• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.3
• /
• pp.248-253
• /
• 2008

This paper presents a sensing system for smart home which can detect an location transition events such as entrance/exit of a member and identify the user in a group at the same time. The proposed system is compose of two sub-systems; a wireless sensor network system and a database server system. The wireless sensing system is designed as a star network where each of sensing modules with ultrasonic sensors and a Bluetooth RF module connect to a central receiver called Bluetooth access point. We propose a method to discriminate a user by measuring the height of the user. The differences in the height of users is a key feature for discrimination. At the same time, the each sensing module can recognize whether the user goes into or out a room by using two ultrasonic sensors. The server subsystem is a sort of data logging system which read the detected event from the access point and then write it into a database system. The database system could provide the location transition information to wide range of context-aware applications for smart home easily and conveniently. We evaluate the developed method with experiments for three subjects in a family with the installation of the developed system into a real house.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.6
• /
• pp.1343-1349
• /
• 2014

Recently feature phones are being replaced by smartphones. Because smartphones have various sensors, there are many applications and research works that utilize them. Very few feature phones have GPS modules but all smartphones are equipped with a GPS sensor. One of the hot issues for smartphone research and development is point interest research. In this paper, we will develop an application which protects children using GPS and WiFi.. If a child gets out of the interest-area which is established by parents or guardian, our system sends them messages.

• Smart Structures and Systems
• /
• v.12 no.2
• /
• pp.209-233
• /
• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.8
• /
• pp.122-131
• /
• 2011

In this paper, the design and analysis of a reconfigurable modular structure, which reforms itself according to the change of the environment and realize appropriate forms and motions, are dealt with. This modular is a free structure from the restrictions with constraints about fixed environment and has various forms and motions by combining units. The form of this unit has a shape of a square with 7 centimeters side each, and has a structure which can be combined in a chain-shape or a lattice-shape. Additionally, The structure has a mobility by being equipped with wheels so that it can be combined for itself. In this paper, all the wireless controllers, sensor system, and communicating method between modules according to module structures were suggested and transformation method to be transformed to shape of snakes, caterpillars were presented. Moreover, simulations for each method were performed to show the validity of the motions including motor torque analysis. All the motions suggested were realized and experimented, whereby the availability of the designed mechanism and algorithm was verified with the result of experiments.

• Korean Journal of Remote Sensing
• /
• v.19 no.5
• /
• pp.393-402
• /
• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Smart Structures and Systems
• /
• v.10 no.1
• /
• pp.1-14
• /
• 2012

Given an object, its positioning in the space is a main concern in structural monitoring and a required feedback in structural health monitoring, structural control and robotics. In addition, to make the sensor unit wireless is a crucial issue for advanced applications. This paper deals with the exploitation of wireless transmission technology to long-term monitoring GPS (Global Positioning System) receivers - like the Leica GMX 902 and the Leica GRX 1200-pro. These GPS receivers consist of five parts: antenna, receiver, user client computer, interface and power supply. The antenna is mounted on the object to be monitored and is connected with the receiver by a coaxial-cable through which the radio frequency signals are transmitted. The receiver unit acquires, tracks and demodulates the satellite signals and provides, through an interface which in this paper is made wireless, the resulting GPS raw data to the user client computer for being further processed by a suitable positioning algorithm. The power supply reaches the computer by a wired link, while the other modules rely on batteries re-charged by power harvesting devices. Two wireless transmission systems, the 24XStream and the CC1110, are applied to replace the cable transmission between the receiver and the user client computer which up to now was the only market offer. To verify the performance and the reliability of this wireless transmission system, some experiments are conducted. The results show a successful cable replacement.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.25 no.5
• /
• pp.246-254
• /
• 2013

Some characteristics of nitrogen-water slug flow were optically measured, in vertical acrylic tubes of 2, 5 and 8 mm diameter. Bubble velocity, bubble and unit cell lengths were measured, by analyzing the light intensity signals from two sets of dot laser-infrared sensor modules mounted along the transparent tubes. Optical images of the bubbles were also taken and analyzed, to measure bubble shapes and liquid film thickness. It was found that the measured bubble velocities were in good agreement with the empirical models in the literature, except for those measured under high superficial velocity condition in the 2 mm tube. Bubble length was found to be the longest in the 2 mm tube, being 4 to 5 times those of the other tubes. Liquid film was found to have developed early in the 2 mm tube, which made the blunt shape of the bubble head. Liquid film thickness in the 8 mm tube was measured at almost twice those of the other tubes.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1760-1768
• /
• 2022

When gamma-camera sensor modules, which are key components of radiation imagers, are derived from the coupling between scintillators and photosensors, the light collection efficiency is an important factor in determining the effectiveness with which the instrument can identify nuclides via their derived gamma-ray spectra. If the pixel area of the scintillator is larger than the pixel area of the photosensor, light loss and cross-talk between pixels of the photosensor can result in information loss, thereby degrading the precision of the energy estimate and the accuracy of the position-of-interaction determination derived from each active pixel in a coded-aperture based gamma camera. Here we present two methods to overcome the information loss associated with the loss of photons created by scintillation pixels that are coupled to an associated silicon photomultiplier pixel. Specifically, we detail the use of either: (1) light guides, or (2) scintillation pixel areas that match the area of the SiPM pixel. Compared with scintillator/SiPM couplings that have slightly mismatched intercept areas, the experimental results show that both methods substantially improve both the energy and spatial resolution by increasing light collection efficiency, but in terms of the image sensitivity and image quality, only slight improvements are accrued.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.9
• /
• pp.2846-2866
• /
• 2022

Caenorhabditis elegans exhibits sophisticated chemotaxis behavior through two parallel strategies, klinokinesis and klinotaxis, executed entirely by a small nervous circuit. It is therefore suitable for inspiring fast and energy-efficient solutions for autonomous navigation. As a random search strategy, the Lévy walk is optimal for diverse animals when foraging without external chemical cues. In this study, by combining these biological strategies for the first time, we propose a spiking neural network model for search and contour tracking of specific concentrations of environmental variables. Specifically, we first design a klinotaxis module using spiking neurons. This module works in conjunction with a klinokinesis module, allowing rapid searches for the concentration setpoint and subsequent contour tracking with small deviations. Second, we build a random exploration module. It generates a Lévy walk in the absence of concentration gradients, increasing the chance of encountering gradients. Third, considering local extrema traps, we develop a termination module combined with an escape module to initiate or terminate the escape in a timely manner. Experimental results demonstrate that the proposed model integrating these modules can switch strategies autonomously according to the information from a single sensor and control steering through output spikes, enabling the model worm to efficiently navigate across various scenarios.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.53-62
• /
• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.