• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of IKEEE
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• v.28 no.1
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• pp.90-96
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• 2024

In this paper, we propose an automated system. It utilizes a Raspberry Pi camera and a function generator to analyze luminance in an image. Then, it applies voltage based on this analysis to control light transmission through coloring smart windows. The existing luminance meters used to measure luminance are expensive and require unnecessary movement from the user, making them difficult to use in real life. However, after taking a photography, luminance analysis in the image using the Python Open Source Computer Vision Library (OpenCV) is inexpensive and portable, so it can be easily applied in real life. This system was used in an environment where smart windows were applied to detect the luminance of windows. Based on the brightness of the image, the coloring of the smart window is adjusted to reduce the brightness of the window, allowing occupants to create a comfortable viewing environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1136-1141
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• 2016

IoT technology has been used as a core technology of convergence service that needs intelligent information processing, and the importance is largely emerging now. And internal network construction thru IoT interaction device can connect with IoT device effectively, provide diverse services by connection with open platform. Especially, beacon that is based on low electric power bluetooth device is receiving attention as one of core technology of IoT. Beacon technology is utilized widly in various fields of industry, and there are lot of demands in the specific environment and conditions beyond the basic function. On this thesis, the authors are proposing the beacon device that utilized acceleration sensor and hole sensor. this beacon device can control the target on specific situation thru sensing of moving target. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.499-508
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• 2004

The Smart Home or intelligent home network control system has the need for home devices to cooperate for the purpose of providing the automated services to residents. The cooperation of home devices can be defined as the service for residents that it controls simultaneously two or more home devices with the same purpose about user's control request of specific home device. A object of home device cooperation are the function object of home device, it is well defined in each device model in AHAM(Association of Home Appliance Manufactures) nth(Connected Home Appliances). AMAM CHA is to promote new appliance services and features enabled through networking by describing generic appliance models, objects, and high-level messages, but does not consider the description and process of cooperation between objects of each device model. This paper defines the cooperation relationship that could be discovered in among home devices, and proposes the cooperation model that AHAM objects could process the cooperation relationship.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.563-565
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• 2010

LED is low power and pro-environment semiconductor element. That can be used not only as the lighting function but also for Visible Light Communication(VLC). The VLC is the communication technology that can send data by blinking a fluorescent or LED using visible spectrum. That velocity of blinking can not be usually recognized by eyesight. Visible Light Communication using LED can be used in many fields. In the field of ITS(Intelligent Transportation System), Under construction on the road, Emitting traffic signs can be applied to transfer the vehicle information. In this paper, Emitting traffic signs in addition to the VLC give information about road condition, safety distance and the lane change. We design Communication protocol to provide safety service and verify protocol by experiment.

• Journal of Auto-vehicle Safety Association
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• v.10 no.4
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• pp.33-39
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• 2018

Recently, the automobile industry has developed ADAS (Advanced Driver Assistance System) to prevent traffic accidents and reduce driver's driving burden. Among the ADAS, the LKAS (Lane Keeping Assistance System) is a support system for the convenience and safety of the driver, and the main function is to maintain the driving lane of the vehicle. LKAS is a system that uses radar sensor and camera sensor to collect information about the position of the vehicle in the lane and to support keeping the lane through control if necessary. In many countries, LKAS has already been commercialized and the convenience and safety of drivers have been improved. The international LKAS evaluation test procedure is being developed and discussed by standardization committees such as the ISO (International Organization for Standardization) and the Euro NCAP (New Car Assessment Program). In Korean, the LKAS test method is specified in the KNCAP (Korean New Car Assessment Program), but the evaluation method is not defined. Therefore, the LKAS test procedure that meets international standards and is suitable for domestic road environment is necessary. In this paper, development of LKAS test evaluation scenarios that meets international standards and considering domestic road environment, and the formula that can evaluate the result value after control as the relative distance of lane and the front wheel are suggested. And a comparative analysis was conducted to verify the validity of the suggested scenario and formula. The test evaluation was conducted using the vehicle equipped with the LKAS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.141-152
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• 2011

Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.