AI-Assisted Urban Flood Prevention Services Decision-Making Framework With Multi-Dimensional Data Fusion via Govern-Intranet Article Swipe
Xiaohu Fan
,
Jing Zeng
,
Xuejiao Pang
,
Xiaolin Wang
,
Wei Wei
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.4018/ijwsr.375425
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.4018/ijwsr.375425
Urban flood prevention faces challenges in real-time monitoring, data integration, and decision-making support, particularly under constraints of sensitive data security and efficient emergency response. This study proposes an artificial intelligence-assisted decision-making framework for urban flood prevention, integrating multi-dimensional data fusion via an intranet. A city-level digital twin platform is developed, combining real-time sensor data, meteorological information, and social media data using a geographic information system, the Internet of Things, and artificial intelligence algorithms. The framework ensures secure data processing through intranet-based operations, enhancing flood prediction accuracy and emergency response efficiency. The system was successfully implemented in Hebi City, Henan Province, demonstrating significant improvements in flood risk management. This research advances urban resilience and provides a scientific basis for flood management in smart cities.
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Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4018/ijwsr.375425
- https://www.igi-global.com/ViewTitle.aspx?TitleId=375425&isxn=9798337315645
- OA Status
- diamond
- Cited By
- 1
- References
- 56
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410162077
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4410162077Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.4018/ijwsr.375425Digital Object Identifier
- Title
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AI-Assisted Urban Flood Prevention Services Decision-Making Framework With Multi-Dimensional Data Fusion via Govern-IntranetWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-05-07Full publication date if available
- Authors
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Xiaohu Fan, Jing Zeng, Xuejiao Pang, Xiaolin Wang, Wei WeiList of authors in order
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https://doi.org/10.4018/ijwsr.375425Publisher landing page
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https://www.igi-global.com/ViewTitle.aspx?TitleId=375425&isxn=9798337315645Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.igi-global.com/ViewTitle.aspx?TitleId=375425&isxn=9798337315645Direct OA link when available
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Computer science, Intranet, Sensor fusion, Flood myth, Data science, Data mining, World Wide Web, Artificial intelligence, The Internet, Philosophy, TheologyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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56Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Internet | 66 |
| abstract_inverted_index.accuracy | 85 |
| abstract_inverted_index.advances | 109 |
| abstract_inverted_index.platform | 47 |
| abstract_inverted_index.proposes | 26 |
| abstract_inverted_index.provides | 113 |
| abstract_inverted_index.research | 108 |
| abstract_inverted_index.response | 88 |
| abstract_inverted_index.security | 19 |
| abstract_inverted_index.support, | 12 |
| abstract_inverted_index.Province, | 99 |
| abstract_inverted_index.combining | 50 |
| abstract_inverted_index.efficient | 21 |
| abstract_inverted_index.emergency | 22, 87 |
| abstract_inverted_index.enhancing | 82 |
| abstract_inverted_index.framework | 31, 74 |
| abstract_inverted_index.intranet. | 42 |
| abstract_inverted_index.real-time | 6, 51 |
| abstract_inverted_index.response. | 23 |
| abstract_inverted_index.sensitive | 17 |
| abstract_inverted_index.artificial | 28, 70 |
| abstract_inverted_index.challenges | 4 |
| abstract_inverted_index.city-level | 44 |
| abstract_inverted_index.developed, | 49 |
| abstract_inverted_index.geographic | 62 |
| abstract_inverted_index.management | 119 |
| abstract_inverted_index.prediction | 84 |
| abstract_inverted_index.prevention | 2 |
| abstract_inverted_index.processing | 78 |
| abstract_inverted_index.resilience | 111 |
| abstract_inverted_index.scientific | 115 |
| abstract_inverted_index.algorithms. | 72 |
| abstract_inverted_index.constraints | 15 |
| abstract_inverted_index.efficiency. | 89 |
| abstract_inverted_index.implemented | 94 |
| abstract_inverted_index.information | 63 |
| abstract_inverted_index.integrating | 36 |
| abstract_inverted_index.management. | 106 |
| abstract_inverted_index.monitoring, | 7 |
| abstract_inverted_index.operations, | 81 |
| abstract_inverted_index.prevention, | 35 |
| abstract_inverted_index.significant | 101 |
| abstract_inverted_index.improvements | 102 |
| abstract_inverted_index.information, | 55 |
| abstract_inverted_index.integration, | 9 |
| abstract_inverted_index.intelligence | 71 |
| abstract_inverted_index.particularly | 13 |
| abstract_inverted_index.successfully | 93 |
| abstract_inverted_index.demonstrating | 100 |
| abstract_inverted_index.intranet-based | 80 |
| abstract_inverted_index.meteorological | 54 |
| abstract_inverted_index.decision-making | 11, 30 |
| abstract_inverted_index.multi-dimensional | 37 |
| abstract_inverted_index.intelligence-assisted | 29 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.80984162 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |