Opportunities and Applications of GenAI in Smart Cities: A User-Centric Survey

TL;DR

This paper surveys how Generative AI can enhance smart city applications through user-centric conversational interfaces, leveraging multimodal data and models to improve urban management for citizens, operators, and planners.

Contribution

It provides the first comprehensive review of GenAI techniques tailored for smart city users, focusing on applications, models, and data integration strategies.

Findings

GenAI enables natural language interfaces for smart city systems.

Applications span citizens, operators, and planners with tailored solutions.

GenAI leverages existing city data and digital twins for enhanced urban services.

Abstract

The proliferation of IoT in cities, combined with Digital Twins, creates a rich data foundation for Smart Cities aimed at improving urban life and operations. Generative AI (GenAI) significantly enhances this potential, moving beyond traditional AI analytics and predictions by processing multimodal content and generating novel outputs like text and simulations. Using specialized or foundational models, GenAI's natural language abilities such as Natural Language Understanding (NLU) and Natural Language Generation (NLG) can power tailored applications and unified interfaces, dramatically lowering barriers for users interacting with complex smart city systems. In this paper, we focus on GenAI applications based on conversational interfaces within the context of three critical user archetypes in a Smart City - Citizens, Operators and Planners. We identify and review GenAI models and techniques that have been proposed or deployed for various urban subsystems in the contexts of these user archetypes. We also consider how GenAI can be built on the existing data foundation of official city records, IoT data streams and Urban Digital Twins. We believe this work represents the first comprehensive summarization of GenAI techniques for Smart Cities from the lens of the critical users in a Smart City.