Cargometrics Technologies, LLC

Diversified Technologies, Inc.

Robert A Weisenseel

Scott G Borgerson

James E Scully

Ronnie Hoogerwerf

Ethan E Rowe

Marcel P Gaudreau

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.

System and method for generating commodity flow information

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.

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.

Apparatus, and related method, for remotely measuring at 1east one environmental condition includes an electromagnetically resonant sensor having a measurable resonance characteristic (e.g., center resonance frequency, quality factor, or bandwidth) that varies in correspondence to changes in the environmental condition present at the sensor. The sensor emits an electromagnetic return signal representative of a state of the resonance characteristic when an electromagnetic excitation signal impinges on the sensor. The electromagnetic excitation signal is generated by a generator located separate and away from the sensor, and the excitation signal is then directed at the remote sensor. The sensor thus remotely detects and measures the environmental condition. In one embodiment, the sensor is an electromagnetically resonant electrical circuit. In another embodiment, the sensor is an antenna resonator (e.g., a half-wavelength antenna) made of a conductive material.

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Arlington, MA, United States of America

Robert A Weisenseel