• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.90-97
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• 2017

Nowadays, the most of commercial buildings are build-out with complex architecture and decorated with more complicated interiors of buildings so establishing intelligible escape routes becomes an important case of fire or other emergency in a limited time. The commercial buildings are already equipped with multiple exit signs and these exit signs may create confusion and leads the people into different directions under emergency. This can jeopardize the emergency situation into a chaotic state, especially in a complex layout buildings. There are many research focused on implementing different approached to improve the exit sign system with better visual navigating effects, such as the use of laser beams, the combination of audio and video cues, etc. However the digital signage system based emergency exit sign management is one of the best solution to guide people under emergency situations to escape. This research paper, propose an intelligent evacuation route GUIDE that uses the combination centralized Wireless Sensor Networks (WSN) and digital signage for people safety and avoids dangers from emergency conditions. This proposed system applies WSN to detect the environment condition in the building and uses an evacuation algorithm to estimate the safe route to escape using the sensor information and then activates the signage system to display the safe evacuation route instruction GUIDE according to the location the signage system is installed. This paper presented the prototype of the proposed signage system and execution time to find the route with future research directions. The proposed system provides a natural intelligent evacuation route interface for self or remote operation in facility management to efficiently GUIDE people to the safe exit under emergency conditions.

• Smart Structures and Systems
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• v.31 no.3
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• pp.275-281
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• 2023

In recent years, technological developments have rapidly increased the number of complex structures and equipment in the industrial. Accordingly, the prognostics and health monitoring (PHM) technology has become significant. The safety assessment of industrial sites requires data obtained by installing a number of sensors in the structure. Therefore, digital twin technology, which forms the core of the Fourth Industrial Revolution, is attracting attention in the safety field. The research on digital twin technology of structures subjected to seismic loads has been conducted recently. Hence, this study proposes a digital twin system that estimates the responses and arbitrary load in real time by utilizing the minimum sensor to a pipe that receives a seismic and arbitrary load. To construct the digital twin system, a finite-element model was created considering the dynamic characteristics of the pipe system, and then updating the finite-element model. In addition, the calculation speed was improved using a finite-element model that applied the reduced-order modeling (ROM) technology to achieve real-time performance. The constructed digital twin system successfully and rapidly estimated the load and the point where the sensor was not attached. The accuracy of the constructed digital twin system was verified by comparing the response of the digital twin model with that derived by using the load estimated from the digital twin model as input in the finite-element model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.547-553
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• 2020

As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.175-182
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• 2017

In this paper, we present a multi-depth generation method using a time-of-flight (ToF) fusion camera system. Multi-view color cameras in the parallel type and ToF depth sensors are used for 3D scene capturing. Although each ToF depth sensor can measure the depth information of the scene in real-time, it has several problems to overcome. Therefore, after we capture low-resolution depth images by ToF depth sensors, we perform a post-processing to solve the problems. Then, the depth information of the depth sensor is warped to color image positions and used as initial disparity values. In addition, the warped depth data is used to generate a depth-discontinuity map for efficient stereo matching. By applying the stereo matching using belief propagation with the depth-discontinuity map and the initial disparity information, we have obtained more accurate and stable multi-view disparity maps in reduced time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.1039-1046
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• 2000

This paper introduces the control and measurement of a double parallel robot manipulator applied for unknown geometric surface grinding. A measurement system is developed to recognize a grinding path by a vision camera and to observe a grinding load by a current sensor. With the measured fusion information, an intelligent controller identifies the unknown geometric surface and moves the robot along the grinding path with a constant grinding load.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.289-297
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• 2009

This paper presents the development and control of a two wheeled car-like mobile robot using balancing mechanism whose heading control is done by turning the handle. The mobile inverted pendulum is a combined system of a mobile robot and an inverted pendulum system. A sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. Experimental studies of the trajectory following control task has been conducted by command of steering wheel while balancing.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2019-2023
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• 2005

In this paper, an autonomous omni directional cleaning robot which recognizes an obstacle and a battery charger is introduced. It utilizes a robot vision, ultra sonic sensors, and infrared sensors information along with appropriate algorithm. Three omni-directional wheels make the robot move any direction, enabling a faster maneuvering than a simple track typed robot. The robot system transfers command and image data through Blue-tooth wireless modules to be operated in a remote place. The robot vision associated with sensor data makes the robot proceed in an autonomous behavior. An autonomous battery charger searching is implemented by using a map-building which results in overcoming the error due to the slip on the wheels, and camera and sensor information.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.175-175
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• 2000

In this Paper we propose a navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with biases and measurement noise, are investigated with theoretically data from KRISO's AUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system comment)'used aboard underwater vehicle.