International Journal of Architecture, Arts and Applications
Volume 5, Issue 2, June 2019, Pages: 42-49
Received: Jun. 24, 2019;
Accepted: Sep. 2, 2019;
Published: Sep. 2, 2019
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Tao Shen, Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi City, Japan
Yukari Nagai, Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi City, Japan
We are entering a new area of information science that we calling the Internet of Things (IoT). It connects machine with machine, machine with infrastructure and machine with environment, the Internet of everything. More generally, we see IoT as massive amounts of connected concepts that encompass every aspect of our lives. Meanwhile, architects often explore novel design ideas of their knowledge and skills for innovation, even though such ideas rely on their own experience, expertise or intuition, so that it brings the negative effects on creative architecture design. Numerous studies have investigated that concept-synthesizing processes is a key to creative design. However, there is little work specifically on understanding the use of IoT systems as architecture design stimuli. In this paper, we present a model of using IoT systems as design stimuli for architecture concept generation, in this model we abstract IoT systems into ‘input part’, ‘process part’ and ‘output part’. Through a controlled experiment and extended protocol analysis, this research showed that IoT systems stimulate creative architecture design both in design process and design result, in addition, participants often choose the ‘input part’ as design stimuli while ‘input part’ and ‘output part’ both have the promoter action to creativity. Moreover, ‘process part’ prefers to enhance the extension of idea space in concept generation process.
Understanding the Use of IoT Systems as Architecture Design Stimuli, International Journal of Architecture, Arts and Applications. Special Issue: Innovation in Architecture Design.
Vol. 5, No. 2,
2019, pp. 42-49.
Karimi, K., & Atkinson, G. (2013). What the Internet of Things (IoT) needs to become a reality. White Paper, FreeScale and ARM, 1-16.
Cross, N. (2001). Strategic knowledge exercised by outstanding Designers. Strategic knowledge and concept formation III, 17-30.
Chiu, I., & Shu, L. H. (2007). Using language as related stimuli for concept generation. AI EDAM: Artificial Intelligence for Engineering Design, Analysis, and Manufacturing, 21 (02), 103-121.
Benami, O., & Jin, Y. (2002). Creative stimulation in conceptual design. In ASME 2002 international design engineering technical conferences and computers and information in engineering conference (pp. 251-263). American Society of Mechanical Engineers.
Rothenberg, A. (1979). The emerging goddess: The creative process in art, science, and other fields.
Lubart, T (1994) Creativity in R J Stenberg (ed) Thinking and problem solving, Academic Press, USA pp 289-332.
Nagai, Y., Taura, T., & Mukai, F. (2009). Concept blending and dissimilarity: factors for creative concept generation process. Design Studies, 30 (6), 648-675.
Taura, T., Nagai, Y., & Tanaka, S. (2005). Design space blending-A key for creative design. In ICED 05: 15th International Conference on Engineering Design: Engineering Design and the Global Economy (p. 1481). Engineers Australia.
Hampton, J. A. (1997). Emergent attributes in combined concepts. Creative thought: An investigation of conceptual structures and processes, 83-110.
Costello, F. J., & Keane, M. T. (2000). Efficient creativity: Constraint-guided conceptual combination. Cognitive Science, 24 (2), 299-349.
Nagai, Y., & Taura, T. (2006). FORMALDESCRIPTION OF CONCEPT-SYNTHESIZING PROCESS FOR CREATIVE DESIGN. In Design computing and cognition’06 (pp. 443-460). Springer, Dordrecht.
Taura, T., & Nagai, Y. (2013). A systematized theory of creative concept generation in design: first-order and high-order concept generation. Research in Engineering Design, 24 (2), 185-199.
Lawson, B. (1997). How Designers Think, ed.
Ericsson, K. A., & Simon, H. A. (1984). Protocol analysis: Verbal reports as data. the MIT Press.
Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition: Theory, research, and applications.
Miller, G. A. (1995). WordNet: a lexical database for English. Communications of the ACM, 38 (11), 39-41.
Varelas, G., Voutsakis, E., Raftopoulou, P., Petrakis, E. G., & Milios, E. E. (2005, November). Semantic similarity methods in wordNet and their application to information retrieval on the web. In Proceedings of the 7th annual ACM international workshop on Web information and data management (pp. 10-16). ACM.
Howard, T. J., Dekoninck, E. A., & Culley, S. J. (2010). The use of creative stimuli at early stages of industrial product innovation. Research in Engineering design, 21 (4), 263-274.
Hatchuel, A., & Weil, B. (2009). CK design theory: an advanced formulation. Research in engineering design, 19 (4), 181.