• Journal of Sensor Science and Technology
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• v.3 no.2
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• pp.50-56
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• 1994

Fiber-optic biosensor for the detection of organophosphorus compounds in a contaminated water was developed, which was the component of pesticides and agricultural agent. The detection principle of designed sensor was the pH variance induced by a reaction of acetylcholinesterase enzyme inhibited by organophosphorus compounds. The pH variance was detected by the optical system to measure the organophosphorus compounds. Litmus was selected as the pH-sensitive dye suitable to the enzyme reaction and a light source to be detected by the optical system. The enzyme entrapped in Ca-alginate gel was immobilized at the inner wall to maintain the high activity of enzyme and to be reused for a long period. The optical fiber was used to miniaturize and control remotely the sensor system. The He-Ne laser with 632 nm was selected as the light source to prevent light intensity fluctuation by the product. Cheap plastic optical fibers were used as the transmission part of the light and the phototransistor was used as the reception part of light based on the wavelength of He-Ne laser. The proposed fiber-optic biosensor has the linear analytical range of 0 ppm-1.5 ppm with response time of 5 minutes.

• Journal of the Korean Geosynthetics Society
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• v.19 no.4
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• pp.41-50
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• 2020

Since cracks in concrete structures expedite corrosion of reinforced concrete over a long period of time, regular on-site inspections are essential to ensure structural usability and prevent degradation. Most of the safety inspections of facilities rely on visual inspection with naked eye, so cost and time consuming are severe, and the reliability of results differs depending on the inspector. In this study, a portable measuring device that can be used for safety diagnosis and maintenance was developed as a device that measures the width and length of concrete cracks through image analysis of cracks photographed with a camera. This device captures the cracks found within a close distance (3 m), and accurately calculates the unit pixel size by laser distance measurement, and automatically calculates the crack length and width with the image processing algorithm developed in this study. In measurement results using the crack image applied to the experiment, the measurement of the length of a 0.3 mm crack within a distance of 3 m was possible with a range of about 10% error. The crack width showed a tendency to be overestimated by detecting surrounding pixels due to vibration and blurring effect during the binarization process, but it could be effectively corrected by applying the crack width reduction function.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.676-681
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• 2013

For underwater vehicles, the use of sensors such as cameras and laser scanners is limited by the difference in environment compared to robots designed to work on dry land. In underwater environments, if use is made of sound signals, valuable information can be obtained. The most important application is the localization of underwater sound sources. The estimated location of a sound source can be used to control underwater robots or submarines. Thus, the purpose of this research is to estimate the source's direction and location in a noisy underwater environment. The direction of the sound source is obtained using two hydrophones. Furthermore, if we assume that the robot or sound source is moving, the location of the sound source is estimated using more than two estimated directions. The feasibility of the developed algorithm is examined by experiments in a water tank and in the ocean.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.130-130
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• 2009

This paper describes the temperature characteristics of polycrystalline 3C-SiC micro resonators. The 1.2 ${\mu}m$ and 0.4 ${\mu}m$ thick polycrystalline 3C-SiC cantilever and doubly clamped beam resonators with 60 ~ 100 ${\mu}m$ lengths were fabricated using a surface micromachining technique. Polycrystalline 3C-SiC micro resonators were actuated by piezoelectric element and their fundamental resonance was measured by a laser vibrometer in vacuum at temperature range of $25{\sim}200^{\circ}C$. The TCF(Temperature Coefficient of Frequency) of 60, 80 and 100 ${\mu}m$ long cantilever resonators were -9.79, -7.72 and -8.0 $ppm/^{\circ}C$. On the other hand, TCF of 60, 80 and 100 ${\mu}m$ long doubly clamped beam resonators were -15.74, -12.55 and -8.35 $ppm/^{\circ}C$. Therefore, polycrystalline 3C-SiC resonators are suitable with RF MEMS devices and bio/chemical sensor applications in harsh environments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1005-1013
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• 2008

This paper describes a new sensor system for 3D range measurement using the structured infrared light. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and the projected infrared light are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Identification of the cells from the pattern is the key issue in the proposed method. Several methods of correctly identifying the cells are discussed and verified with experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.610-630
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• 2020

A large number of people suffered from traffic accidents each year, so people pay more attention to traffic safety. However, the traditional methods use laser sensors to calculate the vehicle distance at a very high cost. In this paper, we propose a method based on deep learning to calculate the vehicle distance with a monocular camera. Our method is inexpensive and quite convenient to deploy on the mobile platforms. This paper makes two contributions. First, based on Light-Head RCNN, we propose a new vehicle detection framework called Light-Car Detection which can be used on the mobile platforms. Second, the planar homography of projective geometry is used to calculate the distance between the camera and the vehicles ahead. The results show that our detection system achieves 13FPS detection speed and 60.0% mAP on the Adreno 530 GPU of Samsung Galaxy S7, while only requires 7.1MB of storage space. Compared with the methods existed, the proposed method achieves a better performance.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.493-504
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• 2007

This paper proposes a stereo vision-based forward obstacle detection and distance measurement method. In general, stereo vision-based obstacle detection methods in automotive applications can be classified into two categories: IPM (Inverse Perspective Mapping)-based and disparity histogram-based. The existing disparity histogram-based method was developed for stop-and-go applications. The proposed method extends the scope of the disparity histogram-based method to highway applications by 1) replacing the fixed rectangular ROI (Region Of Interest) with the traveling lane-based ROI, and 2) replacing the peak detection with a constant threshold with peak detection using the threshold-line and peakness evaluation. In order to increase the true positive rate while decreasing the false positive rate, multiple candidate peaks were generated and then verified by the edge feature correlation method. By testing the proposed method with images captured on the highway, it was shown that the proposed method was able to overcome problems in previous implementations while being applied successfully to highway collision warning/avoidance conditions, In addition, comparisons with laser radar showed that vision sensors with a wider FOV (Field Of View) provided faster responses to cutting-in vehicles. Finally, we integrated the proposed method into a longitudinal collision avoidance system. Experimental results showed that activated braking by risk assessment using the state of the ego-vehicle and measuring the distance to upcoming obstacles could successfully prevent collisions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2360-2366
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• 2011

The Unmanned Ground Vehicle is comprised of four systems of obstacle detection: The navigation system, vehicle controlling system, obstacle detecting and an integration system that use the various sensors. The research introduced utilizes 6 lasers to recognize obstacles. The system operates an avoidance system within the unmanned ground vehicle, using six lasers. The Unmanned Ground Vehicle's parallel parking and right angle parking is in development using algorithms. This algorithms' certification is intended to be installed in the encoder, in the GPS. By using the Laser Scannerfor the position's calculation, errors are both reduced and minimized, so the tire's slip minimized to the point where the vehicle had a limit of about 5Km/h.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.43-50
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• 2014

This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.

• Transactions on Electrical and Electronic Materials
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• v.14 no.3
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• pp.148-151
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• 2013

The control of Ga doping in ZnO nanowires (NWs) by physical vapor deposition has been implemented and characterized. Various Ga-doped ZnO NWs were grown using the vapor-liquid-solid (VLS) method, with Au catalyst on c-plane sapphire substrate by hot-walled pulsed laser deposition (HW-PLD), one of the physical vapor deposition methods. The structural, optical and electrical properties of Ga-doped ZnO NWs have been systematically analyzed, by changing Ga concentration in ZnO NWs. We observed stacking faults and different crystalline directions caused by increasing Ga concentration in ZnO NWs, using SEM and HR-TEM. A $D^0X$ peak in the PL spectra of Ga doped ZnO NWs that is sharper than that of pure ZnO NWs has been clearly observed, which indicated the substitution of Ga for Zn. The electrical properties of controlled Ga-doped ZnO NWs have been measured, and show that the conductance of ZnO NWs increased up to 3 wt% Ga doping. However, the conductance of 5 wt% Ga doped ZnO NWs decreased, because the mean free path was decreased, according to the increase of carrier concentration. This control of the structural, optical and electrical properties of ZnO NWs by doping, could provide the possibility of the fabrication of various nanowire based electronic devices, such as nano-FETs, nano-inverters, nano-logic circuits and customized nano-sensors.