• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.4
• /
• pp.475-482
• /
• 2014

In this paper, we have implemented mobile based smart greenhouse system that can grasp and control the situation for greenhouse from distance. Using existing web based greenhouse system is controlled in real time, but it has a drawback used in limited place. To solve this problem, we have emphasized usability of smart greenhouse system by using mobile device. By using mobile devices (smartphones - the Android based) software we have to raise the comfort and productivity for grasping and controling the situation for greenhouse from distance.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.64 no.5
• /
• pp.27-39
• /
• 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.

• Transactions of the Korean hydrogen and new energy society
• /
• v.23 no.1
• /
• pp.100-109
• /
• 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
• /
• v.1 no.1
• /
• pp.69-74
• /
• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.505-507
• /
• 2021

Image recognition technology is a technology that recognizes an image object by using the generated feature descriptor and generates object feature points and feature descriptors that can compensate for the shape of the object to be recognized based on artificial intelligence technology, environmental changes around the object, and the deterioration of recognition ability by object rotation. The purpose of the present invention is to implement a power management framework required to increase profits and minimize damage to livestock farmers by preventing accidents that may occur due to the improvement of efficiency of the use of livestock house power and overloading of electricity by integrating and managing a power fire management device installed for analyzing a complex environment of power consumption and fire occurrence in a smart safety livestock house, and to develop and disseminate a safe and optimized intelligent smart safety livestock house.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.35 no.2
• /
• pp.160-164
• /
• 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.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.3
• /
• pp.537-546
• /
• 2019

In this paper, a system that integrates a home concentrate unit(HCU) in a smart electricity meter to collects water, gas, hot water, and heating usage required for AMI has been proposed. The collected data could be transmitted to the in house display(IHD) and server to provide a more economical AMI system. The developed system is less expensive in the network configuration than the existing system, which could reduce the operating cost, and be easy to install. By applying the developed system, the usage of electricity, water, gas, hot water and heating could be measured and these make it easier to apply AMI system. The main contents of the development are the smart electricity meter and embedding of HCU into the smart electricity meter, and transferring these data to IHD and server to structure the AMI system. The each developed unit has been networked to structure the AMI system to perform the actual meter reading operation and show the result.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.10
• /
• pp.1795-1803
• /
• 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.

• Journal of Climate Change Research
• /
• v.7 no.3
• /
• pp.217-229
• /
• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.818-821
• /
• 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.