Explain how computer vision systems detect PPE non-compliance, proximity risk and restricted-zone intrusion.
Occupational Health & Safety
Computer Vision Safety Monitoring with Worker Privacy Safeguards
Shows safety and technology teams how to deploy computer vision cameras for PPE, proximity and near-miss detection while meeting data protection duties and keeping workforce trust intact.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
A camera that can flag a missing hard hat or a forklift passing too close to a pedestrian offers a safety team continuous coverage no supervisor could match, but the same lens raises immediate questions about surveillance, consent and what happens to the footage. This course teaches safety, IT and data protection professionals how computer vision safety systems detect PPE non-compliance, restricted-zone intrusion and proximity risks between people and mobile plant, and how to deploy them without eroding workforce trust. Participants examine the technical building blocks, cameras, edge processing, detection models and alert thresholds, and learn to validate detection accuracy before relying on an alert. The course covers data protection principles and the EU AI Act's treatment of workplace monitoring systems, anonymisation techniques such as face blurring, and the workforce consultation a rollout needs before cameras go live. Sessions also address human oversight of automated alerts, monitoring for model drift as conditions change, vendor due diligence and contract terms, and how footage is retained and handled when it becomes evidence in an incident investigation. By the end, participants can run a pilot, judge whether a vendor's accuracy claims hold up on site, and govern a system that supports safety without turning into blanket surveillance.
Expected Learning Outcomes
Assess camera, edge processing and detection model choices against a site's safety monitoring needs.
Apply data protection principles and EU AI Act workplace monitoring rules to a camera deployment.
Design anonymisation and consultation measures that maintain workforce trust in a monitoring system.
Validate detection accuracy and manage false positive and false negative alert rates during a pilot.
Set human oversight and escalation procedures for alerts before automated responses are trusted.
Evaluate vendor contracts, data handling terms and footage retention rules for investigation use.
Who Should Attend
Health and safety managers evaluating computer vision systems for hazard detection.
IT and data protection officers assessing workplace monitoring technology proposals.
Operations managers in warehousing, manufacturing and logistics with mobile plant risks.
Safety technology vendors and integrators supporting workplace camera deployments.
Union and employee representatives consulted on workplace monitoring proposals.
Risk and compliance teams governing AI system use under emerging regulation.
Course Modules
Select any module to see its sessions and points.
01How Computer Vision Safety Systems Work
2 sessions · 8 points
Session 1Core Detection Use Cases for Workplace Safety
- Identify PPE compliance, proximity and restricted-zone use cases suited to computer vision detection.
- Compare fixed camera, body-worn camera and drone-based computer vision deployments for coverage.
- Map near-miss and incident data to the detection use cases most likely to reduce recurrence.
- Distinguish tasks better suited to computer vision from those still requiring human observation.
Session 2Cameras, Edge Processing and Detection Models
- Explain the roles of camera hardware, edge processing and cloud analysis in a detection pipeline.
- Assess lighting, camera angle and occlusion factors that affect detection model performance.
- Compare on-premise edge processing with cloud-based analysis for latency and data residency.
- Set alert thresholds that balance early warning against nuisance alarm frequency.
02Privacy, Data Protection and Workforce Trust
2 sessions · 8 points
Session 1Data Protection Principles and the EU AI Act
- Apply data minimisation and purpose limitation principles to workplace video monitoring.
- Assess whether a monitoring use case falls within the EU AI Act's treatment of workplace AI systems.
- Define data retention periods and access controls appropriate to safety monitoring footage.
- Document a data protection impact assessment before a camera system goes live.
Session 2Consultation, Transparency and Anonymisation
- Consult employees and their representatives before introducing a computer vision monitoring system.
- Communicate clearly what the system detects, what it ignores and who can access footage.
- Apply anonymisation techniques such as face blurring to protect identity where detection allows it.
- Set a clear boundary between safety monitoring and performance or productivity surveillance.
03Deployment, Accuracy and Governance
2 sessions · 8 points
Session 1Piloting and Validating Detection Accuracy
- Design a pilot that tests detection accuracy against real site conditions before wider rollout.
- Measure false positive and false negative rates and set acceptable thresholds with the vendor.
- Adjust camera placement and model configuration based on pilot performance data.
- Compare pilot results against existing incident and near-miss data to judge added value.
Session 2Human Oversight and Model Drift Monitoring
- Assign a named role responsible for reviewing and acting on system-generated alerts.
- Set escalation procedures that keep a human decision-maker in the loop before enforcement action.
- Monitor for model drift as site layout, lighting or work patterns change over time.
- Schedule periodic revalidation of detection accuracy rather than treating the model as fixed.
04Procurement, Integration and Investigation Use
2 sessions · 8 points
Session 1Vendor Due Diligence and Contract Terms
- Evaluate vendor claims on accuracy, bias testing and data handling before signing a contract.
- Negotiate contract terms covering data ownership, footage retention and breach notification.
- Assess total cost of ownership including cameras, licensing, storage and ongoing model tuning.
- Check vendor support for integration with existing safety and incident management systems.
Session 2Integrating Alerts and Using Footage in Investigations
- Integrate camera alerts into the existing safety management system's reporting workflow.
- Set a chain-of-custody procedure for footage used as evidence in incident investigations.
- Brief investigators on the system's limitations so footage is interpreted with appropriate caution.
- Review aggregated detection trends to target training and engineering controls where risk concentrates.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
Complete your registration
We will contact you within one business day to confirm.
Ready to start?
Reserve your seat and start building the skill.