Fall Prevention Analysis System Workflow

1. Image Input & Validation

   The system accepts image input through a local file path with comprehensive validation:

   • File existence verification
   • Size validation (max 10MB)
   • Image format verification (JPEG/PNG)
   • Content validation and preprocessing

2. Image Preprocessing

   Before analysis, the image undergoes preparation:

   • Conversion to RGB format if needed
   • Base64 encoding for API transmission
   • Metadata extraction (dimensions, format, etc.)

3. API Analysis (Primary Path)

   The system attempts analysis using Nebius AI Studio:

   • Image and detailed prompt sent to Qwen2-VL-72B-Instruct
   • Model analyzes for specific risk factors:
     • Slippery surfaces and obstacles
     • Lighting conditions
     • Structural support availability
     • Other environmental hazards
   • Response parsed for structured risk assessment

4. Local Analysis (Fallback Path)

   If API fails, basic local analysis is performed:

   • Image converted to grayscale
   • Brightness histogram analysis
   • Basic risk score calculation
   • Limited recommendations generated

5. Risk Assessment & Scoring

   The system calculates a comprehensive risk score:

   • High Risk (75): When "high risk" detected in response
   • Moderate Risk (50): Default or "moderate/medium" keywords
   • Minimal Risk (25): When "minimal risk" detected

   The scoring algorithm automatically extracts risk levels from the model's natural language response and converts them to numerical values.

6. Report Generation

   The system produces two report formats:

   • HTML Report: Visual, interactive report with:
     • Risk score visualization
     • Detailed findings by category
     • Specific recommendations
   • JSON Report: Complete technical record including:
     • System information
     • API call details
     • Raw analysis results

Error Handling Architecture

Robust error management throughout the pipeline:

• Multi-stage image validation with detailed error messages
• Graceful API failure fallback to local analysis
• Comprehensive error logging in JSON reports
• User-friendly error presentation in HTML output

Example API Prompt

Analyze this image for fall risk factors. Consider:
- Slippery surfaces (wet floors, spills)
- Uneven flooring or obstacles
- Poor lighting conditions
- Lack of handrails or support
- Other potential hazards

Provide a detailed risk assessment with specific recommendations.
Rate the overall fall risk as high, moderate, or minimal.

The prompt is carefully engineered to elicit structured responses that can be automatically parsed while allowing for natural language flexibility.

Report Design Features

The HTML report includes sophisticated elements:

• Fully responsive design with mobile optimization
• Interactive visual risk indicators
• Dark/light mode support
• Accessibility-compliant color scheme
• Print-friendly formatting