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Elderly Toilet Time Abnormal Detection (>30 min) | 老年人如厕时间异常（超30分钟）识别

Using a camera installed at the bathroom doorway (or inside the bathroom only detecting human silhouettes, without capturing private details), the system uses human detection and entry/exit tracking to identify when an elderly person enters or leaves the toilet and calculates the continuous occupancy time. | 通过在卫生间门口（或内部仅检测人体，不采集隐私细节）安装的摄像头，利用人体检测和进出跟踪技术，识别老年人进入和离开卫生间的时刻，计算连续占用时间。当占用时间超过预设安全阈值（默认30分钟）时，输出异常预警，通知家属或护理人员及时查看，预防老年人因跌倒、突发疾病（如中风、心梗）或体力不支导致的无法自主移动等意外。

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.3k

Updated

Oct 9, 2026

Version

1.0.13

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.3K downloads reported by the source. Last updated 10/9/2026.

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 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2.3K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.13release · observed Sep 27, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-elderly-toilet-time-abnormal-analysis

Install using `clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-elderly-toilet-time-abnormal-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/18072937735/smyx-elderly-toilet-time-abnormal-analysis before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-18072937735-smyx-elderly-toilet-time-abnormal-analysis/snapshot"

Documentation

CLAWHUB

148,321 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "smyx-elderly-toilet-time-abnormal-analysis"
description: "Using a camera installed at the bathroom doorway (or inside the bathroom only detecting human silhouettes, without capturing private details), the system uses human detection and entry/exit tracking to identify when an elderly person enters or leaves the toilet and calculates the continuous occupancy time. | 通过在卫生间门口（或内部仅检测人体，不采集隐私细节）安装的摄像头，利用人体检测和进出跟踪技术，识别老年人进入和离开卫生间的时刻，计算连续占用时间。当占用时间超过预设安全阈值（默认30分钟）时，输出异常预警，通知家属或护理人员及时查看，预防老年人因跌倒、突发疾病（如中风、心梗）或体力不支导致的无法自主移动等意外。"
version: "1.0.14"
license: "MIT-0"
---

# 🚽 Elderly Toilet Time Abnormal Detection (>30 min) | 老年人如厕时间异常（超30分钟）识别
> **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 | **老年人如厕时间异常（超30分钟）识别** |
| 🎯 核心目标 | 通过在卫生间门口（或内部仅检测人体，不采集隐私细节）安装的摄像头，利用人体检测和进出跟踪技术，识别老年人进入和离开卫生间的时刻，计算连续占用时间。当占用时间超过预设安全阈值（默认30分钟）时，输出异常预警，通知家属或护理人员及时查看，预防老年人因跌倒、突发疾病（如中风、心梗）或体力不支导致的无法自主移动等意外。 |
| 🖼️ 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_ELDERLY_TOILET_TIME_ABNORMAL_ANALYSIS` |

Using a camera installed at the bathroom doorway (or inside the bathroom only detecting human silhouettes, without capturing private details), the system uses human detection and entry/exit tracking to identify when an elderly person enters or leaves the toilet and calculates the continuous occupancy time. When occupancy exceeds a preset safety threshold (default 30 minutes), the system outputs an abnormal alert and notifies family members or caregivers to check in time, preventing accidents such as falls, sudden illness (stroke, heart attack) or exhaustion that may prevent the elderly from moving by themselves. Application scenarios: solo-living elder households, nursing homes, senior apartments. The system runs automatically; if the elderly stay in the toilet for more than 30 minutes without coming out, urgent reminders are pushed via app suggesting an on-site check. Skill features: sudden illness or falls during toileting that prevent the elderly from calling for help is a common safety risk. Automatic occupancy-time monitoring helps detect anomalies in time and gain rescue time. Can be integrated into nursing-home management systems or home-security platforms to enhance elderly safety.

通过在卫生间门口（或内部仅检测人体，不采集隐私细节）安装的摄像头，利用人体检测和进出跟踪技术，识别老年人进入和离开卫生间的时刻，计算连续占用时间。当占用时间超过预设安全阈值（默认30分钟）时，输出异常预警，通知家属或护理人员及时查看，预防老年人因跌倒、突发疾病（如中风、心梗）或体力不支导致的无法自主移动等意外。应用场景：独居老人家庭、养老院、老年公寓。系统自动监测，若老人进入卫生间超过30分钟未出，通过APP推送紧急提醒并建议上门查看。技能特点：老年人如厕时突发疾病或跌倒后无法呼救是常见安全隐患。通过自动监测停留时间，可及时发现异常，争取救援时间。该技能可集成到养老院管理系统或居家安防平台中，提升老人安全保障水平。

## 🤖 AI 角色 | AI Role
| 角色要点 | 说明 |
|---|---|
| 说明 1 | **假设你是一个专业的老年人安全监测 AI。你的任务是分析卫生间门口（或内部仅检测人体轮廓）固定摄像头的视频，检测老年人的进入和离开事件，计算每次在卫生间内的连续停留时间。当停留时间超过预设阈值（默认 30 分钟）时，输出异常预警。为保护隐私，系统可对画面进行模糊化处理，仅识别人体进出。不要提供医疗诊断或具体救援操作方案，仅输出基于人体进出的统计与预警结果。** |

## 🎬 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

基于卫生间门口/内部隐私化人体监控视频，识别老人进出事件并

_meta.json

{
  "ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
  "slug": "smyx-elderly-toilet-time-abnormal-analysis",
  "version": "1.0.13",
  "publishedAt": 1790543974438
}

references/api_doc.md

# API 接口文档

此处用于存放老年人如厕时间异常（超30分钟）识别 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` - 启动老年人如厕时间异常监测任务
2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果与异常预警
3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史如厕监护记录
4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告

## 场景代码

- `SMYX_ELDERLY_TOILET_TIME_ABNORMAL_ANALYSIS` - 老年人如厕时间异常（超30分钟）识别

## 输入约束

- 推荐摄像头安装于卫生间门口（首选）
- 如必须安装在卫生间内部，**仅检测人体轮廓**，画面建议做模糊化/像素化处理，禁止采集隐私细节
- 24 小时全天候采集（含红外夜视）
- 视频帧率建议 ≥ 10 FPS

## 关键检测事件

- `enter_toilet` - 进入卫生间事件（含时间戳）
- `exit_toilet` - 离开卫生间事件（含时间戳）
- `current_occupancy_sec` - 当前连续停留秒数
- `occupancy_session` - 完整一次停留会话（起止时间 + 持续秒数）

## 默认安全阈值（可由调用方覆盖）

- 如厕停留预警阈值：30 分钟（toilet_duration_threshold_min）
- 分级预警：
  - 20-30min → info（接近阈值）
  - 30-60min → warning（异常）
  - ≥ 60min → critical（紧急，疑似突发疾病/跌倒）

## 输出字段（参考）

- `person_detected` - 是否检测到人体
- `is_in_toilet` - 当前是否在卫生间内
- `enter_time` - 本次进入时间
- `current_duration_min` - 本次停留时长（分钟）
- `occupancy_history` - 当日如厕会话历史
- `abnormal_alert` - 是否触发停留时间异常预警
- `alert_level` - 预警等级（none / info / warning / critical）
- `alert_message` - 预警文本（如"老人已在卫生间停留 35 分钟，建议立即上门查看"）
- `suggested_contacts` - 建议通知的联系人（子女 / 护理人员 / 社区网格员）

> 仅基于人体进出与停留时长输出统计与预警，不提供医疗诊断；为保护隐私，原始画面建议在采集端做模糊化/像素化处理。

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

{}

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