• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2674-2676
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• 2004

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligence robot. A web based monitoring system is implemented by porting Linux at embeded systems which include Xscale processors. A divice driver is developed to receive data from multy-axis force sensors in Linux operation systems. To control this device driver, a soket program for web browser is also developped.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.632-639
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• 2014

In this paper, we propose a PC's self-monitoring system for protecting illegal outflow of important personal files, which are managed in the Windows environment PC. This paper is based on the idea that it should be a read (access) file operation in order to outflow files through the network. To compare the information (name, some content) obtained from all operations of the reading of the 'Windows File System Driver' and captured transmission packets of mini port of 'Windows NDIS (Network Driver Interface Specification) Driver', and, if two pieces of information match, this system will determine the transmission to user. In this paper, tentatively, we developed a function to gather file information about file read operation and developed a function for transmission packet capture. This demonstration implementation showed that the proposed process has validity and the proposed process verified that it does not significantly affect the PC's performance.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1186-1191
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• 2007

Human driver monitoring system is one of the most important systems for the safety in driving vehicles, and therefore driver assistance system has gained much attention during the last decade. This paper proposed an intelligent driver assistance system which monitors human driver's states from bio-signals such as ECG and Blood Pressure. The proposed system used mamdani fuzzy inference to evaluate the driver's mental strain and generated warning signals to the driver. The approach using bio-signals in driver assistance system is the main issue of the related systems and the preliminary results showed the possibility of further research topics in developing more intelligent embedded systems with bio-signal feedback.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.545-548
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• 2009

Recently, researches related to automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for $SpO_2$ sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, $SpO_2$ and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the $SpO_2$ and ECG signals. HRV(Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.153-159
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• 2012

Driver's view has blind spot of automobile surroundings due to physical components of automobile architecture. Obstacles on blind spot are the cause of car destruction and car accidents. Cars which produced in recent have obstacle detection sensors and rear view cameras which provide information of obstacles on the blind sopt, and have also AVM(Around View Monitoring) which provides automobile surroundings for driver's safe driving. During a low-speed travel while parking or moving in a narrow street, a driver get help for safe driving by taking information of automobile surroundings using the above-mentioned devices. In this paper, we present a design and implementation of a 4-sided monitoring (4SM) system, which helps a driver see an integrated view of a vehicle's perimeter at a glance, using a car PC connected to four cameras installed on the front, rear, left, and right sides.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.188-190
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• 2005

In this study, a smart motor control and monitoring system is developed with an embedded board where Intel PXA255B CPU is mounted. Linux is ported into the embedded board as RTOS(Real Time Operating System), and the environment which communicate with a motor driver through serial protocol and is capable of controlling and monitoring the motor in real time is built in the system. A user friendly GUI is developed for the convenient operation of the system. Also, the environment which is able to control and monitor the motor driver remotely is built in the system using TCP/IP protocol.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3820-3841
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• 2018

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver's head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver's distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver's distraction, i.e., driver's head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver's head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.

• Journal of IKEEE
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• v.28 no.3
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• pp.296-302
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• 2024

In this paper, we propose a driver condition monitoring system using FMCW in-cabin radar, which is free from wearing inconvenience and privacy issues. Using 77GHz high-precision radar, the system detects changes in eye blinking patterns according to changes in the driving environment and the driver's condition using an adaptive multiple filtering algorithm, and accurately determines drowsy driving by measuring the number of eye blinks and the time it takes to open and close the eyes through the detected data. With the emergence of high-performance radars that are becoming more and more miniaturized, it is possible to embed them in the instrument panel or rearview mirror of the vehicle, and if the driver is judged to be drowsy, it can wake up the driver through an alarm or interlock with the vehicle's driving system to slow down and make an emergency stop to prevent accidents and promote driver safety.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.362-367
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• 2010

In this paper, we describe implementation of FPGA-based Nios II embedded processor system and linux device driver for image monitoring system which is supplement weakness for fixed surveillance area of existing CCTV system and by manual operation of the camera's moving. Altera Nios II processor 8.0 is supported MMU which is stable and efficient managed memory. We designed the image monitoring and control system by using Altera Nios II soft-core processor system which is flexible in various application and excellent adaptability. By implementation of camera device driver and VGA decvice driver for Linux-based Nios II system, we implemented image serveillance system for Nios II embedded processor system.