作为配置的角色：农业洪水的生成式利益相关者报告
Persona-as-Configuration: Generative Stakeholder Reporting for Agricultural Floods
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中文总结 AI 辅助
研究网络物理系统决策日志解读问题，提出基于单向消费和角色即配置的架构模式，实例化为上下文感知仪表板层，经专家评审在多质量维度获好评，为后续农业利益相关者最终用户评估奠定基础。
中文摘要 AI 辅助
基于确定性边缘推理构建的网络物理系统，如用于农田的车载洪水检测，会产生结构化决策日志，而异质利益相关者对此有不同解读。将此类系统与大语言模型配对生成特定于利益相关者的报告存在矛盾：生成层是非确定性的，而边缘平面必须保持可重放和可审计。我们提出一种基于两个不变量的架构模式：单向消费，即生成层是确定性平面的严格只读消费者且从不回写；角色即配置，即利益相关者适配是版本化的提示模板工件而非运行时即兴创作。我们将该模式实例化为基于先前发布的基于边缘的积水检测系统的JSON决策日志的上下文感知仪表板层，并分析集成边界如何将标准生成可靠性缓解措施作为配置或中间件级扩展点。结构化专家评审在五个与ISO/IEC 25010对齐的质量维度上对该模式给予好评，在关注点分离方面达成最强共识。计划在未来工作中对农业利益相关者进行最终用户评估。
英文摘要
Cyber-physical systems built on deterministic edge inference, such as on-vehicle flood detection for agricultural fields, produce structured decision logs that must be interpreted differently by heterogeneous stakeholders. Pairing such systems with large language models (LLMs) to generate stakeholder-specific reports introduces a tension: the generative layer is non-deterministic, while the edge plane must remain replayable and auditable. We propose an architectural pattern resting on two invariants: unidirectional consumption, in which the generative layer is a strict read-only consumer of the deterministic plane and never writes back, and persona-as-configuration, in which stakeholder adaptation is a versioned prompt-template artifact rather than runtime improvisation. We instantiate the pattern as a context-aware dashboard layer over the JSON decision logs of a previously published edge-based standing-water detection system, and analyse how the integration boundary admits standard generative-reliability mitigations as configuration- or middleware-level extension points. A structured expert review rated the pattern favourably across five ISO/IEC 25010-aligned quality dimensions, with strongest agreement on separation of concerns. End-user evaluation with agricultural stakeholders is planned for future work.
发表机构
- University of Southern Denmark（南丹麦大学）
- Maersk Mc-Kinney Moller Institute（马士基麦肯尼·莫勒研究所）
机构由 AI 辅助整理，请以论文原文为准。
