• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.110-117
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• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• Convergence Security Journal
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• v.16 no.5
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• pp.3-9
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• 2016

The wireless sensor networks have become an economically viable monitoring solution for a wide variety of civilian and military applications. The main challenge in wireless sensor networks is the secure transmission of information through the network, which ensures that the network is secure, energy-efficient and able to identify and prevent intrusions in a hostile or unattended environment. In that correspondence, this paper proposes a distributed clustering process that integrates the necessary measures for secure wireless sensors to ensure integrity, authenticity and confidentiality of the aggregated data. We use the notion of pre-distribution of symmetric and asymmetric keys for a secured key management scheme, and then describe the detailed scheme which each sensor node within its cluster makes use of the pre-distribution of cryptographic parameters before deployment. Finally, we present simulation results for the proposed scheme in wireless sensor network.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.21-29
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• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.127-133
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• 2015

In order for location information to deliver the collected information, it needs Sensor Nodes in an environment of Sensor Network. Each sensor sends data to a base station through the process of routing in a wireless sensor network environment. Therefore, Offering accurate location information is very important in a wireless sensor network environment. Most of existed routing methods save all the informations of nodes at the area of 1-hop. In order to save these informations, unnecessary wasted energy and traffics are generated. Routing Protocol proposed in this paper doesn't save node's location information, and doesn't exchange any periodic location information to reduce wasted energy. It includes transmission range of source nodes and nodes with the location information, however it doesn't include any nodes' routing near 1-hope distance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1478-1485
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• 2007

In this paper, a meteorological system including a wind speed & direction module and the DSP(Digital Signal Processor) sensor interface circuit board are proposed. This DSP system accepts and process the informations from a wind speed & direction module, the atmospheric pressure sensor, the ambient air temperature sensor and transfers it to the PC monitoring system. Especially, a wind speed & direction module and a DSP hardware are directly designed and applied. A wind speed & direction module have a construction that it have four film type RID(Resistive Temperature Detectors) resistive sensor adhered around the circular metal body heated constantly by heating coil for obtaining vector informations about wind. By this structure, the module is enabled precise measurement having a robustness about vibration, humidity, corrosion. A sensor signal processing circuit is using TMS320F2812 TI(Texas Instrument) Corporation high speed DSP. An economical meteorological system could be constructed through the data from wind speed & direction module and by the fast processing of DSP interface circuit board.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.585-588
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• 2014

This paper presents a self-powered sensor node circuit using photovoltaic and vibration energy harvesting. The harvested energy from a solar cell and a vibration device(PZT) is stored in a storage capacitor. The stored energy is managed by a PMU(Power Management Unit). In order to supply a stable voltage to the sensor node, an LDO(Low Drop Out Regulator) is used. The LDO drives a temperature sensor and a SAR ADC(Successive Approximate Register Analog-to-Digital Converter), and 10-bit digital output data corresponding to current temperature is obtained. The proposed circuit is designed in a 0.35um CMOS process, and the designed chip size including PADs is $1.1mm{\times}0.95mm$.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.149-156
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• 2011

There is much information of equipment in shop floor because the manufacturing processes are different as the equipment within the manufacturing process is varied. To provide effective process information to MES and other production systems, the DAS requires an equipment monitoring system that takes into account the characteristics of the equipment on the shop floor. In this study, we proposed some methods for collecting the required information about various equipments on a shop floor. The equipments such as CNC can be interfaced with the DAS by using a PLC-based method and a sensor-based interface board can be used to interface general equipments. The proposed methods can be used to collect information on the shop floor in real-time. Moreover these methods are very adaptive and can be easily modified according to the changes made to the shop floor. The information about a real shop floor acquired by employing these methods is saved in a database and the can be provided to a supervisor and MES so that they are aware of the status of the shop floor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1117-1128
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• 2015

In order to secure an important competitive advantage in manufacturing business, an automation and information system from manufacturing process has been introduced; however, small and medium enterprises have not met the power of information in the manufacturing fields. They have been managing the manufacturing process that is depending on the operator's experience and data written by hand, which has limits to reveal cause of defective goods clearly, in the case of happening of low-grade goods. In this study, we analyze critical factors which affect the quality of some manufacturing process in terms of 4M. We also studied the automobile parts processing of the small and medium manufacturing enterprises controlled with data written by hand so as to collect the data written by hand and to utilize sensor data in the future. Analysis results show that there is no deference in defective quantity in machines, while raw materials, production quality and task tracking have significant deference.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.507-515
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• 2009

In this paper, we propose an image signal processor (ISP) for an ultra small HD-grade video sensor with 3A (AWB, AE, and AF) in camera phones that can process 720P/30fps videos. In order to enhance the video quality of the systems, it is necessary to achieve the high performance of the 3A. The proposed AWB algorithm multiplies the adjusted coefficients of color gains to the captured data of white objects. The proposed AE method adopts the index step moving based on the difference between an averaged Y luminance and a target luminance, together with IIR filters with variable time responses. The proposed AF technique controls the focus curve to find the lens position that maximizes the integrated high frequency components in luminance values by using highpass filters. Finally, we compare the image quality captured from our system to the quality of a commercial HD camcorder in order to evaluate the performance of the proposed ISP. The proposed ISP system is also fabricated with 0.18um CMOS flash memory process.