Explainable Artificial Intelligence for Smart Cities

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Explainable Artificial Intelligence for Smart Cities

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 350 p.
  • 言語 ENG
  • 商品コード 9781032001135
  • DDC分類 307.760285

Full Description

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in 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 cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and 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 Data, IoT architectures), the mechanisms of these systems become 'black-box' to users. As this means that there is 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 the 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 the societal and technical aspects of XAI-based smart city research efforts.

This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Contents

Contributors. 1 An Overview of Explainable Artificial Intelligence (XAI) from a Modern Perspective. 2 Explainable Artificial Intelligence for Services Exchange in Smart Cities. 3 IoT- and XAI-Based Smart Medical Waste Management. 4 The Impact and Usage of Smartphone among Generation Z: A Study 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 Functions. 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 Analysis of 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. Index.

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