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- 14 MarHyperbody presents at RAM/ramfoundation exhibition "T.O.P. UP" opening on the 16th of March 2014
- 08 MarKeynote Lecture by Kas Oosterhuis at the 11th International Convention of Architecture in Budapest
- 28 Febprof. Kas Oosterhuis lectures at MC2014 conference - Grenoble, France
- 27 FebDr. Nimish Biloria appointed as Technical Program Committee member of SEC2014 conference
- 17 FebDr. Nimish Biloria publishes article: Inter-performing morphologies in the Architecture Institute of Korea Magazine
- 07 FebDr.-Ing. Henriette Bier lectures on Robotic Buildings at the Institute of Experimental Architecture, University of Innsbruck, Austria
- 05 FebDr.-Ing. Henriette Bier lectures on Robotics in Architecture at the chair for Building Realisation and Robotics at TUM, Germany
- 04 FebDr.-Ing. Henriette Bier and Ir. Chris Kievid join the Delft Robotics Institute delegation visiting potential Horizon 2020 partners in the Munich area
- 24 JanFinal Review MSc1 Design Studio: 2628CLIMATOR
- 11 JanAchilleas Psyllidis publishes an article in the ATLANTIS Magazine
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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.