Data-Driven Mining, Learning and Analytics for Secured Smart Cities : Trends and Advances

Data-Driven Mining, Learning and Analytics for Secured Smart Cities : Trends and Advances edited by Chinmay Chakraborty, Jerry Chun-Wei Lin, Mamoun Alazab - First edition 2021 - 1 recurso en línea (X, 383 páginas) 93 ilustraciones, 74 ilustraciones a color - Advanced Sciences and Technologies for Security Applications 2363-9466 Computer Science (SpringerNature-11645) Computer Science (R0) (SpringerNature-43710) .

1. Smart City Ecosystem - An Introduction -- 2. Datafication for secured smart cities -- 3. Secured big data infrastructure services -- 4. Intelligent infrastructure of secured smart cities -- 5. Cyber-physical systems for secured smart cities -- 6. Blockchain for smart cities -- 7. Context-aware security and privacy of smart cities -- 7. Privacy and social Issues in smart cities -- 8. Sensor and RFID applications of smart cities -- 9. Advanced data mining for secured smart cities -- 10. Big data for secured smart cities -- 11. Data analytics tools and technologies for smart cities -- 12. Machine learning and AI for secured smart cities.

This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

9783030721398

10.1007/978-3-030-72139-8 doi


Data mining
Ciudades inteligentes

QA76.9 .D343 / 2021 EB