๐Ÿ”ด LIVE DETECTION

AI-Powered Factory Safety Detection

Detect PPE violations and behavioral safety risks in real-time โ€” using only your computer's webcam or a pre-recorded video file.

No edge hardware. No factory CCTV required. Just connect and detect: 4 violation types, sub-2-second latency, incident dashboard included.

Detection Feed โ€” CAM_01LIVE
no-helmet 94%
phone 87%
YOLOv8 ยท Live frame
Active Violations
No HelmetNo GlovesPhone UsageSmoke
Incidents today14
4
Violation Types
Helmet, Gloves, Smoke, Phone
>82%
Detection Accuracy
mAP@50 on helmet detection
<2s
Detection Latency
Real-time live webcam feed

Does Your Factory Have a Blind Spot?

Manual supervision can't catch every violation, every shift. These incidents happen in real factories, every day.

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Unreported PPE Violations

Supervisors can't watch every worker every second. Helmet and glove violations go unnoticed until an injury occurs.

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Hidden Fire Risks

Smoking in production zones is a critical hazard. It happens in blind spots away from supervisors.

๐Ÿ“ต

Phone Distraction

Workers distracted near heavy machinery create invisible risk. Manual spot-checks are too infrequent.

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No Incident Paper Trail

When violations happen without detection, there's no record and no data to drive corrective action.

4 Detection Use Cases

What VisionAI Detects

Each use case runs as a separate YOLO detection head โ€” all four execute simultaneously in every frame.

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PPE Violationโš ๏ธ HIGH

No Helmet

Detects workers without head protection (safety hard hat) in the detection zone.

Incident Label
โ€œPPE violation: No Helmetโ€
Confidence Threshold
0.70
YOLO Classes
person, helmet, no-helmet
Demo Scenario
Put on / remove a hard hat in front of the webcam. System flags the violation within 1โ€“2 seconds.

Key Facts

Head region tracking
SHWD + SH17 datasets
>82% mAP@50
1โ€“2s detection latency

Other Use Cases

From Setup to Incident Log in 3 Steps

No configuration, no hardware, no IT team required.

01
๐Ÿ“ท

Connect Your Input

Open the live webcam feed directly in your browser, or upload a pre-recorded MP4/AVI video file for batch processing. No special hardware required.

02
๐Ÿง 

YOLO Detection Runs

The YOLO model processes each frame in real-time, identifying persons and checking for 4 violation types simultaneously: PPE absence and behavioral incidents.

03
๐Ÿ“Š

Incidents Are Logged

Every detected violation creates an incident record: violation type, timestamp, confidence score, and a screenshot. All incidents appear instantly on the dashboard.

Two Input Modes

Detect violations live via webcam, or batch-process an uploaded video file.

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Live Webcam Detection

Open the browser, allow camera access, and detection starts immediately. Bounding boxes overlay the live feed in real-time. Violations are flagged within 1โ€“2 seconds of occurring.

  • No installation required
  • Real-time bounding box overlay
  • Sub-2-second violation flagging
  • Works with any USB or built-in webcam
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Video Upload Detection

Upload any MP4 or AVI file. The system processes it frame-by-frame, extracts all violation incidents with timestamps and screenshots, and presents the full incident log on the dashboard.

  • Supports MP4 and AVI formats
  • Frame-by-frame YOLO processing
  • All incidents extracted with timestamps
  • Ideal for reviewing past footage
Safety Report Dashboard

Every Violation. Logged. Analysed. Reported.

A built-in report dashboard gives you full visibility across all detected incidents โ€” by type, severity, shift, and time.

๐Ÿ‘๏ธ
VisionAI โ€” Safety Monitor
Factory Floor Incident Report
Today
This Week
This Month
โš ๏ธLIVE
7
Total Incidents
Today
๐Ÿ”ดLIVE
3
High Severity
Requires action
๐ŸŸ LIVE
4
Medium Severity
Monitor closely
โœ…LIVE
84%
Compliance Rate
vs 71% last week
Violations by Type
Today's breakdown
โ›‘๏ธNo Helmet
3
๐ŸงคNo Gloves
4
๐Ÿ“ฑPhone Usage
2
๐ŸšฌSmoke / Lighter
1
Incidents by Hour
Morning shift (06:00 โ€” 14:00)
06
07
08
09
10
11
12
13
High activity
Normal
Live Incident Log
Most recent first
LIVE
โ›‘๏ธ
No Helmet
09:14:32
HIGH94%
๐Ÿšฌ
Lighter Detected
09:12:07
HIGH91%
๐Ÿงค
No Gloves
09:08:45
MEDIUM79%
๐Ÿ“ฑ
Phone Usage
09:05:11
MEDIUM87%
Camera Feed
CAM_01_FLOOR_A
Shift
Morning โ€” 06:00 to 14:00
Detection Model
YOLOv8 ยท 4 classes
Avg. Confidence
87.5%
Export CSV
Download Report

Frequently Asked Questions

Don't Let Another Preventable Incident Go Undetected

Book a demo and see the detection engine running live on your own machine, in under 15 minutes.

Book a Demo โ†’Contact Us