AI Centralized Image Screening System

System Overview

Disrupting the outdated model of assigning one on-site image reviewer per security lane, the system transmits baggage and parcel images from all security lanes across the station to a centralized back-end image review room. The system intelligently assigns tasks, allowing idle reviewers to remotely conduct unified image review, with AI performing initial screening and human operators conducting secondary verification. During peak hours, multiple seats collaborate to handle tasks; during off-peak hours, manpower input is reduced. Over 40% of image screening positions can be cut.

Core Capabilities

• Intelligent Task Scheduling: Real-time image transmission, automatically assigning image review tasks based on seat availability to balance manpower load
• AI Pre-screening: AI front-end screening reduces pressure on on-site image reviewers and provides foundational data support for the centralized image review model
• Remote Baggage Opening Instructions: One-click dispatch of suspicious baggage to the front-end opening station, forming a full closed loop of "AI identification — remote image review — on-site re-inspection"
• Fault Emergency Switchover: Automatic switchover to backup seats upon equipment failure to ensure business continuity
• Passenger-Baggage Association: Binds passenger facial, ID, and baggage information to achieve one-to-one correspondence between passengers and baggage

Core Value

• Brand-New Security Screening Operation Model: "Front-end Collection + Back-end Centralized Image Review"
• Full-Process Closed Loop: Intelligent identification pre-screening + manual secondary confirmation + baggage opening and re-inspection linkage, building a complete security screening chain
• Significant Staff Reduction & Efficiency Boost: Over 40% of image screening positions can be reduced, achieving "staff reduction and efficiency boost" for security personnel, balancing manpower and greatly lowering labor costs
• Overall Security Screening Efficiency Increased by 50%: Suitable for multi-lane scenarios at large hubs