NAVA Vision AI: DockView – Computer Vision for Dock Operations FREE PoC

The NAVA Vision AI: DockView helps organizations across manufacturing, retail distribution, logistics, industrial warehousing, ports, intermodal facilities, energy plants, and construction material yards optimize loading and unloading operations using real-time computer vision.

DockView uses your existing CCTV/IP camera infrastructure to detect

• Dock door occupancy
• Trailer arrival/departure
• Loading/unloading progress
• Forklift activity patterns
• Pallet movement, and
• Dock worker safety behavior

This eliminates manual dock checks, improves dock scheduling accuracy, reduces detention and demurrage costs, and boosts throughput.

This service uses a combination of technologies including, but not limited to YOLO, Rekognition Custom Labels, SageMaker, Kinesis Video Streams, IoT Core, Lambda, and API Gateway to deliver a scalable, secure, AI-powered dock monitoring system. Optional NVIDIA Jetson or GPU-enabled edge inference supports low-latency analytics in high-traffic loading environments or remote industrial sites.

DockView integrates with WMS, YMS, TMS, ERP, dock scheduling platforms, access control systems, SCADA/DCS, and industrial operations systems, providing near real-time insights for supervisors and inbound/outbound logistics teams.

• Automated identification of loading/unloading events
• Detect forklift activity around docks for safety insights
• Reduce dwell time and increase dock throughput
• Cloud or edge inference using AWS or NVIDIA Jetson
• Integration with WMS, YMS, TMS, ERP, dock scheduling, SCADA/DCS, and more
• QuickSight dashboards for operational insights and KPI tracking

Discovery & Operations Assessment

• Review dock layout, staging areas, camera placement, trailer flow, and workflow pain points

Data Pipeline Setup

• Configure Kinesis Video Streams, S3, and Lambda for video ingestion and real-time processing

Model Development & Optimization

• Train models for dock occupancy, trailer detection, forklift & pallet movement, and load/unload activity

Deployment Options

• Cloud inference via SageMaker/Rekognition
• Edge inference using NVIDIA Jetson or GPU-enabled gateways

System Integration

• APIs for WMS, YMS, TMS, dock scheduling software, ERP, or industrial systems Dashboards & Reporting
• Dashboards for dock utilization, trailer dwell time, throughput, and safety/efficiency analytics

Testing & Validation

• Accuracy validation, environmental testing, trailer type variability, and threshold optimization
• Documentation & Knowledge Transfer
• Operational playbooks, architecture documentation, and user training

• Fully deployed DockView vision analytics pipeline
• Cloud or edge inference environment configured
• Integrated APIs for dock operations systems
• Dashboards with real-time dock analytics
• Trailer dwell & performance reports
• Operational SOPs and system documentation
• Training & knowledge-transfer workshops

• Provide access to live camera feeds or recorded footage • Provide AWS access or resource provisioning approval • Provide integration details for WMS/YMS/TMS/ERP/dock scheduling/SCADA • Provide site map, dock layout, and operations workflow details • Ensure network connectivity for camera → AWS or camera → edge inference device