Smart Port Container Number Recognition Solution

Updated: · 虹音科技 / Hongyin Tech ← Back to Applications

Container number recognition at port gates is best built on the RK3588 core board, where the core is synchronized multi-camera capture plus on-device OCR producing structured, reviewable records ready to write back. The platform pairs a 4×A76 + 4×A55 CPU with a 6TOPS NPU and accepts container, plate and box cameras at once, handling OCR, check-digit validation and plate matching, manual review and an all-in-one lane terminal, integrating with TOS and gate systems over agreed interfaces with local buffering. Hongyin Tech provides a free requirement review and complete-device customization, with selection advice within 48 hours.

Smart Port Container Number Recognition Solution solution architecture diagram

Pain Points

Recommended Hardware Configuration

SoC platformRK3588 (4×Cortex-A76 + 4×Cortex-A55); refer to the datasheet for details
AI computing power6TOPS NPU running container OCR, check-digit validation and plate recognition on-device
Memory & storageOptional LPDDR4/LPDDR5 with eMMC, caching lane images and records for resumable upload
Video inputMulti-channel MIPI CSI, GMSL and Gigabit Ethernet cameras for synchronized container, plate and box views
Network & interfacesDual Gigabit Ethernet with 4G backup; RS485 and digital I/O for barriers, loop detectors and fill lights
Enclosure & protectionSheet-metal lane terminal with anti-corrosion coating and sealing, wide-temperature and surge protection

Software Capabilities

Deliverables & Services

FAQ

Q:Should a port gate use RK3588 or RK3576 for container recognition?

Choose RK3588 when several cameras capture in sync and OCR plus plate models run locally at the same time; RK3576 can be evaluated for a single lane with fewer cameras. RK3588 is 4×A76 + 4×A55 and RK3576 is 4×A72 + 4×A53, both with a 6TOPS NPU; video input and codec capability follow the datasheet. Share lane count, camera channels and TOS interface type for advice within 48 hours.

Q:What recognition rate can be achieved, and how is performance assured?

We do not promise a fixed recognition rate: container OCR accuracy is strongly scenario-dependent and must be calibrated on site. Camera angle and focal length, lighting, code damage and distortion, vehicle position and speed all matter. The usual path is to collect a batch of real lane images for offline evaluation, then fix camera positions, lighting and trigger logic, with acceptance based on field samples both parties agree on.

Q:How are the cost and rollout timeline of a lane upgrade assessed?

Cost has four parts: camera count and model, lane terminal structure, lighting and trigger hardware, and the effort of integrating with TOS and gate systems. A single lane usually starts with prototype validation before replication, paced by site construction windows and how quickly the TOS vendor cooperates. Use the free requirement review to fix the lane list and interface documents; we then provide a line-item effort estimate without promising a fixed lead time.

Q:How does the terminal integrate with TOS, and how is salt fog handled?

Integration follows the customer's existing TOS and gate system interface specifications, supporting HTTP/MQTT, database staging tables and file drops as defined by their documents; lane records and images are cached locally and uploaded automatically after an outage. For salt fog, the enclosure uses anti-corrosion coating and sealed design, with wide-temperature and surge protection verified by whole-device testing, and industry certifications submitted as each project requires.

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