• 한국전자통신학회논문지
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• 제9권4호
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• pp.475-482
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• 2014

본 논문에서는 원거리에서 온실 상황 파악과 온실을 제어 할 수 있는 모바일 기반 스마트 온실 시스템을 구현하였다. 기존의 웹을 이용한 온실 시스템은 실시간으로 제어가 가능하지만, 사용 장소에 제한적이라는 단점이 있었다. 이를 해결하기 위하여 모바일 기기를 이용한 스마트 온실 시스템의 유용성을 강조하였다. 원거리에서 모바일기기(스마트폰 - 안드로이드 기반)에 설치되는 소프트웨어를 이용하여 온실의 상황을 파악하고 장비들을 제어함으로써 편의성과 생산성을 높였다.

• 한국농공학회논문집
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• 제64권5호
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• pp.27-39
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• 2022

The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.

• 한국수소및신에너지학회논문집
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• 제23권1호
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• pp.100-109
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• 2012

In this paper, some ideas are proposed to establish the infrastructure of all-electric houses which are able to reduce primary energy consumption and $CO_2$ emission by adopting heat pump systems and induction heating cookers excluding the use of fossil fuel energy. This electrification concept is based on the consumption of only one type of energy which means electricity as secondary energy and the conventional fossil fuel energy is just consumed to generate electricity as primary energy. All-electric house is laid on the extension of the hydrogen economy in a long-term viewpoint so that the effectiveness of this new conceptual house is estimated analyzing the reduction of $CO_2$ emission. In this analysis, the balance of electricity supply and demand is considered including the construction of new power plants by renewable energy such as nuclear, IGCC and fuel cell because decarbonization is an essential element of hydrogen technology and economy and this action is accomplished in both supply and demand side of electricity. The results are able to contribute to develop various useful hydrogen policies and strategies and some detail researches are required previously to make the best application of this new conceptual house.

• Journal of Smart Tourism
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• 제1권1호
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• pp.69-74
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• 2021

Restaurants are an important area of the hospitality industry. This industry sector has not only experienced severe consequences of the recent lockdowns, but it has also seen the rise of digital technologies. As known from other industries, the digital transformation impacts products, processes and business models alike. Starting from the classical distinction of a restaurant's front- and back-of-the-house processes, this paper presents an overview on current developments in the restaurant industry and based on an analysis of current digital services, it derives some implications for future directions. Among the observations are that restaurants need to cover more touch points, provide more individualized offerings and strive for more automation as well as integration of their systems.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.505-507
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• 2021

영상 인식 기술은 인공지능 기술을 기반으로 인식하고자하는 객체의 형상, 객체 주변의 환경변화 및 객체 회전에 의한 인식 능력 저하를 보완할 수 있는 객체특징점 및 특징 기술자를 생성하고, 생성된 특징 기술자를 이용하여, 영상 객체를 인식하는 기술로, 일반적으로 영상에 나타난 객체를 인식하는 기술을 뜻한다. 스마트 안전 축사에서 전력소비 및 화재 발생 복합 환경 분석을 위해 설치되는 전력화재 관리 디바이스를 통합 관리함으로써 축사 전력 사용의 효율성 향상 및 전기 사용의 과부화로 발생할 수 있는 사고를 방지하여 축산 농가의 이익 증대 및 피해를 최소화하고 안전하고 최적화된 지능형 스마트 안전 축사를 개발하여 보급하는데 요구되는 전력 관리 프레임워크를 구현하는데 목적이 있다.

• 한국전기전자재료학회논문지
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• 제35권2호
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• pp.160-164
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• 2022

In this paper, through the development of a smart panel (LCD kiosk) controller, contents to develop a system that can be operate in a desired environment by operating the window control and ventilation facilities according to the automatic controller operation based on the set values such as temperature, humidity, sunlight, and rainfall. In particular, the MQTT protocol-based sensor module can be directly manufactured and applied at any time based on various communication and power sources such as wireless, wired, and PLC (power line communication) to obtain the desired data, as well as fire, power failure, and intrusion in the house. It is also a system that enables operation and monitoring from a remote location based on the cloud environment by connecting sensors. Kiosks are currently being used in many places, and the demand for them is on the rise, and an active influx of young people can be expected through environmental improvement. It is expected to increase interest and understanding for improvement.

• 한국전자통신학회논문지
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• 제14권3호
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• pp.537-546
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• 2019

본 논문에서는 스마트 전력량계에 세대집중화장치를 내장하여 AMI에 필요한 가스, 수도, 온수, 난방 검침을 일괄검침하는 시스템과, 검침데이터를 에너지정보표시장치(IHD: In House Display)와 서버로 전송하는 방법을 구성하여 보다 경제적으로 AMI 시스템을 구축하는 방법을 제시한다. 개발된 시스템은 기존 시스템 보다 네트워크 구성에 있어서 가격이 저렴하고 운영비용이 절감되며 설치가 용이하다. 개발된 시스템을 적용하면 전기, 수도, 가스, 온수 및 난방의 5종 계량기의 계량값을 원격검침 하고 이에 대한 AMI 적용을 보다 용이하게 구성 가능하다. 주요개발 내용은 스마트 전력량계 구성과 세대집중화장치 결합 및 이들 데이터를 IHD와 서버로 전송하는 방법이며, 이들 요소들을 연계하여 시스템을 구성하고 실제 검침 동작구성을 테스트하고 그 결과를 보여준다.

• 전기학회논문지
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• 제60권10호
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• pp.1795-1803
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• 2011

Advanced Metering Infrastructure (AMI) is one of the important components to form a smart-gird, which is an advanced power system by combining the power system with the communication systems. This AMI makes it possible to exchange information between operators and consumers for the efficient and reliable operation of the power system through a smart meter or a In-Home Display. However, according to the increase of the demanded information such as the power quality, the accurate load-profile, and the billing data to help customers manage their power consumption, it is necessary to gather more accurate analytical data from each house appliances and transfer it to the smart meter for synthesizing the information and controlling each loads. In this paper, the development of the wireless data acquisition device for the individual load data metering, which is connected with the smart meter for advanced functions, is proposed. AVR, a kind of microcontroller, and Bluetooth are used and integrated into the proposed the wireless data acquisition device to transmit the detailed power data (voltage and current) to the smart meter. To verify the effectiveness of the proposed system, a hardware experiment is carried out including the confirmation of the possibility for providing the more various information by applying analysis algorithms to the obtained data. Also, the application structure of the wireless data acquisition device to gather the data from the various house appliances is presented.

• 한국기후변화학회지
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• 제7권3호
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• pp.217-229
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• 2016

Increased evidences reveal that the global climate change adversely affect on the environment. Smart grid system is one of the ways to reduce greenhouse gas emissions in the electricity generation sector. Since 2013, Korea Electric Power Corporation (KEPCO) has installed smart grid station in KEPCO office buildings. The goal of this paper is two folds. One is to quantify the reduction in greenhouse gas emissions through smart grid stations installed in KEPCO office buildings as a part of pilot project. Among components of smart grid stations, this research focused on the photovoltaic power system (PV) and energy storage system (ESS). The other is to estimate the reduction in greenhouse gas emissions when PV is applied on individual houses. Results show that greenhouse gas emissions reduce 5.8~11.3% of the emissions generated through the electricity usage after PV is applied in KEPCO office buildings. The greenhouse gas emissions reduction from ESS is not apparent. When PV of 200~500 W is installed in individual houses, annual greenhouse gas emission reduction in 2016 is expected to be approximately $2.2{\sim}5.4million\;tCO_2-eq$, equivalent to 6~15% of greenhouse gas emissions through the electricity usage in the house hold sector. The saving of annual electricity cost in the individual house through PV of 200 W and 500 W is expected to be 47~179 thous and KRW and 123~451 thousand KRW, respectively. Results analyzed in this study show the environmental effect of the smart grid station. In addition, the results can be further used as guidance in implementing similar projects.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.818-821
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• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.