Analysis of Artificial Intelligence Design Incorporated into Design of Street Space in Small Cities

Lei Song

doi:10.4108/ew.4219

Authors

Lei Song School of Design Shandong University of Arts, Jinan 250300, Shandong, China

DOI:

https://doi.org/10.4108/ew.4219

Keywords:

artificial intelligence, small cities, streets, spatial design

Abstract

INTRODUCTION: At present, China's urbanization continues to develop, but the level of urban planning and design has not kept pace with the progress of development, especially the creation of street space in small cities, which is still not able to adapt to the current needs of people's cultural life. With the development of the economy and science and technology, artificial intelligence and other information technologies are constantly integrated into daily life. Therefore, utilizing artificial intelligence for street space design research is significant.

OBJECTIVES: To improve the development level of artificial intelligence, information technology, and the application level of artificial intelligence in China; to solve the problem of the relatively low level of street space design in the current city, especially in small towns, to meet the needs of people's cultural life; to promote the improvement of the level of artificial intelligence in China for the convenience of civil life, and to further improve the level of street space design in China.

METHODS: Firstly discusses the theories, such as the principles of street space design in small cities, to illustrate the necessity of integrating AI into street space design in small towns; secondly, the model established by AI is used to optimize the street space in small cities; finally, the feasibility of integrating AI design into street space design in small towns is illustrated through cases and examples.

RESULTS: Street space design in small cities in China needs more design aesthetics, and artificial intelligence needs to be integrated into street space design. Artificial intelligence has a noticeable optimization effect on street space design, and using artificial intelligence can improve the design level of limited space. Also illustrates that artificial intelligence can be better integrated into the street space design of small cities through cases.

CONCLUSION: In the context of the digital era, the street space design of small cities needs to apply artificial intelligence. In modernization-oriented urban construction, the street space design level of small towns should be further strengthened to improve the modernization level of cities.

Downloads

Download data is not yet available.

References

Adjetey, L. D., Takyi, S. A., Asibey, M. O., & Amponsah, O. (2023). The fate of urban green spaces: Assessment of the ownership, availability, and conditions of parks in Accra, Ghana. Urban Forestry & Urban Greening, 2023, 2023. https://doi.org/10.1016/j.ufug.2023.127897 DOI: https://doi.org/10.1016/j.ufug.2023.127897

Ahmad, Of., Mori, Y., Misawa, M., Kudo, Se., Anderson, Jt., Bernal, J., Berzin, Tm., Bisschops, R., Byrne, Mf., & Chen, Pj. (2021). Establishing key research questions for implementing artificial intelligence in colonoscopy: A modified Delphi method. Endoscopy, 53(9), 893–901. https://doi.org/10.1055/a-1306-7590 DOI: https://doi.org/10.1055/a-1306-7590

Aydoghmish, F. M., & Rafieian, M. (2022). Developing a comprehensive conceptual framework for city branding based on urban planning theory: Meta-synthesis of the literature (1990-2020). Cities, 35(35), 57–79.

Barzegar, M., Rajabifard, A., Kalantari, M., & Atazadeh, B. (2021). A framework for spatial analysis in 3D urban land administration – A case study for Victoria, Australia. Land Use Policy, 111(111), 2021. https://doi.org/10.1016/j.landusepol.2021.105766 DOI: https://doi.org/10.1016/j.landusepol.2021.105766

Bauelos, J. K., Miranda, lvaro R., Valle-Melón, J. M., Zornoza-Indart, A., Castellano-Román, M., Angulo-Fornos, R., Pinto-Puerto, F., Ibáez, P. A., & Ferreira-Lopes, P. (2021). The Role of Information Management for the Sustainable Conservation of Cultural Heritage. Sustainability, 13(14), 28–37. DOI: https://doi.org/10.3390/su13084325

Caglar, G., Martin, E., Johannes, S., & Steffen, M. (2023). A multi-fidelity Gaussian process for efficient frequency sweeps in the acoustic design of a vehicle cabin. The Journal of the Acoustical Society of America, 47(47), 25–36.

Cai, K., Huang, W., & Lin, G. (2022). Bridging landscape preference and design: A study on the preference and optimal combination of landscape elements based on conjoint analysis. Urban Forestry & Urban Greening, May, 27–35. https://doi.org/10.1016/j.ufug.2022.127615 DOI: https://doi.org/10.1016/j.ufug.2022.127615

Harirchian, M., Azadi, M., Kermanshahi, S., Bashirinia, M., & Ghasri, M. (2021). Revisiting Transit-Oriented Development Evaluation for Urban Master Plans in the Context of Developing Countries: Transportation Research Record, 2675(10), 1069–1082. https://doi.org/10.1177/03611981211014526 DOI: https://doi.org/10.1177/03611981211014526

Jaljolie, R., Riekkinen, K., & Dalyot, S. (2021). A topological-based approach for determining spatial relationships of complex volumetric parcels in land administration systems. Land Use Policy, 109-109. DOI: https://doi.org/10.1016/j.landusepol.2021.105637

Mohamed, A. A., & Van, H. M. (2022). Street network and home-based business patterns in Cairo’s informal areas. Land Use Policy, 36(36), 45–60. https://doi.org/10.1016/j.landusepol.2022.106010 DOI: https://doi.org/10.1016/j.landusepol.2022.106010

Park, K., Federico, I., Di Lorenzo, E., Ezer, T., Cobb, K. M., Pinardi, N., & Coppini, G. (2022). The contribution of hurricane remote ocean forcing storm surge along the Southeastern U.S. coast. Coastal Engineering, Apr., 173. DOI: https://doi.org/10.1016/j.coastaleng.2022.104098

Patricia, S. (2021). Place and Space in Nineteenth-Century Representations of Old London: The Thieves’ House on West Street. Journal of Victorian Culture, 356(356), 34–50.

Qiu, W., Li, W., Liu, X., Zhang, Z., Li, X., & Huang, X. (2023). Subjective and objective measures of streetscape perceptions: Relationships with property value in Shanghai. Cities, 26(26), 13–25. https://doi.org/10.1016/j.cities.2022.104037 DOI: https://doi.org/10.1016/j.cities.2022.104037

Rana, A., Sadiq, R., Alam, M. S., Karunathilake, H., & Hewage, K. (2021). Evaluation of financial incentives for green buildings in the Canadian landscape. Renewable and Sustainable Energy Reviews, 135, 110199. https://doi.org/10.1016/j.rser.2020.110199 DOI: https://doi.org/10.1016/j.rser.2020.110199

Rodriguez-Valencia, A., & Ortiz-Ramirez, H. A. (2021). Understanding Green Street Design: Evidence from Three Cases in the U.S. Sustainability, 13(4), 1916. https://doi.org/10.3390/su13041916 DOI: https://doi.org/10.3390/su13041916

Song, J., Saathoff, H., Gao, L., Gebhardt, R., Jiang, F., Vallon, M., Bauer, J., Norra, S., & Leisner, T. (2022). Variations of PM_(2.5) sources in the context of meteorology and seasonality at an urban street canyon in Southwest Germany. Atmospheric Environment., Aug., 282. DOI: https://doi.org/10.1016/j.atmosenv.2022.119147

Stokel-Walker, C. (2023). What is the future of artificial intelligence? New Scientist, 38(38), 45–58. https://doi.org/10.1016/S0262-4079(23)00886-2 DOI: https://doi.org/10.1016/S0262-4079(23)00886-2

Sun, Z. (2021). A rhythm analysis approach to understanding the vending-walking forms and everyday use of urban street space in Yuncheng, China. Urban Studies, 2, 004209802199704. DOI: https://doi.org/10.1177/0042098021997044

Um, H., Dong, J., Choi, M., & Jeong, J. (2021). The Effect of Cultural City on Regional Activation through the Consumer Reactions of Urban Service. Sustainability, 13(13), 25–38. DOI: https://doi.org/10.3390/su13115778

Valente, R., Mozingo, L., Bosco, R., Cappelli, E., Donadio, C., & Li, Mr. S. (2021). Environmental Regeneration Integrating Soft Mobility and Green Street Networks: A Case Study in the Metropolitan Periphery of Naples. Sustainability, 15(15), 67–73. https://doi.org/10.3390/su13158195 DOI: https://doi.org/10.3390/su13158195

Vincent, N. C., Bhakar, R. R., Nadarajan, S. R., Syamala, A., & Varghese, J. (2021). Impact of Artificial Intelligence in the Aviation and Space Sector. Artificial Intelligence, 256, 56–70. https://doi.org/10.1201/9781003095910-15 DOI: https://doi.org/10.1201/9781003095910-15

Wu, W., Niu, X., & Li, M. (2021). Influence of Built Environment on Street Vitality: A Case Study of West Nanjing Road in Shanghai Based on Mobile Location Data. Sustainability, 13(13), 35–47. DOI: https://doi.org/10.3390/su13041840