• Title/Summary/Keyword: Internet of Things (IoT) Model

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Smart Aquaculture Industrialization Model and Technology Development Direction Considering Technology, Economy and Environment (기술·경제·환경적 측면에서의 스마트양식 산업화 모델과 기술개발 방향)

  • Donggil Lee;Hae Seung Jeong;Junhyuk Seo;Hyeong Su Kim;Jeonghwan Park
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.56 no.6
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    • pp.759-765
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    • 2023
  • Owing to the increase in the elderly population at aquaculture farm and decrease in the number of aquaculture farmers, the need to improve aquaculture production system is increasing. In addition, asvirtual interactions become new normal after COVID-19 pandemic, the speed at which science and technology such as the internet of things (IoT), information and communications technology (ICT), and artificial intelligence (AI) are applied to each field is accelerating. Efforts are being made to enhance the quality of life of aquaculture farmer and competitiveness of the aquaculture industry by incorporating digital technology. This study analyzed national and global aquaculture technology development and policy trends, smart aquaculture terminology application scenarios, and prior research cases to propose smart aquaculture industrialization models and technology development directions considering technology, economy, and environment. This study can also provide valuable reference for promoting smart and efficient development of aquaculture.

Neural Network and Cloud Computing for Predicting ECG Waves from PPG Readings

  • Kosasih, David Ishak;Lee, Byung-Gook;Lim, Hyotaek
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.11-20
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    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

The Intelligent Blockchain for the Protection of Smart Automobile Hacking

  • Kim, Seong-Kyu;Jang, Eun-Sill
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.33-42
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    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

Implementation of a Sensor Fusion FPGA for an IoT System (사물인터넷 시스템을 위한 센서 융합 FPGA 구현)

  • Jung, Chang-Min;Lee, Kwang-Yeob;Park, Tae-Ryong
    • Journal of IKEEE
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    • v.19 no.2
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    • pp.142-147
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    • 2015
  • In this paper, a Kalman filter-based sensor fusion filter that measures posture by calibrating and combining information obtained from acceleration and gyro sensors was proposed. Recent advancements in sensor network technology have required sensor fusion technology. In the proposed approach, the nonlinear system model of the filter is converted to a linear system model through a Jacobian matrix operation, and the measurement value predicted via Euler integration. The proposed filter was implemented at an operating frequency of 74 MHz using a Virtex-6 FPGA Board from Xilinx Inc. Further, the accuracy and reliability of the measured posture were validated by comparing the values obtained using the implemented filters with those from existing filters.

A Study on the Prediction of Strawberry Production in Machine Learning Infrastructure (머신러닝 기반 시설재배 딸기 생산량 예측 연구)

  • Oh, HanByeol;Lim, JongHyun;Yang, SeungWeon;Cho, YongYun;Shin, ChangSun
    • Smart Media Journal
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    • v.11 no.5
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    • pp.9-16
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    • 2022
  • Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

New Mathematical Model for Travel Route Recommendation Service (여행경로 추천 서비스를 위한 최적화 수리모형)

  • Hwang, Intae;Kim, Heungseob
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.3
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    • pp.99-106
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    • 2017
  • With the increased interest in the quality of life of modern people, the implementation of the five-day working week, the increase in traffic convenience, and the economic and social development, domestic and international travel is becoming commonplace. Furthermore, in the past, there were many cases of purchasing packaged goods of specialized travel agencies. However, as the development of the Internet improved the accessibility of information about the travel area, the tourist is changing the trend to plan the trip such as the choice of the destination. Web services have been introduced to recommend travel destinations and travel routes according to these needs of the customers. Therefore, after reviewing some of the most popular web services today, such as Stubby planner (http://www.stubbyplanner.com) and Earthtory (http://www.earthtory.com), they were supposed to be based on traditional Traveling Salesman Problems (TSPs), and the travel routes recommended by them included some practical limitations. That is, they were not considered important issues in the actual journey, such as the use of various transportation, travel expenses, the number of days, and lodging. Moreover, although to recommend travel destinations, there have been various studies such as using IoT (Internet of Things) technology and the analysis of cyberspatial Big Data on the web and SNS (Social Networking Service), there is little research to support travel routes considering the practical constraints. Therefore, this study proposes a new mathematical model for applying to travel route recommendation service, and it is verified by numerical experiments on travel to Jeju Island and trip to Europe including Germany, France and Czech Republic. It also expects to be able to provide more useful information to tourists in their travel plans through linkage with the services for recommending tourist attractions built in the Internet environment.

S-FEAR: Secure-Fuzzy Energy Aware Routing Protocol for Wireless Sensor Networks

  • Almomani, Iman;Saadeh, Maha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.4
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    • pp.1436-1457
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    • 2018
  • Secure routing services in Wireless Sensor Networks (WSNs) are essential, especially in mission critical fields such as the military and in medical applications. Additionally, they play a vital role in the current and future Internet of Things (IoT) services. Lightness and efficiency of a routing protocol are not the only requirements that guarantee success; security assurance also needs to be enforced. This paper proposes a Secure-Fuzzy Energy Aware Routing Protocol (S-FEAR) for WSNs. S-FEAR applies a security model to an existing energy efficient FEAR protocol. As part of this research, the S-FEAR protocol has been analyzed in terms of the communication and processing costs associated with building and applying this model, regardless of the security techniques used. Moreover, the Qualnet network simulator was used to implement both FEAR and S-FEAR after carefully selecting the following security techniques to achieve both authentication and data integrity: the Cipher Block Chaining-Message Authentication Code (CBC-MAC) and the Elliptic Curve Digital Signature Algorithm (ECDSA). The performance of both protocols was assessed in terms of complexity and energy consumption. The results reveal that achieving authentication and data integrity successfully excluded all attackers from the network topology regardless of the percentage of attackers. Consequently, the constructed topology is secure and thus, safe data transmission over the network is ensured. Simulation results show that using CBC-MAC for example, costs 0.00064% of network energy while ECDSA costs about 0.0091%. On the other hand, attacks cost the network about 4.7 times the cost of applying these techniques.

A study on the Revitalization of Traditional Market with Smart Platform (스마트 플랫폼을 이용한 전통시장 활성화 방안 연구)

  • Park, Jung Ho;Choi, EunYoung
    • Journal of Service Research and Studies
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    • v.13 no.1
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    • pp.127-143
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    • 2023
  • Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

A Novel Reference Model for Cloud Manufacturing CPS Platform Based on oneM2M Standard (제조 클라우드 CPS를 위한 oneM2M 기반의 플랫폼 참조 모델)

  • Yun, Seongjin;Kim, Hanjin;Shin, Hyeonyeop;Chin, Hoe Seung;Kim, Won-Tae
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.2
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    • pp.41-56
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    • 2019
  • Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

A Software Vulnerability Analysis System using Learning for Source Code Weakness History (소스코드의 취약점 이력 학습을 이용한 소프트웨어 보안 취약점 분석 시스템)

  • Lee, Kwang-Hyoung;Park, Jae-Pyo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.11
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    • pp.46-52
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    • 2017
  • Along with the expansion of areas in which ICT and Internet of Things (IoT) devices are utilized, open source software has recently expanded its scope of applications to include computers, smart phones, and IoT devices. Hence, as the scope of open source software applications has varied, there have been increasing malicious attempts to attack the weaknesses of open source software. In order to address this issue, various secure coding programs have been developed. Nevertheless, numerous vulnerabilities are still left unhandled. This paper provides some methods to handle newly raised weaknesses based on the analysis of histories and patterns of previous open source vulnerabilities. Through this study, we have designed a weaknesses analysis system that utilizes weakness histories and pattern learning, and we tested the performance of the system by implementing a prototype model. For five vulnerability categories, the average vulnerability detection time was shortened by about 1.61 sec, and the average detection accuracy was improved by 44%. This paper can provide help for researchers studying the areas of weaknesses analysis and for developers utilizing secure coding for weaknesses analysis.