• Title/Summary/Keyword: IoT Enviornment

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A Study on the Development of ESG Indicators for Sustainable Smart Ports (지속가능한 스마트 항만을 위한 ESG 지표 개발에 관한 연구)

  • Jae-Hoon Lee;Myung-Hee Chang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.296-297
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    • 2022
  • A smart port refers to a port built based on digital technologies such as IoT, big data, AI, and block chain, and refers to a port that minimizes waste of time, space and resources as the only means of survival of the port. Sustainability refers to 'environmental, economic, and social characteristics that enable people to continue to use the environment, ecosystem, or publicly used resources'. It contains the meaning of 'future sustainability' that can be maintained in the future. In the face of the 4th industrial revolution, interest and realization of smart port construction and sustainability are actively progressing around the world. In this study, core indicators of the ESG (Enviornment, Social, Governance) area, which are key elements of sustainable smart ports, were developed,

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Legged Robot Trajectory Generation using Evolved Fuzzy Machine for IoT Environments (IoT 환경을 위한 진화된 퍼지머신을 이용한 로봇의 궤적생성)

  • Kim, Dong Won
    • Journal of Internet of Things and Convergence
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    • v.6 no.3
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    • pp.59-65
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    • 2020
  • The Internet of Things (IoT) era, in which all items used in daily life are equipped with a network connection function, and they are closely linked to increase the convenience of life and work, has opened wide. Robots also need to develop according to the IoT environment. A use of new type of evolved fuzzy machine (EFM) for generating legged robot trajectory in IoT enviornmentms is discussed in this paper. Fuzzy system has been widely used for describing nonlinear systems. In fuzzy system, determination of antecedent and consequent structures of fuzzy model has been one of the most important problems. EFM is described which carries out evolving antecedent and consequent structure of fuzzy system for legged robot. To generate the robot trajectory, parameters of each structure in the fuzzy system are tuned automatically by the EFM. The results demonstrate the performance of the proposed approach for the legged robot.