基于大型语言模型的应急人机协同救援关键技术

Key Technologies for Human-machine Collaborative Rescue Based on Large Language Models

现有的应急救援指挥系统存在灾情信息分析效率低下、人机协作过程不够人性化等问题,具备较强自然语言理解能力和多模态理解能力的大型语言模型(LLM)将有望解决上述难题。通过调研LLM最新研究进展和应急救援控制领域对LLM的任务需求并进行梳理和分析,评估了现有LLM应用于应急救援领域的技术成熟度,并就灾情信息分析理解等5个任务场景探讨了可能的LLM应用构建方案和综合构建方案,对LLM技术对应急救援系统的未来发展的影响进行展望。

The existing emergency rescue systems are plagued with issues such as inefficient analysis of disaster information and a lack of humanization in the human-machine collaboration process.Large language models(LLM)with robust natural language understanding and multimodal comprehension abilities are expected to tackle the above difficult problems.By surveying the latest research progress in large models and sorting out and analyzing the mission requirements for LLM in emergency rescue and control field,the current technological maturity of LLM for application in the emergency rescue field is evaluated.The potential LLM application construction plans and a comprehensive construction plan for five task scenarios,including disaster information analysis and understanding,etc.are discussed.Finally,the future impact of LLMtechnology on the development of emergency rescue systems is prospected.