Artificial Intelligence in Sustainable Urban Housing and Infrastructure Planning: A Systematic Review of Emerging Approaches and Challenges

Sharajsharifi, Mahsa

doi:10.22059/jcss.2023.102629

Artificial Intelligence in Sustainable Urban Housing and Infrastructure Planning: A Systematic Review of Emerging Approaches and Challenges

Author

Mahsa Sharajsharifi

Department of Architectural Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran

10.22059/jcss.2023.102629

Abstract

As urbanization accelerates, AI has emerged as a critical enabler of sustainable housing and infrastructure planning. This study presents a systematic review of peer-reviewed literature from 2000 to 2025, synthesizing advancements in AI applications across energy management, healthcare monitoring, environmental sensing, and user-centric design in smart urban systems. Drawing on 25 rigorously selected studies, the review identifies key AI techniques—including machine learning, neural networks, reinforcement learning, and AIoT frameworks—that facilitate adaptive, efficient, and inclusive urban environments. It also highlights geographic and methodological gaps in the literature, particularly the underrepresentation of the Global South and limited interdisciplinary integration. Challenges such as data privacy, algorithmic transparency, and lack of regulatory frameworks are critically examined. The findings emphasize the transformative potential of AI when aligned with sustainability goals, while calling for collaborative, ethically informed, and context-specific research and policy strategies.

Keywords

AIoT, artificial intelligence, interdisciplinary governance, smart housing

energy efficiency, sustainable urban planning

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