• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.77-84
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• 2017

In order to provide healthcare services based on context-awareness techniques in IoT environments, a system requires to collect user profile and environmental information. To collect environmental information, accessing sensor device and gathering sensor data should be proceeded. Although this process is necessary to build environmental information, there is no proper sensor data acquisition model. In this paper, we propose sensor data acquisition model that contains schema to connect each device and to collect various kinds of data from sensor device at one point. In experiment, we demonstrate sensor data acquisition procedures with a description following suggested scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.851-858
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• 2012

In this paper, we design a seismic data acquisition system(SDAS) and implement it. This system is essential for development of a noble local earthquake disaster preventing system in population center. In the system, we choose a proper MEMS-type triaxial accelerometer as a sensor, and FPGA and ARM processor are used for implementing the system. In the SDAS, each module is realized by Verilog HDL and C Language. We carry out the ModelSim simulation to verify the performances of important modules. The simulation results show that the FPGA-based data acquisition module can guarantee an accurate time-synchronization for the measured data from each axis sensor. Moreover, the FPGA-ARM based embedded technology in system hardware design can reduce the system cost by the integration of data logger, communication sever, and facility control system. To evaluate the data acquisition performance of the SDAS, we perform experiments for real seismic signals with the exciter. Performances comparison between the acquired data of the SDAS and the reference sensor shows that the data acquisition performance of the SDAS is valid.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.45-54
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• 2023

Under combat simulation environment when inputting the detection performance data of the real system into the simulated object the given data affects the simulation analysis result. ACQUIRE-Target Task Performance Metric (TTPM)-Target Angular Size (TAS) model is used as a target acquisition model to simulate the detection ability of entities in the main combat simulation tool. This model estimates the decomposition curve of the object sensor and output the detection distance according to the target type. However, it is not easy to apply the performance of the new detection object that the user wants to input to the target acquisition model. Users want to input the detection distance into the target acquisition model, but the target acquisition model requires sensor decomposition curve data according to encounter conditions. In this paper, we propose a method of inversely deriving the sensor decomposition curve data of the target acquisition model by taking the detection distance to the target as an input. Here, the sensor decomposition curve data simultaneously satisfies each detection distance for three types of targets: personnel, ground vehicles, and aircraft. Finally, the detection distance of various reconnaissance equipment is applied to the detection object, and the detection effect according to the reconnaissance equipment is analyzed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.123-131
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• 2009

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. Recently, Nilsson et al. proposed a key management scheme for PCS/SCADA, which was claimed to provide forward and backward secrecies. In this paper, we define four different types of adversaries or attackers in wireless sensor network environments in order to facilitate the evaluation of protocol strength. We then analyze Nilsson et al. 's protocol and show that it does not provide forward and backward secrecies against any type of adversary model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.5
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• pp.28-37
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• 2007

IEEE 1451 standard defines an interface for network and transducer. In this paper, We propose an architectural model to configure data acquisition system and wireless smart sensor node based on IEEE 1451 standard. Proposed Network Capable Application Processor(NCAP) supports the task of data acquisition and communication for smart sensor node and network. The NCAP is able to reconfigure without interrupting the functionality of the wireless sensor node and receives the critical information of transducer using the DB. Smart sensor node is able to provide the basic information of sensor in digital format. This digital format is called Transducer Electronic Data Sheet(TEDS), is capable of plug-and-play capability of wireless sensor node and the NCAP. We simplify the format of TEDS and template to apply to wireless network environment. information of TEDS and template is transmitted using ad-hoc routing. This study system uses body temperature sensor and ECG(Electrocardiogram) sensor to provide the medical information service. The format of template is selected by data sheet of the sensor and reconfigured to accurately describe the property of the sensor. DB of NCAP is possible to register new template and information of the property as developing new sensor.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.191-199
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• 2023

In this paper, we propose a method to extract the features of five sensor-only facilities built as infrastructure for autonomous cooperative driving, which are from point cloud data acquired by LiDAR. In the case of image acquisition sensors installed in autonomous vehicles, the acquisition data is inconsistent due to the climatic environment and camera characteristics, so LiDAR sensor was applied to replace them. In addition, high-intensity reflectors were designed and attached to each facility to make it easier to distinguish it from other existing facilities with LiDAR. From the five sensor-only facilities developed and the point cloud data acquired by the data acquisition system, feature points were extracted based on the average reflective intensity of the high-intensity reflective paper attached to the facility, clustered by the DBSCAN method, and changed to two-dimensional coordinates by a projection method. The features of the facility at each distance consist of three-dimensional point coordinates, two-dimensional projected coordinates, and reflection intensity, and will be used as training data for a model for facility recognition to be developed in the future.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.158-165
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• 2000

Reverse engineering is reproducing products by directly extracting geometric information from physical objects such as clay model wooden mock-up etc. The fundamental work in the reverse engineering is to acquire the geometric data for modeling the objects. This research proposes a novel method for data acquisition aiming at unmanned fast and precise measurement. This is come true by the sensor fusion with CCD camera using structured light beam and touch trigger sensor. The vision system provides global information of the objects data. In this case the number of data and position allocation for touch sensor is critical in terms of the productivity since the number of vision data is very huge. So we applied wavelet transform to reduce the number of data and to allocate the position of the touch probe. The simulated and experimental results show this method is good enough for data reduction.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.67-71
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• 2004

Increasing number and acquisition rate of satellite imagery promoted researches related with DEM generation based on satellite imagery. SPOT image gave us advantage to generate DEM which covers wide area of $60km{\times}60km$. In the case of rigorous sensor model of SPOT imagery, ephemeris data and several ground control points are need and requires arduous computational costs to produce DEM. In this study, using alternative sensor model based on Direct Linear Transform, we generated DEM using small number of ground control points. As a result, it was possible to acquire the DEM with suitable accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.