Granted Patent B2

US 12,748,676 · App. 18/678,511 · Granted Sep 29, 2026

Inventors: Melissa E. Murphy (Weehawken, NJ); Terhan Yong (Woodside, NY); Richard L. Peterson, II (Brewster, NY)

Assignee: Delphi Technology Solutions, Corp.

G06F11/3438G06F11/3051G06F16/908

Abstract

Claims (78)

1 . A computer-implemented method for digital twin-based asset management, comprising:

receiving, from a user application of a user device associated with a user, a data set, the data set comprising at least one of: one or more details associated with the user received from a user interface of the user application, and one or more records associated with the user retrieved from the user device;

parsing and sorting the data by topic, and identifying, from sorted data, using at least one multi-dimensional clustering technique, at least one data attribute associated with the user;

constructing, from the at least one data attribute, at least one non-fungible data token (NFDT) associated with the at least one data attribute;

constructing, from the at least one data attribute and at least one other data attribute, a digital twin comprising a personal non-fungible data token (PNFDT) associated with the user;

presenting at least one of the at least one NFDT and the PNFDT to the user via the user application, and receiving a user authorization; and

after receiving the user authorization, accessing a digital marketplace based on the at least one of the at least one NFDT and the PNFDT, and performing at least one transaction, comprising one of:

selling data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace; and

searching the digital marketplace for data matching the at least one of the at least one NFDT and the PNFDT, and determining a reconstruction cost for the at least one of the at least one NFDT and the PNFDT.

2 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace, wherein selling the data comprises:

listing the data for sale on the digital marketplace in an open auction; and

receiving a plurality of bids in the open auction.

3 . The computer-implemented method according to claim 2 , wherein receiving the plurality of bids in the open auction further comprises:

upon receiving a bid in the plurality of bids, automatically checking a credential of a bidding party.

4 . The computer-implemented method according to claim 2 , wherein selling the data further comprises:

prior to receiving the plurality of bids, receiving an application from a prospective bidding party;

conducting reputation mining of the prospective bidding party; and

making a determination of whether the application of the prospective bidding party should be approved, forwarded, or vetoed based on a result of the reputation mining.

5 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on a plurality of digital marketplaces, wherein selling the data comprises:

listing a first portion of the data for sale on a first digital marketplace in a first open auction, and requiring authentication of bidders in the first digital marketplace; and

listing a second portion of the data for sale on a second digital marketplace in a second open auction without requiring authentication of bidders in the second digital marketplace.

6 . The computer-implemented method according to claim 5 , further comprising:

separating the data into the first portion and the second portion by at least one of data type or data source.

7 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on a digital marketplace in a plurality of digital marketplaces, wherein selling the data comprises:

determining, from the data, a location of the user; and

selectively enabling access to the digital marketplace and selectively disabling access to at least one other digital marketplace in the plurality of digital marketplaces based on the location of the user.

8 . The computer-implemented method according to claim 7 , wherein determining, from the data, the location of the user comprises at least one of:

determining citizenship information associated with a profile of the user;

determining current GPS information from the user device; and

identifying the location from a search history of the user.

9 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace, wherein selling the data comprises:

listing the data for sale on the digital marketplace;

receiving transaction requests from a plurality of prospective buyers including a first buyer having a first reputation score above a threshold and a second buyer having a second reputation score below the threshold; and

imposing a confirmation delay requirement on the second buyer.

10 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace in aggregate with a plurality of instances of other data, wherein selling the data comprises:

aggregating the data with the plurality of instances of other data into aggregated data, comprising removing personally identifying information from the aggregated data;

listing the aggregated data for sale on the digital marketplace;

receiving a transaction request from a prospective buyer;

performing a first validation transaction comprising providing the data to the prospective buyer; and

after completing the first validation transaction, providing a remainder of the aggregated data to the prospective buyer.

11 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes selling the data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace, wherein receiving the user authorization comprises:

receiving, from a user application, uploaded data;

receiving, from a user application, a selection of data for sale including at least the uploaded data; and

receiving, from the user application, at least one opt-out request excluding other data from the selection of data for sale.

12 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes searching the digital marketplace to determine the reconstruction cost, wherein searching the digital marketplace to determine the reconstruction cost comprises:

identifying a first instance of at least one marketplace trade for information matching the at least one of the at least one NFDT and the PNFDT;

identifying a second instance of at least one marketplace trade for information matching the at least one of the at least one NFDT and the PNFDT; and

identifying the reconstruction cost based on a lower of a cost of the first instance and a cost of the second instance.

13 . The computer-implemented method according to claim 12 , further comprising identifying a certainty level associated with each of the first instance and the second instance.

14 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes searching the digital marketplace to determine the reconstruction cost, wherein searching the digital marketplace to determine the reconstruction cost comprises:

identifying at least one marketplace trade for first information matching the at least one of the at least one NFDT and the PNFDT;

identifying at least one other marketplace trade for second information, and determining that the first information can be derived from the second information;

identifying the reconstruction cost based on a lower of a cost of the at least one marketplace trade and a cost of the at least one other marketplace trade.

15 . The computer-implemented method according to claim 1 , wherein the at least one transaction includes searching the digital marketplace to determine the reconstruction cost, further comprising:

after determining the reconstruction cost, causing the user device to display a visualization of a plurality of marketplace trades for replicating the at least one of the at least one NFDT and the PNFDT.

16 . The computer-implemented method according to claim 1 , wherein the digital twin further includes at least one interrelationship with at least one other digital twin, the digital twin and the at least one other digital twin arranged in a network of digital twins; and

wherein the method includes performing analysis including the at least one transaction on the network of digital twins.

17 . The computer-implemented method according to claim 1 , wherein the at least one data attribute includes at least two data attributes, wherein the at least one NFDT is at least three NFDTs based on the at least two data attributes, wherein the at least three NFDTs include a first NFDT corresponding to a first data attribute, a second NFDT corresponding to a second data attribute, and a third NFDT corresponding to an association between the first data attribute and the second data attribute.

18 . The computer-implemented method according to claim 1 , wherein the at least one NFDT is at least two NFDTs including at least a first NFDT corresponding to a first alias of the user and a second NFDT corresponding to a second alias of the user; and

wherein the at least one transaction includes searching the digital marketplace to determine the reconstruction cost associated with the first NFDT and a different reconstruction cost associated with the second NFDT.

19 . A non-transitory computer-readable medium comprising program code that, when executed, causes a server comprising a network connection and configured to communicate with a user device to carry out steps of:

receiving, from a user application of a user device associated with a user, a data set, the data set comprising at least one of: one or more details associated with the user received from a user interface of the user application, and one or more records associated with the user retrieved from the user device;

parsing and sorting the data by topic, and identifying, from sorted data, using at least one multi-dimensional clustering technique, at least one data attribute associated with the user;

constructing, from the at least one data attribute, at least one non-fungible data token (NFDT) associated with the at least one data attribute;

constructing, from the at least one data attribute and at least one other data attribute, a digital twin comprising a personal non-fungible data token (PNFDT) associated with the user;

presenting at least one of the at least one NFDT and the PNFDT to the user via the user application, and receiving a user authorization; and

after receiving the user authorization, accessing a digital marketplace based on the at least one of the at least one NFDT and the PNFDT, and performing at least one transaction, comprising one of:

selling data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace; and

searching the digital marketplace for data matching the at least one of the at least one NFDT and the PNFDT, and determining a reconstruction cost for the at least one of the at least one NFDT and the PNFDT.

20 . A system for digital twin-based asset management, comprising a server comprising a processor, a memory, and a network connection, the server configured to communicate with a user device via the network connection to carry out steps of:

receiving, from a user application of the user device associated with a user, a data set, the data set comprising at least one of: one or more details associated with the user received from a user interface of the user application, and one or more records associated with the user retrieved from the user device;

parsing and sorting the data by topic, and identifying, from sorted data, using at least one multi-dimensional clustering technique, at least one data attribute associated with the user;

constructing, from the at least one data attribute, at least one non-fungible data token (NFDT) associated with the at least one data attribute;

constructing, from the at least one data attribute and at least one other data attribute, a digital twin comprising a personal non-fungible data token (PNFDT) associated with the user;

presenting at least one of the at least one NFDT and the PNFDT to the user via the user application, and receiving a user authorization; and

after receiving the user authorization, accessing a digital marketplace based on the at least one of the at least one NFDT and the PNFDT, and performing at least one transaction, comprising one of:

selling data associated with the at least one of the at least one NFDT and the PNFDT on the digital marketplace; and

searching the digital marketplace for data matching the at least one of the at least one NFDT and the PNFDT, and determining a reconstruction cost for the at least one of the at least one NFDT and the PNFDT.

Assignments (1)

Continuity (2)

References Cited (15)