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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: July 2026
Volume 11 | Issue 7
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Impact Factor : 8.14
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| Paper Title: | A Generative AI and Spatial Intelligence Framework for Real-Time Disaster Prediction, Risk Mapping, and Safe Zone Identification |
| Authors Name: | Palagummi Syam kumar , Dr. Suribabu Boyidi , Dr. Yalla Venkat , D Pavani Sesharatnam |
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IJRTI_213333
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| Published Paper Id: | IJRTI2606049 |
| Published In: | Volume 11 Issue 6, June-2026 |
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| Abstract: | Natural and human-induced disasters pose significant challenges to communities, often causing loss of life, property damage, and economic disruption. Traditional disaster management systems face limitations in providing accurate real-time predictions and effective emergency coordination. This research proposes a Generative AI and Spatial Intelligence Framework for Real-Time Disaster Prediction and Emergency Response that integrates advanced artificial intelligence with geospatial technologies to enhance disaster preparedness and mitigation. The framework leverages real-time data from satellite imagery, weather reports, IoT sensors, social media feeds, and historical disaster records to predict potential disaster events and assess their impact. Generative AI models analyze complex patterns and generate actionable insights, while spatial intelligence techniques provide location-based risk assessment and dynamic hazard mapping. The proposed system also supports emergency response by optimizing resource allocation, evacuation planning, and communication among rescue agencies. Real-time visualization and predictive analytics enable authorities to make informed decisions during critical situations. By combining AI-driven forecasting with geospatial analysis, the framework improves the accuracy, speed, and reliability of disaster management operations. The proposed approach aims to reduce response time, minimize losses, and enhance community resilience against natural and man-made disasters. This intelligent framework contributes to the development of smart, data-driven disaster management systems for a safer and more sustainable future. |
| Keywords: | Generative Artificial Intelligence (GenAI), Spatial Intelligence, Real-Time Disaster Prediction, Emergency Response Systems, Disaster Management, Geospatial Analytics, Geographic Information Systems (GIS), Remote Sensing, Machine Learning, Deep Learning, Predictive Analytics, Early Warning Systems, Internet of Things (IoT), Big Data Analytics, Satellite Imagery, Climate Risk Assessment, Hazard Mapping, Crisis Management, Decision Support Systems, Resource Optimization, Evacuation Planning, Smart Cities, Digital Twin Technology, Resilient Infrastructure, Situational Awareness, Risk Assessment, Humanitarian Logistics, Disaster Resilience, Multi-Hazard Monitoring, Sustainable Development. |
| Cite Article: | "A Generative AI and Spatial Intelligence Framework for Real-Time Disaster Prediction, Risk Mapping, and Safe Zone Identification", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a508-a524, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606049.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2606049
Registration ID:213333
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a508-a524 Country: Amalapuram, Andhra Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606049 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606049 |
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ISSN: 2456-3315
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