PPE and safety-zone detection from your existing CCTV

The problem: safety rules depend on someone watching

Most sites already have PPE rules and CCTV cameras. What they lack is a person watching every camera all shift. Supervisors catch some violations, an audit catches others, and an incident catches the rest. In factories, warehouses and construction sites, a missed helmet or vest is a risk to a person, and a pattern of missed PPE is a risk to the business.

Computer vision can watch every feed continuously, flag a violation as it happens, and give the safety officer a daily picture of where compliance is slipping.

How it works

1. Connect to existing cameras. We use your RTSP-capable IP cameras. After a site survey, we may recommend adjusting a few angles or lighting, but a camera replacement is rarely needed.
2. Detect on the edge. A small edge computer on site runs an object detection model, so video does not have to be streamed to the cloud. See edge AI.
3. Identify PPE and zones. The model detects people and checks for helmets, high-visibility vests, gloves and masks. Virtual zones around machines, forklift lanes or edges flag unauthorised entry.
4. Confirm over time. Rules require a violation to persist across several frames before alerting, which cuts false alarms from passing glitches.
5. Alert. A short snapshot and the location go to a WhatsApp group or phone, or trigger a local siren or light for urgent zones.
6. Report. Events are logged to a dashboard with daily compliance by area, shift and type of violation.

Inputs, what the AI does, outputs

Input	What the AI does	Output
CCTV video streams	Detects people, helmets, vests, gloves, masks	PPE status per person per frame
Camera view and zone map	Checks entry into restricted or hazardous areas	Zone breach events
Repeated detections	Confirms violations over several frames	Filtered, reliable alerts
Alert rules	Sends snapshot and location to the right people	WhatsApp message or siren
Day of events	Aggregates by area, shift and type	Daily compliance dashboard

Privacy considerations

This system looks at whether PPE is worn, not who is wearing it. No face recognition is used by default. Alerts show the area and a snapshot, not an identity. If you want snapshots blurred, retained for a short period only, or limited to certain roles, we configure that. Workers should be told that the system is in use and why. Laws on workplace monitoring and personal data, including India's DPDP Act, may apply, so confirm your obligations with your adviser. See our privacy policy for how we handle data.

Integrations

The system works with standard IP cameras and NVRs, WhatsApp Business for alerts, a hooter or beacon through a relay, and your safety register or EHS tool through export or API. Dashboards are built as custom BI dashboards if you need richer reporting.

Guardrails and human review

• A person decides what to do about an alert; the system does not discipline anyone.
• Accuracy depends on camera angle, distance, lighting and clothing, so we measure it on your footage before go-live and report where it is weak.
• Alert thresholds and quiet hours are configurable to avoid alert fatigue.
• Model errors reported by the safety team are used to retrain the model.

Data you need to start

• A list of cameras with locations, and RTSP access or NVR details.
• A few days of sample footage per area, in day and night conditions.
• Your PPE rules by zone (for example, helmet and vest on the loading bay, gloves at the press).
• The people who should receive alerts, and during which shifts.

A hypothetical walkthrough

A worker enters the loading bay without a high-visibility vest. The edge device sees a person without a vest for several consecutive frames, so it raises an alert. A snapshot with the label "Loading bay 2, vest missing" arrives on the shift supervisor's WhatsApp. The supervisor walks over and corrects it. If a person steps into a marked forklift lane, a beacon at the lane entrance lights up. By evening the dashboard shows the bay had the most vest alerts during the second shift. The names and numbers are fictional.

What changes for your team day to day

Supervisors receive a handful of specific alerts instead of watching a wall of screens. The safety officer opens one daily report to decide where to run a toolbox talk. Over time, the trend by area and shift shows whether training is working, which is more useful than a count of incidents alone.

Rollout

We begin with a site survey and sample footage from your cameras. A prototype on that footage shows detection quality for your PPE types and conditions. Then we install the edge device on one or two cameras, tune alert rules with your safety team and run it in alert-only mode. Once the team trusts the alerts, we extend to more cameras and areas. Ongoing monitoring and model updates fall under an annual maintenance contract. Read more about the approach in computer vision or contact us.

Who it fits

Factories, warehouses, construction sites and plants with existing CCTV and clear PPE rules. It is an aid to your safety programme, not a replacement for supervisors or training.