Emergency communication infrastructures are of critical importance in disaster rescue scenarios, responsible for providing reliable connection services among victims, rescuers, and public safety command centers. Moreover, many rescue missions demand effective perception and real-time decision making, which highly rely on effective data collection and processing, and the availability of low-latency computation platforms. In this article, we propose an edge intelligence-based MCWEN to address these challenges, by leveraging edge-based technologies including edge caching, edge computing, and edge learning. In particular, MCWEN showcases a three-layer architecture, consisting of end devices, edge servers, and remote clouds. Intelligent mission cognition involves the understanding of key features of various tasks, as well as the environment and available rescue resources, and it plays an essential role in the MCWEN. We highlight edge-assisted approaches to support the key functionalities of MCWEN, including data collection, information extraction, and decision making. Typical application examples are provided to illustrate the practical significance of the proposed MCWEN framework.

中文翻译：

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用于任务认知无线应急网络的边缘智能

紧急通信基础设施在灾难救援场景中至关重要，它负责在受害者，救援人员和公共安全指挥中心之间提供可靠的连接服务。此外，许多救援任务需要有效的感知和实时决策，这高度依赖有效的数据收集和处理以及低延迟计算平台的可用性。在本文中，我们提出了一种基于边缘智能的MCWEN，以通过利用包括边缘缓存，边缘计算和边缘学习在内的基于边缘的技术来应对这些挑战。特别是，MCWEN展示了一个三层体系结构，该体系结构由终端设备，边缘服务器和远程云组成。智能任务认知涉及对各种任务的关键特征的理解，以及环境和可用的救援资源，它在MCWEN中起着至关重要的作用。我们重点介绍了边缘辅助方法来支持MCWEN的关键功能，包括数据收集，信息提取和决策。提供了典型的应用示例，以说明所提出的MCWEN框架的实际意义。