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Official Verified data analysis Safety 4/5

Progress Photo Analyzer

Analyze construction site photos to track progress, detect safety issues, and compare against BIM models using computer vision.

Why use this skill?

Automate construction tracking and safety audits with the Progress Photo Analyzer. Scan site photos, track milestones, and compare against BIM models using AI.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/datadrivenconstruction/progress-photo-analyzer
Or

What This Skill Does

The Progress Photo Analyzer is a sophisticated computer vision tool integrated into the OpenClaw platform designed to streamline construction site management. By leveraging advanced AI models, this skill automatically ingests construction photos to provide real-time updates on project milestones and site safety. It moves beyond simple image storage by performing semantic analysis to identify work activities—such as foundation work, steel erection, or MEP rough-ins—while calculating estimated percentage completions. Furthermore, the tool acts as a tireless safety inspector, flagging potential hazards like missing PPE, fall risks, or scaffolding irregularities. By comparing current site imagery against BIM (Building Information Modeling) data, users can objectively verify if construction is proceeding according to the digital twin or if there are deviations that require immediate project management intervention.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal or command-line interface:

clawhub install openclaw/skills/skills/datadrivenconstruction/progress-photo-analyzer

Ensure your OpenClaw instance is updated to the latest version before installation to ensure full compatibility with the metadata schemas provided in the source repository.

Use Cases

  • Automated Daily Reporting: Transform a folder of raw site photos into a structured, data-rich progress report for project stakeholders.
  • Safety Compliance Audits: Automatically scan worker photos to ensure all personnel on-site are wearing required safety gear, reducing liability and improving site safety culture.
  • BIM Verification: Identify discrepancies between the planned 3D model and the physical site progress, catching costly errors early in the construction cycle.
  • Subcontractor Performance Tracking: Use activity detection to document when specific tasks (e.g., concrete pours) were completed for billing and scheduling verification.

Example Prompts

  1. "Analyze all photos in the 'Site_Visit_2023-10-25' folder. Create a summary of current construction progress and list any safety concerns detected."
  2. "Compare the images of the 3rd-floor structural steel against the BIM model and highlight any deviations found in the steel erection sequence."
  3. "Generate a safety incident report based on the uploaded site photos and identify the location and severity of the housekeeping issues found."

Tips & Limitations

To maximize the accuracy of the Progress Photo Analyzer, ensure that site photos are well-lit and uploaded with clear, consistent metadata regarding the zone and level of the building. The tool performs best when images are captured from consistent perspectives. Note that while the AI provides high-confidence suggestions, it is designed as a decision-support tool; significant safety hazards or construction deviations should always be verified by a qualified site engineer or safety officer. The system relies on accurate BIM model inputs; if your model is outdated or misaligned, the comparison analysis may produce false positives. Regularly calibrate your camera positions and ensure high-resolution input for the best detection metrics.

Metadata

Stars1100
Views0
Updated2026-02-17
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-datadrivenconstruction-progress-photo-analyzer": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#construction#computer-vision#bim#safety#project-management
Safety Score: 4/5

Flags: file-read