基于多光谱成像与边缘计算的物流安全风险预警模式及系统实现

Logistics Safety Risk Early Warning Scheme and System Implementation Based on Multispectral Imaging and Edge Computing

摘要: 物流运输过程中，环境、设备及人为风险耦合形成的复杂风险场景，对安全监管与风险预警系统的感知能力、响应效率及成本适配性提出了更高要求。针对中小物流企业在安全管理中面临的传统单光谱视频监控局限、云端处理延迟及部署维护成本过高等问题，本文提出一种基于多光谱成像与边缘计算的物流安全风险预警模式(简称：MIEC-EWS)及系统实现方案。以经济性、易用性与可靠性作为MIEC-EWS模式的核心构建原则，通过可见光与热红外双光谱的融合感知，在优化硬件成本的同时，强化复杂环境下的风险目标识别能力；依托边缘侧轻量化推理与端–边–云三层协同架构提升实时响应性能；结合云端SaaS化服务与模块化部署方案，适配中小物流企业的成本控制及运维需求。现场模拟测试验证表明，MIEC-EWS预警系统在复杂运输场景中风险识别准确率与实时性显著优于传统单光谱监控方案，且硬件成本、部署效率及运维模式均适配中小物流企业的实际需求，为中小物流企业的运输安全监管提供了一种低成本、高可靠性的系统级解决方案。

Abstract: In the process of logistics transportation, complex risk scenarios formed by the coupling of environmental, equipment, and human risks have put forward higher requirements for the perception capability, response efficiency, and cost adaptability of safety supervision and risk early warning systems. Aiming at the problems faced by small and medium-sized logistics enterprises (SMEs) in safety management, such as the limitations of traditional single-spectral video monitoring, cloud processing delay, and high deployment and maintenance costs, this paper proposes a logistics safety risk early warning mode (abbreviated as MIEC-EWS) and its system implementation scheme based on multispectral imaging and edge computing. Taking economy, usability, and reliability as the core construction principles of the MIEC-EWS mode, the scheme enhances the risk target recognition capability in complex environments while optimizing hardware costs through the fusion perception of visible light and thermal infrared dual spectra; improves real-time response performance relying on edge-side lightweight inference and the end-edge-cloud three-tier collaborative architecture; and adapts to the cost control and operation and maintenance needs of SMEs by combining cloud-based SaaS services and modular deployment solutions. Field simulation test verification shows that the MIEC-EWS early warning system is significantly superior to the traditional single-spectral monitoring scheme in terms of risk recognition accuracy and real-time performance in complex transportation scenarios. Moreover, its hardware cost, deployment efficiency, and operation and maintenance mode are all adapted to the actual needs of SMEs, providing a low-cost and high-reliability system-level solution for the transportation safety supervision of small and medium-sized logistics enterprises.