植物物联网中的声学、VOC和多模态胁迫源定位
Acoustic, VOC, and Multimodal Stress Source Localization in the Internet of Plants
AI总结：
提出一种两阶段粗到细定位流程，结合声学到达时间差多边定位和VOC弥散格林函数模型，实现植物网络中胁迫源的空间定位。
摘要：
植物物联网将分布式植物网络视为环境监测的生物传感基础设施，但胁迫源在该网络中的空间定位问题尚未解决。植物胁迫信号具有根本不同的空间动态：声发射全向传播且不受风影响，而挥发性有机化合物羽流狭窄且受平流主导。我们提出了一种针对嵌入冠层的“代理植物”网络（生物混合传感节点）的两阶段粗到细定位流程。第一阶段通过声学到达时间读数上的到达时间差多边定位定位源；第二阶段利用闭式稳态格林函数模型（VOC弥散）细化该估计。VOC信息门和逆方差融合规则根据跨试验可靠性结合两个估计，当未检测到信息性VOC信号时，优雅降级为仅TDOA估计。我们在一个新的开源数据集上评估了仅TDOA、仅VOC和融合方法，该数据集包含通过有限体积平流-扩散求解器和基于射线的声衰减模型生成的52个场景。在1到50个代理植物的网络密度下，一旦三个或更多代理处于声学范围内，TDOA多边定位实现亚米级平均绝对误差，远优于仅VOC定位（所有密度下MAE > 3米）。在大多数情况下，融合与仅TDOA估计的差异很小，且与噪声在统计上不可区分。该流程对物理参数扰动、到达时间噪声、VOC门阈值和边界半径具有鲁棒性。TDOA定位可部署于当前声学硬件，而VOC定位仍是前瞻性能力，有待紧凑型生化传感器的进展。
英文摘要：
The Internet of Plants (IoP) treats distributed plant networks as bio-sensing infrastructure for environmental monitoring, but spatial localization of stress sources within such networks remains unaddressed. Plant stress signals have fundamentally different spatial dynamics: acoustic emissions propagate omnidirectionally and independently of wind, while volatile organic compound (VOC) plumes are narrow and advection-dominated. We propose a two-stage, coarse-to-fine localization pipeline for a network of ``agent plants'' -- bio-hybrid sensing nodes embedded in the canopy. Stage 1 localizes the source via time-difference-of-arrival (TDOA) multilateration on acoustic time-of-arrival (ToA) readings; Stage 2 refines this estimate using a closed-form, steady-state Green's function model of VOC dispersion. A VOC informativeness gate and an inverse-variance fusion rule combine the two estimates according to their across-trial reliability, with graceful degradation to the TDOA-only estimate when no informative VOC signal is detected. We evaluate TDOA-only, VOC-only, and fused approaches on a new open-source dataset of 52 scenarios generated via a finite-volume advection-diffusion solver and a ray-based acoustic attenuation model. Across network densities of 1 to 50 agent plants, TDOA multilateration achieves sub-meter mean absolute error (MAE) once three or more agents are within acoustic range, far outperforming VOC-only localization (MAE $> 3$ m at all densities). Fusion differences from the TDOA-only estimate are small and statistically indistinguishable from noise in most cases. The pipeline is robust to physical parameter perturbations, ToA noise, the VOC gate threshold, and the bounding radius. TDOA localization is deployable with current acoustic hardware, whereas VOC localization remains a forward-looking capability pending advances in compact biochemical sensors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
