• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.397-400
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• 2007

Indoor air-conditioning system(IAS) using wireless sensor network serves to reduce the amount of pollution entering the room from outside and also the pollution that is generated indoor. Small-size and lower power wireless sensor node and sensor interface board was designed for indoor air-conditioning system in buildings of offices and industrial establishments. Many sensor nodes forms Ad-hoc network topology using simple forwarding routing to transmit polluting gas concentration data from different rooms to the indoor air-conditioning system. Sensor node analyzes pollution concentration in the each room and air-conditioning system performs to air-distribution and air-inhalation according to room's pollution by regulating the fan of indoor air-conditioning system. To reduce power consumption electrochemical gas sensor was used in the design. Thus the designed system can optimize state of indoor environment. Graphic user interface displays node sate, gas concentration and temperature of each room.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.385-390
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• 2008

The Study of environment monitoring through huge network of wireless sensor node is worked with activity. The sensor nodes must be very small, light and low cost. The localization which may determine where a given node is physically located in a network is one of the quite important problems for wireless sensor network. But simple localization method is required as excluding the usage of GPS(Global Positioning System) by the limit condition such as the node size, costs, and so on. In this paper, very simple method using connectivity for the outdoor RF communication environment is proposed. The proposed method is demonstrated through simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.357-360
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• 2007

An asset tracking using wireless sensor network is concerned with geographical locations of sensor nodes. The limited size of sensor nodes makes them attractable for tracking service, at the same time their size causes power restrictions, limited computation power, and storage restrictions. Due to such constrained capabilities, the wireless sensor network basically assumes the failure of sensor nodes. This causes a set of concerns in designing asset tracking system on wireless sensor network and one of the most critical factors is location uncertainty of sensor nodes. In this paper, we classify the location uncertainty problem in asset tracking system into following cases. First, sensor node isn't read at all because of sensor node failure, leading to misunderstanding that asset is not present. Second, incorrect location is read due to interference of RSSI, providing unreliable location of asset. We implemented and installed our asset tracking system in a real environment and continuously monitored the status of asset and measured error rate of location of sensor nodes. We present experimental results that demonstrate the location uncertainty problem in asset tracking system using wireless sensor network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.699-700
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• 2010

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.465-471
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• 2007

Many hospitals have been considering new technology such as wireless sensor network(WSN). The technology can be used to track the location of medical devices needed for inspections or repairs, and it can also be used to detect of a theft of an asset. In an asset-tracking system using WSN, acquiring the location of moving sensor nodes inherently introduces uncertainty in location determination. In fact, the sensor nodes attached to an asset are prone to failure from lack of energy or from physical destruction. Therefore, even if the asset is located within the predetermined area, the asset-tracking application could "misunderstand" that an asset has escaped from the area. This paper classifies the causes of such unexpected situations into the following five cases: 1) an asset has actually escaped from a predetermined area; 2) a sensor node was broken; 3) the battery for the sensor node was totally discharged; 4) an asset went into a shadow area; 5) a sensor node was stolen. We implemented and installed our asset-tracking system in a hospital and continuously monitored the status of assets such as ventilators, syringe pumps, wheel chairs and IV poles. Based on this real experience, we suggest how to differentiate each case of location uncertainty and propose possible solutions to prevent them.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.3
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• pp.152-156
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• 2009

This paper designs and implements wake up module for WBAN/USN sensor node which is using dynamic reference voltage demodulation circuit. When a comparator is used in a system for detecting received voltage level, comparator must have a reference voltage. However, the reference voltage is fixed, the system can communicate only a few range because received voltage level is changing widely due to distance of the wireless sensor nodes. Therefore, the proposed wake up module employs a dynamic reference voltage demodulation circuit for increasing communication range.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4536-4544
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• 2014

This paper proposes a development tool to efficiently develop node software for various operating system platforms in a sensor network. The proposed tool consisted of several modules, such as writing graphical model diagram, PIM and PSM design, code generation, and deployment file generation. Through the proposed tool, the users can graphically draw a sensor network model and design the PIM and PSM of the node software by setting the values of the predefined attributes. The source code of the node software is generated automatically from the PSM using the code templates of the target platform. The deployment files for installing node software on each node are generated automatically. The proposed tool helps the users to develop node software easily for a range of target platforms, even though they do not have details of the low-level information for a sensor network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.67-71
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• 2007

Recently, a health care need according to the increase of an advanced age population is increasing. The requirement about a health care monitoring is increasing rapidly from general people as well as patient. The requisition about a medical treatment technique and a medical treatment information service is the trend to be expanding. That can be possible minimizing the inconvenience of the patient to take a medical service and continuously monitoring the status of the patient to take a health care service. This paper discusses an implementation of wireless physiological signal monitoring system for health care. The system are composed of the sensor node and monitoring program. The sensor node has the physiological signal measurement part and the wireless communication part. The remote monitoring system has a monitoring program that are communicating the sensor node using bluetooth. The sensor node measured the ECG, pulse wave, blood pressure, Sp02, and heart rate.