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Infant Prone Sleep Suffocation Risk Detection icon

Infant Prone Sleep Suffocation Risk Detection

AI Agent Updated 2026.08.30

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Please follow https://skillhub.cn/install/skillhub.md to install @user_15292d5a/yjkj-smyx-infant-suffocation-risk-detection-analysis

About this skill

Problem

During infant sleep, prone positioning or mouth/nose occlusion by blankets, pillows, plush toys, or other objects can create suffocation risk, especially when adult supervision is delayed. Standard baby monitor footage often requires manual review and lacks a structured way to track posture, occlusion area, risk severity, and historical events.

How It Works

This skill processes video from a fixed camera above the crib and produces a risk alert report, not a medical diagnosis.

  • Input: local mp4/avi/mov file path or public video URL, preferably under 10MB
  • Detection: infant presence, sleep posture supine/side/prone/unknown, mouth/nose occlusion, and occlusion object such as blanket/pillow/plush_toy/bedding_fold/parent_arm
  • Output: risk level low/medium/high/critical, risk_duration_sec, event_time, and snapshot_url
  • History: use --list to query cloud-stored reports and render them as a Markdown table with report name, risk level, analysis time, and link

The open-id is mandatory and must be obtained from the user; historical reports must be fetched from the cloud API rather than local memory. Use the bundled script with parameters such as --input, --url, --open-id, and --detail.

Boundaries

It is suitable as an auxiliary safety module for smart baby cameras, cribs, or daycare monitoring, prompting caregivers to check the infant promptly. The output is visual analysis only and does not replace adult supervision, medical diagnosis, or emergency response. Infant video involves minor privacy; obtain caregiver consent and store recordings securely.

Use Cases

  • Childcare product teams reviewing smart baby camera firmware need to verify whether prone sleep and mouth/nose occlusion reliably trigger graded alerts.
  • Childcare safety administrators auditing overnight monitor clips need risk-level reports that can be traced and retained.
  • Hardware solution engineers evaluating smart crib monitoring need to connect overhead video analysis and emit event time and snapshot links.
  • Care record system developers integrating cloud alert history into a front end need API data rendered as linked tables.

Best For

  • Hardware product managers building smart baby camera safety features who need posture and occlusion risk as configurable device alerts.
  • Childcare nursing supervisors responsible for overnight monitoring who need to review high-risk clips and retain alert reports.
  • Backend engineers building infant care monitoring systems who need video analysis APIs and historical report queries.
  • Embedded engineers integrating monitoring into smart cribs who need structured risk fields and snapshot data.