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

The use-case is related with the optimization of 3GPP-compliant Mission Critical Services (MCX) over 5G networks and beyond 1 to better handle different emergency conditions and scenarios. To this end, Nemergent Solutions (NEM) and European Emergency Number Association (EENA) propose together the AIPREMSET-MCX project. We will integrate cutting-edge technology with different preventive and reactive flavours of AI/ML algorithms applied to different control loops over information sources. The idea is to dynamically optimize MCX over broadband networks in both RAN and 5G Core domains using crime hotspot heatmaps, location of gNodeBs (provided by TrialsNet in the Romanian site), first-responder or end-users tentative initial and expected position (using SUMO tools), possible traffic demand (already a collaboration with University of Chile with track record of disaster scenario emulation), characterization of MCX traffic profiles (ongoing PhD Thesis that lacks proper testing place like the Romanian site for instance) and so forth.