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Vison Detection Agent
Detect unauthorized access, perimeter breaches and operational anomalies across Critical Infrastructure environments through specialized edge visual models.
#ComputerVision #EdgeAI #CriticalInfrastructure #SmartSurveillance
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Business Challenge
Airports and critical infrastructure operators must continuously monitor sensitive areas, access points, passenger flows and operational assets with limited staff and high security requirements. Manual surveillance is difficult to scale, prone to missed events and often too slow for early intervention.
At the same time, generic video analytics are not sufficient for critical environments: false positives create operational noise, while missed detections can lead to unauthorized access, perimeter breaches, congestion, service delays or safety incidents.
Solution Overview
Vison Detection Agent is a suite of specialized visual detection models for high-criticality environments where accuracy, operational continuity and false-positive control are essential. The solution processes live video streams directly at the edge, with no image retention after analysis, in line with GDPR requirements. Images are made available only in the event of a verified alarm.
The application transforms existing camera infrastructure into an intelligent, always-on monitoring layer for security, passenger flow and operational asset visibility. It combines scenario-specific computer vision models, real-time edge inference, configurable detection settings [ST1.1]and pre-alarm zones, automated alerting, and integration with existing operational workflows.
The solution’s main scenarios, currently developed for airport environments, include:
Intrusion Detection for Critical Vehicle Gates
Detects unauthorized access attempts, wrong-direction movements and suspicious object or person transfers at secured airport perimeter gates. The solution applies vehicle and person detection, movement-direction analysis, virtual line crossing and configurable pre-alarm zones to identify abnormal behaviors before a full breach occurs. It runs on edge-based AI inference for real-time alarm generation.Tailgating Detection for Automated E-Gates
Identifies unauthorized follow-through attempts in real time, ensuring that only one person passes per authentication or boarding cycle. Person detection and multi-object tracking are correlated with gate events to count individuals crossing the controlled passage and detect multiple entries within the same validation window. Camera feeds are processed locally on edge hardware.Fence Climbing and Perimeter Breach Detection
Monitors protected barriers, fences, balustrades and restricted areas to detect climbing, jumping, scaling or circumvention attempts. Computer vision models analyze body position, trajectory, dwell time and interaction with predefined barrier zones to distinguish normal movement from breach-related behaviors. The solution runs fully on-premise on an NVIDIA [ST2.1]edge AI computer and can trigger on-site alarms through connected sirens or operator panels.People Flow Monitoring
Analyzes passenger density, movement patterns, queues and congestion in high-traffic areas. The system combines real-time people detection, counting, zone occupancy estimation and movement-flow analytics to generate live density metrics, heatmaps and threshold-based alerts for early bottleneck detection. Processing is performed on-premise at the edge and is camera-brand agnostic for RTSP-capable CCTV systems.PRM Wheelchair and Mobility Asset Tracking
Tracks the real-time location and availability of wheelchairs and mobility assets across terminal zones. High-resolution cameras feed an on-premises computer vision pipeline that detects, classifies and tracks mobility aids such as wheelchairs, buggies and transport chairs across camera handoffs. The solution runs on an NVIDIA [ST3.1]edge AI computing unit and does not require RFID tags, beacons or hardware modifications to assets.
Technical Implementation
Vison Detection Agent is deployed on local edge AI hardware connected to existing or newly installed IP/CCTV cameras. Video streams are ingested through standard protocols such as RTSP and processed or any cloud provider environment by specialized computer vision models tailored to each use case.
The solution combines object detection, classification, multi-object tracking, movement-direction analysis and zone-based event logic. Each camera view is set up with detection areas, exclusion zones, virtual lines, pre-alarm zones, confidence thresholds and escalation rules, enabling the system to distinguish normal activity from security-relevant or operationally relevant events.
The vision models are adapted to the specific operational context through fine-tuning, site calibration and rule-based event validation. Object classes, camera perspectives and alert thresholds are adjusted for each deployment to reduce false positives and improve detection reliability. This allows the same core architecture to support gate intrusion, tailgating, perimeter breach detection, crowd density monitoring and PRM asset tracking while maintaining consistent edge processing, alerting and privacy controls.
The solution is built on a modular and extensible architecture, ensuring seamless integration with existing airport systems, operational workflows, and future solution extensions.
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