Work

Analysis of the Historically Compatibility of AI-Assisted Urban Furniture Design Using the Semantic Differentiation Method: The Case of Elazığ Harput

Year: 2025

Type: article

Abstract: This study examined the historical compatibility of urban furniture in Harput Sarahatun Mosque Square, Elazığ, Türkiye. It evaluated AI-generated modern and classical-style alternatives using the Semantic Differentiation Method. The research aimed to compare existing furniture with AI-assisted designs and identify key attributes influencing historical and spatial integration. The methodology consists of four stages: (1) defining adjective pairs to assess historical compatibility through expert opinions and literature review; (2) photographing existing urban furniture and generating AI-assisted modern and classical-style urban furniture (benches, trash cans, and lighting elements); (3) determination expert opinion using the survey; (4) statistical analysis of results through descriptive statistics and explanatory factor analysis (EFA). The study, which was conducted online in February 2025, involved 31 experts from the architecture and landscape architecture disciplines. The findings show that existing furniture is mainly judged by practicality and usability, with limited attention to historical integration. Modern AI-generated designs emphasize innovation, minimalism, and contemporary aesthetics. In contrast, classical-style AI-generated furniture is appreciated for its historical compatibility, cultural resonance, and aesthetic harmony. Experts favored classical alternatives for their alignment with traditional urban character. The results highlight the need for future designs to balance functionality, sustainability, and historical continuity, ensuring urban furniture contributes to cultural preservation and modern urban needs.

Source: Sustainability

DOI: 10.3390/su17083402

Authors: Ayca Gulten, Betul Yildirim, Muge Unal

Institution: Fırat University

Language: English

Topic: Urban Development and Cultural Heritage

Subfield: Urban Studies

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896