AI/ML-based Preventive and Reactive Emergency handling (AI-PREMSET-MCX)

The trial validated the integration of AI/ML-driven optimization with 3GPP-compliant MCX services in a realistic emergency-response environment involving 34 participants over hybrid 5G SA/NSA networks. The system met all target KPIs in areas with adequate coverage, with performance improving after optimized group deployment and scaling of microservice components. Coverage remained the most critical factor, with errors mainly observed in low-coverage zones, highlighting the need for future RAN enhancements. These results confirm the robustness of the MCX solution, its ability to adapt dynamically to network conditions, and its potential to enhance communication reliability and efficiency in PPDR scenarios, especially with further improvements in coverage and proactive resource management.