cargo-partner launches real time container tracking service
June 17, 2019: International transport and info-logistics provider cargo-partner has launched a new tracking service available via the supply chain management platform SPOT.
June 17, 2019: International transport and info-logistics provider cargo-partner has launched a new tracking service available via the supply chain management platform SPOT. The state-of-the-art technology provides users with end-to-end data.
SPOT helps cargo-partner manage all transports via air, sea and road and provide full transparency to its customers. Accessible from any web browser or as a mobile app, SPOT now allows users to track their containers in real time.
Stefan Krauter, CEO of cargo-partner, said: “We are continuously expanding our digital solutions to integrate ourselves more deeply into our customers’ supply chains. With this new tracking technology, we can offer our customers reliable end-to-end information on their seafreight transports. Thus, our clients have access to valuable data that supports their decisions on supply chain optimisation and inventory management. Meanwhile, our operations benefit from the automated system which replaces manual data entry and ensures maximum efficiency and speedy information exchange.”
The service uses data from sources like shipping schedules and status information provided by carriers, vessel location data sent via AIS, as well as port and terminal information.
Using geofencing technology, the time and place a vessel enters a certain zone are recorded. Once the vessel has departed from the port of origin, the intelligent algorithm calculates the expected dates for the upcoming milestones – transshipment, arrival, unloading etc. – and sends them to SPOT.
All further ports and stops along a container’s journey are also included in the tracking data, and milestones are continuously updated. Users can opt to be notified of any relevant changes according to their preferences. Furthermore, the new alert function enables management by exception focusing on deviations with high risk potential.
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