Abstract: A predictive methodology for the grain and grain products market, including a robust predictor of grain-based cargo loading. The method may rely on data sources, AIS and machine learning to predict cargo operation. In some cases, grains and grain products are traded using a synonym. Synonyms have been accounted for in this method wherever available via an extensive commodity hierarchy taxonomy. The method provides benchmarking information on the basis of port calls, SOFs (statements of facts) and ullage reports to select the best berth for a grain commodity. The system and method provide for improved berth selection and facilitate quality improvements in cargo management systems. The method improves the currently available business intelligence related to cargo at berth and quality of information for shipping executives, managers, charterers and traders.

Abstract: An accurate predictive methodology for crude oil markets. Use of both technology and domain expertise to build a robust predictor of crude oil cargo (and its derivatives) loading. The method relies on a plurality data sources to verify the accuracy of the data. AIS for locating a vessel and machine learning are employed for prediction. In some cases, crude oils are traded using a synonym. Synonyms have been accounted for in this method wherever available via an extensive commodity hierarchy taxonomy. The method provides benchmarking information on basis the port calls, SOFs (statements of facts) and ullage Reports to select the best berth for a commodity. The system and method provide for improved berth selection and facilitate quality improvements in cargo management systems. The method improves the currently available business intelligence related to cargo at berth and improves quality of information or shipping executives, managers, charterers and traders.

Abstract: A system and method for determining operating characteristics of a maritime vessel by receiving AIS information, including vessel draft information, analyzing vessel location information, including analyzing the history of vessel positions at loading and discharging stations, and comparing that information to determine loading and discharging operations. Certain embodiments provide for calculating an amount of cargo using a predetermined vessel characteristic tonnes per centimeter immersion. The system and method provide for improved vessel performance metrics and facilitate quality improvements in cargo management systems.