Toward a Smart Emergency Reserve System Using Big Data Analysis

This article explores themes surrounding artificial intelligence, knowledge management systems, knowledge capture and storage, and the application of technical systems. The research employs techniques such as long short-term memory networks and spatial analysis. The system also involves multi-departmental collaboration and data sharing, touching on facilitators and barriers to knowledge sharing. The innovation of this article lies in applying big data-driven methods to the management of emergency material reserves, shifting from experience-based to data-driven strategies, and optimizing resource allocation. Emphasizing this innovation highlights how it addresses lagging predictions and uneven distribution in traditional models. The empirical results demonstrate the system's effectiveness in demand forecasting and dynamic response, offering a meaningful contribution to the field of knowledge management.