The research focused on the use of AI and secure data processing in managing the public health crisis. It proposed a Java-based system that provides predictive analytics and real-time monitoring that can support crisis responses. SQL and NoSQL databases have been implemented for the management of structured and unstructured public health data, respectively ensuring efficiency in storage and retrieval. AI-driven prediction mechanisms help analyze the crisis trends and resource allocations to make better decisions. The research has evolved involving the system’s scalable architecture and secure handling of data. This research greatly assists in developing advanced management of the public health crisis by including advanced technologies with scalable solutions.
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