AI-Driven Disaster Management: Integrating Digital Media, GIS, and IOT for Early Warning Systems
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AI-Driven Disaster Management: Integrating Digital Media, GIS, and IOT for Early Warning Systems
Dr. Hansa Rajput
Department of Computer Science and Application, Unique College, Parasia
Email: rajputhansa1991@gmail.com
Abstract
Disasters pose a significant threat to human life, infrastructure, and the environment worldwide. Traditional disaster management approaches often face limitations in timeliness, accuracy, and reach of early warnings. This paper proposes an AI-driven disaster management framework that integrates digital media, IoT sensors, and GIS mapping to enhance early warning systems and improve community resilience. The framework leverages machine learning models for predictive analysis of disaster events, using real-time sensor data collected via IoT networks, such as river water levels, seismic activity, and weather parameters. These predictions are then visualized using GIS tools, enabling authorities and communities to identify risk-prone areas efficiently. Additionally, digital media platforms and social networks are employed to disseminate alerts and awareness messages, facilitating rapid information sharing and crowd-sourced data collection from affected populations. The proposed approach not only enhances accuracy and responsiveness in disaster situations but also fosters community participation through digital engagement. Case studies on floods and cyclones demonstrate the practical applicability of the system, highlighting improvements in early detection and response times. This interdisciplinary approach bridges computer science, disaster management, and communication studies, demonstrating the potential of emerging technologies to transform disaster preparedness. The paper concludes by discussing challenges, such as data privacy, false alerts, and infrastructure constraints, while suggesting future directions including integration of drone-based monitoring and AI-enhanced decision support systems. Overall, this study provides a comprehensive framework for leveraging AI and digital technologies to mitigate disaster risks and protect vulnerable communities effectively.
Keywords: AI-driven disaster management, IoT, GIS mapping, early warning systems, predictive analytics, digital media alerts, community resilience
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