• Title/Summary/Keyword: Smart industry index

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Developing a performance index for efficient improving techniques and implement of Smart Water Management (스마트물관리기술 평가툴 개발)

  • Lim, Kwangsuop;Lee, Namsoo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.578-578
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    • 2016
  • In the past decade, many countries developed varies promising theories, methodologies and technologies for water resources management, such as Smart Water in Korea, eWater in Australia, Intelligent Water in Untied States, and Internet of Water in China. It is no exaggeration to say that Smart Water Management(SWM) will have a major role to play in addressing the global water challenges in the background of climate change, population growth and rapid urbanization. As a result, we can see major shifts taking place in the structure of the water industry, with a need for new approaches, skills, and water management policies. All these point towards a brighter future for the smart water sector and a new water paradigm, with applications and potential throughout the water cycle. However, each countries have their technology and industry standard system which may swift similar innovation and technology into different channels. In that sense, developing a common performance index and standard docking adapter for assessing Smart Water Management Initiatives(SWMI) is crucial for drawing a linkage of SWMI and SWMs to a way to implement advanced technology across Asia and Pacific. The performance index and standard docking adapter will facilitate quantitative and qualitative effects of utilized SWM techniques.

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Evaluation of Smart Manufacturing Innovation Readiness of Domestic SMEs According to Maturity Model (성숙도 모델에 따른 국내 중소기업의 스마트제조혁신 준비도 평가)

  • Kyung-Ihl Kim
    • Journal of Industrial Convergence
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    • v.21 no.1
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    • pp.103-110
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    • 2023
  • In this study, clustering analysis was performed to find out the influence of the maturity level of Industry 4.0 of SMEs in Korea, index factors of clustering, and major factors on the self-evaluation of companies. When 80 domestic SMEs were classified into 4 categories, it was found that there was a significant positive correlation between process, technology and organization. In addition, the majority of the 80 companies tested according to the maturity model appear to be immature or partially mature, and many improvements and re-evaluation of innovation strategies related to Industry 4.0 are needed. Finally, it was concluded that the Singapore Smart Industry Readiness Index is suitable for conducting self-assessment in domestic SMEs. These conclusions can serve as useful maturity and grouping guidelines for practitioners and researchers.

Smart Dairy Management System Development Using Biometric/Environmental Sensors and Farm Control Gateway (생체 환경 정보 센싱 모듈 및 농장 제어 게이트웨이를 이용한 스마트 낙농 관리 시스템 개발)

  • Park, Yongju;Moon, Jun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.1
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    • pp.15-20
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    • 2016
  • Recently, the u-IT applications for plants and livestock become larger and control of livestock farm environment has been used important in the field of industry. We implemented wireless sensor networks and farm environment automatic control system for applying to the breeding barn environment by calculating the THI index. First, we gathered environmental information like livestock object temperature, heart rate and momentum. And we also collected the farm environment data including temperature, humidity and illuminance for calculating the THI index. Then we provide accurate control action roof open and electric fan in of intelligent farm to keep the best state automatically by using collected data. We believed this technology can improve industrial competitiveness through the u-IT based smart integrated management system introduction for industry aversion and dairy industries labor shortages due to hard work and old ageing.

A Study on Development of a Tourism Course in Seosan using Social using Media Big Data

  • Ha, Yeon-Joo;Park, Jong-Hyun;Yoo, Kyoungmi;Moon, Seok-Jae;Ryu, Gihwan
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.134-140
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    • 2021
  • Big data has recently been used in various industries such as tourism, medical care, distribution, and marketing. And it is evolving to the stage of collecting real-time information or analyzing correlations and predicting the future. In the tourism industry, big data can be used to identify the size and shape of the tourism market, and by building and utilizing a large-capacity database, it is possible to establish an efficient marketing strategy and provide customized tourism services for tourists. This paper has begun with anticipation of the effects that would occur when big data is actively used in the tourism field. Because the method of use must have applicability and practicality, the spatial scope will be limited to Seosan, Chungcheongnam-do, and research will be conducted. In this paper, to improve the quality of tourism courses by collecting and analyzing the number of mention data and sentiment index data on social media, which reflect the tourist's interest, preference and satisfaction. Therefore, it is used as basic data necessary for the development of new local tourism courses in the future. In addition, the development of tourism courses will be able to promote tourism growth and also revitalizing the local economy.

Smart Factory Promotion and Operation Analysis in the 4th Industrial Revolution Environment

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • International journal of advanced smart convergence
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    • v.11 no.3
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    • pp.42-48
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    • 2022
  • Currently, the world is facing severe inflation due to Corona and the war in Ukraine, and it is causing a lot of difficulties for us. Companies are facing a lot of restrictions on their economic activities compared to the past due to supply chain problems and foreign exchange rates. In this situation, many countries have been implementing various smart factory promotion projects to secure competitiveness through productivity improvement in the manufacturing industry. In this study, the contents of smart factory promotion in major countries were reviewed, and problems raised about the implementation of smart factory in Korea, which are being implemented based on this, were described. It is most reasonable to judge the success of a smart factory by the achievement of the performance indicators presented at the time of the project. Therefore, based on the performance index of the business, which is a key factor in determining the success or failure of a smart factory, we investigated whether the company's smart factory promotion can be carried out successfully through examples

Case Study on the Implementation of Facility AI Platform for Small and Medium Enterprises of Korean Root Industry (뿌리업종 중견중소기업의 설비 AI 플랫폼 구축에 관한 사례연구)

  • Lee, Byong Koo;Moon, Tae Soo
    • The Journal of Information Systems
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    • v.32 no.3
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    • pp.205-224
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    • 2023
  • Purpose This study investigates the impact of organizational characteristics on organizational performance through case studies of smart factory implementation in the context of Korean small and medium Enterprises (SMEs). To achieve this goal, this study adopts the smart factory index of KOSMO (Korea Smart Manufacturing Office) established by Korean Ministry of SMEs and Startups. We visited 3 firms implemented smart factory projects. This study presents the results of field study in detail with evaluation criteria on how organizational competences like AI technology adoption and facility automation can be exploited to positively influence organizational performance through smart factory implementation. Design/methodology/approach There are not so many results of empirical studies related to smart factories in Korea. This is because organizational support and user involvement are required for facility AI platform service beyond factory automation after the start of the 4th Industrial Revolution. Korean government's KOSMO (Korean Smart Manufacturing Office) has developed and proposed a level measurement index for smart factory implementation. This study conducts case studies based on the level measurement method proposed by KOSMO in the process of conducting case studies of three companies belonging to the root and mechanic industries in Korea. Findings The findings indicate that organizational competences, such as facility AI platform adoption and user involvement, are antecedents to influence smart factory implementation, while smart factory implementation has significant relationship with organizational performance. This study provides a better understanding of the connection between organizational competences and organizational performance through smart factory case studies. This study suggests that SMEs should focus on enhancing their organizational competences for improving organizational performance through implementing smart factory projects.

Smart Beta Strategies based on the Quality Indices (퀄리티 지수를 이용한 스마트 베타 전략)

  • Ohk, Ki Yool;Lee, Minkyu
    • Management & Information Systems Review
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    • v.37 no.4
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    • pp.63-74
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    • 2018
  • Recently, in the asset management industry, the smart beta strategy, which has an intermediate nature between passive and active strategies, is attracting attention. In this smart beta strategy, value, momentum, low volatility, and quality index are widely used. In this study, we analyzed the quality index which is not clear and complicated to calculate. According to the MSCI methodology, the quality index was calculated using three variables: return on equity, debt to equity, and earnings variability. In addition, we use the index using only return on equity variable, the index using only two variables of return on equity and debt to equity, and the KOSPI index as comparison targets for the quality index. In order to evaluate the performance of the indices used in the analysis, the arithmetic mean return, the coefficient of variation, and the geometric mean return were used. In addition, Fama and French (1993) model, which is widely used in related studies, was used as a pricing model to test whether abnormal returns in each index are occurring. The results of the empirical analysis are as follows. First, in all period analysis, quality index was the best in terms of holding period returns. Second, the quality index performed best in the currency crisis and the global financial crisis. Third, abnormal returns were not found in all indices before the global financial crisis. Fourth, in the period after the global financial crisis, the quality index has the highest abnormal return.

Development of a CCTV Based Smart Safety Management System in Thermal Power Plants (석탄발전산업을 위한 지능형 CCTV 기반 스마트안전관리시스템 개발 연구)

  • Song, Ho Jun;Gao, Jianxi;Shin, Wan Seon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.3
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    • pp.50-63
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    • 2021
  • There has been a steady rate of accident in Coal Thermal Power Plants which have relatively higher chance of mortality. However, neither the systematic view of safety management nor the methodology such as safety factors or system requirements are yet to be studied in detail. Therefore, this study aims to propose a methodology to preemptively deal with safety issues and to secure fact focused responsibility in safety. It consists of two main parts. First, the Safety Measurement Index(SMI) with total 50 factors is proposed by analyzing the key factors that contribute to safety accidents based on failure mode and effect analysis (FMEA) and quality function deployment (QFD). To analyze the safety requirements, index presented by major countries and organizations are discussed. Second, main features of intelligent CCTV are studied to determine their relative importance for the framework of Smart Safety Management System (SSMS). Main features are discussed with four technological steps. Also, QFD was held to analyze to analyze how key technologies deal with Quality Measurement Index(QMI). The research results of this study reveal that scientific approaches could be utilized in integrating CCTV technologies into a smart safety management system in the era of Industry 4.0. Moreover, this reasearch provides an specific approach or methodology for dealing with safety management in Coal Thermal Power Plant.

Development of an IAQ Index for Indoor Garden Based IoT Applications for Residents' Health Management (실내거주자 건강 관리를 위한 IoT기반 실내정원용 IAQ지수 개발)

  • Lee, Jeong-Hun;An, Sun-Min;Kwak, Min-Jung;Kim, Kwang Jin;Kim, Ho-Hyun
    • Journal of Environmental Health Sciences
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    • v.44 no.5
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    • pp.421-432
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    • 2018
  • Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.

A Study on IoT based Real-Time Plants Growth Monitoring for Smart Garden

  • Song, Mi-Hwa
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.130-136
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    • 2020
  • There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.