• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.299-305
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• 2021

Dissolved oxygen, pH, and temperature are the most important factors for fish farming because they affect fish growth and mass mortality of the fish. Therefore, fish farm workers must always check all pools on the farm, but this is very difficult in reality. That's why we developed a control system for smart fish farms. This system includes a gateway, sensor gatherers, and a PC program using LabVIEW. One sensor gatherer can cover up to four pools. The sensor gatherers are connected to the gateway in the form of a bus. For the gateway, the ATmega2560 is used as the main processor for communication and the STM32F429 is used as a sub-processor for displaying LCD. For the sensor gatherer, ATmega2560 is used as the main processor for communication. MQTT (Message Queuing Telemetry Transport), RS-485, and Zigbee are used as the communication protocols in the control system. The users can control the temperature and the dissolved oxygen using the PC program. The commands are transferred from the PC program to the gateway through the MQTT protocol. When the gateway gets the commands, it transfers the commands to the appropriate sensor gatherer through RS-485 and Zigbee.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.124-132
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• 2023

In this paper, we present a simple classification model based on statistical features and demonstrate the successful implementation of a brain-computer interface (BCI) based light on/off control system. This research shows study and development of light on/off control system based on BCI technology, which allows the users to control switching a lamp using electroencephalogram (EEG) signals. The logistic regression algorithm is used for classification of the EEG signal to convert it into light on, light off control commands. Training data were collected using 14-channel BCI system which records the brain signals of participants watching a screen with flickering lights and saves the data into .csv file for future analysis. After extracting a number of features from the data and performing classification using logistic regression, we created commands to switch on a physical lamp and tested it in a real environment. Logistic regression allowed us to quite accurately classify the EEG signals based on the user's mental state and we were able to classify the EEG signals with 82.5% accuracy, producing reliable commands for turning on and off the light.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.91-100
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• 2009

In this paper, we propose autonomous intelligent wheelchair system which recognize the commands using the gaze recognition and avoid the detected obstacles by sensing the distance through range sensors on the way to driving. The user's commands are recognized by the gaze recognizer which use a centroid of eye pupil and two reflection points extracted using a camera with infrared filter and two infrared LEDs. These are used to control the wheelchair through the user interface. Then wheelchair system detects the obstacles using 10 ultrasonic sensors and assists that it avoid collision with obstacles. The proposed intelligent wheelchair system consists of gaze recognizor, autonomous driving module, sensor control board and motor control board. The gaze recognizer cognize user's commands through user interface, then the wheelchair is controled by the motor control board using recognized commands. Thereafter obstacle information detected by ultrasonic sensors is transferred to the sensor control board, and this transferred to the autonomous driving module. In the autonomous driving module, the obstacles are detected. For generating commands to avoid these obstacles, there are transferred to the motor control board. The experimental results confirmed that the proposed system can improve the efficiency of obstacle avoidance and provide the convenient user interface to user.

• Proceedings of the ESK Conference
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• 2004.10a
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• pp.5-5
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• 2004

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.565-569
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• 2014

Recently, various kinds of new computer controlled devices have been introduced in a wide range of areas, and convenient user interfaces for controlling the devices are strongly needed. To implement natural user interfaces(NUIs) on top of the devices, new technologies like a touch screen, Wii Remote, wearable interfaces, and Microsoft Kinect were presented. This paper presents a natural and intuitive gesture-based model for controlling contents of LCD display. Microsoft Kinect sensor and its SDK are used to recognize human gestures, and the gestures are interpreted into corresponding commands to be executed. A command dispatch model is also proposed in order to handle the commands more naturally. I expect the proposed interface can be used in various fields, including display contents control.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.262-273
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• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.39-47
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• 2005

Different CAx systems are being utilized throughout the product lifecycle due to the practical reasons in the supply chain and design processes. One of the major problems facing enterprises of today is how to share and exchange data among heterogeneous applications. Since different software applications use different terminologies, it is difficult to share and exchange the product data with internal and external partners. This paper presents a method to enhance the CAD model interoperability based on feature ontology. The feature ontology has been constructed based on the feature definition of modeling commands of CAD systems. A method for integration of semantic data has been proposed, implemented, and tested with two commercial CAD systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.5
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• pp.388-395
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• 2016

Electric vehicles (EV) and hybrid EVs (HEV) are designed and manufactured by GM, Toyota, Honda, and Hyundai motors. The propulsion system design process for EV requires integrating subsystem designs into an overall system model to maximize the performance of a given propulsion architecture. Therefore, high-power density and high-torque density are important attributes required for EV applications. To improve torque and power density, propulsion motors are designed for saturation during high-torque operation. The nonlinearity associated with core saturation is modeled by incorporating the cross-coupling inductances, which also behave nonlinearly. Furthermore, in EV environments, the battery is directly connected to the DC link, and the battery changes depending on the state of charge. It will be onerous if as many optimal current commands as different $V_{dc}$ were made. This paper presents the optimal current commands in the various operating condition and the current control technique in EV environments.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.884-892
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• 2006

This paper describes a framework for multimodal object manipulation in virtual environments. The gist of the proposed framework is the semantic integration of multimodal input using spatial ontology and user context to integrate the interpretation results from the inputs into a single one. The spatial ontology, describing the spatial relationships between objects, is used together with the current user context to solve ambiguities coming from the user's commands. These commands are used to reposition the objects in the virtual environments. We discuss how the spatial ontology is defined and used to assist the user to perform object placements in the virtual environment as it will be in the real world.