Glossary

Vision-based access control uses AI Vision to detect and enforce who can enter defined areas, especially restricted or high-risk zones.

AI Vision refers to the use of computer vision models to interpret images and video streams so organizations can automatically detect events, risks, and operational conditions in real time.

AI Vision for frontline safety delivers real-time risk detection directly to workers and supervisors.

An AI Vision platform provides the tools to build, deploy, and scale AI Vision applications across organizations.

AI safety technology uses AI Vision to automatically detect unsafe conditions and behaviors in real time.

Workplace AI applies artificial intelligence enabled computer vision (AI Vision) to improve safety, efficiency, and decision-making in industrial environments.

Real-time safety monitoring alerts notify teams when AI Vision detects unsafe conditions.

Visual analytics converts video data into measurable, actionable and timely safety and operational insights.

Anomaly detection identifies unusual or unexpected visual patterns that may indicate emerging risk.

Asset protection uses AI Vision to prevent damage to equipment and infrastructure.

Behavior-based safety focuses on identifying and addressing unsafe actions by workers to prevent incidents before they occur.

Blind spots are areas where safety risks go undetected due to limited supervision, changing shift patterns, or broken processes and procedures.

Bottleneck detection identifies congestion that reduces throughput and increases risk.

Existing camera systems are the CCTV and IP cameras already installed across industrial sites that can be leveraged for AI Vision deployments.

CCTV refers to closed-circuit television systems used to capture continuous video across industrial and commercial environments.

CCTV analytics applies AI Vision to CCTV feeds to detect safety events automatically.

CCTV footage is the video data captured by fixed cameras that AI Vision systems analyze to extract safety and operational insights.

Collision avoidance is the process of detecting and preventing impacts between people, vehicles, and equipment. Reducing collisions is especially important in environments with forklifts, yard vehicles, and heavy machinery. Early detection allows teams to intervene, adjust workflows, or redesign layouts, helping prevent injuries, asset damage, and unplanned downtime.