  Emergency personnel respond to various situations ranging from fire, medical,
hazardous materials, industrial accidents, to natural disasters. Situations
such as natural disasters or terrorist acts require a multifaceted response of
firefighters, paramedics, hazmat teams, and other agencies. Engineering AI
systems that aid emergency personnel proves to be a difficult system
engineering problem. Mission-critical "edge AI" situations require low-latency,
reliable analytics. To further add complexity, a high degree of model accuracy
is required when lives are at stake, creating a need for the deployment of
highly accurate, however computationally intensive models to
resource-constrained devices. To address all these issues, we propose an
agent-based architecture for deployment of AI agents via 5G service-based
architecture.
