• 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.

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.137-155
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• 2024

To achieve the national goal of "2050 Carbon Neutrality" in the era of the climate crisis, it is important to support the decarbonization of ports, which are the vital node of the global supply chain. Following the establishment of the concept of port's decarbonzation, this study reviewed the obstacles and solutions to port decarbonization through literature research. Furthermore, the goals and strategies for decarbonization implementation of world major ports were examined through case analysis, and the level of decarbonization implementation of the five Korean major ports was quantitatively evaluated using a performance-based score measurement method. As a result of the analysis, the level of decarbonization of Korean ports is generally far behind that of advanced countries. In particular, measures for environment-friendly inland transportation, future alternative fuel bunkering facilities, and various market-based incentive policies are needed. As a policy task for the decarbonization of Korean ports, first, the necessity of establishing a emission inventory, monitoring, and reporting system and the disclosure of related information, second, the mixing strategy of various greenhouse gas reduction measures, and third, the increase in the proportion of renewable energy at ports were suggested.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.285-290
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• 2016

In rural area, our farmers confront decreasing benefits owing to imported crops and increased cost. Recently, the government encourage the 6th Industry that merges farming, rural resources, and information and communication technology. Therefor the government makes an investment in supplying 'smart greenhouse' in which a farmer monitor growing crops and environment information to control growing condition. The objective of this study is developing an Moving Monitor and Control System for crops in green House. This system includes a movable sensing unit, a controlling unit, and a server PC unit. The movable sensing unit contains high resolution IP camera, temperature and humidity sensor and WiFi repeater. It rolls on a rail hanging beneath the ceiling of a green house. The controlling unit contains embedded PC, PLC module, WiFi router, and BLDC motor to drive the movable sensing unit. And the server PC unit contains a integrated farm management software and home pages and databases in which the images of crops and environment informations. The movable sensing unit moves widely in a green house and gathers lots of information. The server saves these informations and provides them to customers with the direct commercing web page. This system will help farmers to control house environment and sales their crops in online market. Eventually It will be helpful for farmers to increase their benefits.

• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.251-259
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• 2018

BACKGROUND: Various culture media have been used for hydroponic cultures of horticultural plants under the smart greenhouses with natural and artificial light types. Management of the culture medium for the control of medium amounts and/or necessary components absorbed by plants during the cultivation period is performed with ICT (Information and Communication Technology) and/or IoT (Internet of Things) in a smart farm system. This study was conducted to develop the cloud-based data analysis system for effective management of culture medium applying to hydroponic culture and plant growth in smart greenhouses. METHODS AND RESULTS: Conventional inorganic Yamazaki and organic media derived from agricultural byproducts such as a immature fruit, leaf, or stem were used for hydroponic culture media. Component changes of the solutions according to the growth stage were monitored and plant growth was observed. Red and green lettuce seedlings (Lactuca sativa L.) which developed 2~3 true leaves were considered as plant materials. The seedlings were hydroponically grown in the smart greenhouse with fluorescent and light-emitting diodes (LEDs) lights of $150{\mu}mol/m^2/s$ light intensity for 35 days. Growth data of the seedlings were classified and stored to develop the relational database in the virtual machine which was generated from an open stack cloud system on the base of growth parameter. Relation of the plant growth and nutrient absorption pattern of 9 inorganic components inside the media during the cultivation period was investigated. The stored data associated with component changes and growth parameters were visualized on the web through the web framework and Node JS. CONCLUSION: Time-series changes of inorganic components in the culture media were observed. The increases of the unfolded leaves or fresh weight of the seedlings were mainly dependent on the macroelements such as a $NO_3-N$, and affected by the different inorganic and organic media. Though the data analysis system was developed, actual measurement data were offered by using the user smart device, and analysis and comparison of the data were visualized graphically in time series based on the cloud database. Agricultural management in data visualization and/or plant growth can be implemented by the data analysis system under whole agricultural sites regardless of various culture environmental changes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.764-771
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• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• The Journal of Engineering Geology
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• v.28 no.2
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• pp.133-160
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• 2018

$CO_2$ storage is a very important technology for reduction of greenhouse gas emissions and has been considered as almost the only viable and effective option for immediate large-scale $CO_2$ sequestration. Small-scale demonstration project for offshore $CO_2$ storage in the Pohang Basin is the transitional stage R&D program for technological preparation of large-scale $CO_2$ storage project in Korea. Through the extensive exploration research for prospective $CO_2$ storage sites, the offshore strata in the Pohang Basin was recommended for the storage formation of the small-scale demonstration project. The Pohang Offshore Storage Project launched at 2013, and has accomplished the technical demonstration and technological independence in a wide range of $CO_2$ storage technology, such as geophysical exploration, storage site characterization, storage design, offshore platform construction, injection-well drilling and completion, deployment of injection facility, operation of $CO_2$ injection, and $CO_2$ monitoring. The project successfully carried out $CO_2$ test injection in early 2017, and achieved its final goal for technical development and demonstration of $CO_2$ storage in Korea. The realization of $CO_2$ injection in this project is the measurable result and has been recorded as the first success in Korea. The Pohang Offshore Storage Project has a future plan for the continuous operation of $CO_2$ injection and completion of $CO_2$ monitoring system. The project has provided in-house technical and practical expertises, which will be a solid foundation for the commercial-scale $CO_2$ storage business in Korea. Additionally, the project will help to secure national technical competitiveness in growing international technology market for $CO_2$ storage.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.12
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• pp.863-870
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• 2012

The market trends of automatic meter reading associated with smart water meters were investigated. Also, recent developments and field applications of key technology for automatic meter reading associated with smart water meters were analyzed. Smart water meters have been manufactured mostly in United States and Europe and have been expanded their business to Asia. Integrated water management system combining with the additional functions such as real-time consumption metering, cost notification, water conservation, leak detection, water quality monitoring, and flow control have been operated in automatic meter reading. Both water quality and quantity data measured from smart water meters and sensors were transferred to data concentration units through neighborhood area network, and then were transferred to integrated server through wide area network. The data transfer methods were determined by comprehensively considering urban scale, density of smart water meters, power supply and network topologies. Common data collection methods such as fixed network to data concentation units, vehicles drive by, people walk by, and drone fly by have been applied. The automatic meter reading associated with smart water meters are spread throughout the world, and both water and energy savings result in saving the money and reducing the greenhouse gases emission.

• Journal of Korean Society of Forest Science
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• v.102 no.2
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• pp.189-197
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• 2013

The Cancun Agreements under the United Nations Framework Convention on Climate Change require developing countries aiming to undertake REDD+ activities to develop a national strategy or action plan, addressing the drivers of deforestation and forest degradation, a measurement, reporting and verifying (MRV) system including forest monitoring system, and safeguards to ensure equity and co-benefits for local communities and indigenous peoples, and biodiversity. The Government of Indonesia and the Government of Norway established REDD+ cooperation through signing a 'Letter of Intent' in May, 2010. Indonesia agreed on 'a two year suspension on all new concessions for conversion of peat and natural forest'. In turn, Norway agreed to support Indonesia's REDD+ implementation efforts up to one billion United States dollars. Indonesia's REDD+ national strategy (June, 2012) accepted most of the requests included in the 'Letter of Intent'. The REDD+ national strategy, however, does not reflect requests of the Cancun Agreements which noted identification of the drivers of deforestation and forest degradation and guarantee of real greenhouse gas emissions reductions. Indonesia lays emphasis on Norwegian requests which includes expected financial support rather than the Cancun Agreements which have a weak legally-binding requirements.