BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformPractical articles on AI video analytics, Edge AI, CCTV integration, Vision Policies, deployment architecture and enterprise camera intelligence.
Adding AI to existing CCTV cameras is possible when the camera infrastructure exposes compatible streams. This guide explains the assessment, integration and deployment process.
AI video analytics converts video streams into structured detections, tracks and operational events. This article explains the technology and how it differs from traditional CCTV recording.
Edge AI processes video near the camera. Cloud analytics processes it remotely. This article explains the tradeoffs and when each approach is appropriate.
Schools and campuses can use AI video analytics for entry monitoring, restricted-zone events, crowd awareness and perimeter intelligence using compatible existing camera infrastructure.
Manufacturing environments can use AI video analytics for worker safety, restricted-zone monitoring, PPE compliance and visual quality inspection using compatible camera infrastructure.
Edge AI video analytics runs approved inference on-site or near the cameras. This article explains what it means, how BAV Edge implements it and when it is the right architectural choice.
Person detection and facial recognition are fundamentally different capabilities. This article explains the distinction and why it matters for AI video analytics deployments.
Vision Policies are the decision layer in BAV ONE that determines when a detection becomes an operational event. They combine zones, schedules, duration, severity and business rules.
AI perimeter surveillance uses virtual boundaries, object detection, tracking and Vision Policies to create operational events when configured conditions are met at a site boundary.
On-premise video analytics keeps processing local. Cloud analytics centralizes it remotely. This article compares both approaches and explains when hybrid architecture is the right choice.
Compare traditional CCTV recording with AI-enabled CCTV that applies perception, tracking, context and Vision Policies.
A practical buyer guide to assessing camera compatibility, deployment, policies, integrations and privacy for AI video analytics.
Learn how computer vision turns compatible CCTV streams into detections, tracking, context and operational events.
Understand a privacy-aware campus architecture for compatible cameras, local inference, Vision Policies and centralized operational events.
How computer vision can support PPE, restricted-area, machine-zone and vehicle interaction workflows without promising accident prevention.
Use compatible warehouse cameras for assessed loading dock, restricted-zone, vehicle, dwell and after-hours workflows.
Understand the difference between motion detection, object detection and policy-based AI intrusion events.
How virtual lines, within-camera tracks and direction rules create practical crossing events.
How detection, tracking, calibrated zones and aggregation support assessed people-counting analytics.
How a person or object, configured zone, duration and policy can create a neutral dwell event.
From visual data to enterprise intelligence
Start with a camera and workflow assessment to determine which AI video analytics workflows are suitable for your environment.
