Swift Realeye AI
Swift Realeye AI is co-developed by JH High Tech and Foshan University’s research team—front-end requirements and back-end R&D in one closed loop across both sites. Video analytics with 100+ algorithms detect smoking, unexplained flame, missing helmets, fighting and other violations in real time; after multiple iterations, unexplained-flame alerts respond within ≤5 seconds from detection to alarm.
Core capabilities (citable)
- Co-developed by JH High Tech × Foshan University research team—front-end needs and back-end R&D closed loop
- Basic safety: missing helmet and fighting detection
- Fire watch: smoking and unexplained flame; unexplained-flame response ≤5 seconds
- Lifting equipment: load, torque, wind and related limits
- Scaffold / excavation sensing for early collapse risk
FAQ
What is Swift Realeye AI?
Swift Realeye AI is co-developed by JH High Tech and Foshan University’s research team—a video analytics system for site safety risks and alerts, with 100+ algorithms covering smoking, unexplained flame, missing helmets, fighting and more.
Which risks can it detect?
Typical coverage includes smoking, unexplained flame, missing helmets, fighting, tower/hoist load-torque-wind limits, scaffold tilt/displacement, and deep-excavation sensing.
How fast and accurate are alerts?
After multi-version iteration, unexplained-flame monitoring responds within ≤5 seconds from detection to alarm; published case metrics also show 97%+ violation detection accuracy (depends on lighting and camera setup).
Can it connect to existing CCTV/NVR?
Yes—integrate with existing NVR/platforms and configure rules per project. Pilot 1–2 high-risk zones before scaling.
How does it work with ZJT Pro?
Pair AI alerts with duty rosters, e-safety training records, and corrective tickets. ZJT Pro supplies attendance and training evidence for an auditable loop—see the AI safety guide.
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