详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Syed Mhamudul Hasan, Anas AlSobeh, Hussein Zangoti, Abdur R. Shahid
- 文章类型
- PAPER
- 语言
- en
- 发布日期
- 2026-07-29
摘要
arXiv:2607.26042v1 Announce Type: new Abstract: We present VetClaw, an edge-cloud multimodal agentic system for early veterinary disease screening. VetClaw uses a camera module as an edge sensing device and sends captured images, together with optional symptom descriptions, to a server-hosted vision-language model for zero-shot disease classification. The system separates agent interaction from workflow orchestration: OpenClaw provides scheduling, tool access, user interaction, and notification services on the edge device, while LangGraph manages the stateful screening workflow, including input validation, image transmission, model invocation, safety checks, conditional routing, failure handling, and structured logging. This design moves beyond static image classification by enabling the system to collect visual evidence, invoke external models, apply deterministic safety rules, and generate diagnostic-support alerts.