International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Advancements in Wildfire Prediction and Detection: A Systematic Review

Author(s) Vinoth Kumar Kolluru, Advaitha Naidu Chintakunta, Yudhisthir Nuthakki, Sonika Koganti
Country United States
Abstract This comprehensive review provides a detailed analysis of wildfire prediction and detection research, focusing on methodologies, techniques, and challenges in wildfire management. Through a systematic examination of literature, we identify common approaches, key findings, and major challenges in the field. We explore a wide array of methodologies, including machine learning and deep learning techniques, such as decision trees, logistic regression, neural networks, and convolutional neural networks, among others. Additionally, we investigate the integration of emerging technologies like unmanned aerial vehicles (UAVs), satellite imagery, and Internet of Things (IoT) devices into wildfire management systems. The review underscores the importance of interdisciplinary collaboration and stakeholder engagement in addressing socio-ecological challenges associated with wildfires. Furthermore, we highlight the need for continued innovation, data standardization, and knowledge exchange to advance wildfire prediction and detection capabilities.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 4, Issue 6, November-December 2022
Published On 2022-12-05
Cite This Advancements in Wildfire Prediction and Detection: A Systematic Review - Vinoth Kumar Kolluru, Advaitha Naidu Chintakunta, Yudhisthir Nuthakki, Sonika Koganti - IJFMR Volume 4, Issue 6, November-December 2022.
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E-ISSN 2582-2160
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