ARTIFICIAL INTELLIGENCE AND CLOUD-BASED COLLABORATIVE PLATFORMS FOR MANAGING EMERGENCY OPERATIONS

Emergency management operations increasingly depend on cutting-edge technological solutions to support better disaster response, resource coordination, and recovery. This research uses artificial intelligence (AI) and cloud-based collaborative platforms to enhance emergency management in pre-disaster, disaster, and post-disaster phases. AI predictive abilities allow for early risk estimation, enhancing disaster forecast accuracy by 47% for wildfires and 42% for earthquakes. In emergencies, real-time data analysis and AI automated response cut response times from 12–24 hours to 2–6 hours, boosting situational awareness and resource allocation by 55%. Cloud platforms enable real-time sharing of data between emergency responders, which promotes the number of individuals contacted within the initial 48 hours by 200% and cuts down on incident costs by 60%. The research highlights a gap in AI-based decision-making systems and the scalability of the cloud, especially in developing countries. It suggests more interdisciplinary research to create standardized AI models for emergency management. The results underscore that AI and cloud platforms improve disaster response effectiveness, resource optimization, and cost savings and overcome data security, privacy, and system  integration issues.