• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.953-958
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• 2015

Raspberry Pi is a credit card-sized computer with support for a large number of input and output peripherals. This makes it the perfect platform for interaction with many different devices and for usage in a wide range of applications. When combined with Wi-Fi, it can communicate remotely, therefore increasing its suitability for the construction of wireless sensor nodes. In addition, data processing and decision-making can be based on artificial intelligence, what is performed in developed testbed on the example of monitoring and determining the confidence of fire. In this paper, we demonstrated the usage of Raspberry Pi as a sensor web node for fire-safety monitoring in a building. When the UV-flame sensors detect a flame as thin as that of a candle, the Raspberry Pi sends a push-message to notify the assigned smartphone of the on-site situation through the GCM server. A mobile app was developed to provide a real-time video streaming service in order to determine a false alarm. If an emergency occurs, one can immediately call for help.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.355-360
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• 2023

Fire is a disaster that causes irreversible damage to many people due to personal injury and property damage. Various fire detection equipments are installed around us to detect and cope with it quickly. However, due to various problems such as artificial, environmental, and aging, fire detection equipment is activated even though it is not a actual fire, and there are many problems such as delaying the support to the necessary fire scene. In this paper, we analyze the non-fire alarm of the fire detection equipment and propose a system that enables the field staff to check the scene situation through the video as a way to prevent the mobilization due to the misinformation by checking the fire. The purpose of the present invention is to stably cope with a disaster by suggesting a customized automatic guidance system which induces a rapid evacuation by sending an evacuation guidance notification to a range of a fire occurrence neighboring area, and supports a rapid and accurate processing by a rapid dispatch of a firefighter, rather than a wide range of guidance such as an existing emergency disaster guidance letter when it is determined to be an actual fire through the confirmation procedure.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.339-343
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• 2012

Security and monitoring system has many applications and commonly used for detection, warning, alarm, etc. As the networking technology advances, user requirements are getting higher. An intelligent and cooperative surveillance system is proposed to meet current user demands and improve the performance. This paper focuses on the implementation issue for the embedded intelligent surveillance system. To cover wide area cooperative function is implemented and connected by wireless sensor network technology. Also to improve the performance lots of sensors are employed into the surveillance system to reduce the error but improve the detection probability. The proposed surveillance system is composed of vision sensor (camera), mic array sensor, PIR sensor, etc. Between the sensors, data is transferred by IEEE 802.11s or Zigbee protocol. We deployed a private network for the sensors and multiple gateways for better data throughput. The developed system is targeted to the traffic accident detection and alarm. However, its application can be easily changed to others by just changing software algorithm in a DSP chip.

• IE interfaces
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• v.20 no.3
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• pp.288-297
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• 2007

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.1971-1977
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• 2001

Multipath Rayleigh fading channels for mobile radio transmission can be represented by the linear filter model, and depending on the delay path characteristics, only a selected number of taps may have significance in the receiver structure design. By using tap-selective equalization, reduction in both processing complexity and power consumption can be obtained. In this paper, we present an optimal tap selection method for a given channel model, and demonstrate the performance improvement over an existing method. We show the method performs the CFAR (Constant False Alarm Rate) detection when the noise power information is available, and derive exact expressions of the error probability for the case of noise power estimation. Using the derived formulas and simulation results, it is demonstrated that the error probability quickly approaches to the optimal performance as the number samples used for the noise power estimation increases.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.241-244
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• 2014

Wireless Sensor Network(WSN) has been attracting lots of interest in recent years for smart surveillance systems. WSN-based surveillance systems need to figure out the occurrence or existence of events or objects and to find out where the events have occurred or the objects are present. In our surveillance system, it is needed to give an alarm only when the detected object is human (not pets or rodents) for reducing false alarms and improving the system reliability. In this paper, we propose a height prediction mechanism to determine if the detected object is human using Heron's formula. Finally, we verify the performance of our proposed mechanism through various experiments.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.39-40
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• 2015

본 논문에서는 대용량의 영상을 빠르고 정확하게 편집해야 하는 방송 환경에서 오픈 소스를 활용한 방송용 영상 편집 시스템과 편집 결과를 신속히 통보하는 다기능 알람 시스템에 대하여 다루었다. 디지털 방송에서 사용하는 영상은 매우 고품질이면서 동시에 매우 큰 데이터 용량을 가지고 있으며, 또 방송이라는 매체의 성격상 방송 시간에 맞춰 영상 편집을 완료해야 하는 시간적 부담이 있다. 본 논문에서 제안하는 방송 편집 시스템은 갈수록 그 기능이 다양하고 좋은 성능을 보여주는 오픈 소스 영상 처리 소프트웨어를 활용하는 동시에, 분산 처리 시스템을 도입하여 영상의 빠른 편집 기능을 저렴한 도입 비용으로 가능하도록 하였다. 오픈 소스 영상 처리 소프트웨어는 백엔드 모듈로 동작하며, 영상의 다양한 편집 기능들, 예를 들어 영상의 구간 자르기, 붙이기, 자막넣기, 로고 넣기, 비디오/오디오 포맷 변환 등을 수행한다. 사용자 편의성을 위한 프론트엔드 시스템은 자바 기반의 프레임워크를 사용하였으며, 비디오 편집 기능 결과 및 과정에 대한 다기능 알람 기능을 첨가하여 방송 종사자들의 업무 편리를 도모하였다. 본 시스템은 기존의 고가 방송 편집 장비와 비교하여 매우 저렴하면서도 안정된 성능을 보장하여 디지털 방송 시대에 활용 가능성이 매우 높다고 할 수 있다.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.164-170
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• 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 Satellite, Information and Communications
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• v.8 no.4
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• pp.89-94
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• 2013

This paper presents color video flame detection algorithm based on wavelet transform to remove detection of flickering non-flame objects. Conventional flame detection algorithms consist of simple or mixed functions using colors, temporal and spatial characteristics. But those algorithms detect non-flame objects as flame regions sometimes. False alarm reasons are flame-like objects with regular flickering lights such as car signal lamps, alarm lights etc. The proposed algorithm is to reduce false detection which is occurred in periodic flickering lights. At first, It segments the candidate flame regions by using frame difference, flame colors. Then it distinguish flame regions and non flame regions including flickering car lights by analyzing wavelet coefficients. Computer simulation results showed that the proposed algorithm removes false detection due to the periodic flickering lamps by performing 97.9% of correct detection rate while false detection rate is 7.3%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.1-11
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• 2008

In this paper, we propose the new eye detection method by using adaboost (adaptive boosting) method. Also, to reduce the false alarm rate which identifies the non-eye region as genuine eye that is the Problems of previous method using conventional adaboost, we proposed the post processing methods which used the cornea specular reflection and determined the optimized ratio of eye detecting box. Based on detected eye region by using adaboost, we performed the double circular edge detector for localizing a pupil and an iris region at the same time. Experimental results showed that the accuracy of eye detection was about 98% and the processing time was less than 1 second in mobile device.