发表机构
Ifremer; IMT Atlantique（法国海洋开发研究院; IMT大西洋高等电信学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对海洋生物监测受能量等限制的问题，提出结合边缘传感与局部推理的低功耗水下监测架构，采用分层设计，利用特定嵌入、识别层及多智能体框架，经案例研究评估，实现低功耗连续传感与局部多模态智能结合，减少能耗与通信开销。
AI 中文摘要
海洋生物监测受到严格能量限制、水下连通性差以及从远程部署传输原始多模态数据成本高的限制。本文提出了一种低功耗水下监测架构，将始终开启的边缘传感与选择性高性能局部推理相结合。系统采用分层主卫星设计，超低功耗微控制器持续监测视觉和声学信号，英伟达Jetson Orin NX仅在预定处理、事件驱动分析或研究人员交互时激活。激活后，Jetson执行全局部多模态管道进行数据摄取等操作。使用BioCLIP/OpenCLIP嵌入组织数据，专用识别层支持自适应物种识别。基于LangChain的多智能体框架协调相关任务。通过视觉和声学监测案例研究评估该架构，其实现了超低功耗连续传感与局部多模态智能的结合，能产生结构化知识并压缩数据以灵活传输，减少能量使用和通信开销。
英文摘要
Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data from remote deployments. This paper proposes a low-consumption underwater monitoring architecture that combines always-on edge sensing with selective high-performance local reasoning. The system follows a hierarchical master--satellite design in which ultra-low-power MAX78000/MAX78002 microcontrollers continuously monitor visual and acoustic signals, while an NVIDIA Jetson Orin NX is activated only for scheduled processing, event-driven analysis, or researcher interaction. Once active, the Jetson executes a fully local multimodal pipeline for data ingestion, visual target extraction, embedding-based indexing, species identification, retrieval-augmented reasoning, and automated reporting. BioCLIP/OpenCLIP embeddings are used to organize mission data, marine taxonomic references, scientific documents, and operational metadata in local ChromaDB collections. A dedicated identification layer combines visual similarity search, centroid-based classification, and supervised classifiers to support adaptive species recognition. A LangChain-based multi-agent framework coordinates query routing, structured analysis, energy management, hardware reconfiguration, and report generation. The architecture is evaluated through visual and acoustic monitoring case studies. The proposed system bridges ultra-low-power continuous sensing with local multimodal intelligence, enabling underwater stations to produce structured, researcher-ready knowledge while compressing local data for flexible acoustic, optical, or satellite transmission, minimizing both energy use and communication overhead.
CommentsContains 25 pages, 11 figures. To be submitted to Elsevier Ocean Engineering
