The Potentials of the Interaction of Biomimicry and Artificial Intelligence Technology in Participatory Urban Design

Öz

Biomimicry is a discipline that develops human-made solutions inspired by the design and function of living things in nature. This approach aims to provide innovative and effective solutions in terms of sustainability and efficiency. Artificial intelligence is a field of technology that enables computer systems to have human-like intelligence. These systems can assist humans by performing tasks such as data analysis, learning and problem solving and have great potential in solving complex problems. This paper evaluates the interaction of participatory urban design, biomimicry and artificial intelligence technologies in the field of urban planning and design. Biomimicry explores how nature-inspired designs and processes can be used in urban spaces, while AI technologies utilise analytical and predictive capabilities to improve the efficiency of urban systems. The paper discusses examples of both concepts at the urban scale and discusses the benefits that arise from bringing these stakeholders together. The use of biomimicry principles in urban planning and design contributes to issues such as sustainability, energy efficiency, efficient use of natural resources, energy and resource conservation, adaptation and resilience. Artificial intelligence technologies, on the other hand, increase efficiency while solving complex and difficult problems in urban areas with big data analytics, predictive capabilities and automated decision-making systems. In this article, a participatory process model is proposed to reveal the interaction of biomimicry and artificial intelligence technologies in urban planning and design. Increasing research in this field will contribute to the optimisation of planning processes and the realisation of sustainable development goals.

Anahtar Kelimeler

• Cities
• Biomimicry
• Artificial Intelligence
• Participatory Urban Design
• Urban Design
• Sustainability

Katılımcı Kentsel Tasarımda Biyomimikri ve Yapay Zekâ Teknolojisi Etkileşiminin Barındırdığı Potansiyeller

Öz

Biyomimikri, doğadaki canlıların tasarım ve işlevlerinden ilham alarak insan yapımı çözümler geliştiren bir disiplindir. Bu yaklaşım, sürdürülebilirlik ve verimlilik açısından yenilikçi ve etkili çözümler sunmayı hedefler. Yapay zeka, bilgisayar sistemlerinin insan benzeri zekaya sahip olmasını sağlayan bir teknoloji alanıdır. Bu sistemler, veri analizi, öğrenme ve problem çözme gibi görevleri gerçekleştirerek insanlara yardımcı olabilir ve karmaşık sorunları çözmede büyük potansiyele sahiptir. Bu makale, katılımcı kentsel tasarım, biyomimikri ve yapay zeka teknolojilerinin etkileşimini kentsel planlama ve tasarım alanındaki potansiyellerini değerlendirmektedir. Biyomimikri, doğadan ilham alarak yapılan tasarımların ve süreçlerin kentsel alanlarda nasıl kullanılabileceğini araştırırken, yapay zeka teknolojileri ise kentsel sistemlerin verimliliğini artırmak için analitik ve öngörü yeteneklerini kullanır. Makalede iki kavram özelinde kentsel ölçekte yapılmış örnekler tartışılmakta ve bu paydaşların bir araya gelmesinden kaynaklanan faydalar ele alınmaktadır. Biyomimikri prensiplerinin kentsel planlama ve tasarımda kullanılması, sürdürülebilirlik, enerji verimliliği, doğal kaynakların etkin kullanımı, enerji ve kaynak tasarrufu, adaptasyon ve dayanıklılık gibi konulara katkı sağlar. Yapay zeka teknolojileri ise büyük veri analitiği, öngörü yetenekleri ve otomatik karar verme sistemleriyle kentsel alanlarda karmaşık ve zor problemleri çözerken verimlilik artışı sağlar. Bu çalışma kapsamında, biyomimikri ve yapay zeka teknolojilerinin kentsel planlama ve tasarım alanındaki etkileşiminin ortaya çıkarılmasına yönelik katılımcı bir süreç modeli önerilmektedir. Bu alanda sürdürülen araştırmaların artması planlama süreçlerinin optimizasyonuna ve sürdürülebilir kalkınma hedeflerinin karşılanmasına katkı sağlayacaktır.

Anahtar Kelimeler

• Kentler
• Biomimikri
• Yapay zeka
• Katılımcı Kentsel tasarım
• Kentsel tasarım
• Sürdürülebilirlik

Kaynakça

1. Allmendinger, P.; Haughton, G. (2009). Soft spaces, fuzzy boundaries, and metagovernance: The new spatial planning in the Thames Gateway. Environ. Plan. A, 41, 617–633.
2. Aschwanden, G.; Wijnands, J.S.; Thompson, J.; Nice, K.A.; Zhao, H.F.; Stevenson, M. (2021). Learning to walk: Modeling transportation mode choice distribution through neural networks. Environ. Plan. B Urban Anal. City Sci., 48, 186–199.
3. Ayres, R.U. (1989). Industrial Metabolism, in J.H. Ausubel and H. Sladovich, eds., Environment and Technical Change, National Academy Press, Washington, DC, USA.
4. Batty, M., Marshall, S. (2009). Centenary Paper: The Evolution of Cities: Geddes, Abercrombie and the New Physicalism. Town Plan. Rev. 80 (6), 551-574.
5. Baek, I. (2015). A study on the sustainable infrastructure of the Songdo City Project: from the viewpoint of the metabolic flow perspective.
6. BaezaR, A. (2018). A Methodology for Urban Sustainability Indicator Design. TeMA - Journal of Land Use, Mobility and Environment, 11(3), 285-303. https://doi.org/10.6092/1970-9870/5795
7. Benyus, J.M. (1997). Biomimicry: Innovation Inspired by Nature. New York: HarpenCollins.
8. Blanco, E.; Pedersen Zari, M.; Raskin, K.; Clergeau, P. (2021) Urban Ecosystem-Level Biomimicry and Regenerative Design: Linking Ecosystem Functioning and Urban Built Environments. Sustainability, 13, 404. https://doi.org/ 10.3390/su13010404

9. Buck, N.T. (2017). The art of imitating life: The potential contribution of biomimicry in shaping the future of our cities. Environ. Plan. B Urban Anal. City Sci., 44, 120–140.
10. Casey, W.A., Cai, Y. (2023). Renaissance of Biomimicry Computing. Mobile Netw Appl. 28, 490.
11. Doost Mohammadian, H., & Rezaie, F. (2020). Blue-Green Smart Mobility Technologies as Readiness for Facing Tomorrow’s Urban Shock toward the World as a Better Place for Living (Case Studies: Songdo and Copenhagen). Technologies, 8(3), 39. https://doi.org/10.3390/technologies8030039
12. Filomena, G.; Verstegen, J.A.; Manley, E. (2019). A computational approach to ‘The Image of the City.’ Cities, 89, 14–25.
13. Ghahramani, M.; Galle, N.J.; Duarte, F.; Ratti, C.; Pilla, F. (2021). Leveraging artificial intelligence to analyze citizens’ opinions on urban green space. City Environ. Interact., 10, 100058.
14. Guerreiro, M. (2011). Urban solutions inspired by nature, Proceedings of 7VCT, Lisbon, Portugal.
15. Haqbeen, J.; Sahab, S.; Ito, T.; Rizzi, P. (2021). Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level. Sustainability, 13, 5453.
16. Hwang, S., Lee, Z., & Kim, J. (2019). Real-Time Pedestrian Flow Analysis Using Networked Sensors for a Smart Subway System. Sustainability, 11, 6560.
17. Kamrowska-Załuska, D. (2021). Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities. Land, 10(1209).
18. Karapınar, Y. E. (2017). Akıllı Şehirler. İTÜ Dergisi (77), 14-19.
19. Kirwan, C., Zhiyong, F. (2020). Smart Cities and Artificial Intelligence Convergent Systems for Planning, Design, and Operations. Elsevier, 25-49.
20. Küçükali, U. (2016). Ecological Influences on the Evolving Planning System in Turkey. Population Growth and Rapid Urbanization in the Developing World, 298–312. https://doi.org/10.4018/978-1-5225-0187-9.ch015
21. Lang, J. (1994). Urban Design: The American Experience, New York: Van Nostrand Reinhold
22. Lang, J. (2005). Urban Design: A Typology of Procedures and Products Illustrated With Over 50 Case Studies, UK.
23. Langendorf, R. (1985) Computers and Decision Making, Journal of the American Planning Association, 51:4, 422-433.
24. Lazarus, M.A., & Crawford, C. (2011). Returning Genius to the Place. Architectural Design, 81, 48-53.
25. MacCowan, R.J. (2012). Biomimicry+Urban Design. (https://www.academia.edu/2120475/Biomimicry_Urban_Design)
26. McCarthy, J. (2004). What is artificial intelligence?. (http://wwwformal.stanford.edu/jmc/whatisai/).
27. McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. AI Magazine, 27(4), 12.
28. Never Enough Architecture. (2023). AI x Biomimicry. Retrieved May 13, 2024, from https://neverenougharchitecture.com/ai-x-biomimicry/
29. Newman, P.; Jennings, I. (2008). Cities as Sustainable Ecosystems: Principles and Practices, Washington: Island Press
30. Özkan A., Günkaya Z., Özdemir A., BANAR M. (2018). Sanayide Temiz Üretim ve Döngüsel Ekonomiye Geçişte Endüstriyel Simbiyoz Yaklaşımı: Bir Değerlendirme. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi B- Teorik Bilimler, 6;1.
31. P. Zari, M. (2007). Biomimetic Approaches To Architectural Design For Increased Sustainability”. Sustainable Building Conference (SB07) Auckland, New Zealand.
32. Rienow, A., Stenger, D., & Menz, G. (2014). Sprawling cities and shrinking regions – forecasting urban growth in the Ruhr for 2025 by coupling cells and agents. ERDKUNDE, 68(2), 85–107. https://doi.org/10.3112/erdkunde.2014.02.02
33. Rossin, K. J. (2010). Biomimicry: nature’s design process versus the designer’s process. WIT Transactions on Ecology and the Environment, 138, 559-570.
34. Thakuriah, P.; Tilahun, N.; Zellner, M. (2014). Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In Proceedings of the NSF Workshop on Big Data and Urban Informatics, Chicago, IL, USA, pp. 4–32.
35. Sanoff, H. (2008). Multiple Views of Participatory Design, IJAR, 2 (1), 57-69.
36. Smart, S. (2019). Lavasa, India's first planned hill city. Retrieved May 13, 2024, from https://www.slideshare.net/saumitrasmart/lavasa-indias-first-planned-hill-city
37. Sun, Y.; Shao, Y.W. (2020). Measuring visitor satisfaction toward peri-urban green and open spaces based on Social Media Data. Urban For. Urban Green., 53, 126709.
38. Valentine, S. V. (2016). Kalundborg symbiosis: fostering progressive innovation in environmental networks. Journal of Cleaner Production, 118, 65-77.
39. Volstad, N.L. and Boks, C. (2012). On the Use of Biomimicry as a Useful Tool for the Industrial Designer. Sustainable Development, 20(3)
40. Wang, J. (2023). Principles And Applications of Artificial Intelligence (AI) Algorithms: A Review of The Literature. Highlights in Science, Engineering and Technology, 57, 76-84. https://doi.org/10.54097/hset.v57i.9983
41. Yigitcanlar, T.; Kankanamge, N.; Vella, K. (2021). How Are Smart City Concepts and Technologies Perceived and Utilized? A Systematic Geo-Twitter Analysis of Smart Cities in Australia. J. Urban Technol., 28, 135–154.
42. Yin, H.; Zhang, Z.; Liu, Y. (2023). The Exploration of Integrating the Midjourney Artificial Intelligence Generated Content Tool into Design Systems to Direct Designers towards Future-Oriented Innovation. Systems, 11(566).
43. URL1:(https://thrive-collaborative.com/blog/2016/5/2/how-biomimicry-can-help-redesign-civilization)
44. URL2: (https://neverenougharchitecture.com/ai-x-biomimicry/#biomimicryResults)
45. URL3: (https://www.slideshare.net/lavasacity/lavasa-indias-planned-hill-city)
46. URL4: (https://www.asla.org/awards/2005/05winners/544.html)
47. URL5:(https://circulareconomy.europa.eu/platform/en/good-practices/kalundborg-symbiosis-six-decades-circular-approach-production)
48. URL6: (https://www.arch2o.com/langfang-eco-smart-city-hok/)
49. URL7:(https://www.arch2o.com/langfang-eco-smart-city-hok/)
50. URL8:(https://www.archdaily.com/962924/building-a-city-from-scratch-the-story-of-songdo-korea/60bc0becf91c81b13100000e-building-a-city-from-scratch-the-story-of-songdo-korea-image