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- 11 NovH. Bier and S. Mostafavi publish journal paper on Data-Driven Architectural Design to Production and Operation in Systema's special issue Architectural Ecologies
- 26 OctRobotic Painting / Machining Emotion project team at Dubai Design Week
- 26 OctJia-Rey Chang published a paper in the New Architecture Journal NO.5: "Digital Techniques and Architectural Evolution"
- 25 OctIn ACADIA 2015 Peer Reviewed Projects, Sina Mostafavi and Henriette Bier published a project on Informed Design to Robotic Production systems.
- 25 OctDr. Nimish Biloria, Jia-Rey Chang and Dieter Vandoren published a paper "Ambiguous Topology" at IEEE VISAP'15 conference, Chicago, USA
- 23 OctHenriette Bier talks at the 3TU symposium Real Additive Manufacturing
- 22 OctNew website "Machining Emotion" is launched by the Robotic Painting project team
- 21 OctAt Dutch Design Week 2015, Sina Mostafavi talks about Creative applications of Design to Robotic Production systems in architectural design and building processes
- 01 OctHyperbody hosts Delft Robotics Institute's monthly RoboCafé on "Pro-active Robotics"
- 25 SepSocialGlass is featured on NRCQ, the leading business news site in the Netherlands
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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.