• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.13-25
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• 2021

The particulate matters (PM₁₀ and PM_2.5) and ammonia emitted from livestock farms as dispersed to urban and residential areas can increase the public's concern over the health problem, social conflicts, and air quality. Understanding the atmospheric dispersion of such matters is important to prevent the problems for the regulatory purposes. In this study, AERMOD modeling was performed to predict the dispersion of livestock particulate matters and ammonia in Gwangju metropolitan city and five surrounding cities. The five cities were divided into 40 sub-zones to model the area-based emissions which varied with the number of livestock farms, species and growth stages of the animals. As a result, the concentrations of PM₁₀, PM_2.5 and ammonia resulted from livestock farms located in the surrounding cities were 2.00 ㎍ m^-3, 0.30 ㎍ m^-3 and 0.04 ppm in the southwestern part of Gwangju based on the average concentration of 1 hour. These values accounted for 0.7% of PM₁₀ concentration, 0.5% of PM_2.5 concentration, and 0.4% of the ammonia concentration in Gwangju, contributing to a small amount of air pollution compared to other sources. As preventive measures, the plantation was applied to high emission source areas to reduce particulate matters and ammonia emissions by 35% and 31%, respectively, and resulted in decrease of the area of influence by 57% for particulate matters and 59% for ammonia.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.2
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• pp.37-44
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• 2022

In this paper, for the smart village project in Geumsan-gun, the problems of the village were derived for the residents. And the business model of the smart village was presented. In the introduction, we looked at domestic cases related to the smart village project. And In November 2019, this paper reflected the results of the resident survey(314) and extracted important smart services using the IPA method. The results of the investigation are as follows. The government's smart village project aims to increase agricultural and fishery production and improve the urban environment. Geumsan residents want to increase agricultural production and develop tourism. The smart village model in Geumsan-gun is promoted in three directions. (1) Smart villages require smart services for crime prevention, parking lots, and public transportation. (2) Smart villages need ICT-based ginseng festivals, smart farms, and tourism services. (3) Smart villages need ICT-based culture and welfare services. The rural areas in Korea are expected to improve the quality of their living environment through the smart village project.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.665-667
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• 2018

The agriculture is the first industrial technology to lay the foundation for human development and is an essential component to human survival. With the emergence of various industries, agriculture has become a relatively neglected industry. However, with the recent development of IT technology, agricultural technology has found an infinite potential for development and has been selected as a promising industry that will not be lost in the future. Smart Farm improved the quality of life by improving the poor working environment of existing farmers. In addition, it is expected that physically disadvantaged workers can participate in the industry, and by promoting the inflow of excellent workers, the staff can be increased and the level can be increased. Currently, smart farms are in the early stages of commercialization and need to develop more diverse technologies. The project aims to popularize smart farms and to collect and database crop growth environment information through sensors.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.135-141
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• 2019

In this study, the "Insect Smart Farm Air Conditioning System" is designed and proposed for the control of breeding environment of Protaetia brevitarsis seulensis larvae. The proposed "Insect Smart Farm Air Conditioning System" separates the breeding room from the air conditioning room. It is a system that creates an environment optimized for breeding and distributes it into a breeding room. When controlling the environment through air-conditioning and humidifiers in insect farms, temperature and humidity vary from part of the breeding room to part. The solution to the problem can be suggested as a solution to the difficulty of producing white-spotted flower mounds of uniform size and weight when selling edible insects. By using the "Insect Smart Farm Air Conditioning System," the temperature difference can be reduced by 6℃ and the humidity difference by 24.7% compared to the environmental control of existing insect farms. The temperature and humidity of different parts of the breeding room were improved. Provide the optimal environment of Protaetia brevitarsis seulensis larvae at all times and ensure uniform CO₂ concentration. It can be expected to increase output through annual production and increase income for insect farmers. The proposed "Insecting Smart Farm Air Conditioning System" also controls the set temperature, humidity and CO₂. Environmental control of the breeding of other edible insects and the reproduction of mushrooms that require environmental control in breeding or breeding will also be possible.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.37-43
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• 2019

The existing smart farm technology has been systematized for the mass production rather than the consumer. There are many problems such as economical aspect to apply to actual rural environment due to aging. The purpose of this study is to apply smart farm technology based on the applicability of population aged in rural areas. Due to the heat wave, the crops in general greenhouse cultivation facilities suffered from damage such as sunlight damage. To minimize such damage, adjust the temperature and humidity environment or install a light-shielding film. However, the workers in the rural areas are aging and the elderly who are farming alone have a lot of difficulties in doing so. In the case of people with weak physical strength, there is a danger that they may lead to safety accidents when carrying heavy loads. In this paper, we propose 'Smart Palm capable of automatic transportation function', applying small smart vehicles that follow workers to existing smart farms to improve and prevent these problems. It is a smart farm that performs the control functions of the existing smart greenhouse environment, installs the rail for each trough, and has a vehicle that follows the worker. The smart app can directly control the greenhouse and the vehicle remotely manually.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.415-418
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• 2017

Recently, the demand for energy efficiency improvement technology through the connection of waste heat energy and SmartGrid has been increasing. Thus, investments for the cultivation of high value crops and produce is increasing through research aimed at synthetic technology in real-time utilization of smart farms and waste heat energy with the concept of using container greenhouses and plant factories. In this aspect, we have carried out research on a practical application technology that will help farmers to increase the economic effectiveness of LED based plant factories in terms of energy efficiency. This can provide opportunities to connect with the large scale automated smart farms in the future. In this study, we focused on the economic effectiveness of crop cultivation using cooling technology in a container greenhouse through waste heat energy. Hereafter, in order to further advance the technology of real-time monitoring/control of the absorption chiller which is used through the container greenhouses and waste heat energy by using IOT, we would like to propose research on new ideas of agricultural technology that can maximize the utility of cooling energy by operating a mobile gateway based on Raspberry PI.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.341-343
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• 2018

Agriculture has the longest history in many industries and is directly or indirectly linked to human development. However, recently agriculture in Korea has difficulties in farm management due to the decrease of rural population, aging of society, increase of material costs, and climate change on the Korean peninsula. Smart farms using ICT are proposed as an alternative to solve these problems. Smart farms manage the temperature and water supply facilities of farms through various sensors, but there is a limit to the delicate management of crops. Therefore, in this paper, unlike the conventional moisture sensor, the water supply is varied according to the depth of the soil, thereby realizing an optimized environment for plant growth.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1196-1213
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• 2020

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.39-45
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• 2013

This paper presents the estimation of minimum BESS capacity for regulating the output of wind farms considering power grid operating condition in Jeju Island. To analyze the characteristics of wind farm outputs with a BESS, the real data of wind farms, Sung-San, Sam-dal and Hang-Won wind farm, located in the eastern part of Jeju island is considered. The wind farms are connected to Sung-san substation to transfer the electric power to Jeju power grid. Consequently, at PCC (Point of Common Coupling), it can see a huge wind farm connected to the substation and thus it can be expected that the smoothing effect is affected by not only the different wind speeds for each area but also the different mechanical inertia of wind turbines. In this paper, two kinds of simulation have been carried out. One is to analyze the real data of wind farm outputs during a winter season, and the other is to connect a virtual BESS to eliminate the unintended generating power changes by the uncontrolled wind farm outputs as shown in the former data. In the conclusion, two kinds of simulation results show that BESS installed in the substation is more efficient than each wind farms with BESS, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.672-680
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• 2019

This paper proposes "A Smart Farm Environment Optimization and Yield Prediction Platform based on IoT and Deep Learning" which gathers bio-sensor data from farms, diagnoses the diseases of growing crops, and predicts the year's harvest. The platform collects all the information currently available such as weather and soil microbes, optimizes the farm environment so that the crops can grow well, diagnoses the crop's diseases by using the leaves of the crops being grown on the farm, and predicts this year's harvest by using all the information on the farm. The result shows that the average accuracy of the AEOM is about 15% higher than that of the RF and about 8% higher than the GBD. Although data increases, the accuracy is reduced less than that of the RF or GBD. The linear regression shows that the slope of accuracy is -3.641E-4 for the ReLU, -4.0710E-4 for the Sigmoid, and -7.4534E-4 for the step function. Therefore, as the amount of test data increases, the ReLU is more accurate than the other two activation functions. This paper is a platform for managing the entire farm and, if introduced to actual farms, will greatly contribute to the development of smart farms in Korea.