AI USE CASE
AI Safety Monitoring for Construction Sites
Automatically detect PPE violations and hazards on construction sites using computer vision.
What it is
Computer vision models analyse live camera feeds across construction sites to detect missing PPE, unsafe proximity to machinery, and other safety violations in real time. Automated reporting replaces manual safety walkthroughs, saving 5–10 hours per site per week. Over time, incident trend data feeds continuous improvement programmes and demonstrates compliance to regulators.
Data you need
Live or recorded video feeds from CCTV or IP cameras covering key site areas, with sufficient resolution to identify PPE and personnel.
Required systems
- none
Why it works
- Conduct a camera audit before deployment to ensure coverage, angle, and resolution meet model requirements.
- Tune alert thresholds iteratively during a pilot phase to balance sensitivity and false-positive rate.
- Communicate the programme to workers as a safety tool, not a disciplinary surveillance measure.
- Integrate alerts into existing site communication tools (e.g. radio, mobile app) for fast response.
How this goes wrong
- Poor camera placement or low-resolution footage leads to high false-negative rates for violations.
- Alert fatigue sets in when false positives are too frequent, causing safety managers to ignore notifications.
- Model performance degrades in varying light conditions, bad weather, or cluttered site environments.
- Resistance from workers and unions over perceived surveillance undermines adoption and trust.
When NOT to do this
Do not deploy this system on a site with fewer than 4–6 well-positioned cameras, as insufficient visual coverage produces unreliable alerts and erodes confidence in the tool.
Example vendors
This page describes an idea. It gives no budget or timeline: those depend on your company. The free diagnostic tells you which ideas fit your situation.