System Hardware Validation

Overview

Before a student can access the exam environment, the platform performs a mandatory System Hardware Validation sequence. This automated pre-flight check ensures that the user's hardware and software environment meet the minimum requirements for AI-powered monitoring.

The validation process is handled within the setup phase of the exam flow, ensuring all anti-cheat signals—such as gaze tracking and audio analysis—will function correctly during the session.

Core Validation Modules

The system validates five critical categories. Each check transitions through states: pending → checking → passed or failed.

1. Browser Compatibility

The platform verifies that the student is using a modern web browser with full WebRTC support.

• Requirement: Latest versions of Chrome, Firefox, Edge, or Safari.
• Verification: Detects browser engine and version to ensure compatibility with real-time media streaming and canvas-based analysis.

2. Network Connection

A stability check is performed to ensure the exam session won't be interrupted by connectivity issues.

• Metrics: Checks for active internet connection (online status) and calculates Round Trip Time (RTT).
• Failure Condition: If the user is offline or has extremely high latency, the system prevents progression to the exam.

3. Webcam Access

Camera access is the cornerstone of the proctoring experience, enabling face-presence detection and gaze tracking.

• Process: Requests permission via navigator.mediaDevices.getUserMedia.
• Validation: Ensures the video stream is active and readable by the AI models.

4. Microphone Access

Audio monitoring is used to detect unauthorized communication or environmental anomalies.

• Audio Visualization: The setup screen provides a real-time decibel meter to confirm the microphone is picking up sound.
• Technical Detail: Uses the Web Audio API to create an AnalyserNode for frequency and volume tracking.

5. Identity Verification

The final check ensures that the student is visible and centered in the frame.

• Face Detection: The system uses canvas pixel analysis to verify that a face is present before the "Start Exam" button is enabled.
• Requirement: Adequate lighting and a clear view of the student's face.

Technical Configuration

The validation logic is structured around the SystemCheck interface, which tracks the state of each hardware component.

interface SystemCheck {
  key: string;
  label: string;
  desc: string;
  icon: React.ElementType;
  status: "pending" | "checking" | "passed" | "failed";
  errorMsg?: string;
}

Handling Permissions

If a student denies camera or microphone permissions, the system displays a failed state with a descriptive error message. The exam cannot be started until these permissions are granted via the browser's security settings.

// Example of how the system requests hardware access
const stream = await navigator.mediaDevices.getUserMedia({ 
  video: true, 
  audio: true 
});

User Experience during Validation

• Real-time Feedback: Students receive immediate visual confirmation as each check completes, indicated by green checkmarks (passed) or red warning icons (failed).
• Audio Level Monitoring: A visual waveform or bar indicates the sensitivity of the microphone, allowing students to adjust their environment before the exam starts.
• Identity Preview: A live webcam feed is displayed so the student can position themselves correctly within the proctoring frame.

Troubleshooting Common Issues

| Issue | Resolution | | :--- | :--- | | Camera Blocked | Ensure no other application (like Zoom or Teams) is using the camera. Refresh the page and click "Allow" when prompted. | | Low Audio Levels | Check the system microphone settings or ensure you are in a quiet environment with a working input device. | | Network Failure | Check your Wi-Fi or Ethernet connection. A stable connection is required to stream telemetry data to the proctoring dashboard. | | Browser Not Supported | Update your browser to the latest version or switch to a supported browser like Google Chrome. |