Explainable Artificial Intelligence for Smart Cities

Thanks to rapid technological developments in terms of Computational Intelligence - smart tools have been taking active roles in daily life. It is clear that the 21st century has brought many advantages of using high level computation and communication solutions to deal with real world problems. However, more technologies bring more changes to society. In this sense, the concept of smart city has been a widely discussed topic in terms of society and Artificial Intelligence oriented research efforts. The rise of smart cities is somewhat a transformation of both communities and technology use habits and surely, there are many different research orientations to shape a better future.

The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, big IoT architectures), mechanisms of these systems become black-box to the users. As black-box level means no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes as well as future insights and both societal and technical aspects of XAI based smart city research efforts.

This book contains nineteen contributions classified into seven main sections. Section I presents a background related to both concepts: Explainable Artificial Intelligence (XAI) techniques and sustainable smart city applications.

Section II, XAI for Smart Healthcare, provides some chapters related to smart healthcare based on XAI techniques. Section III, XAI for Smart Education, explores the exploitation of XAI techniques in the context of smart education. Section IV, XAI for Smart Transportation, covers the various solutions that can contribute to improve smart transportation. Section V, XAI for Smart Environment, provides two chapters that can contribute to improve smart environment. Section VI of this book is about a smart urbanization and governance. A few chapters are fully dedicated to the use of XAI techniques for urbanization and governance. Finally, the last Section, Cyber Security and XAI for Smart Cities covers the latest architectures, and applications of XAI for cybersecurity and privacy in smart cities.