• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.179-184
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• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.1-7
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• 2023

Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.179-182
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• 2008

It needs to consider of turns during a path-finding on real road network. Because a car is delayed by waiting a traffic signal and decreasing speed when drived in a turn road such as cross road and slip road. If a straightness of a path is increased, a real cost of traveling should be able to decrease. An older method, the algorithm with Turn Heuristic, considered of this case. The algorithm, that differently gave weights to left, right and U-turns, improved a straightness of a path, but increased a cost of exploring. In this paper, we propose a improved Turn Heuristic Algorithm. Proposed algorithm uses Dynamic Turn Heuristic. It is able to more decrease a cost of exploring than older method by using the Turn Heuristic in a part of path-finding.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.370-378
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• 2007

In wireless sensor networks (WSNs), thousands of sensors are often deployed in a hostile environment. In such an environment, WSNs can be applied to various applications by using the absolute or relative location information of the sensors. Until now, the time-of-arrival (TOA) based localization method has been considered most accurate. In the TOA method, however, inaccuracy in distance estimation is caused by clock drift and clock skew between sensor nodes. To solve this problem, several numbers of periodic time synchronization methods were suggested while these methods introduced overheads to the packet traffic. In this paper, we propose a new localization method based on multiple round-trip times (RTOA) of a signal which gives more accurate distance and location estimation even in the presence of clock skew between sensor nodes. Our experimental results show that the Proposed RTOA method gives up to 93% more accurate location estimation.

• Smart Structures and Systems
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• v.9 no.3
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• pp.287-301
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• 2012

It is well known that overloaded vehicles may cause severe damages to bridges, and how to estimate and evaluate the status of the overloaded vehicles passing through bridges become a challenging problem. Therefore, based on the monitored strain data from a structural health monitoring system (SHM) installed on a bridge, a method is recommended to identify and analyze the probability of overloaded vehicles. Overloaded vehicle loads can cause abnormity in the monitored strains, though the abnormal strains may be small in a concrete continuous rigid frame bridge. Firstly, the abnormal strains are identified from the abundant strains in time sequence by taking the advantage of wavelet transform in abnormal signal identification; secondly, the abnormal strains induced by heavy vehicles are picked up by the comparison between the identified abnormal strains and the strain threshold gotten by finite element analysis of the normal heavy vehicle; finally, according to the determined abnormal strains induced by overloaded vehicles, the statistics of the overloaded vehicles passing through the bridge are summarized and the whole probability of the overloaded vehicles is analyzed. The research shows the feasibility of using the monitored strains from a long-term SHM to identify the information of overloaded vehicles passing through a bridge, which can help the traffic department to master the heavy truck information and do the damage analysis of bridges further.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.113-121
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• 2013

The rate that women's EMTs(emergency medical technicians) in fire department occupy is increasing, but my general plan is aimed at suggesting the improving plan for the working environment of women's EMTs paying attention to the duty stresses of increasing women's EMTs, because improvement for the working environment of women's EMTs is being proceeded slowly. I suggested my improving plan for solving the working stress on the basis of a survey of the Recognition against women's EMTs as follows. Firstly, I suggested that physical strength of women's EMTs should be managed well continually via program establishment and a defined evaluation not only by employing a professional person in charge for physical strength in firehouse, but also by replenishing the suitable number for the urgent mobilization. Secondly, I suggested that the suitable number for the urgent mobilization should be increased to 3 including an ambulance driver. Thirdly, I suggested necessity such as the fruitful education and the creation of circumstances that can focus on education for improving participation rate, development of various new educational program, incentive program and penalty. finally, I suggested the fact that is related to the actual re-amendment of the concerned law and ordinance such as not only the smooth treatment of penalty for a traffic signal violation of ambulance and the legal remedy system due to aggravation of a patient's condition during a first-aid course, but also workshop and meeting among the periodical EMTs and administration of special therapy program and sufficient recess.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.9
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• pp.820-827
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• 2011

Recently, noise has been regarded as one of the most notorious and frequent environmental pollutions which can be often encountered not only in the living space but also in the industrial site. Studies on physiological and psychological effects of long-term noise exposure to human being have commanded the public interest on noise issues. Since environmental noises such as traffic noise and construction noise is mainly flowed through the open window, it is necessary to develop the active noise control system to reduce it inside the building. Although control speakers and microphones for the noise signal measurement in the control region are essential for the conventional active noise control methods, it is impossible to implement them in the control region in the building environment because the control region is the living quarter and they may hinder activities of the residents. Therefore, we proposed the active window system to reduce the exterior noise flowed through the open window with microphones installed outside the window and control speakers installed at the frame of the window. To confirm the performance of the proposed active window, we carried out the simulation and experiment using active window system with 8 control speakers. Simulation results showed the noticeable noise reduction effect inside the control region within the frequency range without the spatial aliasing. Experimental result showed that the total acoustic potential energy inside the room of the scale model is reduced to about 10dB within the interest of frequency range.