Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data or based on incomplete data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vessel data for a global fleet of vessels, the digital vessel data being one or more of AIS data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vessel or a cargo. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vessels available to load at a specified port and/or deliver a cargo to a specified port, in each case within a specified period of time and generating suggestions for one or more vessels regarding future routes based on the data.

Abstract: Disclosed is method including receiving digital vessel data for a global fleet of vessels, the digital vessel data being one or more of AIS data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data, a loaded/empty status of a vessel or a cargo. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vessels available to load at a specified port and/or deliver a cargo to a specified port, in each case within a specified period of time and generating suggestions for one or more vessels regarding future routes based on the data.

Abstract: This invention provides a global strategic picture of commodity movements generated by tracking ships from satellite and other sources and then combining ship location and movement information with at least one other data set, such as vessel, port, cargo, weather, or market data. Ship positions are integrated with other data, such as vessel, port, cargo, weather, and market information, to create a global strategic picture of commodity flows. A global strategic picture may then be generated by combining (i) ship movements gathered by satellite and other sources, with (ii) vessel, port, cargo, weather, market, and other data from existing sources, and (iii) a time history of these data sets.

Abstract: This invention provides a global strategic picture of commodity movements generated by tracking ships from satellite and other sources and then combining ship location and movement information with at least one other data set, such as vessel, port, cargo, weather, or market data. Ship positions are integrated with other data, such as vessel, port, cargo, weather, and market information, to create a global strategic picture of commodity flows. A global strategic picture may then be generated by combining (i) ship movements gathered by satellite and other sources, with (ii) vessel, port, cargo, weather, market, and other data from existing sources, and (iii) a time history of these data sets.

Abstract: This invention provides a global strategic picture of commodity movements generated by tracking ships from satellite and other sources and then combining ship location and movement information with at least one other data set, such as vessel, port, cargo, weather, or market data. Ship positions are integrated with other data, such as vessel, port, cargo, weather, and market information, to create a global strategic picture of commodity flows. A global strategic picture may then be generated by combining (i) ship movements gathered by satellite and other sources, with (ii) vessel, port, cargo, weather, market, and other data from existing sources, and (iii) a time history of these data sets.

Abstract: This invention provides a global strategic picture of commodity movements generated by tracking ships from satellite and other sources and then combining ship location and movement information with at least one other data set, such as vessel, port, cargo, weather, or market data. Ship positions are integrated with other data, such as vessel, port, cargo, weather, and market information, to create a global strategic picture of commodity flows. A global strategic picture may then be generated by combining (i) ship movements gathered by satellite and other sources, with (ii) vessel, port, cargo, weather, market, and other data from existing sources, and (iii) a time history of these data sets.