Integration of Artificial Intelligence in inclusive urban design to enhance gender and disability safety: A design-based research in Surabaya

Ainin Bashiroh; Ahmad Syaifuddin; Faizatus Sholikhah; Komang Ayu Laksmi Harshinta Sari; Ade Fitriyanti Ulul Azmi; Ionocki Prasetyo

doi:10.30822/arteks.v11i1.4813

Authors

Ainin Bashiroh Universitas Islam Majapahit
Ahmad Syaifuddin Universitas Islam Majapahit
Faizatus Sholikhah Universitas Islam Majapahit
Komang Ayu Laksmi Harshinta Sari Institut Teknologi Nasional Malang
Ade Fitriyanti Ulul Azmi Universitas Islam Majapahit
Ionocki Prasetyo Universitas Islam Majapahit

DOI:

https://doi.org/10.30822/arteks.v11i1.4813

Keywords:

Artificial Intelligence, Disability, Gender, Inclusive City, Urban Design

Abstract

Limited accessibility and safety for women and persons with disabilities remain critical issues in urban development in Indonesia, particularly in public spaces that are insufficiently responsive to vulnerable groups. This study aims to develop an inclusive urban design concept based on gender and disability perspectives through the integration of Artificial Intelligence (AI) and participatory approaches as an evidence-based design foundation. The research adopts a Design-Based Research (DBR) approach using mixed methods that combine AI-based quantitative analysis and participatory qualitative methods. Quantitative data were obtained through YouTube data crawling (853 entries, 729 valid datasets) and analyzed using Named Entity Recognition (NER) to identify potentially unsafe urban locations, then visualized through WebGIS. Qualitative data were collected through Focus Group Discussions (FGDs) involving disability organizations, women’s groups, and policymakers. The results identified three vulnerable locations in Surabaya: Kedung Cowek Street, Wonorejo Timur Street, and Kupang Indah Street. The study formulates inclusive urban design elements, including standardized pedestrian pathways, guiding blocks, gentle ramps, lighting levels of at least 12 lux, accessible transit stops, signage, and gender-sensitive public facilities. The novelty lies in integrating AI-based social media analysis with participatory approaches within a DBR framework to support data-driven inclusive urban design.

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