Customer Profile

Leading Port Terminal Operator in India. Quay Cranes are used for loading/unloading of containers from the ship. While transferring the containers from the landside to the ship or vice-versa, real-time information needs to be captured on which containers are getting loaded/unloaded along with a complete container survey capturing container number, ISO code, Hazard category, Twist lock status, seal presence, latch presence, and container health. The system also needs to ensure the container's decking validation within the ship against the TOS planning module to ensure correctness.

Problem Statement

Capturing the container information including health while it is loading/unloading is a challenge due to various types of moments in the way the container is moved from pickup to drop. This poses challenges to capture the right views to provide 100% accurate inferencing of these parameters managing occlusions, sun-light, and weather conditions along with accurate positioning of the container within the ship managing the vulnerabilities of ocean tides.

Solution

The computer vision-based AI system infers all the details of the container survey along with container health and interlocking the right moment of time to capture the images using Lidar-based sensors to estimate the swing of the spreader etc. ATAI established the sensors such that there are very few movable parts and inferencing at the edge enabled to provide all the details within 10 seconds of latency. truck number and the commodity type. RTK corrected the GNSS system and machine learning algorithms to give accurate positioning of the container within the ship to validate the position against the TOS planning.

Results

This AI-based system reduces the manual checking process improves the safety of the personnel in this hazardous area and provides real-time information along with evidence.

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