여러 단점들을 보완할 수 있어 시스템 구성 및 관리에 유리하다. 무선 감시 시스템은 넘게 분포된 불특정 지점의 데이터를 측정할 수 있으며, 무선 통신에 기본적으로 사용되는 시간 정보를 이용하여 여러 계측기의 데이터를 동시에 측정할 수 있다. 또한 센서에서 데이터를 메인 서버로 전송하는 동작 이외에 메인 서버의 명령으로 센서에서 데이터를 취득하여 메인 서버로 재전송할 수 있는 양방향 통신의 구축 또한 용이하다. 본 논문에서는 CDMA 모듈을 통한 무선 통신을 이용하여 여러 지점의 데이터를 동시에 계측할 수 있는 양방향 통신 시스템 구축에 관하여 연구한다.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.974-975
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• 2006

본 논문에서는 대용량 전력 변환 장치이며 출력 전압 가변이 가능한 H-브릿지 멀티레벨 인버터의 제어 알고리즘을 제안한다. H-브릿지 멀티레벨 인버터는 독립적으로 절연된 직류 부를 갖는 저압의 단상 인버터(셀 유닛)를 다수 직렬 접속하여 고압 3상 전압을 출력하는 Cascaded H-bridge 전압형 인버터이다. 다수의 독립 절연 직류부를 만들기 위해 입력 측에 다권선 변압기를 사용하여 입력 측 고조파 함유율을 축소시킬 수 있다. 인버터를 사용하는 제어방법 중 가장 오래되고 일반적인 방법으로 출력전압과 출력 주파수의 비를 일정하게 제어하여 전동기의 자속 크기를 일정하게 제어하고, 별도의 센서 없이도 운전이 가능한 V/F 제어모드는 저속 모드에서 제어 성능이 떨어지는 것을 실험을 통해 확인할 수 있었다. 정격용량 180kVA이고 출력 전압 480V인 H-브릿지 멀티 레벨 인버터 실험을 통해 벡터제어와 센서리스 벡터제어를 구현하여 저속 모드에서 제어 성능의 향상을 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.276-279
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• 2019

본 논문은 실내 온도, 습도, 조도, 그리고 토양의 습도까지 탐지하여 자동으로 습도와 빛을 조절해주는 스마트 화분을 다룬다. 화분은 일상생활에서 구할 수 있는 화분을 사용했고 다양한 꽃의 생육 정보를 모은 DB를 기반으로 아두이노를 통해서 다양한 센서 값들을 측정하고 모인 센서 값들은 라즈베리파이로 보내진다. 화분에 부착된 다수의 아두이노로부터 온 데이터를 라즈베리파이가 분석하고 판단해서 사용자에게 전달해주고 조치가 필요한 부분은 아두이노에 전송되어 알맞은 처리가 이뤄진다. 이때 다수의 아두이노와 라즈베리파이의 통신은 지그비 통신이며 라즈베리파이와 사용자 간의 통신은 블루투스와 클라우드 서버를 통해 이루어진다.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.11
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• pp.572-580
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• 2007

Wireless sensor networks are sensing, computing and communication infrastructures that allow us to monitor, instrument, observe, and respond to phenomena in the harsh environment. Generally, the wireless sensor networks are composed of many deployed sensor nodes that were designed to be very cost-efficient in terms of production cost. For example, UC Berkeley's MICA motes have only 8-bit CPU, 4KB RAM, and 128KB FLASH memory space. Therefore, sensor operating systems that run on the sensor nodes should be able to operate efficiently in terms of the resource management. In this paper, we present a dynamic threads stack management scheme for space-constrained and multi-threaded sensor operating systems. In this scheme, the necessary stack space of each function is measured on compile-time. Then, the information is used to dynamically allocate and release each function's stack space on run-time. It was implemented in Nano-Qplus sensor operating system. Our experimental results show that the proposed scheme outperforms the existing fixed-size stack allocation mechanism.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.95-102
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• 2007

Recently, a lot of researchers focus on the sensor middleware that hide the complexity of application developments and provide the abstraction of functions to upper application layer. Although there we several factors to design sensor middleware, the attribute-based naming is considered to be an essential factor among them. However, most existing researches were not designed to reflect the characteristics of sensor networks and have the limitation of attribute-based query extension. This study adopts the concept of Virtual Counterpart to suggest the structure there attribute-based naming is supported by virtual sensor nodes of the middleware on the sink node. Unlike traditional data-centric middleware in which individual sensor nodes process attribute-based query, virtual sensor nodes mapped to physical sensor nodes are running on the middleware of the sink node and process attribute-based query as a proxy of the physical sensor. This approach enables attribute-based naming independent of physical infrastructure and easy extensibility.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.47-56
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• 2015

In the multi-sensor system, sensor registration errors such as a sensor bias must be corrected so that the individual sensor data are expressed in a common reference frame. If registration process is not properly executed, large tracking errors or formation of multiple track on the same target can be occured. Especially for launch vehicle tracking system, each multiple observation lies on the same reference frame and then fused trajectory can be the best track for slaving data. Hence, this paper describes an on-line bias estimation/correction and asynchronous sensor fusion for launch vehicle tracking. The bias estimation architecture is designed based on pseudo bias measurement which derived from error observation between GPS and radar measurements. Then, asynchronous sensor fusion is adapted to enhance tracking performance.

• Journal of KIISE
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• v.42 no.1
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• pp.114-121
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• 2015

Large-scale wireless sensor networks are constructed by using a large number of sensor nodes that are non-uniformly deployed over a wide area. As a result, the data collected by the sensor nodes are similar to that from one another since a high density of the sensor nodes may cause an overlap. As a result of the characteristics of the traffic, data is collected from a plurality of sensor nodes by a sink node, and when the sensor nodes transmit their collected data to the sink node, the sensor nodes around the sink node have a higher amount of traffic than the sensor nodes far away from the sink node. Thus, the former sensor encounter bottlenecks due to traffic congestion and have an energy hole problem more often than the latter ones, increasing energy consumption. This paper proposes a congestion control scheme that considers traffic flows in order to control traffic congestion of the sensor nodes that are non-uniformly deployed over a large-scale wireless sensor network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.771-778
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• 2019

The traditional illuminance intensity detection method using a single sensor has a problem that uniformity of illuminance detection is deteriorated depending on the measurement position due to the narrow FOV characteristic. In order to overcome this problem, a method of detecting an average illuminance value through a plurality of illuminance sensors is used, but the complexity and detection error are increased. In this paper, we propose a illuminance intensity detection method based on a single image sensor with wide FOV. The proposed method can solve the problems such as system complexity and error increase of existing illuminance sensor. The test results show that the difference of average value is 12% using a illuminance sensor, 10.7% using five illuminance sensors, and 6.2% using an image sensor compared with the reference value using the color difference illuminometer. It is confirmed that the proposed method can easily and accurately detect the space illuminance with improved uniformity.