Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins
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| Pubblicato in: | Journal of Database Management vol. 36, no. 1 (2025), p. 1-30 |
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| Autore principale: | |
| Altri autori: | , , , , , , |
| Pubblicazione: |
IGI Global
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| Soggetti: | |
| Accesso online: | Citation/Abstract Full Text - PDF |
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| 022 | |a 1063-8016 | ||
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| 024 | 7 | |a 10.4018/JDM.388135 |2 doi | |
| 035 | |a 3255275730 | ||
| 045 | 2 | |b d20250101 |b d20250331 | |
| 084 | |a 11186 |2 nlm | ||
| 100 | 1 | |a Chui, Kwok Tai |u Hong Kong Metropolitan University, Hong Kong, China | |
| 245 | 1 | |a Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins | |
| 260 | |b IGI Global |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Visualization | ||
| 653 | |a Databases | ||
| 653 | |a Data collection | ||
| 653 | |a Data analysis | ||
| 653 | |a Twins | ||
| 653 | |a Machine learning | ||
| 653 | |a Cities | ||
| 653 | |a Smart cities | ||
| 653 | |a Data transmission | ||
| 653 | |a Convergence | ||
| 653 | |a Decision making | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Digital twins | ||
| 653 | |a Innovations | ||
| 653 | |a Urban areas | ||
| 653 | |a Real time | ||
| 700 | 1 | |a Singh, Sunil K. |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India | |
| 700 | 1 | |a Kumar, Sudhakar |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India | |
| 700 | 1 | |a Attar, Razaz Waheeb |u Management Department, College of Business Administration, Princess Nourah bint Abdulrahman University, Saudi Arabia | |
| 700 | 1 | |a Alhomoud, Ahmed |u Department of Computer Science, College of Science, Northern Border University, Arar, Saudi Arabia | |
| 700 | 1 | |a Goyal, Shivam |u Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India | |
| 700 | 1 | |a Arya, Varsha |u Hong Kong Metropolitan University, Hong Kong, China & UCRD, Chandigarh University, Chandigarh, India, & Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India | |
| 700 | 1 | |a Gupta, Brij B. |u Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan, & Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan, & Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India, & School of Cybersecurity, Korea University, Seoul, South Korea | |
| 773 | 0 | |t Journal of Database Management |g vol. 36, no. 1 (2025), p. 1-30 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3255275730/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3255275730/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |