Enhancement of perception capability for smart architectural blocks using hybrid particle swarm optimization algorithm하이브리드형 입자 군집 최적화 알고리즘을 이용한 스마트 건축 블록의 인지능력 향상에 관한 연구

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A moment of evolution is now emerging toward a novel type of architectural space: the smart architectural space (SAS). The SAS consists of smart building components with sensing ability, communication capability and intelligence; it is also self-organizing, scalable and fault tolerant, and thus able to cope with various environmental changes. Because smart building components must be situated in the environment and be able to interact with it, the perception capability should be a priority. These emerging phenomena have prompted researchers to explore new possibilities for sophisticated smart devices to be embedded in various architectural objects. Hence, this dissertation first presents empirical studies concerning the smart architectural block (SAB), equipped with dedicated sensing, computing, and communication devices to support the visionary concept proposed in previous research. The SAB can be used to create the form of such physical construction components as walls or floors. Second, the dissertation proposes hybrid particle swarm optimization (PSO) to facilitate the enhancement of perception capability for SAB. Even though perception capability is an essential function for sensing environmental changes, it is difficult to obtain under the restricted conditions of SAB, specifically its limited sensor deployment and communication capability, currently inaccuracy of sensing information and insufficient for decision-making. These restricted conditions not only prevent occluding the sensing area, maintaining the visibility of the display device and enduring user’s weight at the sensing point, but also prohibit access to centralized control, decision-making without global knowledge, and local communication among neighbors. For this reason, the accuracy issues facing individual SABs and the decision issues facing multiple SABs are not trivial and must be solved to facilitate advancement to new architectural achievements that ride the evolutionary momentum towa...
Advisors
Chang, Seong-Ju장성주
Description
한국과학기술원 : 건설및환경공학과,
Publisher
한국과학기술원
Issue Date
2014
Identifier
568398/325007  / 020095288
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 건설및환경공학과, 2014.2, [ x, 115 p. ]

Keywords

Artificial neural network; 군집 지능; 스마트 건축 공간; 스마트 건축 블록; 센서 정보 퓨전 알고리즘; 입자 군집 최적화; collective decision-making; consensus achievement; distributed sensor system; multi-sensor system; particle swarm optimization; sensor data fusion algorithm; smart architectural block; smart architectural space; swarm intelligence; 인공 신경망; 집단 의사 결정; 합의 도출; 분산 센서 시스템; 다중 센서 시스템

URI
http://hdl.handle.net/10203/197892
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568398&flag=dissertation
Appears in Collection
CE-Theses_Ph.D.(박사논문)
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