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Architecture as service: a case of design on demand (DoD)

  • Mihai Nadin
  • Asma Naz
Original Research

Abstract

The Internet-of-Things (IoT) can facilitate a perception-driven architectural service. A highly personalized adaptive Architecture-as-Service (AaS), meeting individual demands and expectations, is an example of Design-on-Demand—as needed and when it’s needed. This goes beyond reactive smart environments in the direction of a dwelling’s anticipatory characteristics, i.e., adapting to changing requirements. For such an architecture to be possible, intelligent materials need to be integrated via the IoT in new structures adapted to life and work circumstance of our time. The IoT is the only practical implementation that can handle the large number of processes involved and connect to computational resources on the cloud. The personalized AaS is protected via blockchain technology and made available, on demand or according to what the context suggests. For this purpose, a decentralized autonomous organization is put in place. Distributed across a large array of various devices, the ledger representing the blockchain enables digital ownership and, more important, interactions without a central control. The data informing the project was acquired from experiments in a Cave Automatic Virtual Environment (CAVE)-type virtual reality (VR) system. The same VR facility was used as a modeling medium for the future of a new kind of on-demand adaptive architecture.

Keywords

Adaptive Architecture-as-Service (AaS) Interaction Anticipatory Profile 

Notes

Acknowledgements

Several very careful reviewers provided feedback over the last 9 months. So did peers working in computer science (VR, in particular) and AI. For all these we are grateful. If not everything they drew our attention to was improved to meet their exigencies, it is because in some cases we ourselves continue to dig deeper into the subject in order to further clarify what our study proposes. The research upon which this paper is based involved a large number of subjects (129), as well as the cooperation of several laboratories. We hereby acknowledge support from the IRB at the University of Texas at Dallas (approval number 05-19) and at Duke University. Cooperation with Dr. Regis Kopper at the Duke University DiVE (Duke immersive Virtual Environment), and with Dr. Ryan P. McMahan of the VR Group at the University of Texas at Dallas is gratefully acknowledged here. The authors benefited from expertise in blockchain technology provided by Alastair Hewitt, and the expertise in nanotechnology of Dr. Ray Baughman, Director of the NanoTech Institute at UT-Dallas. The lab of the antÉ Institute for Research in Anticipatory Systems (ATEC School, UT-Dallas) provided funding and facilities for experimental work. Over many years, one of the authors benefited from interaction with Jaron Lanier (and, of course, experienced his prosopagnosia). The VR visionary never tires of redefining the field. We share in his optimism that technology will do better.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute for Research in Anticipatory Systems, Ashbel Smith University ProfessorThe University of Texas at DallasRichardsonUSA
  2. 2.The University of Texas at DallasRichardsonUSA

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