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- 10 JanNew Research collaboration initiative between HIT and HyperBODY - Review of Prof. Mei's visit at HyperBODY
- 16 DecDr.-Ing. Henriette Bier and Phd-cand. Yeekee Ku publish paper on Generative and Participatory Parametric Frameworks for Multi-player Design Games
- 12 DecJia-Rey Chang's paper accepted for Ultra Bio- International Design Conference
- 11 DecProf. ir. Kas Oosterhuis and Dr.-Ing. Henriette Bier join the scientific committee of the ArchiDoct journal
- 04 DecProject proposal of Alireza Hakak accepted by VISIONAIR and he is invited to the Milan facility
- 28 NovTiny Apartment, Hyperbody MSc2 students present 1:1 prototypes in Rotterdam
- 14 NovHyperbody participates in METABODY 2nd EVENT, 14-18th November 2013, Dresden
- 06 Novprof. Kas Oosterhuis will lecture at CCDP, University of Technology, Sydney.
- 10 OctLecture on Environmental evaluation and Optimization by Mostapha Roudsari
- 09 OctKas Oosterhuis lectures 9 Oct 2013 at FEADship
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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.