• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.12
• /
• pp.1372-1378
• /
• 2011

The smart air condition system is superior to conventional air condition system in the aspect of control accuracy, environmental preservation and it is foundation for intelligent vehicle such as electric vehicle, fuel cell vehicle. In this paper, failure analyses of smart air condition system will be performed and then sensor fusion technique will be proposed for fail safety of smart air condition system. A sensor fusion logic of air condition system by using CO sensor, $CO_2$ sensor and VOC, $NO_x$ sensor will be developed and simulated by fault injection simulation. The fusion technology of smart air condition system is generated in an experiment and a performance analysis is conducted with fusion algorithms. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.130-136
• /
• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.1
• /
• pp.83-89
• /
• 2010

If an appliance perceives the location or health condition of a resident in the smart home, it can provide more intelligent service actively. That is, while the conventional appliance is operated by manual input of a resident, the location-based human adaptive appliance detects the resident's information such as location, activity pattern, or health condition by itself and provides the most suitable living condition for the resident autonomously. This paper presents the real-time location-based metabolic rate estimation method that measures the amount of physical activity (metabolic rate) for location-based human adaptive air-conditioner. And, the feasibility of the algorithm is evaluated experimentally on a test bed using the pyroelectric infrared sensor-based indoor location aware system (PILAS) that is a non-terminal-based location-aware system.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.559-567
• /
• 2018

In this paper, we propose a new load forecasting method for smart air conditioning (A/C) based on the modified thermodynamics of indoor temperature and the unbiased finite memory estimator (UFME). Based on modified first-order thermodynamics, the dynamic behavior of indoor temperature can be described by the time-domain state-space model, and an accurate estimate of indoor temperature can be achieved by the proposed UFME. In addition, a reliable A/C load forecast can be obtained using the proposed method. Our study involves the experimental validation of the proposed A/C load forecasting method and communication construction between DR server and HEMS in a test bed. Through experimental data sets, the effectiveness of the proposed estimation method is validated.

• 한국전산유체공학회:학술대회논문집
• /
• 2004.10a
• /
• pp.95-99
• /
• 2004

The developing Smart UAV in KARI supposes high speed flight as like a conventional plane, as well as vertical takeoff and landing as like a helicopter. Therefore, the air intake system should be designed to provide the sufficient air flow to the engine and the maximum possible total pressure recovery at the engine intake screen over a wide range of flight conditions. For this purpose, we designed the intake system using a pilot type intake model and plenum chamber In this paper, we designed the intake model and analyzed the performance of designed intake system using the general-purpose commercial CFD code, CFD-ACE+ For 3-D calculation, we generated mesh using the unstructured gird and used $\kappa-\epsilon$ turbulence model. The analysis results of the total pressure variation and the velocity distribution was illustrated in this paper. The pressure recovery and distortion coefficient at a plane coincident with the compressor inlet were calculated and streamline variation through the intake system was investigated at the worst condition as well as the standard flight condition.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.3
• /
• pp.515-524
• /
• 2010

Recently, many actions are taking to accelerate progress toward social consensus and implementation of Smart Grid. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. The most distinguished element will be Advanced Metering Infrastructure (AMI) that will be installed to every end-use consumer's home or building and optimize the energy consumption of the end-use consumer. The key function of AMI is energy management capability that coordinates and optimally controls the various loads according to the operating condition and environments. In this study, we figure out the basic function of AMI in Smart Energy House that can be defined as a model house implementing in Smart Grid. This paper proposes the energy management algorithm that will be implemented in AMI at Smart Energy House. The paper also show how energy saving in Smart Energy House can be achieved applying the proposed algorithm to an actual house model that has mainly lighting, air-conditioning, TV loads.

• Convergence Security Journal
• /
• v.20 no.2
• /
• pp.145-153
• /
• 2020

The aviation safety policy master plan is promoting the development of aviation safety management technology applying the 4th industrial revolution technology with the goal of establishing a flawless aviation safety management system and establishing a future aviation safety infrastructure. The master plan includes the establishment of various aviation safety management systems such as aircraft fault management using AI & Big data and flight training system using VR/AR. Currently, the Air Force is promoting a flight safety management system using new technology under the goal of building smart air force. Therefore, this study intends to apply the 4th Industrial Revolution technology to the aircraft condition check system that finally checks the safety of the aircraft before flight. The Air Force conducts airframe flaw checks and pre-flight aircraft check. In this study, we architect the airframe flaw check system using AI and drones, and the pre-flight aircraft condition check system using the IoT and big data for more precise and detailed check of aircraft condition and flawlessness check.

• Aerospace Engineering and Technology
• /
• v.3 no.2
• /
• pp.197-207
• /
• 2004

The developing Smart UAV in KARI supposes high speed flight as like a conventional plane, as well as vertical takeoff and landing as like a helicopter. Therefore, the air intake system should be designed to provide the sufficient air flow to the engine and the maximum possible total pressure recovery at the engine intake screen over a wide range of flight conditions. For this purpose, we designed the intake system using a pitor type intake model and plenum chamber. In this paper, we designed the intake model and analyzed the performance of designed intake system using the general-purpose commercial CFD code, CFD-ACE+. The analysis results of the total pressure variation and the velocity distribution were illustrated in this paper. The pressure recovery and distortion coefficient at a plane coincident with the compressor inlet were calculated and streamline variation through the intake system was investigated at the worst flight condition as well as the standard flight condition.

• International journal of advanced smart convergence
• /
• v.9 no.2
• /
• pp.123-128
• /
• 2020

We constructed a cooling system for solar cells using convection phenomena and investigated its cooling performance. The cooling system didn't need any driving power or water resources. The convection cooler manufactured with a right-triangle shape of an air duct was attached to the rear of the solar cell to confirm that cooling was performed using convection phenomena. When the ratio of duct width to attachment surface width was 3:7, and the ratio of entrance height and exit height of duct was 5:1, it showed the best cooling performance. Comparative experiments with solar cells without convection cooler showed that cooling effects from 16.5℃ to 20.9℃ occurred after 40 minutes exposed to the 1300W Xenon lamp condition.

• International journal of advanced smart convergence
• /
• v.4 no.1
• /
• pp.45-53
• /
• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.