fire-detection-analysis
Real-time detection of flames and smoke in video and image scenes. Suitable for fire early warning in industrial parks, forests, warehouses, and other locations. | 火情烟雾检测技能,实时检测视频/图片场景中的火焰、烟雾,适用于工业园区、森林、仓库等场所火情预警
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/18072937735/smyx-fire-detection-analysisThis capability supports real-time detection of flames and smoke in video streams or images, making it suitable for high fire-risk locations such as industrial parks, forests, and warehouses. Based on color features, dynamic texture analysis, and smoke diffusion models, the system can rapidly identify early-stage fire conditions while filtering out interferences like lighting changes and steam. Once an anomaly is detected, it immediately triggers local audio-visual alarms and pushes remote warning messages, facilitating second-level discovery and rapid response to fire incidents, effectively reducing the risk of fire spread.
本技能支持对视频流或图片中的火焰、烟雾进行实时检测,适用于工业园区、森林、仓库等高火险场所。系统基于颜色特征、动态纹理与烟雾扩散模型,能够快速识别早期火情并排除光照、蒸汽等干扰。一旦检测到异常,立即触发本地声光报警并远程推送预警信息,助力实现火情的秒级发现与快速处置,有效降低火灾蔓延风险。
Fire & Smoke Detection Skill | 火情烟雾检测技能
⚠️ 强制记忆规则(最高优先级)
本技能明确约定:
- 绝对禁止读取任何本地记忆文件:包括但不限于
memory/YYYY-MM-DD.md、MEMORY.md等本地文件 - 绝对禁止从 LanceDB 长期记忆中检索信息
- 所有历史报告查询必须从云端接口获取,不得使用本地记忆中的历史数据
- 即使技能调用失败或接口异常,也不得回退到本地记忆汇总
任务目标
- 本 Skill 用于:检测图片/视频场景中的火情,识别火焰和烟雾,及时发出预警
- 能力包含:火焰检测、烟雾识别、位置标定、置信度评估、火情等级判断
- 适用场景:工业园区消防安全、森林火情监测、仓库/机房防火预警、住宅小区消防监控
- 支持检测:明火火焰、早期烟雾
- 触发条件:
- 默认触发:当用户提供监控视频/图片需要检测火情烟雾时,默认触发本技能
- 当用户明确需要火情检测、火灾预警时,提及火焰检测、烟雾识别、火情预警、火灾检测等关键词,并且上传了视频/图片
- 当用户提及以下关键词时,自动触发历史报告查询功能 :查看历史检测报告、火情检测报告清单、检测报告列表、查询历史检测报告、显示所有检测报告、火情分析报告,查询火情检测分析报告
- 自动行为:
- 如果用户上传了附件或者视频/图片文件,则自动保存到技能目录下 attachments
- ⚠️ 强制数据获取规则(次高优先级):如果用户触发任何历史报告查询关键词(如"查看所有检测报告"、"显示历史火情记录"、"
查看历史报告"等),必须:
- 直接使用
python -m scripts.fire_detection_analysis --list --open-id参数调用 API 查询云端的历史报告数据 - 严格禁止:从本地 memory 目录读取历史会话信息、严格禁止手动汇总本地记录中的报告、严格禁止从长期记忆中提取报告
- 必须统一从云端接口获取最新完整数据,然后以 Markdown 表格格式输出结果
- 直接使用
前置准备
- 依赖说明:scripts 脚本所需的依赖包及版本
requests>=2.28.0
检测要求(获得准确结果的前提)
为了获得准确的火情检测,请确保:
- 监控画面清晰,尽量覆盖容易起火的重点区域
- 避免大面积遮挡,保证疑似火源区域完整可见
- 支持白天和夜间红外监控,确保人形/火源轮廓可见
操作步骤
🔒 open-id 获取流程控制(强制执行,防止遗漏)
在执行火情检测分析前,必须按以下优先级顺序获取 open-id:
第 1 步:【最高优先级】检查技能所在目录的配置文件(优先)
路径:skills/smyx_common/scripts/config.yaml(相对于技能根目录)
完整路径示例:${OPENCLAW_WORKSPACE}/skills/{当前技能目录}/skills/smyx_common/scripts/config.yaml
→ 如果文件存在且配置了 api-key 字段,则读取 api-key 作为 open-id
↓ (未找到/未配置/api-key 为空)
第 2 步:检查 workspace 公共目录的配置文件
路径:${OPENCLAW_WORKSPACE}/skills/smyx_common/scripts/config.yaml
→ 如果文件存在且配置了 api-key 字段,则读取 api-key 作为 open-id
↓ (未找到/未配置)
第 3 步:检查用户是否在消息中明确提供了 open-id
↓ (未提供)
第 4 步:❗ 必须暂停执行,明确提示用户提供用户名或手机号作为 open-id
⚠️ 关键约束:
- 禁止自行假设,自行推导,自行生成 open-id 值(如 openclaw-control-ui、default、fire123、safety456 等)
- 禁止跳过 open-id 验证直接调用 API
- 必须在获取到有效 open-id 后才能继续执行分析
- 如果用户拒绝提供 open-id,说明用途(用于保存和查询检测报告记录),并询问是否继续
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-18072937735-smyx-fire-detection-analysis": {
"enabled": true,
"auto_update": true
}
}
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