• Journal of Convergence Society for SMB
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• v.3 no.1
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• pp.31-41
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• 2013

There have been various recent methods proposed in detecting driver drowsiness (DD) to avert fatal accidents. This work proposes a hardware/software (HW/SW) co-design approach in implementation of a DD detection system adapted from an AdaBoost-based object detection algorithm with Haar-like features [1] to monitor driver's eye closure rate. In this work, critical functions of the DD detection algorithm is accelerated through custom hardware components in order to speed up processing, while the software component implements the overall control and logical operations to achieve the complete functionality required of the DD detection algorithm. The HW/SW architecture was implemented on an Altera DE2 board with a video daughter board. Performance of the proposed implementation was evaluated and benchmarked against some recent works.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.11-18
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• 2022

The use of multi-spectral cameras is essential for day and night pedestrian detection. In this paper, a color camera and a thermal imaging infrared camera were used to detect pedestrians near a crosswalk for 24 hours at an intersection with a high risk of traffic accidents. For pedestrian detection, the YOLOv5 object detector was used, and the detection performance was improved by using color images and thermal images at the same time. The proposed system showed a high performance of 0.940 mAP in the day/night multi-spectral (color and thermal image) pedestrian dataset obtained from the actual crosswalk site.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.332-334
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• 2021

As fatal accidents due to industrial accidents and deaths due to civil accidents were pointed out as social problems, the Act on Punishment of Serious Accidents Occurred in the Workplace was enacted to ensure the safety of citizens and to prevent serious accidents in advance. Effort is required. In this paper, we propose a distance prediction model in relation to the case where an operator is hit by heavy equipment such as a forklift. For the data, actual forklift trucks and workers roaming environments were directly captured by CCTV, and it was conducted based on the Euclidean distance. It is thought that it will be possible to learn YOLO-v4 by directly building a data-set at the industrial site, and then implement a model that predicts the distance and determines whether it is a dangerous situation, which can be used as basic data for a comprehensive risk situation judgment model.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.1-6
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• 2010

Ball bearings are one of main components that support the rotational shaft in high speed rotary machinery. So, it is very important to detect the incipient faults and fault growth of bearing since the damage and failure of bearing can cause a critical failures or accidents of machinery system. In the past, many researchers mainly performed to detect the bearing fault using traditional method such as wavelet, statistics, envelope etc in vibration signals. But study on the detection technique for bearing fault growth has a little been performed. In this paper, we verified the possibility for monitoring of fault growth and detection of fault size in bearing outer-race by using the envelope powerspectrum and probabilistic density function from measured vibration signals.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1411-1412
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• 2015

Detection of road lanes is an important technology, which is being used in autonomous vehicles from last few years. This method is very helpful and supportive for the drivers to provide them safety and to avoid road accidents. Alot of methods are being used to detect road lane markings. We can categorize them into three major categories: sensor-based, feature-based, and model-based methods. And in this study we give the comprehensive survey on lane marking techniques.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.107-112
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• 2022

The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.5
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• pp.520-524
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• 2023

An algorithm was developed to detect and block serial arc currents using HPF. The AC series arc problem is that the load current is greater than the fault current and no leakage current occurs. As a solution, an arc detection method utilizing differences in high- frequency amplitudes was developed. HPT was applied to the load current and FFT was applied to eliminate low frequencies. An algorithm has been developed to detect arc waveforms when they exceed a certain value compared to the average of normal waveforms. Using one cycle of data, arc detection is faster and arc accidents are prevented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2220-2227
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• 2008

The safety equipments of railway level crossing which are installed at intersections between roads and railway lines prevent level crossing accidents by informing all of the vehicles and pedestrians of approaching trains. The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.55-63
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• 2019

Proximity sensors and rearview cameras for automobile safety are common, but many accidents are still occurring. Using the All Around View and object recognition algorithm to show the front, back, left, right and bottom of the vehicle, the sensor detects the presence of a living body when the vehicle starts or parks, and displays the outside of the vehicle on the screen. In addition, the object recognition algorithm is used to visualize the object by expressing the position of the object. In this way, we propose a strong safety system that can prevent human accidents caused by the vehicle by sensing, screen, and expression.