• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09c
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• pp.72-77
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• 2010

The Incheon Bridge, which was opened to the traffic in October 2009, is an 18.4 km long sea-crossing bridge connecting the Incheon International Airport with the expressway networks around the Seoul metropolitan area by way of Songdo District of Incheon City. This bridge is an integration of several special featured bridges and the major part of the bridge consists of cable-stayed spans. This marine cable-stayed bridge has a main span of 800 m wide to cross the vessel navigation channel in and out of the Incheon Port. In waterways where ship collision is anticipated, bridges shall be designed to resist ship impact forces, and/or, adequately protected by ship impact protection (SIP) systems. For the Incheon Bridge, large diameter circular dolphins as SIP were made at 44 locations of the both side of the main span around the piers of the cable-stayed bridge span. This world's largest dolphin-type SIP system protects the bridge against the collision with 100,000 DWT tanker navigating the channel with speed of 10 knots. Diameter of the dolphin is up to 25 m. Vessel collision risk was assessed by probability based analysis with AASHTO Method-II. The annual frequency of bridge collapse through the risk analysis for 71,370 cases of the impact scenario was less than $0.5{\times}10^{-4}$ and satisfies design requirements. The dolphin is the circular sheet pile structure filled with crushed rock and closed at the top with a robust concrete cap. The structural design was performed with numerical analyses of which constitutional model was verified by the physical model experiment using the geo-centrifugal testing equipment. 3D non-linear finite element models were used to analyze the structural response and energy-dissipating capability of dolphins which were deeply embedded in the seabed. The dolphin structure secures external stability and internal stability for ordinary loads such as wave and current pressure. Considering failure mechanism, stability assessment was performed for the strength limit state and service limit state of the dolphins. The friction angle of the crushed stone as a filling material was reduced to $38^{\circ}$ considering the possibility of contracting behavior as the impact.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.