• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1388-1395
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• 2020

Daily monitoring of the heart rate can facilitate detection of heart-related diseases in their early stages. Therefore, providing an easy-to-use and noninvasive heart rate monitoring system has been a very popular research topic in the field of healthcare. One of good candidate methods is to use commonly available cameras and extract information that can help to estimate heart rate from a human face. Generally, such information can be retrieved using two different approaches: photoplethysmography (PPG) and ballistocardiography (BCG). PPG exploits slight color changes caused by blood volume variations during heartbeats; thus, it tends to be vulnerable to unstable lighting conditions. BCG exploits subtle head motions caused by pumped blood travelling through the carotid artery during heartbeats; thus, it is vulnerable to the voluntary head movements that are not related to heartbeats. Nevertheless, most related works use either to estimate the heart rate. In this paper, we propose to combine two approaches to be robust to challenging conditions. Specifically, we explore possible ways to combine raw signals obtained from two approaches and verify that the proposed combination shows better accuracies under challenging conditions, such as voluntary head movements and ambient lighting changes.

• Journal of Biomedical Engineering Research
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• v.39 no.6
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• pp.278-283
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• 2018

Nowdays, many people suffer from the neck pain due to forward head posture(FHP) and text neck(TN). To assess the severity of the FHP and TN the craniovertebral angle(CVA) is used in clinincs. However, it is difficult to monitor the neck posture using the CVA in daily life. We propose a new method using the cervical flexion angle(CFA) obtained from a wearable sensor to monitor neck posture in daily life. 15 participants were requested to pose FHP and TN. The CFA from the wearable sensor was compared with the CVA observed from a 3D motion camera system to analyze their correlation. The determination coefficients between CFA and CVA were 0.80 in TN and 0.57 in FHP, and 0.69 in TN and FHP. From the monitoring the neck posture while using laptop computer for 20 minutes, this wearable sensor can estimate the CVA with the mean squared error of 2.1 degree.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.367-392
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• 2020

The specific characteristics of near-field earthquake records can lead to different dynamic responses of bridges compared to far-field records. However, the effect of near-field strong ground motion has often been neglected in the seismic performance assessment of the bridges. Furthermore, damage to horizontally curved multi-frame RC box-girder bridges in the past earthquakes has intensified the potential of seismic vulnerability of these structures due to their distinctive dynamic behavior. Based on the nonlinear time history analyses in OpenSEES, this article, assesses the effects of near-field versus far-field earthquakes on the seismic performance of horizontally curved multi-frame RC box-girder bridges by accounting the vertical component of the earthquake records. Analytical seismic fragility curves have been derived thru considering uncertainties in the earthquake records, material and geometric properties of bridges. The findings indicate that near-field effects reasonably increase the seismic vulnerability in this bridge sub-class. The results pave the way for future regional risk assessments regarding the importance of either including or excluding near-field effects on the seismic performance of horizontally curved bridges.

• Smart Structures and Systems
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• v.18 no.5
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• pp.955-982
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• 2016

Recent studies integrating vibration control and structural health monitoring (SHM) use control devices and control algorithms to enable system identification and damage detection. In this study real-time SHM is used to enhance structural vibration control and reduce damage. A newly proposed control algorithm, including integrated real-time SHM and semi-active control strategy, is presented to mitigate both damage and seismic response of the main structure under strong seismic ground motion. The semi-active independently variable stiffness (SAIVS) device is used as semi-active control device in this investigation. The proper stiffness of SAIVS device is obtained using a new developed semi-active control algorithm based on real-time damage tracking of structure by damage detection algorithm based on identified system Markov parameters (DDA/ISMP) method. A three bay five story steel braced frame structure, which is equipped with one SAIVS device at each story, is employed to illustrate the efficiency of the proposed algorithm. The obtained results show that the proposed control algorithm could significantly decrease damage in most parts of the structure. Also, the dynamic response of the structure is effectively reduced by using the proposed control algorithm during four strong earthquakes. In comparison to passive on and off cases, the results demonstrate that the performance of the proposed control algorithm in decreasing both damage and dynamic responses of structure is significantly enhanced than the passive cases. Furthermore, from the energy consumption point of view the maximum and the cumulative control force in the proposed control algorithm is less than the passive-on case, considerably.

• Smart Structures and Systems
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• v.4 no.6
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• pp.727-740
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• 2008

A down hole vertical seismic array is a sequence of instruments installed at various depths in the earth to record the ground motion at multiple points during an earthquake. Numerous studies demonstrate the unique utility of vertical seismic arrays for studying in situ site response and soil behavior. Examples are given of analyses made at two sites to show the value of data from vertical seismic arrays. The sites examined are the Lotung, Taiwan SMART1 array and a new site installed at Jingliao, Taiwan. Details of the installation of the Jingliao array are given. ARX models are theoretically the correct process models for vertical wave propagation in the layered earth, and are used to linearly map deeper sensor input signals to shallower sensor output signals. An example of Event 16 at the Lotung array is given. This same data, when examined in detail with a Bayesian inference model, can also be explained by nonlinear filters yielding commonly accepted soil degradation curves. Results from applying an ARMAX model to data from the Jingliao vertical seismic array are presented. Estimates of inter-transducer soil increment resonant frequency, shear modulus, and damping ratio are presented. The shear modulus varied from 50 to 150 MPa, and damping ratio between 8% and 15%. A new hardware monitoring system - TerraScope - is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The Pods are nominally 50 mm in diameter, and about 120 mm long. An internal 16-bit micro-controller oversees all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.645-661
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• 2012

Recently, pirates are infesting on the sea and they have been hijacking the several vessels for example Samho Dream and Samho Jewelry of Korea. One of the items to reduce the risk is to adopt the invader detection system. If the pirates break in to the ship, the detection system can monitor the pirates and then call the security alarm. The crew can gain time to hide to the safe room and the report can be automatically sent to the control room to cope with the situation. For the invader detection, an unmanned observation system was proposed using the image detection algorithm that extracts the invader image from the recording image. To detect the motion area, the difference value was calculated between the current image and the prior image of the invader, and the 'AND' operator was used in calculated image and edge line. The image noise was reduced based on the morphology operation and then the image was transformed into morphological information. Finally, a neural network model was applied to recognize the invader. In the experimental results, it was confirmed that the proposed approach can improve the performance of the recognition in the invader monitoring system.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.165-176
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• 2018

The objective of this study was to develop clothing-type wearable motion sensing and feedback systems to enhance children's sports by promoting visual and audio feedback. In this study, several applications, such as fabric sensors, sportswear integrated with various types of fabric sensors, and fabric-based motion sensing module design, as well as a visual and audio feedback system for gaining a better understanding of a child's interest in a type of exercise, were developed. An SWCNT-based stretchable fabric sensor was developed for motion sensing, and sportswear was designed using the fabric sensor that was integrated into the limbs of the garment. The sensing module was developed, and sensory performance was evaluated through a joint motion experiment for children. In addition, using the feedback system that was developed in the form of an accessory, the responses of light and sound were also examined based on the movement of the child who was wearing the sportswear prototypes. This study focused on the development and assessment of prototype designs for children's sportswear and accessory products that can help to ascertain a child's interest in a particular exercise.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.810-816
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• 2007

A security robot system named EGIS-SR is a mobile security robot through one of the new growth engine project in robotic industries. It allows home surveillance through an autonomous mobile platform using onboard cameras and wireless security sensors. EGIS-SR has many sensors to allow autonomous navigation, hierarchical control architecture to handle lots of situations in monitoring home surveillance and mighty networks to achieve unmanned security services. EGIS-SR is tightly coupled with a networked security environment, where the information of the robot is remotely connected with the remote cockpit and patrol man. It achieved an intelligent unmanned security service. The robot is a two-wheeled mobile robot and has casters and suspension to overcome a doorsill. The dynamic motion is verified through $ADAMS^{TM}$ simulation. For the main controller, PXA270 based hardware platform based on linux kernel 2.6 is developed. In the linux platform, data handling for various sensors and the localization algorithm are performed. Also, a local path planning algorithm for object avoidance with ultrasonic sensors and localization using $StarGazer^{TM}$ is developed. Finally, for the automatic charging, a docking algorithm with infrared ray system is implemented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.