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- 23 AprDr.-Ing. Henriette Bier and PhD cand. Sina Mostafavi speak at symposium on Architectural Ecologies
- 14 AprDr.-Ing. Henriette Bier appointed member of PhD candidates review committee for RCAT at AHO
- 09 AprLecture Kas Oosterhuis at Symposium "Smart City, Smart Environment", Internet Of Things IoT Day Rotterdam
- 05 AprEstablishment of the Sino-Dutch Research Center for Building in Extreme Climates the 27th of March 2014 at Harbin Institute of Technology.
- 04 AprAchilleas Psyllidis and Dr. Nimish Biloria will be presenting at the Research Workshop: Smart Cities and Big Data in Aarhus, Denmark.
- 02 AprProf. Kas Oosterhuis has been invited as a Guest Professor at the Harbin Institute of Technology, P. R. China
- 27 MarProf. Kas Oosterhuis lectures at Harbin Institute of Technology (HIT), Harbin, China
- 25 MarProf. Kas Oosterhuis lectures at the Tongji University, Shanghai, China
- 21 MarJaime del Val, Associacion Transdiciplinar, Reverso lectures at Hyperbody
- 18 MarThe Value of Design 2014 symposium will be led by prof. Kas Oosterhuis
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A.Liu Cheng, H. Bier, G. Latorre, B. Kemper and D. Fischer publish a paper on A High-Resolution Intelligence Implementation based on Design-to-Robotic-Production and -Operation strategies in the 34th International Symposium on Automation and Robotics in Construction (ISARC 2017) (June 28 - July 1, 2017).
ABSTRACT: This paper presents an initial proof-of-concept implementation of a comprehensively intelligent built-environment based on mutually informing Design-to-Robotic-Production and -Operation (D2RP&O) strategies and methods developed at Delft University of Technology (TUD). In this implementation, D2RP is expressed via deliberately differentiated and function-specialized components, while D2RO expressions subsume an extended Ambient Intelligence (AmI) enabled by a Cyber-Physical System (CPS). This CPS, in turn, is built on a heterogeneous, scalable, self-healing, and partially meshed Wireless Sensor and Actuator Network (WSAN) whose nodes may be clustered dynamically ad hoc to respond to varying computational needs. Two principal and innovative functionalities are demonstrated in this implementation: (1) cost-effective yet robust Human Activity Recognition (HAR) via Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) classification models, and (2) appropriate corresponding reactions that promote the occupant’s spatial experience and well-being via continuous regulation of illumination with respect to colors and intensities to correspond to engaged activities. The present implementation attempts to provide a fundamentally different approach to intelligent built-environments, and to promote a highly sophisticated alternative to existing intelligent solutions whose disconnection between architectural considerations and computational services limits their operational scope and impact.