Install
openclaw skills install smyx-elderly-night-bed-exit-wandering-analysisUsing fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. It identifies bed-exit start time, total bed-exit duration, whether the person repeatedly walks back and forth in the hallway or room (wandering), and judges whether preset safety thresholds (e.g., bed-exit > 30 min or wandering > 10 min) are exceeded. Abnormal alerts are pushed to caregivers' phones or the nurse-station big screen to prevent wandering away, falls, or accidents. Application scenarios: nursing homes, home-based elderly care, community day-care centers. The system runs automatically at night; when bed-exit lasts too long or repeated wandering occurs, it pushes alerts via app or care system (e.g., 'Grandpa Zhang in bed 3 has been out of bed for 45 minutes, please check in time'). Skill features: prolonged night bed-exit (e.g., fall after getting up) and wandering (e.g., night roaming by elders with cognitive impairment) are high-risk events in elderly care. AI real-time monitoring enables timely warnings, reduces accidents, and improves caregiving efficiency. Can be integrated into nursing-home management systems or smart-home security platforms. | 通过养老院或居家卧室的固定摄像头(红外夜视),夜间连续监测老年人的离床状态和活动轨迹。识别离床开始时间、离床总时长、是否在走廊或房间内反复来回走动(徘徊),并判断是否超过预设的安全阈值(如离床>30分钟或徘徊>10分钟)。输出异常预警,可联动护理人员手机或护士站大屏,防止老人走失、跌倒或发生意外。应用场景:养老院、居家养老、社区日间照料中心。系统在夜间自动运行,当老人离床时间过长或出现反复徘徊行为时,通过APP或护理系统推送提醒(如'3号床张爷爷离床已45分钟,请及时查看')。技能特点:夜间离床时间过长(如老人下床后跌倒无法起身)和徘徊(如认知障碍老人夜间游荡)是养老院和居家养老中的高风险事件。通过AI实时监测,可及时预警,减少意外发生,提升护理效率。该技能可集成到养老院管理系统或智能家居安防平台。
openclaw skills install smyx-elderly-night-bed-exit-wandering-analysisUsing fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. It identifies bed-exit start time, total bed-exit duration, whether the person repeatedly walks back and forth in the hallway or room (wandering), and judges whether preset safety thresholds (e.g., bed-exit > 30 min or wandering > 10 min) are exceeded. Abnormal alerts are pushed to caregivers' phones or the nurse-station big screen to prevent wandering away, falls, or accidents. Application scenarios: nursing homes, home-based elderly care, community day-care centers. The system runs automatically at night; when bed-exit lasts too long or repeated wandering occurs, it pushes alerts via app or care system (e.g., 'Grandpa Zhang in bed 3 has been out of bed for 45 minutes, please check in time'). Skill features: prolonged night bed-exit (e.g., fall after getting up) and wandering (e.g., night roaming by elders with cognitive impairment) are high-risk events in elderly care. AI real-time monitoring enables timely warnings, reduces accidents, and improves caregiving efficiency. Can be integrated into nursing-home management systems or smart-home security platforms.
通过养老院或居家卧室的固定摄像头(红外夜视),夜间连续监测老年人的离床状态和活动轨迹。识别离床开始时间、离床总时长、是否在走廊或房间内反复来回走动(徘徊),并判断是否超过预设的安全阈值(如离床>30分钟或徘徊>10分钟)。输出异常预警,可联动护理人员手机或护士站大屏,防止老人走失、跌倒或发生意外。应用场景:养老院、居家养老、社区日间照料中心。系统在夜间自动运行,当老人离床时间过长或出现反复徘徊行为时,通过APP或护理系统推送提醒(如'3号床张爷爷离床已45分钟,请及时查看')。技能特点:夜间离床时间过长(如老人下床后跌倒无法起身)和徘徊(如认知障碍老人夜间游荡)是养老院和居家养老中的高风险事件。通过AI实时监测,可及时预警,减少意外发生,提升护理效率。该技能可集成到养老院管理系统或智能家居安防平台。
假设你是一个专业的老年人夜间行为安全 AI。你的任务是分析卧室或走廊摄像头的夜间视频(红外模式),检测老年人是否离开床铺,记录离床的总时长,并识别是否存在反复来回走动的徘徊行为。当离床时长超过设定阈值(如 30 分钟)或徘徊持续时间超过阈值(如 10 分钟)时,输出异常预警。不要提供医疗诊断或具体护理操作方案,仅输出行为统计与报警信息。
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --list --open-id 参数调用 API
查询云端的历史报告数据requests>=2.28.0
在执行老年人夜间离床/徘徊识别前,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:
-m scripts.smyx_elderly_night_bed_exit_wandering_analysis 处理输入(必须在技能根目录下运行脚本)--input: 本地卧室/走廊夜间监控视频文件路径--url: 网络夜间监控视频 URL 地址(API 服务自动下载)--pet-type: 类别标识,老年人夜间监护场景默认 other--open-id: 当前用户的 open-id(必填,按上述流程获取)--list: 显示老年人夜间离床/徘徊历史分析报告列表清单(可以输入起始日期参数过滤数据范围)--api-key: API 访问密钥(可选)--api-url: API 服务地址(可选,使用默认值)--detail: 输出详细程度(basic/standard/json,默认 json)--output: 结果输出文件路径(可选)夜间离床徘徊分析报告-{记录id}形式拼接, "点击查看"
列使用
[🔗 查看报告](reportImageUrl)
格式的超链接,用户点击即可直接跳转到对应的完整报告页面。| 报告名称 | 床位/被监护人 | 分析时间 | 点击查看 |
|---|---|---|---|
| 夜间离床徘徊分析报告-20260312172200001 | 3号床-张爷爷 | 2026-03-12 17:22:00 | 🔗 查看报告 |
# 分析本地夜间监控视频(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --input /path/to/night_room.mp4 --open-id your-open-id
# 分析网络夜间监控视频(以下只是示例,禁止直接使用openclaw-control-ui 作为 open-id)
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --url https://example.com/night_room.mp4 --open-id your-open-id
# 显示历史夜间监护报告/徘徊预警报告清单(自动触发关键词:查看夜间离床历史报告、徘徊预警报告清单等)
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --list --open-id your-open-id
# 输出精简报告
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --input night.mp4 --open-id your-open-id --detail basic
# 保存结果到文件
python -m scripts.smyx_elderly_night_bed_exit_wandering_analysis --input night.mp4 --open-id your-open-id --output result.json