# US 12,182,826 B1 · Apparatus and method for selection of a transport > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,182,826 B1 - Document ID: US12182826B1 - Status: Granted - Kind: B1 - Application number: 18/420,081 - Filed: 2024-01-23 - Granted: 2024-12-31 - Earliest claimed: 2024-01-23 - Assignees: Pitt-Ohio - Applicants: Pitt-Ohio - Inventors: Justine Russo; Stephen Milcoff - Web page: https://patentgrep.com/patent/US12182826B1 ## CPC - G06Q 30/018: Certifying business or products - G06Q 10/08: Logistics, e.g. warehousing, loading or distribution; Inventory or stock management - G06Q 50/40: Business processes related to the transportation industry (shipping G06Q10/083) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract An apparatus for projected carbon emissions of a transport, the apparatus including a computing device configured to receive freight data associated with a transport request, determine one or more transport configurations as a function of the freight data, wherein each transport configuration of the one or more transport configurations includes a temporal element, generate a projected carbon emission for each transport configuration of the one or more transport configurations as a function of the freight data and a carbon projection module, receive a selection of the one or more transport configurations as a function of user input, receive real carbon data associated with the freight data from one or more sensors located on one or more transport carriers as a function of the selection and transmit a carbon departure as a function of the real carbon data and the projected carbon emission to a remote device. ## Claims ### Claim 1 An apparatus for selection of a transport, the apparatus comprising: at least a processor; and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to: receive freight data associated with a transport request; determine one or more transport configurations as a function of the freight data, wherein each transport configuration of the one or more transport configurations comprises a temporal element; generate a projected carbon emission for each transport configuration of the one or more transport configurations as a function of the freight data and a carbon projection module comprising: receiving carbon projection training data from user input, wherein the carbon projection training data correlates a plurality of freight data and/or transportation configuration data to a plurality of projected carbon emission data; training, iteratively, the carbon projection module using the carbon projection training data, wherein training the carbon projection module includes retraining the carbon projection module with feedback from previous iterations of the carbon projection module; and generating the projected carbon emission for each transport configuration of the one or more transport configurations using the trained carbon projection module; receive a selection of the one or more transport configurations as a function of user input; receive real carbon data associated with the freight data from one or more sensors located on one or more transport carriers as a function of the selection; and transmit a carbon departure as a function of the real carbon data and the projected carbon emission to a remote device. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the memory further contains instructions configuring the processor to iteratively train the carbon projection module as a function of the real carbon data. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein: the one or more transport configurations comprises at least a first transport configuration and a second transport configuration; and the temporal element of the first transport configuration differs from the temporal element of the second transport configuration. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein receiving the selection of the one or more transport configurations comprises transmitting a selected transport configuration of the one or more transport configurations to a logistics provider. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein receiving the selection of the one or more transport configurations comprises: modifying a graphical user interface as a function of the one or more transport configurations and the one or more projected carbon emissions; receiving the selection of one or more transport configurations through the graphical user interface as a function of the user input. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein receiving the selection of the one or more transport configurations as a function of the user input comprises: modifying a graphical user interface as a function of the one or more transport configurations and the one or more projected carbon emissions to generate a graphical view, wherein the graphical view comprises: at least a display element generated as a function of the one or more transport configurations; and a selectable graphic corresponding to a first selectable event handler, wherein the first selectable event handler is configured to trigger a first action if the first selectable graphic is selected. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein: the freight data comprises physical attribute data; and determining the one or more transport configurations as a function of the freight data comprises comparing the physical attribute data to one or more transport thresholds. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein generating the projected carbon emission comprises: receiving a plurality of transport routes; determining a projected carbon block for each transport route of the plurality of transport routes; and generating the projected carbon emissions as a function of the plurality of projected carbon blocks. ### Claim 9 (depends on 8) The apparatus of claim 8, wherein determining the projected carbon block for each transport route comprises: receiving projected carbon training data comprising a plurality of transport routes correlated to a plurality of projected carbon blocks; training a projection machine learning model as a function of the projected carbon training data; determining the projected carbon block as a function of the projection machine learning model, wherein the projection machine learning model is iteratively trained with previous transport routes correlated to previous projected carbon blocks. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein the processor is further configured to determine one or more carbon outliers as a function of the real carbon data. ### Claim 11 A method for selection of a transport, the method comprising: receiving, by at least a processor, freight data associated with a transport request; determining, by the at least a processor, one or more transport configurations as a function of the freight data, wherein each transport configuration of the one or more transport configurations comprises a temporal element; generating, by the at least a processor, a projected carbon emission for each transport configuration of the one or more transport configurations as a function of the freight data and a carbon projection module comprising: receiving carbon projection training data from user input, wherein the carbon projection training data correlates a plurality of freight data and/or transportation configuration data to a plurality of projected carbon emission data; training, iteratively, the carbon projection module using the carbon projection training data, wherein training the carbon projection module includes retraining the carbon projection module with feedback from previous iterations of the carbon projection module; and generating the projected carbon emission for each transport configuration of the one or more transport configurations using the trained carbon projection module; receiving, by the at least a processor, a selection of the one or more transport configurations as a function of user input; receiving, by the at least a processor, real carbon data associated with the freight data from one or more sensors located on one or more transport carriers as a function of the selection; and transmitting, by the at least a processor, a carbon departure as a function of the real carbon data and the projected carbon emission to a remote device. ### Claim 12 (depends on 11) The method of claim 11, further comprising, iteratively training, by the at least a processor, the carbon projection module as a function of the real carbon data. ### Claim 13 (depends on 11) The method of claim 11, wherein: the one or more transport configurations comprises at least a first transport configuration and a second transport configuration; and the temporal element of the first transport configuration differs from the temporal element of the second transport configuration. ### Claim 14 (depends on 11) The method of claim 11, wherein receiving, by the at least a processor, the selection of the one or more transport configurations comprises transmitting, by the at least a processor, a selected transport configuration of the one or more transport configurations to a logistics provider. ### Claim 15 (depends on 11) The method of claim 11, wherein receiving, by the at least a processor, the selection of the one or more transport configurations comprises: modifying a graphical user interface as a function of the one or more transport configurations and the one or more projected carbon emissions; and receiving, by the at least a processor, a selection of one or more transport configurations through the graphical user interface as a function of the user input. ### Claim 16 (depends on 11) The method of claim 11, wherein receiving, by the at least a processor, the selection of the one or more transport configurations as a function of the user input comprises: modifying a graphical user interface as a function of the one or more transport configurations and the one or more projected carbon emissions to generate a graphical view, wherein the graphical view comprises: at least a display element generated as a function of the one or more transport configurations; and a selectable graphic corresponding to a first selectable event handler, wherein the first selectable event handler is configured to trigger a first action if the first selectable graphic is selected. ### Claim 17 (depends on 11) The method of claim 11, wherein: the freight data comprises physical attribute data; and determining, by the at least a processor, the one or more transport configurations as a function of the freight data comprises comparing the physical attribute data to one or more transport thresholds. ### Claim 18 (depends on 11) The method of claim 11, wherein generating, by the at least a processor, the projected carbon emission comprises: receiving a plurality of transport routes; determining a projected carbon block for each transport route of the plurality of transport routes; and generating the projected carbon emissions as a function of the plurality of projected carbon blocks. ### Claim 19 (depends on 18) The method of claim 18, wherein determining, by the at least a processor, the projected carbon block for each transport route comprises: receiving, projected carbon training data comprising a plurality of transport routes correlated to a plurality of projected carbon blocks; training a projection machine learning model as a function of the projected carbon training data; determining, by the at least a processor, the projected carbon block as a function of the projection machine learning model, wherein the projection machine learning model is iteratively trained with previous transport routes correlated to previous projected carbon blocks. ### Claim 20 (depends on 11) The method of claim 11, further comprising determining, by the at least a processor, one or more carbon outliers as a function of the real carbon data.