ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
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CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response
Authors
J. Lavanya , Dr. K. Abhirami
Keywords
Cognitive AI, Flood Forecasting, Fire Hazard Prediction, Disaster Response, Deep Learning, IoT, Knowledge Graph, Climate Resilience.
Abstract
The frequency and severity of climate-related disasters like wildfires and floods are rising, endangering infrastructure, the environment, and human lives. Conventional emergency response and forecasting systems frequently lack flexibility, real-time intelligence, and the capacity to pick up on changing environmental patterns. The Cognitive Artificial Intelligence (AI) Framework presented in this research is intended to improve emergency response operations coordination and hazard forecasting accuracy. The suggested framework uses a hybrid architecture that combines deep learning and cognitive reasoning to integrate diverse data sources, such as satellite images, meteorological datasets, geographical information systems (GIS), and historical disaster records. The cognitive layer improves prediction accuracy and facilitates independent decision-making in catastrophe management by utilising contextual comprehension, pattern recognition, and reinforcement learning. When compared to traditional AI-based hazard models, experimental evaluations show that the suggested method greatly increases prediction accuracy and reaction efficiency. Additionally, explainable AI is supported by an adaptive knowledge graph, which guarantees the system's decision-making processes are transparent and dependable. The study demonstrates how cognitive AI's self-learning, adaptable, and intelligent reaction mechanisms have the potential to completely transform disaster predictions and management.
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IJCRT — journal style
"Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 11, page no.c614-c619, November 2025, Available :https://ijcrt.org/papers/IJCRT2511338.pdf
APA — 7th edition
Lavanya, J., & Abhirami, K. (2025). Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response. International Journal of Creative Research Thoughts, 13(11), c614-c619. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338
MLA — 9th edition
Lavanya, J., and K. Abhirami. "Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response." International Journal of Creative Research Thoughts, vol. 13, no. 11, 2025, pp. c614-c619, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338.
Chicago — 17th, bibliography
Lavanya, J., and K. Abhirami. "Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response." International Journal of Creative Research Thoughts 13, no. 11 (2025): c614-c619. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338.
Harvard — author–date
Lavanya, J. and Abhirami, K. (2025) 'Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response', International Journal of Creative Research Thoughts, 13(11), pp. c614-c619. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338
IEEE — numbered reference
J. Lavanya and K. Abhirami, "Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response," IJCRT, vol. 13, no. 11, pp. c614-c619, Nov. 2025.
Vancouver — biomedical
Lavanya J, Abhirami K. Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response. IJCRT. 2025 Nov;13(11):c614-c619.
AMA — 11th edition
Lavanya J, Abhirami K. Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response. IJCRT. 2025;13(11):c614-c619. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2511338,
author = {J. Lavanya and K. Abhirami},
title = {Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response},
journal = {International Journal of Creative Research Thoughts},
volume = {13},
number = {11},
pages = {c614-c619},
year = {2025},
month = {November},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Lavanya, J.
AU - Abhirami, K.
TI - Cognitive AI Framework For Flood And Fire Hazard Forecasting And Response
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 13
IS - 11
PY - 2025
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338
SP - c614-c619
ER -
Issue
Volume 13 Issue 11,
November-2025
Pages : c614-c619
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 13, Issue 11, November 2025
- Pages
- c614-c619
- Published
- November 2025
- Registration ID
- IJCRT_296505
- Published Paper ID
- IJCRT2511338
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Thanjavur, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 203
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2511338
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2511338.pdf
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The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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