| id |
ijac202119404 |
| authors |
Ghandi, Mona; Blaisdell, Marcus; Ismail, Mohamed |
| year |
2021 |
| title |
Embodied empathy: Using affective computing to incarnate human emotion and cognition in architecture |
| source |
International Journal of Architectural Computing 2021, Vol. 19 - no. 4, 532–552 |
| summary |
This research aims to develop a cyber-physical adaptive architectural space capable of real-time responses topeople’s emotions, based on biological and neurological data. To achieve this goal, we integrated artificialintelligence (AI), wearable technology, sensory environments, and adaptive architecture to create anemotional bond between a space and its occupants and encourage affective emotional interactions betweenthe two. The project’s objectives were to (1) measure and analyze biological and neurological data to detectemotions, (2) map and illustrate that emotional data, and (3) link occupants’emotions and cognition to a builtenvironment through a real-time emotive feedback loop. Using an interactive installation as a case study, thiswork examines the cognition-emotion-space interaction through changes in volume, color, and light as ameans of emotional expression. It contributes to the current theory and practice of cyber-physical design andthe role AI plays, as well as the interaction of technology and empathy. |
| keywords |
Places and awareness, artificial intelligence and machine learning in design, intelligent responsive spaces,affective computing in architecture, cognition-emotion-space interaction, embodied empathy, neuromorphicdesign, cyber-physical neurospaces |
| series |
journal |
| email |
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| references |
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|
Alves Lino J, Salem B and Rauterberg M. (2010)
 Responsive environments: user experiences for ambient intelligence
, J Ambient Intell Smart Environ; 2: 347–367. DOI:10.3233/AIS-2010-0080
|
|
|
|
|
Arbib MA. (2012)
Brains, machines and buildings: towards a neuromorphic architecture
, Intell. Build. Int; 4: 147–168. DOI:10.1080/17508975.2012.702863
|
|
|
|
|
Clark A. (2004)
Natural-born cyborgs: minds, technologies, and the future of human intelligence
, Oxford: Oxford University Press
|
|
|
|
|
Cook DJ. (2012)
How smart is your home?
, Science; 335: 1579–1581. DOI:10.1126/science.1217640
|
|
|
|
|
Damasio A. (2000)
The feeling of what happens: body and emotion in the making of consciousness
, 1st ed. San Diego, CA: Mariner Books
|
|
|
|
|
Ekman P. (1993)
Facial expression and emotion
, Am Psychol; 48: 384–392. DOI:10.1037/0003-066X.48.4.384
|
|
|
|
|
Eng K, Douglas RJ and Verschure PFMJ. (2005)
An interactive space that learns to influence human behavior
, IEEE Trans Syst Man Cybern Part A Syst Hum; 35: 66–77. DOI:10.1109/TSMCA.2004.838467
|
|
|
|
|
Farahi B. (2020)
Emotional intelligence: affective computing in architecture and design
, Architectural Intelligence. Singapore: Springer, pp. 235–251
|
|
|
|
|
Farahi B. (2019)
IRIDESCENCE: bio-inspired emotive matter
, ACADIA 19: UBIQUITY and AUTONOMY [Pro-ceedings of the 39th annual conference of the association for computer aided design in architecture the university of texas at austin school of architecture, Austin, Texas, 21-26 October 2019, pp. 674–683
|
|
|
|
|
Kilian A. (2018)
The flexing room architectural robot. An actuated active-bending
, Recalibration on imprecision andinfidelity [Proceedings of the 38th annual conference of the association for computer aided design in architecture, Mexico City, 18-20 October 2018
|
|
|
|
|
Lee YYand Hsieh S. (2014)
Classifying different emotional states by means of EEG-based functional connectivity patterns
, PLoS One; 9: e95415
|
|
|
|
|
Liu J, Meng H, Li M, et al. (2018)
Emotion detection from EEG recordings based on supervised and unsupervised dimension reduction
, Concurr Comput Pract Exp; 30: e4446. DOI:10.1002/cpe.4446
|
|
|
|
|
Love T. (2003)
Design and sense: implications of Damasio’s neurologicalfindings for design theory
, Proceedings ofscience and technology of design, senses and sensibility in technology - linking tradition to innovation through design, Lisbon, Portugal, 25-26 September 2003
|
|
|
|
|
Mozer MC, Dodier RH, Anderson M, et al. (1995)
The neural network house: an overview
, L Niklasson and M Boden(eds)Current trends in connectionism. Hillsdale, NJ: Erlbaum, pp. 371–380
|
|
|
|
|
Mozer MC. (2005)
Lessons from an adaptive house
, D Cook and R Das (eds)Smart environments: technologies, protocols, and applications. Hoboken, NJ: John Wiley & Sons, pp. 273–294
|
|
|
|
|
Negroponte N. (1969)
Toward a theory of architecture machines
, J Archit Educ; 23: 9–12. DOI:10.2307/1423828
|
|
|
|
|
Panksepp J. (1992)
A role for “affective neuroscience” in understanding stress: the case of separation distress circuitry
, SPuglisi-Allegra and A Oliverio (eds) Psychobiology of stress. Dordrecht, Netherlands: Kluwer Academic, pp.41–58
|
|
|
|
|
Picard RW. (2003)
Affective computing: challenges
, Int J Hum Comput Stud; 59: 55–64. DOI:10.1016/s1071-5819(03)00052-1
|
|
|
|
|
Picard RW. (1995)
Affective Computing
, Report No. 321. M.I.T Media Laboratory Perceptual Computing Section
|
|
|
|
|
Sabin JE, Hilla J, Pranger D, et al. (2020)
Embedded architecture: Ada, driven by humans, powered by AI
, Fabricate 2020. London: UCL Press, pp. 246–255
|
|
|
|
| last changed |
2024/04/17 14:29 |
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