Imagen de Portada

Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins

Guardado en:
Publicado en:Journal of Database Management vol. 36, no. 1 (2025), p. 1-30
Autor principal: Chui, Kwok Tai
Otros Autores: Singh, Sunil K., Kumar, Sudhakar, Attar, Razaz Waheeb, Alhomoud, Ahmed, Goyal, Shivam, Arya, Varsha, Gupta, Brij B.
Publicado:
IGI Global
Materias:
Visualization
Databases
Data analysis
Data collection
Twins
Machine learning
Cities
Smart cities
Data transmission
Convergence
Decision making
Artificial intelligence
Digital twins
Innovations
Urban areas
Real time
Acceso en línea:Citation/Abstract
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:The convergence of digital twin technology and data analytics continues in the area of smart cities focusing on the comprehensive study of data analysis and its visualization. It begins by standing a foundational framework for data analytics and discussing the importance of these ideas in figuring out complex patterns, concluding, and supporting thoughtful decision-making. The article emphasizes the crucial role of data analytics for urban innovation in the context of smart cities using digital twins. The study delves into the complexities of data collection, integration challenges, and innovative solutions, underscoring the necessity of constructing a robust digital twin ecosystem with a variety of sensors and data sources with its visualization. Smart recommendations by monitoring, prescriptive, and real-time analytics are becoming essential tools for vigilant urban management for taking the best and next course of action. The article delves into predictive analytics, highlighting the synergy of data streams for a comprehensive understanding of urban dynamics.
ISSN:1063-8016
1533-8010
1047-9430
DOI:10.4018/JDM.388135
Fuente:ABI/INFORM Global