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- 03 JulHyperbody's MSc 2 Robotic Environments projects exhibited at Science Centre and V2_
- 02 Jul Hyperbody's Robotic Building team participates with MSc 2 projects in the D2RP event taking place 2-4 July at V2_
- 27 JunLecture by Prof. Kas Oosterhuis at the Huazhong University of Science and Technology
- 27 JunAchilleas Psyllidis publishes a book chapter in Computer-Aided Architectural Design Futures: The Next City, by Springer
- 16 JunLecture by Prof. Kas Oosterhuis at Leibniz Universität Hannover
- 16 JunAchilleas Psyllidis wins the 1st Prize for his project ROUTE on Linked Open Data for Smart Cities
- 14 JunDr. Nimish Biloria appointed as a member of the OCEAN design research association
- 08 JunSmart Textiles Workshop: Hyperbody and Smart Textiles at the University of Borås
- 29 MayAchilleas Psyllidis's paper accepted for publication and demonstration at the 15th International Conference on Web Engineering (ICWE 2015)
- 29 MayKas Oosterhuis, Henriette Bier, Sina Mostafavi and Jelle Feringa lecture at InDeSem 15
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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.