• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2010.06a
• /
• pp.293-293
• /
• 2010

In this paper, we propose a stereo vision based monitoring concept for passenger's safety on railroad platform. In general, basic concept of stereo image processing technique uses the correlations between left and right images, and extracts additional distance information. It provides easy removal of ambient illumination changes, which has been difficult to achieve with conventional 2D based image processing technique. In the paper, we present developed stereo camera and stereo vision based detection algorithm in order to monitor possible accidents at platform area, and verified the detection performance of proposed system with experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.10
• /
• pp.1751-1768
• /
• 2011

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.

• Smart Structures and Systems
• /
• v.6 no.9
• /
• pp.1079-1105
• /
• 2010

Railway transport of goods and passengers is effective in terms of energy conservation and travel time savings. Safety and ride quality have become important issues as train speeds have increased. Due to increased speeds, minor damage to railway structures and abnormal interactions between trains and structures have given rise to increasingly serious accidents. Therefore, structural health and operational conditions must be monitored continuously in all service environments. Currently, various health and operation management systems are being developed and these are reducing both maintenance frequency and costs associated with disassembly. In this review, major damage and malfunctions and their locations are first analyzed based on numerous references. Then advanced train health and operation management technologies are classified into wayside detection methods and advanced integrated sensor methods and their operating principle and functions are reviewed and analyzed.

• Proceedings of the KIEE Conference
• /
• 1994.07b
• /
• pp.1636-1638
• /
• 1994

Salt deposited on the surface of insulators used in electric power system causes flash-over accidents. Therefore, the quantity of salt on insulators should be monitored not to exceed a critical value. We propose a new remote sensing technique to measure the quantity of salt on insulators of power systems. A pulsed laser beam is focussed on ah insulator to dissociate the salt to sodium atoms. The amount of the salt is measured from the intensity of the spontaneous mission from the sodium atoms. In this paper, a compact salt meter composed of pulsed Nd:YAG laser and omission signal detection system will be introduced. And measurement condition such as the sensitivity, detection range, required laser fluence will be investigated.

• Proceedings of the KIPE Conference
• /
• 2013.07a
• /
• pp.471-472
• /
• 2013

When ESS(Energy Storage System) is under normal operation, island situation can be occur because of grid accidents. When island operation occur, the system mode switches in to UPS(Uninterruptible Power Supply) mode to supply stabled load power. To decide island operation, checking grid magnitude or frequency is general. But regulation for sag and swell is required. In this paper, it proposes grid connection error detection algorithm for UPS operation when sag and swell occurs in grid, and analyzed by simulation.

• Journal of the Korea Safety Management & Science
• /
• v.17 no.2
• /
• pp.47-54
• /
• 2015

To prevent safety hazards in dangerous working area, we have proposed an intelligent image analysis system. Six common patterns of safety violations of workers' are defined and its motion detection algorithms are developed for alarm to CCTV monitoring system. Developed algorithms are implemented at 195 dangerous areas such as chemical and gas treated room. The results of violated motion detection ratio by developed system shows 94.95% of true positive cases, and 0.21% of false positive cases from all 587,645 event cases in one month implementation period. In the period, it is observed that the number of safety rule violations and the following accidents are decreased.

• Journal of Auto-vehicle Safety Association
• /
• v.10 no.4
• /
• pp.13-24
• /
• 2018

According to DEKRA (a Germany Certification and Inspection Agency)'s accident rate analysis by vehicle defect factor, as a result of analysis of the causes of accidents by flaws, it was found that braking devices accounted for 41%. Defects in the braking system are closely related to the accident, so it is very important to find faulty brking systems to ensure safety. The EU and USA uses ISO brake tester and the Korea is brake teater is first introduse in Japan for vehicle inspection and maintanance. KOTSA introduce the ISO brake tester in order to promote the advanced standardization of the inspection equipment and inspection tecnology, and examined the detection characteristics and applied it to the improvement direction of the brake tester to secure the driving safety.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.2
• /
• pp.109-118
• /
• 2022

Workers' anomalous trajectories allow us to detect emergency situations in the workplace, such as accidents of workers, security threats, and fire. In this work, we develop a scheme to detect abnormal trajectories of workers using the edit distance on real sequence (EDR) and density method. Our anomaly detection scheme consists of two phases: offline phase and online phase. In the offline phase, we design a method to determine the algorithm parameters: distance threshold and density threshold using accumulated trajectories. In the online phase, an input trajectory is detected as normal or abnormal. To achieve this objective, neighbor density of the input trajectory is calculated using the distance threshold. Then, the input trajectory is marked as an anomaly if its density is less than the density threshold. We also evaluate performance of the proposed scheme based on the MIT Badge dataset in this work. The experimental results show that over 80 % of anomalous trajectories are detected with a precision of about 70 %, and F1-score achieves 74.68 %.

• The KIPS Transactions:PartC
• /
• v.11C no.2
• /
• pp.157-162
• /
• 2004

Recently, the growth of information infrastructure is getting fatter and faster. At the same time, the security accidents are increasing together. We have problem that do not handle traffic because we have the Intrusion Detection Systems in low speed environment. In order to overcome this, we need effective security analysis techniques that ran Processed data of high-capacity because high speed network environment. In this paper we proposed the Gigabit Intrusion Detection System for coordinated security function such as intrusion detection, response on the high speed network. We suggested the detection mechanism in high speed network environment that have pattern matching function based packet header and based packet data that is proceeded in system kernel area, we are shown that this mechanism was excellent until maximum 20 times than existing system in traffic processing performance.

• Journal of Broadcast Engineering
• /
• v.21 no.4
• /
• pp.609-620
• /
• 2016

Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.