AI Agents in Emergency Response Applications

• URL: http://arxiv.org/abs/2109.04646v1
• Date: Fri, 10 Sep 2021 03:24:50 GMT
• Title: AI Agents in Emergency Response Applications
• Authors: Aryan Naim, Ryan Alimo, and Jay Braun
• Abstract summary: Emergency personnel respond to various situations ranging from fire, medical, hazardous materials, industrial accidents, to natural disasters. Mission-critical "edge AI" situations require low-latency, reliable analytics. We propose an agent-based architecture for deployment of AI agents via 5G service-based architecture.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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