Towards Designing Smart Public Spaces: A Framework for Designers to Leverage AI and IoT Technologies | SpringerLink
Skip to main content
Springer Nature Link
Log in

Towards Designing Smart Public Spaces: A Framework for Designers to Leverage AI and IoT Technologies

  • Conference paper
  • First Online:
HCI International 2023 – Late Breaking Papers (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14057))

Included in the following conference series:

Abstract

Artificial Intelligent (AI) and Internet of Things (IoT) will provide novel solutions in the area of public spaces design if the designers could understand how these technologies can be best utilized. This study aims to address the question, “How can practitioners be supported in applying AI and IoT technologies in the early design process of smart public spaces?” In order to answer the question, the author developed a framework includes three categories and 48 technologies that can be utilized in smart public spaces design. A focus group was run to evaluate the feasibility. The evaluation suggests that the framework can be used as design stimuli in the concept design phase. At the end, the paper discusses the usage and iteration direction for the framework.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 11439
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 14299
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Suurenbroek, F., Nio, I.,  de Waal, M.: Responsive public spaces: exploring the use of interactive technology in the design of public spaces (2019)

    Google Scholar 

  2. Premier, A., GhaffarianHoseini, A.: Solar-powered smart urban furniture: preliminary investigation on limits and potentials of current designs. Smart Sustainable Built Environ. (2022)

    Google Scholar 

  3. Ciaramella, A., et al.: Smart furniture and smart city.  IOP Conf. Ser. Mater. Sci. Eng. 365(2), 022012 (2018)

    Google Scholar 

  4. Oberheitmann, A.: The Development of Smart Cities in China. Smart Urban Regeneration, pp. 201–213 (2017)

    Google Scholar 

  5. Burange, A.W.,  Misalkar, H.D.: Review of Internet of Things in development of smart cities with data management & privacy. In: 2015 International Conference on Advances in Computer Engineering and Applications, pp. 189–195. IEEE (2015)

    Google Scholar 

  6. Dove, G., Halskov, K., Forlizzi, J., Zimmerman, J.: UX design innovation: Challenges for working with machine learning as a design material. In: Proceedings of the 2017 Chi Conference on Human Factors in Computing Systems, pp. 278–288 (2017)

    Google Scholar 

  7. Yang, Q., Steinfeld, A., Rosé, C., Zimmerman, J.: Re-examining whether, why, and how human-AI interaction is uniquely difficult to design. In: Proceedings of the 2020 Chi Conference on Human Factors in Computing Systems, pp. 1–13 (2020)

    Google Scholar 

  8. Townsend, A.M.: Smart Cities: Big Data, Civic Hackers, And The Quest For A New Utopia. W.W. Norton & Company, New York (2013)

    Google Scholar 

  9. Yang, Q.: Machine learning as a UX design material: how can we imagine beyond automation, recommenders, and reminders?. In: AAAI Spring Symposia, vol. 1(2.1), pp. 2–6 (2018)

    Google Scholar 

  10. Yang, Q., Zimmerman, J., Steinfeld, A., Tomasic, A.: Planning adaptive mobile experiences when wireframing. In: Proceedings of the 2016 ACM Conference on Designing Interactive Systems, pp. 565–576 (2016)

    Google Scholar 

  11. Bond, R.R., et al.: Human centered artificial intelligence: weaving UX into algorithmic decision making. In: RoCHI, pp. 2–9 (2019)

    Google Scholar 

  12. Xu, W.: Toward human-centered AI: a perspective from human-computer interaction. Interactions 26(4), 42–46 (2019)

    Article  Google Scholar 

  13. Amershi, S., et al.: Guidelines for human-AI interaction. In: Proceedings of the 2019 Chi Conference on Human Factors in Computing Systems, pp. 1–13 (2019)

    Google Scholar 

  14. Yang, Q., Scuito, A., Zimmerman, J., Forlizzi, J., Steinfeld, A.: Investigating how experienced UX designers effectively work with machine learning. In: Proceedings of the 2018 Designing Interactive Systems Conference, pp. 585–596 (2018)

    Google Scholar 

  15. Zhou, Z., Sun, L., Zhang, Y., Liu, X., Gong, Q.: ML lifecycle canvas: designing machine learning-empowered UX with material lifecycle thinking. Hum.-Comput. Interact. 35(5–6), 362–386 (2020)

    Article  Google Scholar 

  16. Cardwell, D.: Copenhagen lighting the way to greener, more efficient cities, New York Times, p. 8 (2014)

    Google Scholar 

  17. Pk, J., Sen, A., Chen, X.,  Murali, A.: Inside Haidian Park: A stroll through the world’s first “ai-park” (2018). https://archive.factordaily.com/inside-haidian-park-the-worlds-first-artificial-intelligence-park/ 

  18. Arriany, A.A.,  Musbah, M.S.: Applying voice recognition technology for smart home networks. In: 2016 International Conference on Engineering & MIS (ICEMIS), pp. 1–6. IEEE (2016)

    Google Scholar 

  19. Li, L., Mu, X., Li, S., Peng, H.: A review of face recognition technology. IEEE access 8, 139110–139120 (2020)

    Article  Google Scholar 

  20. Praveen, G.B., Dakala, J.: Face recognition: challenges and issues in smart city/environments. In 2020 International Conference on Communication Systems & NetworkS (COMSNETS, pp. 791–793. IEEE (2020)

    Google Scholar 

  21. Pujol, F.A., Mora, H.,  Martínez, A.: Emotion recognition to improve e-healthcare systems in smart cities. In: Research & Innovation Forum 2019: Technology, Innovation, Education, and their Social Impact 1, pp. 245–254. Springer International Publishing (2019). https://doi.org/10.1007/978-3-030-30809-4_23

  22. Hossain, M.S., Muhammad, G.: Emotion recognition using deep learning approach from audio–visual emotional big data. Informat. Fusion 49, 69–78 (2019)

    Article  Google Scholar 

  23. Marsden, M., McGuinness, K., Little, S.,  O'Connor, N.E.: Resnetcrowd: a residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification. In: 2017 14th IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS), pp. 1–7. IEEE (2017)

    Google Scholar 

  24. Jarvis, N., Hata, J., Wayne, N., Raychoudhury, V.,  Gani, M.O.: Miamimapper: crowd analysis using active and passive indoor localization through wi-fi probe monitoring. In: Proceedings of the 15th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, pp. 1–10 (2019)

    Google Scholar 

  25. Atta, S., Sadiq, B., Ahmad, A., Saeed, S.N.,  Felemban, E.: Spatial-crowd: a big data framework for efficient data visualization. In: 2016 IEEE International Conference on Big Data (Big Data), pp. 2130–2138. IEEE (2016)

    Google Scholar 

  26. Yan, R., Tang, J., Shu, X., Li, Z.,  Tian, Q.: Participation-contributed temporal dynamic model for group activity recognition. In: Proceedings of the 26th ACM international conference on Multimedia, pp. 1292–1300 (2018)

    Google Scholar 

  27. Deng, Z., Vahdat, A., Hu, H., Mori, G.: Structure inference machines: Recurrent neural networks for analyzing relations in group activity recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4772–4781 (2016)

    Google Scholar 

  28. Channi, H. K.,  Kumar, R.: The role of smart sensors in smart city. In: Smart Sensor Networks: Analytics, Sharing and Control, pp. 27–48. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-77214-7_2

  29. Siregar, B., Nasution, A.B.A.,  Fahmi, F.: Integrated pollution monitoring system for smart city. In: 2016 International Conference on ICT For Smart Society (ICISS), pp. 49–52. IEEE (2016)

    Google Scholar 

  30. Hancke, G.P., de Carvalho e Silva, B.,  Hancke Jr., G.P.: The role of advanced sensing in smart cities. Sensors 13(1), 393–425 (2012)

    Google Scholar 

  31. Dheena, P.F., Raj, G.S., Dutt, G.,  Jinny, S.V.: IOT based smart street light management system. In: 2017 IEEE International Conference on Circuits and Systems (ICCS), pp. 368–371. IEEE (2017)

    Google Scholar 

  32. Sarmento, P., Holmqvist, O., Barthet, M.: Musical Smart City: Perspectives on Ubiquitous Sonification. arXiv preprint arXiv:2006.12305. (2020)

  33. Murshed, S.M., Al-Hyari, A.M., Wendel, J., Ansart, L.: Design and implementation of a 4D web application for analytical visualization of smart city applications. ISPRS Int. J. Geo Inf. 7(7), 276 (2018)

    Article  Google Scholar 

  34. Clarke, V., Braun, V., Hayfield, N.: Thematic analysis. Qualitative Psychol.  Pract. Guide  Res. Methods 3, 222–248 (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tongji University, Shanghai, 200000, China

    Shuran Li, Yuwei Wu & Zhiqiang Wu

  2. Tongji Architectural Design and Research Institute (Group) Co., Ltd., Shanghai, 200000, China

    Chengwei Wang

  3. Future City (Shanghai) Design Consulting Co., Ltd., Shanghai, 200000, China

    Liying Rong

Authors
  1. Shuran Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chengwei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liying Rong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuwei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhiqiang Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhiqiang Wu .

Editor information

Editors and Affiliations

  1. Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

  2. Technische Universitat Ilmenau, Ilmenau, Germany

    Heidi Krömker

  3. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  4. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, S., Wang, C., Rong, L., Wu, Y., Wu, Z. (2023). Towards Designing Smart Public Spaces: A Framework for Designers to Leverage AI and IoT Technologies. In: Duffy, V.G., Krömker, H., A. Streitz, N., Konomi, S. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14057. Springer, Cham. https://doi.org/10.1007/978-3-031-48047-8_34

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48047-8_34

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48046-1

  • Online ISBN: 978-3-031-48047-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics