Building a data pipeline to predict damage to ship’s cargo
in Research, Sponsoring by FleetMon HQ
We support students and researchers by offering access to the FleetMon API Suite and our extensive AIS Data Archive with historical vessel position and port call data. Read this guest article we received by Niklas Scherer, a master’s degree student of the University of Applied Sciences in Bingen, Germany.
The academic project investigates a correlation between specific weather conditions a vessel was exposed to and occurring cargo damage. AIS data and weather data were used to examine if certain weather conditions on maritime high-traffic lanes are likely to cause damage to freight in order to prevent damage by realistic forecasting.
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