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Building Information
Science & Technology

Recent publication

​대체모델을 활용한 관측 가상센서 성능 고도화 방법 제시

Youngwoong Choi and Sungmin Yoon

국제학술지 Building and Environment (IF 7.400)에 게재,

실물센서로 계측되지 않는 변수를 측정하는 관측 가상센서를 개발하고, 대체 모델을 통해 성능을 고도화 하는 방법을 제시함.

밤 도시

Building Systems

  • AI-based energy efficient building operations

  • Fault detection and diagnosis (FDD)

  • Holistic Operational signatures (HOS)

Indoor environment

  • Building airflow and impacts

  • Building energy simulation and calibration

  • Stack effect and dwelling infiltration

Smart City

  • Signature-based symbolic clustering

  • Big data mining for smart cities

  • Data-driven urban building energy analytics 

Digitial twins &
Sensing technologies

  • Digital twining in building operations

  • Virtual sensing in digital twins

  • Virtual in-situ calibration (VIC)

  • Virtual and physical sensor fusion


지능형건축설비연구실(BIST)은 건물시스템에 대한 이해와 건물 생애주기에서 발생하는 다양한 정보/데이터를 기반으로 지능형 건물을 실현하는 것을 목표로 합니다. 이를 위해, 센서, 장치, 시스템, 건물, 도시 단위에서의 다양한 융복합 연구를 수행하고 있으며, 건물시스템의 자율운전과 자가진화기술을 개발하고 있습니다.

BIST lab. is intended to realize intelligent buildings based on the building science, informatics, and building life-cycle data. We are actively pursuing progress on the different levels of sensors, equipment, systems, buildings, and a city and their interactions. Recently, a self-evolving building management technology was proposed, and the study is ongoing with in-situ virtual sensing paradigm in the context of digital building twins.

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