Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins
Year: 2025
Type: article
Abstract: 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.
Source: Journal of Database Management
DOI: 10.4018/jdm.388135
Institutions: Panjab University, Chandigarh University, University of Petroleum and Energy Studies, Hong Kong Metropolitan University, Princess Nourah bint Abdulrahman University, Asia University, China Medical University, Korea University, Symbiosis International University, China Medical University Hospital, Northern Border University
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Award: G4721466738
OpenAlex ID: W4414147597