인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록·키워드
There is an increasing need for robust smart city platforms to support real-time monitoring, data analysis, and informed decision-making. Digital Twin technology enables the creation of virtual representations of physical objects or systems that are continuously updated with real-time data, accurately reflecting the object's lifestyle. When combine with Deep Learning, Digital Twin can simulate scenarios and perform complex analyses, making them valuable tools for sustainable urban development.
As cities expand, the integration of Digital Twin with AI-driven insights will be instrumental in optimizing energy use, reducing costs, and enhancing residents quality of life. In this study, a Digital Twin platform was developed to visualize a smart area in South Korea, incorporating a Deep Learning model for Personal Thermal Comfort analysis to aid in energy management within buildings and homes. Leveraging Building Information Modeling for 3D data, this research also provides a road map for Smart City Platform development, addressing current gaps in the field. By establishing a robust framework, this work not only tackles existing challenges but also sets a foundation for future urban planning and management innovations.
As cities expand, the integration of Digital Twin with AI-driven insights will be instrumental in optimizing energy use, reducing costs, and enhancing residents quality of life. In this study, a Digital Twin platform was developed to visualize a smart area in South Korea, incorporating a Deep Learning model for Personal Thermal Comfort analysis to aid in energy management within buildings and homes. Leveraging Building Information Modeling for 3D data, this research also provides a road map for Smart City Platform development, addressing current gaps in the field. By establishing a robust framework, this work not only tackles existing challenges but also sets a foundation for future urban planning and management innovations.
본문·목차
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