What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Greenhouse Climate Plant Feedback Analysis | 温室环境与植物状态联动调控

Using fixed cameras in a smart greenhouse to analyze plant morphology in real time (e.g., leaf wilting angle, stem uprightness, leaf color changes) combined with environmental sensors (light intensity, temperature, humidity, soil moisture), an AI decision model outputs climate control commands including irrigation (pump/solenoid valve), shade-net opening, fan/wet-curtain on-off, heater on-off, etc. | 通过智能温室中的固定摄像头实时分析植物的形态（如叶片萎蔫角度、茎秆挺直度、叶色变化）以及结合环境传感器（光照强度、温度、湿度、土壤水分），利用AI决策模型输出环境调控指令，包括灌溉（水泵/电磁阀）、遮阳网开度、风机/湿帘启停、加热器开关等。

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.7k

Updated

Oct 10, 2026

Version

1.0.12

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.7K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.7K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.12release · observed Oct 2, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17cfv2h26b7hq5w47tgfy23xx83z9x6:smyx-greenhouse-climate-plant-feedback-analysis

Install using `clawhub skill install s17cfv2h26b7hq5w47tgfy23xx83z9x6:smyx-greenhouse-climate-plant-feedback-analysis` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/smyx-sunjinhui/smyx-greenhouse-climate-plant-feedback-analysis before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-smyx-sunjinhui-smyx-greenhouse-climate-plant-feedback-a/snapshot"

Documentation

CLAWHUB

141,217 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "smyx-greenhouse-climate-plant-feedback-analysis"
description: "Using fixed cameras in a smart greenhouse to analyze plant morphology in real time (e.g., leaf wilting angle, stem uprightness, leaf color changes) combined with environmental sensors (light intensity, temperature, humidity, soil moisture), an AI decision model outputs climate control commands including irrigation (pump/solenoid valve), shade-net opening, fan/wet-curtain on-off, heater on-off, etc. | 通过智能温室中的固定摄像头实时分析植物的形态（如叶片萎蔫角度、茎秆挺直度、叶色变化）以及结合环境传感器（光照强度、温度、湿度、土壤水分），利用AI决策模型输出环境调控指令，包括灌溉（水泵/电磁阀）、遮阳网开度、风机/湿帘启停、加热器开关等。"
version: "1.0.15"
license: "MIT-0"
---

# 🏡 Greenhouse Climate Plant Feedback Analysis | 温室环境与植物状态联动调控
> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询

---

## 🧭 技能概览 | Overview

| 模块 | 内容 |
|---|---|
| 🏷️ 技能名称 | **温室环境与植物状态联动调控** |
| 🎯 核心目标 | 通过智能温室中的固定摄像头实时分析植物的形态（如叶片萎蔫角度、茎秆挺直度、叶色变化）以及结合环境传感器（光照强度、温度、湿度、土壤水分），利用AI决策模型输出环境调控指令，包括灌溉（水泵/电磁阀）、遮阳网开度、风机/湿帘启停、加热器开关等。 |
| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |
| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |
| 🧩 场景码 | `SMYX_GREENHOUSE_CLIMATE_PLANT_FEEDBACK_ANALYSIS` |

Using fixed cameras in a smart greenhouse to analyze plant morphology in real time (e.g., leaf wilting angle, stem uprightness, leaf color changes) combined with environmental sensors (light intensity, temperature, humidity, soil moisture), an AI decision model outputs climate control commands including irrigation (pump/solenoid valve), shade-net opening, fan/wet-curtain on-off, heater on-off, etc. This skill implements closed-loop control driven by plant demand, improving resource efficiency and crop yield. Application scenarios: smart greenhouses, plant factories, multi-span greenhouses. The system continuously monitors plant state and environmental parameters: when plants wilt (water shortage) and soil moisture falls below a threshold it issues an irrigation command; when light is too strong and leaves curl it issues a shading command; when temperature/humidity exceed thresholds and plants show heat stress it issues fan/wet-curtain start commands. Skill features: precision energy saving.

通过智能温室中的固定摄像头实时分析植物的形态（如叶片萎蔫角度、茎秆挺直度、叶色变化）以及结合环境传感器（光照强度、温度、湿度、土壤水分），利用AI决策模型输出环境调控指令，包括灌溉（水泵/电磁阀）、遮阳网开度、风机/湿帘启停、加热器开关等。该技能实现基于植物需求的闭环控制，提高资源利用效率和作物产量。应用场景：智能温室、植物工厂、连栋大棚。系统持续监测植物状态和环境参数，当检测到植物萎蔫（缺水）且土壤湿度低于阈值时输出灌溉指令；当光照过强导致叶片卷曲时输出遮阳指令；当温湿度超过设定阈值且植物表现出热胁迫时输出风机/湿帘启动指令。技能特点：精准节能。

## 🤖 AI 角色 | AI Role
| 角色要点 | 说明 |
|---|---|
| 说明 1 | **假设你是一个专业的温室环境智能控制 AI。你的任务是分析植物的实时图像（叶片角度、茎秆弯曲度、叶色）以及接收环境传感器数据（光照强度 lux、空气温度 ℃、相对湿度 %、土壤湿度 %），综合判断植物当前的水分、光照、温度胁迫状态，并输出相应的环境调控指令（灌溉、遮阳、风机、加热等）。不要提供具体的控制参数（如 PID 值、阀门开度百分比），仅输出动作指令及优先级（HIGH / MEDIUM / LOW）。** |

## 🎬 技能演示 | Skill Demo

[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)

---

## 🎯 任务目标 | Goals
### 1. 🧩 技能用途

基于温室固定摄像头的植物形态图像 + 可选环境传感器数据，输出闭环环境调控指令集，实现按需灌溉、遮阳、通风、加热

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 叶片萎蔫角度估算 |
| 2 | 茎秆挺直度评估 |
| 3 | 叶色变化识别（黄化/卷曲/灼烧） |
| 4 | 水分胁迫判断 |
| 5 | 光照胁迫判断 |
| 6 | 温度胁迫判断 |
| 7 | 调控指令生成（灌溉/遮阳/风机

_meta.json

{
  "ownerId": "kn7cyxkr2ymf7zwsrybpedg8xx83ywrj",
  "slug": "smyx-greenhouse-climate-plant-feedback-analysis",
  "version": "1.0.12",
  "publishedAt": 1790927981406
}

references/api_doc.md

# API 接口文档

此处用于存放温室环境与植物状态联动调控 API 的接口文档，待后续补充。

## 接口规范

- 基础地址：由 smyx_common 配置统一管理
- 认证方式：API Key 鉴权
- 响应格式：JSON

## 主要接口

1. `/web/health-analysis/v2/start-health-analysis` - 启动温室联动调控分析任务
2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果与调控指令
3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史调控记录
4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告

## 场景代码

- `SMYX_GREENHOUSE_CLIMATE_PLANT_FEEDBACK_ANALYSIS` - 温室环境与植物状态联动调控

## 输入约束

- 推荐使用温室内固定摄像头实时采集的植物冠层图像/视频（光照充足或夜间补光）
- 可选配套环境数据：光照强度 lux、空气温度 ℃、相对湿度 %、土壤湿度 %、CO₂ 浓度（ppm）
- 关键观测特征：叶片萎蔫角度、茎秆挺直度、叶色变化（黄化/卷曲/灼烧斑）

## 调控指令枚举（输出参考）

- IRRIGATE_ON / IRRIGATE_OFF - 灌溉水泵/电磁阀开关
- SHADE_OPEN / SHADE_CLOSE / SHADE_PARTIAL - 遮阳网开度
- FAN_ON / FAN_OFF - 风机启停
- WET_CURTAIN_ON / WET_CURTAIN_OFF - 湿帘启停
- HEATER_ON / HEATER_OFF - 加热器开关

> 仅输出动作指令及优先级（HIGH / MEDIUM / LOW），不输出具体 PID/开度数值。

skills/smyx_analysis/references/api_doc.md

# API接口文档

## 接口规范

- 基础地址：由 smyx_common 配置统一管理
- 认证方式：API Key 鉴权
- 请求格式：支持文件上传
- 响应格式：JSON

## 错误码说明

| 错误码 | 说明       |
|-----|----------|
| 400 | 请求参数错误   |
| 401 | API密钥无效  |
| 403 | 权限不足     |
| 413 | 文件过大     |
| 415 | 不支持的文件格式 |
| 500 | 服务器内部错误  |

scripts/config.yaml

{}

Github ReposUpdated 11h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.