Explainable Artificial Intelligence for Smart Cities
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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.
Table of Contents
1. An Overview of Explainable Artificial Intelligence (XAI) from a Modern Perspective
2. Explainable Artificial Intelligence For Smart Cities Services Exchange
3. IoT and explainable artificial intelligence based smart medical waste management
4. The impact and usage of smartphone among Generation Z: A study conduct based on data mining techniques
5. Explainable artificial intelligence: Guardian for cancer care
6. ANN-Based Brain Tumor Classification: Performance Analysis Using K-means and FCM Clustering with Various Training Function
7. Recognition of the most common trisomies through automated identification of abnormal metaphase chromosome cells
8. Smart learning solutions for combating Covid-19
9. AN ANALYTICS ON MACHINE LEARNING FOR SMART TRANSPORTATION SYSTEM (STS)
10. Classification of Kinematic Data using Explainable Artificial Intelligence (XAI) for Smart Motion
11. Smart Urban Traffic Management for an Efficient Smart City
12. Systematic Comparison of Feature Selection Methods for Solar Energy Forecasting
13. Indoor Environment Assistance Navigation System using Deep convolutional Neural Networks
14. Pixel-based Classification of Land Use/Land Cover Built-Up and Non Built-Up Areas using Google Earth Engine in an Urban Region, Delhi, India
15. Emergence of Smart Home Systems Using IoT: Challenges and Limitations
16. Acceptance of Blockchain in Smart City Governance from the User Perspective
17. Explainable AI in machine/deep learning for intrusion detection in intelligent transportation systems for smart cities
18. Real Time Identity Censorship of Videos to Enable Live Telecast Using NVIDIA Jetson Nano
19. Smart Cities’ information security: Deep learning-based Risk Management
Mohamed LAHBY is Associate Professor at the Higher Normal School (ENS) University Hassan II of Casablanca, Morocco. His PhD in Computer Science from Faculty of Sciences and Technology of Mohammedia, University Hassan II of Casablanca, in 2013. His research interests are wireless communication and network, mobility management, QoS/QoE, Internet of things, Smart cities, Optimization and Machine learning. He has published more than 35 papers (book chapters, international journals, and conferences), 1 edited book, and 1 authored book. He has served and continues to serve on executive and technical program committees of numerous international conferences such as IEEE PIMRC, ICC, NTMS, IWCMC, WINCOM, ISNCC. He also serves as a referee of many prestigious Elsevier journals : Ad Hoc Networks, Applied Computing and Informatics and International journal of disaster risk reduction. He organized and participated more than 40 conferences and workshops. He is the chair of many international workshops and special sessions such as MLNGSN’19, CSPSC’19, MLNGSN’20, AI2SC ’20 and WCTCP’20. Utku Kose received the B.S. degree in 2008 from computer education of Gazi University, Turkey as a faculty valedictorian. He received M.S. degree in 2010 from Afyon Kocatepe University, Turkey in the field of computer and D.S. / Ph. D. degree in 2017 from Selcuk University, Turkey in the field of computer engineering. Between 2009 and 2011, he has worked as a Research Assistant in Afyon Kocatepe University. Following, he has also worked as a Lecturer and Vocational School – Vice Director in Afyon Kocatepe University between 2011 and 2012, as a Lecturer and Research Center Director in Usak University between 2012 and 2017, and as an Assistant Professor in Suleyman Demirel University between 2017 and 2019. Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, authored and edited books, proceedings, and reports. He is also in editorial boards of many scientific journals and serves as one of the editors of the Biomedical and Robotics Healthcare book series by CRC Press. His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, optimization, the chaos theory, distance education, e-learning, computer education, and computer science. AKASH KUMAR BHOI has completed his B.Tech. (Biomedical Engineering) from Trident Academy of Technology, BPUT University, Odisha and M.Tech. (Biomedical Instrumentation) from Karunya University, Coimbatore in the year 2009 and 2011 respectively. In 2019 he is awarded Ph.D. in the area of Biomedical Signal Processing from Dept. of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, India. He is working as Assistant Professor-I in the Department of Electrical and Electronics Engineering at Sikkim Manipal Institute of Technology (SMIT), India since 2012. He is the University Ph.D. Course Coordinator for “Research & Publication Ethics (RPE)”. He is member of IEEE, ISEIS and IAENG, associate member of IEI, UACEE and editorial board member reviewer of Indian and international journals. He is also a regular reviewer of journals of repute namely IEEE, Springer, Elsevier, Taylor and Francis, Inderscience etc. His areas of research are biomedical signal processing, medical image processing, sensors and transducers, and medical instrumentation. He has published several papers in national and international journals and conferences. He has 90+ documents registered in Scopus database. He has also served on numerous organizing panels for the international conferences and workshops. He is currently editing several books with Springer Nature and serving as Guest editor for special issues of the journal like Springer Nature and Inderscience.