Work

From Optimisation to Closed-Loop Urban Automation: A Conceptual Framework for Spatial Intelligence and Physical AI in AI–IoT-Enabled Smart Cities

Year: 2026

Type: article

Abstract: Artificial intelligence (AI) and the Internet of Things (IoT) are converging to create densely sensed, connected, and increasingly automated urban environments. However, research on AI–IoT integration remains dominated by optimisation-centric perspectives that under-specify spatial reasoning, physical actuation, and institutional accountability. This perspective addresses that gap by developing closed-loop urban automation as an analytical lens for understanding how AI–IoT systems move from urban sensing to consequential intervention. Drawing on a narrative, theory-driven synthesis of literature on Urban AI, IoT, Physical AI, spatial intelligence, digital twins, robotics, automation, and governance, the paper differentiates the framework from AIoT, cyber-physical systems, embodied AI, and optimisation-centric smart-city models. It identifies the distinctive conditions of urban automation, proposes six examinable propositions, and outlines implications for planning support, intelligent control, human oversight, and democratic legitimacy.

Source: Automation

DOI: 10.3390/automation7040122

Authors: Alok Tiwari, Yasser Qaffas

Institution: King Abdulaziz University

Language: English

Topic: Smart Cities and Technologies

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,207