AI and Data Engineering for Smart Cities

1. Auflage 2027
ISBN: 978-1-032-74091-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 384 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: Chapman & Hall/Distributed Computing and Intelligent Data Analytics Series

This book explores the transformative potential of artificial intelligence (AI) and data engineering in shaping the future of smart cities. With the rapid growth of urbanisation, cities are facing complex challenges such as efficient resource management, urban mobility, environmental sustainability, and citizen well-being. It offers authoritative insights and perspectives brought together by leading experts to delve into the latest advancements and applications of AI and data engineering in addressing urban challenges.

• Includes practical insights, case studies and real-world examples of how AI and data engineering are being applied in smart city initiatives

• Presents the role of AI in enhancing urban infrastructure, optimizing energy consumption, enabling intelligent transportation systems, and empowering citizen participation.

• Showcases how AI and data engineering can revolutionise urban landscapes and pave the way for sustainable and intelligent cities

• Discusses the ethical and privacy concerns related to the use of these technologies in cities, highlighting the importance of responsible and sustainable development.

• Presents an interdisciplinary approach, exploring the intersection of AI and data engineering with fields such as urban planning, transportation, energy and health.

The book is primarily aimed at researchers, practitioners, and students in the fields of computer science, engineering and urban planning. It is also relevant to policymakers, government officials, and other professionals involved in the development and implementation of smart city solutions.

Zielgruppe

Academic and Professional Reference

Autoren/Hrsg.

Kumar M. V., Manoj

M., Niranjanamurthy

Darshan S. L., Shiva

Azaad Moonesar, Immanuel

Rao, Ananth

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
• Sozialwissenschaften Politikwissenschaft Regierungspolitik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Geowissenschaften Geographie | Raumplanung Regional- & Raumplanung Stadtplanung, Kommunale Planung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

Chapter 1. Introduction to Smart Cities and AI. Chapter 2. Navigating the Smart City Landscape: The Power of AI in Urban Planning. Chapter 3. The Road Ahead: Toward Holistic Urban Intelligence.
Chapter 4. Knowledge governance and innovation clusters as exemplified in global smart cities: A comparative cross-regional analysis of Dubai, Los Angeles, Shanghai, and Hamburg. Chapter 5. Sustainability Logistics of Intelligent Transportation in Smart Cities: Technologies, Issues and Challenges. Chapter 6. Transportation Safety for Smart Cities. Chapter 7. Smart IoT Enabled Convolution Neural Network for classification of Garbage Disposal. Chapter 8. Privacy and Security Concerns in the Smart City. Chapter 9. Revolutionising Smart Cities with Deepstream-Powered Intelligent Video Analytics. Chapter 10. AI Model for Optimizing Automatic Transportation Systems through IoT. Chapter 11. Leveraging Artificial Intelligence and Data Analytics in Urban Planning for Enhanced Flood Resilience. Chapter 12. Smart City Data Visualization and Communication. Chapter 13. Data Privacy and Security in Smart Cities. Chapter 14. Design and Implementation of Smart Health Care Monitoring Device for Diabetes Using an IoT. Chapter 15. Internet of Things-based Fog Computing Model for Humidity Level Identification. Chapter 16. AI Sentry: Enabling Comprehensive Home Protection with 24/7 Intelligent Security Systems. Chapter 17. Architectural Design to Achieve Operational Efficiency in Smart Cities through Digital Transformation. Chapter 18. Future Directions for AI and Data Engineering in Smart Cities. Chapter 19. Smart Health- Revolutionizing the Future of Healthcare. Chapter 20. Leveraging AI, Machine Learning, and Data Engineering for CKD Management in Smart Cities. Chapter 21. Integrating Smart Tracking and Predictive Health Insights for Enhanced Medication Adherence in Smart City Ecosystems

Über Autor(innen)

Manoj Kumar M. V. is a Professor and Head of the Department of Information Science and Engineering at Nitte Meenakshi Institute of Technology, Bengaluru. He is also a Non-Resident Research Fellow at the Mohammed Bin Rashid School of Government, Dubai, and a Visiting Professor at Université Des Mascareignes, Mauritius. His research interests include Process Mining and Data Science, and he has delivered over 50 invited talks and workshops globally.

Niranjanamurthy M. is an Associate Professor (S), Department of Artificial Intelligence and Machine Learning, BMS Institute of Technology and Management, Bangalore, INDIA. His area of interest are Data Science, ML, E-Commerce, and M-Commerce related to Industry Internal tool enhancement, Web Services, Cloud Computing, and Networking.

Shiva Darshan S. L. is an Assistant Professor at the Department of Computer Science and Engineering at the National Institute of Technology Warangal (NITW). His research interests focus on cybersecurity, malware analysis, intrusion detection systems, IoT security, and AI-driven threat analytics.

Immanuel Azaad Moonesar is a Professor of Health Policy and Systems Research, Mohammed Bin Rashid School of Government, Dubai, United Arab Emirates. His research interests include well-being, mental health, healthcare workforce, IB policy, public policy, healthcare management & leadership, maternal & child health, health policy and innovation, nutrition, AI, and quality management.

Ananth Rao is an Emeritus Professor of Finance, former Dean of Dubai Business School, and former Chief Academic Officer at University of Dubai. His research focuses on Enterprise Risk Management, Corporate Finance, AI in Public Health, and more.