The maritime container transport industry faces substantial complexity due to the involvement of numerous stakeholders and the handling of massive volumes of both container and related data. Ensuring the traceability and security of transported goods is a challenge that shipping companies and freight forwarders face every day on behalf of their end customers, the owners of the goods being transported. The use of IoT devices generates a huge amount of data about the goods, the container and its environment that needs to be processed and analysed. Therefore, to address this challenge, we conducted research on leveraging the insights offered by the IoT to gain a better understanding of the dynamics within the supply chain at the container level and all along its path through different stakeholders. We proposed an original service based on machine learning algorithms to focus on providing accurate estimates of the Expected Time of Arrival from door to door.