• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1254-1262
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• 2021

Recently, the agricultural environment in Korea is rapidly changing due to the aging and decline of the agricultural population, and in order to solve these problems, it is urgently required to improve the agricultural productivity and reduce the labor force. To solve this problem, a smart farm fused with ICT technology is being proposed as an alternative. In Korea, smart farms are currently mainly used in greenhouses. In this paper, this smart farm technology is to be applied to the cultivation of sprouted ginseng. To this end, we use seedlings (about 1.0g) to grow a solid medium and bed for cultivating sprouted ginseng, a fresh ginseng that is produced in a short period of time (2~3 months) with a clean environment management technology that does not use chemical pesticides and hydroponics in a greenhouse developed. In addition, an IoT-based growth environment management system was developed to monitor the growth process of sprouted ginseng in such an environment and to control driving devices.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.51-63
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• 2022

Up-to-date statistics of crop cultivation status is essential for farm land management planning and the advancement in remote sensing technology allows for rapid update of farming information. The objective of this study was to develop a classification model of rice paddy or winter crop fields based on NDWI, NDVI, and HSV indices using Sentinel-2 satellite images. The 18 locations in central Korea were selected as target areas and photographed once for each during summer and winter with a eBee drone to identify ground truth crop cultivation. The NDWI was used to classify summer paddy fields, while the NDVI and HSV were used and compared in identification of winter crop cultivation areas. The summer paddy field classification with the criteria of -0.195

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.47-56
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• 2023

Hydrogen energy is an eco-friendly energy that produces heat and electricity with high energy efficiency and does not emit harmful substances such as greenhouse gases and fine dust. In particular, smart hydrogen energy is an economical, sustainable, and safe future smart hydrogen energy service, which means a service that stably operates based on 'data' by digitally integrating hydrogen energy infrastructure. In this paper, in order to implement a data-based hydrogen charging station demand forecasting model, three hydrogen charging stations (Chuncheon, Sokcho, Pyeongchang) installed in Gangwon-do were selected, supply and demand data of hydrogen charging stations were secured, and 7 machine learning and deep learning algorithms were used. was selected to learn a model with a total of 27 types of input data (weather data + demand for hydrogen charging stations), and the model was evaluated with root mean square error (RMSE). Through this, this paper proposes a machine learning-based hydrogen charging station energy demand prediction model for optimal hydrogen energy supply and demand.

• Journal of the Korean Institute of Gas
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• v.28 no.1
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• pp.1-10
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• 2024

In this study, we constructed a process simulation model for an agricultural by-products based Solid Oxide Fuel Cell (SOFC) combined heat and power generation system as part of the introduction of technology for energy self-sufficiency in the agricultural sector. The aim was to reduce the burden of increasing fuel and electricity consumption due to rapid fluctuations in international oil prices and the expansion of smart farming in domestic farms, while contributing to the national greenhouse gas reduction goals. Based on the experimental results of 0.3 ton/day torrefied agricultural by-product gasification experiment, a model for an agricultural by-product-based SOFC cogeneration system was constructed, and optimization of the heat exchange network was conducted for SOFC capacities ranging from 4 to 20 kW. The results indicated that an 8 kW agricultural by-product-based SOFC cogeneration system was optimal under the current system conditions. It is anticipated that these research findings can serve as foundational data for future commercial facility design.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.12-18
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• 2024

The accelerated pace of climate crisis due to continuous industrialization and greenhouse gas emissions necessitates sustainable solutions that simultaneously address mitigation and adaptation to climate change. Naturebased Solutions (NbS) have gained prominence as viable approaches, with Green Infrastructure being a representative NbS. Green Infrastructure involves securing green spaces within urban areas, providing diverse climate adaptation functions such as removal of various air pollutants, carbon sequestration, and isolation. The proliferation of Green Infrastructure is influenced by the quantification of improvement effects related to various projects. To support decision-making by assessing the climate vulnerability of Green Infrastructure, the U.S. Department of Agriculture (USDA) has developed i-Tree Tools. This study proposes a comprehensive evaluation approach for climate change adaptation types by quantifying the climate adaptation performance of urban Green Infrastructure. Using i-Tree Canopy, the analysis focuses on five urban green spaces covering more than 30 hectares, considering the tree ratio relative to the total area. The evaluation encompasses aspects of thermal environment, aquatic environment, and atmospheric environment to assess the overall eco-friendliness in terms of climate change adaptation. The results indicate that an increase in the tree ratio correlates with improved eco-friendliness in terms of thermal, aquatic, and atmospheric environments. In particular, it is necessary to prioritize consideration of the water environment sector in order to realize climate change adaptive green infrastructure, such as increasing green space in urban areas, as it has been confirmed that four out of five target sites are specialized in improving the water environment.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.415-426
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• 2013

Smart work has recently introduced as a way to solve problems such as greenhouse gas emissions, low birth rate and aging as well as to improve productivity. Because of development of ICT infrastructure and the proliferation of smart devices, the mobile office has the most commonly used within types of smart work in Korea. But the adoption of the mobile office in small businesses is only half of that of large corporations. The security issue appears to be one of the biggest obstacles to the introduction of smart work in small businesses. Therefore, the purpose of this study is to analyze the information security factors that should be considered when the mobile office is introduced to small businesses. By analyzing the previous studies, the information security factors of the mobile office are classified 5 groups composed of 24 factors. 5 groups are terminals, applications and platforms, networks, servers and users. According to the survey result using AHP, 'User' was drawn to the most important group, and 'Data Encryption', 'Wireless LAN Control' and 'Terminal Recovery When Leaving' were drawn to the important information security factors of the mobile office among 24 factors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.290-298
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• 2019

The proportion of farm households in the total population is decreasing every year. The aging of rural areas is expected to deepen. The aging of agriculture is continuing due to the aging of the aged population and the decline of the young population, and agricultural manpower shortage is emerging as a threat to agriculture and rural areas. The existing facility cultivation was concentrated on the production / yield per unit area. However, nowadays, not only production but also crop quality should be good so that the quality of crops must be improved because they can secure competitiveness in the market. Therefore, the government plans to increase the productivity by hi-techization of ICT infrastructure horticulture and to plan the dissemination of energy saving smart greenhouse. Therefore, it is necessary to develop a Smart Farm convergence service system based on a hybrid algorithm to enhance diversity and connectivity. Therefore, this study aims to develop smart farm convergence service system which collects data of growth environment of the rhizosphere environment of crops by wireless and monitor smartphone.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• IE interfaces
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• v.25 no.3
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• pp.338-346
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• 2012

Regarding the green environment, it is important to boost the spread of environmentally friendly vending machines and to operate the vehicles for their inventory replenishments while minimizing emissions of greenhouse gases. In general, the vending machine management company lacks capability to operate the supply chain effectively in an integrated way under the dynamic, complex, and stochastic environment. This paper presents a decision support system, termed DSSVM, for the operations of the general and smart vending machine supply chains with stock-out-based, one stage item substitution in a green logistics environment. The DSSVM supports the estimation of item demand and substitution probabilities, determination of operation parameters, supply chain analysis, what-if analysis, and $CO_2$ analysis for which various analytical models are employed.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.