Automatic Container Details Identification

Problem

• Manual data entry is slow and often inaccurate. Especially during peak hours at the gates. It causes shipment delays.
• Incorrect container details disrupt real-time inventory systems and increase operational costs.
• The absence of a container number recognition system leads to inefficient processing and tracking.

Solution

We developed a computer vision in logistics solution that automatically identifies container details in real time.

• The system captures images using a high-speed camera and processes them with OCR container recognition. It is to read container and license plate data.
• Works on fast-moving containers with high accuracy.
• Allows manual correction in case of missed or false detection.
• Extract container numbers, ISO codes, operational markings, CSC plates, IMDG codes and certifications.
• Data is stored securely with access via a cloud-based portal by contributing to efficient logistics automation solutions.

Implementation Challenges

We developed a computer vision in logistics solution that automatically identifies container details in real time.

• Capturing accurate data from fast moving containers.
• Handling poor lighting, weather conditions and damaged markings.
• Integrating OCR with multiple regional formats and container types is important.
• Ensuring smooth cloud sync for centralized access.
• Aligning with gate workflow requirements for a seamless gate automation solution.

Key Features

• AI based container detection with real time OCR.
• Supports high speed recognition at entry/exit points.
• Automatic image capture and data extraction.
• Manual override option for quality control.
• Centralized cloud access for reporting and auditing.
• Scalable integration with existing gate automation solutions.