A container changes several hands in its journey from the sender to the receiver—from the manufacturer's warehouse to the logistics solution provider’s storage to port authorities, and so on. Therefore, damage or pilferage at any stage of this journey is a real possibility, exposing the handling company to liabilities and reputation loss. Currently, logistics companies and port management firms have no foolproof way of proving that the damage did not happen at their end.

Currently, the arriving containers are inspected manually to check for damage or open door seals. The process is time-consuming and prone to error and dispute [for lack of incontrovertible evidence]. Claiming insurance becomes difficult as damage or pilferage responsibility is hard to establish. Moreover, the movement of container-handling equipment throughout the yard would require seamless network coverage while ensuring no breaks/disruption to generate real-time insight for the operators. These challenges result in a sub-optimal experience, with handlers even running the risk of losing business.

ContainerSight, an AI-based video analytics solution, assists logistics firms and port authorities in generating real-time insight into the condition of containers at the time of entry and exit; eliminating false claims and avoiding reputation loss.

Multiple cameras are installed at entry and exit points to capture and record data on container conditions. ContainerSight solution then analyses these live video streams running over analytical algorithms to furnish proof of container condition during entry and exit points in the facility. The data is analyzed in real-time via an application hosted over on-prem edge server. The solution assesses and reports the container condition on the following parameters: