• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.480-483
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• 2018

In this paper, we study the interference canceling and image sensing processing technology of multiple light sources for high speed transmission in CMOS sensor based visible light communication system. To improve transmission capacity in optical camera communications via image sensors, different data must be transmitted simultaneously from each LED. However, multiple LED light source environments for high-speed transmission can cause interference between adjacent LEDs. In this case, since the visible light communication system generally uses intensity modulation, when a plurality of LEDs transmit data at the same time, it is difficult to accurately detect the respective LEDs due to the light scattering interference of the adjacent LEDs. In order to solve this problem, the ON / OFF state of many LEDs of the light source is accurately recognized by using a dual CMOS sensor, and the spectral estimation technique and the pixel image signal processing technique of each LED are proposed. This technique can accurately recognize multiple LED pixels and improve the total average bit error rate and throughput of a MISO-VLC system.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.78-84
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• 2022

In this paper, we propose a closed-form based 3D localization method in the presence of multiple signal sources. General localization methods such as TDOA, AOA, and FDOA can estimate a location when a single signal source exists. When there are multiple unknown signal sources, there is a limit in estimating the location. The proposed method calculates a cross-correlation vector of signals received by sensors having an array antenna, and estimates TDOA and AOA values from the cross-correlation values. Then, the coordinate transformation is performed using the position of the reference sensor. Then, the coordinate rotation is performed using the estimated AOA value for the transformed coordinates, and then the three-dimensional position of each emitter is estimated. The proposed method verifies its performance through computer simulation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• Smart Structures and Systems
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• v.8 no.4
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• Journal of Magnetics
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• v.21 no.3
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• pp.330-339
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• 2016

A magnetic field sensing system with a single primary sensor and multiple reference sensors deployed locally and orthogonally, was proposed for downlink signal reception and interference cancelling for Through-the-Earth Communication (TEC). This paper mathematically analyzes a design optimization process for a search coil magnetometer (SCM), and applies that process to minimize the bandwidth of the primary SCM for TEC signal reception and the volume of reference SCMs for multiple distributions. The primary SCM achieves a 3-dB bandwidth of 7 Hz, a sensitivity threshold of 120 fT/${\surd}$Hz, and a volume of $2.32{\times}10^{-4}m^3$. The entire sensing system volume is as small as $10^{-2}m^3$. Experiments with interference from industrial frequency harmonics demonstrated an average of 36 dB and 18 dB improvements in signal-to-interference ratio and signal-to-interference plus noise ratio, respectively, using multichannel recursive-least-squares algorithm. Thus, the proposed sensing system can reduce the interference effectively and allows reliable downlink signal reception.

• Journal of Sensor Science and Technology
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• v.23 no.4
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• pp.272-277
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• 2014

At present, the index of chemical oxygen demand (COD) is widely used as an indicator of organic water pollution with biochemical oxygen demand (BOD). But, traditional COD measurement method are not only with various chemical reagents exhausted, but also long time consumed, the operation procedure and the modification are much professional. This paper reported a novel COD measurement system using double-beam and multiple wavelength analysis UV-VIS spectrometries. It consists of pulsed xenon lamp, two-way optical fiber, optical switch, spectrometer and main processor. Proposed COD measurement system obtains any spectral information of water sample (KHP standard sample and two river water and wastewater) and reference sample (distilled water) in the range of 200~520 nm, corresponding to the COD concentration from 0 to 300 mg/L through calculating the UV absorbance. The system show improved precision and can work continuously fast at time interval about 25 seconds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2853-2873
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• 2013

Over the last few years, one of the most common purposes of smart homes is to provide human centric services in the domain of u-healthcare by analyzing inhabitants' daily living. Currently, the major challenges in activity recognition include the reliability of prediction of each classifier as they differ according to smart homes characteristics. Smart homes indicate variation in terms of performed activities, deployed sensors, environment settings, and inhabitants' characteristics. It is not possible that one classifier always performs better than all the other classifiers for every possible situation. This observation has motivated towards combining multiple classifiers to take advantage of their complementary performance for high accuracy. Therefore, in this paper, a method for activity recognition is proposed by optimizing the output of multiple classifiers with Genetic Algorithm (GA). Our proposed method combines the measurement level output of different classifiers for each activity class to make up the ensemble. For the evaluation of the proposed method, experiments are performed on three real datasets from CASAS smart home. The results show that our method systematically outperforms single classifier and traditional multiclass models. The significant improvement is achieved from 0.82 to 0.90 in the F-measures of recognized activities as compare to existing methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.45-51
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• 2012

In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.159-173
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• 2009

Locations of positioned nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times. And this research verifies this technology is excellent in terms of performance, accuracy, and scalability through simulation.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.193-207
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• 2017

In this study, the vibration of an electrostatically actuated micro cantilever beam is analyzed in which a viscoelastic layer covers a portion of the micro beam length. This proposed model is considered as the main element of mass and pollutant micro sensors. The nonlinear motion equation is extracted by means of Hamilton principle, considering nonlinear shortening effect for Euler-Bernoulli beam. The non-linear effects of electrostatic excitation, geometry and inertia have been taken into account. The viscoelastic model is assumed as Kelvin-Voigt model. The motion equation is discretized by Galerkin approach. The linear free vibration mode shapes of non-uniform micro beam i.e. the linear mode shape of the system by considering the geometric and inertia effects of viscoelastic layer, have been employed as comparison function in the process of the motion equation discretization. The discretized equation of motion is solved by the use of multiple scale method of perturbation theory and the results are compared with the results of numerical Runge-Kutta approach. The frequency response variations for different lengths and thicknesses of the viscoelastic layer have been founded. The results indicate that if a constant volume of viscoelastic layer is to be deposited on the micro beam for mass or gas sensor applications, then a modified configuration may be found by using the analysis of this paper.