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

Titre:

ISBN (Numéro international normalisé des livres):

9783030721398

Edition:

1st ed. 2021.

PRODUCTION_INFO:

Cham : Springer International Publishing : Imprint: Springer, 2021.

Description physique:

X, 383 p. 93 illus., 74 illus. in color. online resource.

Collections:

Advanced Sciences and Technologies for Security Applications,

Table des matières:

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.

Extrait:

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.

Terme sujet:

Computer networks .

Data mining.

Artificial intelligence.

Security systems.

Urban policy.

Computer Communication Networks.

Data Mining and Knowledge Discovery.

Security Science and Technology.

Auteur ajouté:

Chakraborty, Chinmay.

Lin, Jerry Chun-Wei.