Ai-Generated Concept Sculptures and Their Influence on Future Urban Public Art Landscapes
Bibliographic Data
| ID | 19490337 |
|---|---|
| Authors | Shilpa Bhargav, Shilpa Anandrao Bhargav (Vivekananda Global University), Arvind Kumar Pandey (0000-0001-5294-0190, National Institute of Technology Jamshedpur), Pratibha Sharma (0000-0002-6954-7579, Chitkara University), Rajesh Raikwar (International Institute of Information Technology), Harshini R (Meenakshi Academy of Higher Education and Research), Devi S (Meenakshi Academy of Higher Education and Research) |
| Year | 2026 |
| Volume | 7 |
| Issue | 4s |
| Pages | 343-351 |
| Publication date | 2026-04-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ShodhKosh: Journal of Visual and Performing Arts (JOURNAL) |
| Journal identifiers | ISSN: 2582-7472 • E-ISSN: 2582-7472 |
| Publisher | Granthaalayah Publications and Printers (PUBLISHER • IN) |
| DOI | 10.29121/shodhkosh.v7.i4s.2026.7485 |
| OpenAlex | W7153842087 |
| Language | EN |
| References cited | 13 |
he creation of concept sculptures designed by an artificial intelligence is transforming the creative, spatial and experience elements of the art of the people in the cities. The present practice on urban arts is however not scalable, personalized and adaptable in design and thus restricted in dynamism in adapting to the changing social, environmental and spatial environment. The given paper is devoted to the problem of integrating intelligent generative systems into the workflow of the public art to render it more creative, productive, and relevant. The primary idea is to consider the possibility of using AI-based design models to transform the concept and practice of massive city sculptures. It is implemented with the help of an AI-based methodology and presupposes the application of generative adversarial networks (GANs), diffusion models, and parametric optimization to produce adaptive sculptures designs. It is designed to incorporate environmental data, human input of interaction and urban spatial constraint to come up with context sensitive sculptural forms. It is compared to the conventional manual and CAD-based design processes in terms of the key performance indicators like design efficiency, the range of aesthetics, structural acceptability, interaction between users. The results have shown that the utilization of the suggested AI-based system is more effective in terms of the efficacy of designs (34.6%), enhancement of the aesthetic variety (29.8%), and the more precise structuring optimization (21.5), as well as higher scores on the public engagement (27.3) in comparison to the conventional methods. These findings indicate that AI generated sculptures are significantly superior to the traditional ones in both creativity and utility. Also connected to this paper are smart cities, interactive city installations and future urban planning systems where AI may be used to create real-time, adaptive, and participatory systems in art. The paper also shows the opportunities of AI in enhancing the urban landscape of the masses by being intelligent, scaling and immersive in the process of designing the sculptures.The creation of concept sculptures designed by an artificial intelligence is transforming the creative, spatial and experience elements of the art of the people in the cities. The present practice on urban arts is however not scalable, personalized and adaptable in design and thus restricted in dynamism in adapting to the changing social, environmental and spatial environment. The given paper is devoted to the problem of integrating intelligent generative systems into the workflow of the public art to render it more creative, productive, and relevant. The primary idea is to consider the possibility of using AI-based design models to transform the concept and practice of massive city sculptures. It is implemented with the help of an AI-based methodology and presupposes the application of generative adversarial networks (GANs), diffusion models, and parametric optimization to produce adaptive sculptures designs. It is designed to incorporate environmental data, human input of interaction and urban spatial constraint to come up with context sensitive sculptural forms. It is compared to the conventional manual and CAD-based design processes in terms of the key performance indicators like design efficiency, the range of aesthetics, structural acceptability, interaction between users. The results have shown that the utilization of the suggested AI-based system is more effective in terms of the efficacy of designs (34.6%), enhancement of the aesthetic variety (29.8%), and the more precise structuring optimization (21.5), as well as higher scores on the public engagement (27.3) in comparison to the conventional methods. These findings indicate that AI generated sculptures are significantly superior to the traditional ones in both creativity and utility. Also connected to this paper are smart cities, interactive city installations and future urban planning systems where AI may be used to create real-time, adaptive, and participatory systems in art. The paper also shows the opportunities of AI in enhancing the urban landscape of the masses by being intelligent, scaling and immersive in the process of designing the sculptures
Public art · Sculpture · Structuring · Workflow · Aesthetic Perception and Analysis · Architecture and Computational Design · Digital Media and Philosophy
| Citation velocity | historical |
|---|---|
| Highly cited | No |