• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2007년도 하계종합학술대회 논문집
• /
• pp.479-480
• /
• 2007

It is study about implementation of the home network system that used an ubiquitous sensor network and an embedded system in this paper. PXA270 and CC2420 were used, and the home server of a wireless sensor home network system composed it. A wireless control system is composed of a gas valve, a DC motor, a lamp and a door rock. A wireless detection system is composed of a gas detection sensor, a movement detection sensor, an extension detection sensor The wireless detection system that was an environment sensing system was composed of temperature, humidity, mic, illuminance, a speed-up, infrared rays temperature sensing module, and modular, other RFID established an USB camera, and an ubiquitous home network was composed.

• 한국통신학회논문지
• /
• 제25권9A호
• /
• pp.1273-1281
• /
• 2000

In this paper we studied for multi-user detection system, which hold the merit of CDMA system and can enhance the system capacity. We designed actually realizable quasi-optimal multiuser detection system by use of linear equalizer on the concept that multiuser detection algorithm can be reduced by combining TDMA with CDMA. we call this the hybrid TDMA/CDMA system. And we proposed multiuser detection system, which can use PSAD and MSDD channel estimation method. As a result of performance analysis we acquired equal or much better performance by use of linear multichannel equalizer in the case of not so many user. And on the occasion of many user within cell we can also acquired much better performance in comparison with conventional single user detection system by use of hybrid TDMA/CDMA system.

• 한국화재소방학회논문지
• /
• 제16권4호
• /
• pp.28-32
• /
• 2002

성능위주의 화재감지설비 설계시 공조설비 또는 실내 온도조절장치에 의한 실내기류 순환으로 연기기류가 정상해석에 의한 연기분포, 연기농도가 형성되지 못하여 화재감지지연이 예상되는 것을 실험 및 분석을 통하여 성능위주의 예방설비 구현을 위한 연구를 수행하였다. 실험연구는 공조설비가 가동하고 있는 통신기계실의 화재시 화재감지기의 작동을 예측하고자 천장부의 연기농도분포를 측정·분석하는 실험을 수행하였으며, 그 결과 기류순환에 의해 기존 Passive Type의 화재감지장치는 감지불가 또는 감지지연이 예상되었으며, 조기화재감지를 위하여 방호공간의 공기를 강제로 흡입·분석하여 화재를 감지하는 Active Type의 Air Sampling Smoke Detection system의 적용이 필요한 것으로 나타났다.

• 센서학회지
• /
• 제28권3호
• /
• pp.164-170
• /
• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• Journal of Information Processing Systems
• /
• 제18권3호
• /
• pp.428-442
• /
• 2022

A reliable automatic passenger counting (APC) system is a key point in transportation related to the efficient scheduling and management of transport routes. In this study, we introduce a lightweight head detection network using deep learning applicable to an embedded system. Currently, object detection algorithms using deep learning have been found to be successful. However, these algorithms essentially need a graphics processing unit (GPU) to make them performable in real-time. So, we modify a Tiny-YOLOv3 network using certain techniques to speed up the proposed network and to make it more accurate in a non-GPU environment. Finally, we introduce an APC system, which is performable in real-time on embedded systems, using the proposed head detection algorithm. We implement and test the proposed APC system on a Samsung ARTIK 710 board. The experimental results on three public head datasets reflect the detection accuracy and efficiency of the proposed head detection network against Tiny-YOLOv3. Moreover, to test the proposed APC system, we measured the accuracy and recognition speed by repeating 50 instances of entering and 50 instances of exiting. These experimental results showed 99% accuracy and a 0.041-second recognition speed despite the fact that only the CPU was used.

• 한국도로학회논문집
• /
• 제15권5호
• /
• pp.177-185
• /
• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• 대한임베디드공학회논문지
• /
• 제17권1호
• /
• pp.41-49
• /
• 2022

This paper proposes a novel lane detection algorithm based on inverse perspective transformation and machine learning in lightweight embedded system. The inverse perspective transformation method is presented for obtaining a bird's-eye view of the scene from a perspective image to remove perspective effects. This method requires only the internal and external parameters of the camera without a homography matrix with 8 degrees of freedom (DoF) that maps the points in one image to the corresponding points in the other image. To improve the accuracy and speed of lane detection in complex road environments, machine learning algorithm that has passed the first classifier is used. Before using machine learning, we apply a meaningful first classifier to the lane detection to improve the detection speed. The first classifier is applied in the bird's-eye view image to determine lane regions. A lane region passed the first classifier is detected more accurately through machine learning. The system has been tested through the driving video of the vehicle in embedded system. The experimental results show that the proposed method works well in various road environments and meet the real-time requirements. As a result, its lane detection speed is about 3.85 times faster than edge-based lane detection, and its detection accuracy is better than edge-based lane detection.

• 한국지능시스템학회:학술대회논문집
• /
• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
• /
• pp.217-220
• /
• 2007

In this paper, we present a new anchor shot detection system which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) anchor shot detection module using a support vector data description. According to our computer experiments, the proposed system shows not only the comparable accuracy to the recent other results, but also more faster detection rate than others.

• 한국멀티미디어학회논문지
• /
• 제18권3호
• /
• pp.287-297
• /
• 2015

A railway security detection system is very important. There are many safety factors that directly affect the safe operation of trains. Security detection technology can be divided into passive and active approaches. In this paper, we will first survey the railway security systems and compare them. We will also propose a subway security detection system with computer vision technology, which can detect three kinds of problems: the spark problem, the obstacle problem, and the lost screw problem. The spark and obstacle detection methods are unique in our system. In our experiment using about 900 input test images, we obtained about a 99.8% performance in F- measure for the spark detection problem, and about 94.7% for the obstacle detection problem.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 추계학술대회 논문집
• /
• pp.306-312
• /
• 1996

The performance of the failure detection algorithm may be greatly influenced by the model uncertainty. It is very important to design a robust failure detection system to the model uncertainty. In this paper, a design procedure to generate failure detection algorithm is proposed. The design procedure suggested is based on the concept of the‘threshold selector［1］’. The H$\infty$ control algorithm is used to derive a threshold selector which is robust to the model uncertainty, The threshold selector derived can be used to develop a failure detection system together with the weighted cumulative sum algorithm［3］. Computer simulation study showed that the failure detection system designed for an ISA(Integrated Servo Actuator) system by using the proposed method is robust to the model uncertainty.