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EAISC 2021 : Edited Book: Explainable Artificial Intelligence for Smart Cities


When Jun 1, 2021 - Jul 1, 2021
Where Taylor & Francis Group
Submission Deadline Jan 31, 2021
Final Version Due Apr 15, 2021
Categories    artificial intelligence   machine learning   smart cities   internet of things

Call For Papers


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 technology brings more change 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. Because the rise of smart cities is somehow a transformation of both communities and technology use habits, there are many different research orientations to shape a better future.

Moving from the explanations, the objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart cities developments. Because 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. Because black-box level means no clear clue about what is going within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, the issue has tried to be solved with additional use of XAI methods to improve transparency level. This book will provide a timely, wide international reference source about cutting edge research efforts to ensure the XAI factor in smart city-oriented developments. The book welcomes both positive and negative outcomes as well as future insights and both societal and technical aspects of XAI based smart city research efforts.


* XAI for Smart Education

- Machine learning for smart education
- Deep learning for smart education
- Evolutionary algorithms for smart education
- Smart learning solutions for combating Covid-19

* XAI for Smart Health

- Machine learning for smart health
- Deep learning for smart health
- Evolutionary algorithms for smart health
- Smart health solutions for combating Covid-19

* XAI for Smart transportation

- Machine learning for smart transportation
- Deep learning for smart transportation
- Evolutionary algorithms for smart transportation
- Smart learning solutions for combating Covid-19

*XAI for Smart Finance

- Machine learning for smart finance
- Deep learning for smart finance
- Evolutionary algorithms for smart finance
- Machine Learning for smart Trading
- Deep Learning for smart Trading
- Banking and Financial Services for combating Covid-19
- Smart Contracts and Financial Instruments
- Fraud Detection and Financial Crime Prevention

* XAI for Smart Environment

- Machine learning for smart environment
- Deep learning for smart environment
- Evolutionary algorithms for smart environment
- Smart environment solutions for combating Covid-19

* Cyber Security and XAI for Smart Cities

- AI-based protocols and services for smart cities
- IA-based communications Security
- Security for Ubiquitous/Pervasive Computing
- Big Data Analytics for Smart Cities Security
- Machine Learning techniques for Cybersecurity and Privacy
- Deep Learning techniques for Cybersecurity and Privacy

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