• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.487-488
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• 2022

본 논문에서는 가정에서 식물 재배 환경에 따라 설정이 가능한 스마트 IoT 온실을 개발하였다. 개발한 온실은 사용자가 웹을 통하여 원하는 식물을 선정하면 자동으로 미니온실의 온도와 습도가 맞춰지도록 개발하였다. 온도와 습도, 물주기까지 사람이 직접 관리하는 것이 아닌 웹으로 원격 제어가 가능하기 때문에 높은 정확도와 편리함 속에서 식물을 좀 더 오랫동안 쉽게 기를 수 있을 것이라 기대된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.519-531
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• 2020

Global warming is accelerating as greenhouse gas emissions increase owing to the increase in population and urbanization rates worldwide. As an alternative to this solution, smart cities are being promoted. The purpose of this paper is to suggest a plan for developing energy service modules for the Sejong 5-1 living area, which has been selected as a test-bed for smart cities in Korea. Based on the smart city plans announced by the government for this study, a survey questionnaire on 12 energy services was composed by collecting the opinions of experts. The survey was conducted with 1,000 citizens, the degree of necessity of energy service that citizens think of was identified. Principal Component Analysis and Association Rule Mining were conducted to describe 12 energy service items in a reduced manner and analyze the correlation and relationship of each energy service. Finally, three modules were suggested using the analyzed results so that 12 energy services could be implemented in an efficient platform. These results are expected to contribute to the realization of a smart city to make them easily accessible for those who want to promote platform services in the energy field and envision energy service items.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.256-264
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• 2023

Smart farm technology using IoT is one of the technologies that can increase productivity and improve the quality of agricultural products in agriculture, which is facing difficulties due to the decline in rural population, lack of rural manpower due to aging, and increase in diseases and pests due to climate change. . Smart farms using existing IoT simply monitor farms, implement smart plant growers, and have automatic greenhouse opening and closing systems. This paper implements a smart farm system based on MQTT, an industry standard protocol for the Internet of Things, and Node-RED, a representative development middleware for the Internet of Things. First, data is extracted from Arduino sensors, and data is collected and transmitted from IoT devices using the MQTT protocol. Then, Node-RED is used to process MQTT messages and store the sensing data in real time in MongoDB, a representative NoSQL, to store the data. Through this smart farm system, farm managers can use a computer or mobile phone to check sensing information on the smart farm in real time, anytime, anywhere, without restrictions on time and space.

• Korean Journal of Materials Research
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• v.9 no.6
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• pp.635-653
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• 1999

The present work considers work considers research strategies to address global warming. Specifically, this work considers the development of technologies of importance for the reduction of greenhouse gas emission and, especially, the materials that are critical to these technologies. It is argued that novel materials that are essential for the production of environmentally friendly energy may be developed through a special kind of engineering: interface engineering, rather than through classical bulk chemistry. Progress on the interface engineering requires to increase the present state of understanding on the local properties of materials interfaces and interfaces processes. This, consequently, requires coordinated international efforts in order to establish a strong background in the science of materials interfaces. This paper considers the impact of interfaces, such as surfaces and grain boundaries, on the functional properties of materials. This work provides evidence that interfaces exhibit outstanding properties that are not displayed by the bulk phase. It is shown that the local interface chemistry and structure and entirely different than those of the bulk phase. In consequence the transport of both charge and matter along and across interfaces, that is so important for energy conversion, is different than that in the bulk. Despite that the thickness of interfaces is of an order to a nanometer, their impact on materials properties is substantial and, in many cases, controlling. This leads to the conclusion that the development of novel materials with desired properties for specific industrial applications will be possible through controlled interface chemistry. Specifically, this will concern materials of importance for energy conversion and environmental monitoring. Therefore, there is a need to increase the present state of understanding of the local properties of materials interfaces and the relationship between interfaces and the functional properties of materials. In order to accomplish this task coordinated international efforts of specialized research centres are required. These efforts are specifically urgent regarding the development of materials of importance for the reduction of greenhouse gases. Success of research in this area depends critically on financial support that can be provided for projects on materials of importance for a sustainable environment, and these must be considered priorities for all of the global economies. The authors of the present work represent an international research group economies. The authors of the present work represent an international research group that has entered into a collaboration on the development of the materials that are critical for the reduction of greenhouse gas emissions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.485-488
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• 2016

The level of domestic greenhouse complex environmental control technology is a hardware-oriented automation steps that mechanically control the environments of greenhouse, such as temperature, humidity and $CO_2$ through the technology of cultivation and consulting experts. This automation brings simple effects such as labor saving. However, in order to substantially improve the output and quality of agricultural products, it is essential to track the growth and physiological condition of the plant and accordingly control the environments of greenhouse through a software-based complex environmental control technology for controlling the optimum environment in real time. Therefore, this paper is a part of general methods on the greenhouse complex environmental control technology. and presents a horticulture production forecasting methods using artificial neural networks through the analysis of big data systems of smart farm performed in our country and artificial neural network technology trends.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1701-1710
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• 2012

Recently, it has been found that it is important to use a smart grid to reduce greenhouse-gas emissions worldwide. A smart grid is a digitally enabled electrical grid that gathers, distributes, and acts on information regarding the behavior of all participants (suppliers and consumers) to improve the efficiency, importance, reliability, economics, and sustainability of electricity services. The smart grid technology uses two-way communication, where users can monitor and limit the electricity consumption of their home appliances in real time. Likewise, power companies can monitor and limit the electricity consumption of home appliances for stabilization of the electricity supply. However, if information regarding the measured electricity consumption of a user is leaked, serious privacy issues may arise, as such information may be used as a source of data mining of the electricity consumption patterns or life cycles of home residents. In this paper, we propose a data transaction protocol for privacy protection in a smart grid. In addition, a power company cannot decrypt an encrypted home appliance ID without the user's password.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.827-830
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• 2013

Due to strong wind of smartphone, change in human life is facing 21 Century's new revolution. The end of 2012, The record rate of supply of smartphone is up to 58.8 percent. So the reputation of IT power are continuing. Korea is boasting IT infrastructure, and the reputation of IT power with rapidly evolving. But Korea is one of OECD country with the longest working hours and in labor productivity, yet is located in the lower rank. Now, common social issues such as low-carbon, green growth, low birthrate, graying, labor productivity growth, the reduce greenhouse gas is constantly increasing in worldwide. So Smart Work is getting attention as a way to resolve this. In this paper, we study the impact of small business on local economy and the status information of small business on statistical point of view. And we offer the smart work countermeasures of small business through detailed action elements and the model proposed fot driving factor for the promotion of smart work. Through this, we propose the IT system model for The SMEs-type smart work system.