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.
翻译:自然灾害或恐怖主义行为等情况需要消防人员、护理人员、保健人员、哈兹马特小组和其他机构作出多方面的反应。援助应急人员的工程AI系统证明是一个困难的系统工程工程工程问题。任务危急的“尖端AI”情况需要低时间、可靠的分析。为了进一步增加复杂性,当生命受到威胁时,需要高度的模型准确性,这就需要将高度准确的、无论计算密集的模型部署到资源紧张的装置上。为了解决这些问题,我们建议建立一个基于代理的建筑,通过5G服务型建筑部署AI代理。