AEMS-Sim-Repro: Synthetic Dataset for Analytical and PoC Simulation of AI-Based Emergency Bed Matching System

This dataset provides a fully synthetic data collection used for the analytical and proof-of-concept (PoC) validation of the AI-Based Emergency Bed Matching System (AEMS).It includes four core tables: hospital profiles, emergency incidents, bed-capacity time series, and travel-time matrices.The data were generated to emulate realistic emergency-medical-service (EMS) conditions while containing no personally identifiable information (PII).Each record reflects the operational parameters described in Section 4.4 of the corresponding IEEE Access manuscript, including the assumed hospital acceptance probability (p = 0.4), mean response delay (1\/\u03bc = 30 s), and mean travel time (~12\u201313 min).The dataset can be used to replicate analytical simulations of time-to-accept, call-to-arrival performance, and resource-allocation efficiency.All files are provided in CSV format and accompanied by a YAML configuration file defining the simulation parameters.This dataset is intended for research on AI-driven hospital coordination, emergency response modeling, and healthcare resource optimization.