US 12,254,427 B2
Systems and methods for forward market purchase of machine resources
Charles Howard Cella, Pembroke, MA (US)
Assigned to Strong Force TX Portfolio 2018, LLC, Fort Lauderdale, FL (US)
Filed by Strong Force TX Portfolio 2018, LLC, Ft. Lauderdale, FL (US)
Filed on May 31, 2023, as Appl. No. 18/203,725.
Application 18/203,725 is a continuation of application No. 16/696,457, filed on Nov. 26, 2019, granted, now 11,741,402.
Application 16/696,457 is a continuation of application No. 16/457,890, filed on Jun. 28, 2019, abandoned.
Application 16/457,890 is a continuation of application No. PCT/US2019/030934, filed on May 6, 2019.
Claims priority of provisional application 62/787,206, filed on Dec. 31, 2018.
Claims priority of provisional application 62/751,713, filed on Oct. 29, 2018.
Claims priority of provisional application 62/667,550, filed on May 6, 2018.
Prior Publication US 2023/0306319 A1, Sep. 28, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 10/04 (2023.01); G05B 19/00 (2006.01); G05B 19/418 (2006.01); G06F 9/38 (2018.01); G06F 9/46 (2006.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06F 9/54 (2006.01); G06F 16/18 (2019.01); G06F 16/182 (2019.01); G06F 16/23 (2019.01); G06F 16/24 (2019.01); G06F 16/27 (2019.01); G06F 16/951 (2019.01); G06F 18/214 (2023.01); G06F 21/10 (2013.01); G06F 30/27 (2020.01); G06N 3/02 (2006.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06Q 10/0631 (2023.01); G06Q 10/067 (2023.01); G06Q 20/06 (2012.01); G06Q 20/22 (2012.01); G06Q 20/36 (2012.01); G06Q 20/38 (2012.01); G06Q 20/40 (2012.01); G06Q 30/0201 (2023.01); G06Q 30/0202 (2023.01); G06Q 30/0204 (2023.01); G06Q 30/0241 (2023.01); G06Q 30/0273 (2023.01); G06Q 30/06 (2023.01); G06Q 40/04 (2012.01); G06Q 40/10 (2023.01); G06Q 50/04 (2012.01); G06Q 50/06 (2012.01); G06Q 50/18 (2012.01); H02J 3/00 (2006.01); H02J 3/14 (2006.01); H02J 3/28 (2006.01); H02J 3/38 (2006.01); H04L 9/00 (2022.01); H04L 12/14 (2006.01); H04L 47/78 (2022.01); H04L 47/783 (2022.01); H04L 47/83 (2022.01); G06F 16/2457 (2019.01); G06N 3/044 (2023.01); G06N 3/047 (2023.01); G06Q 30/0251 (2023.01); G06Q 50/00 (2012.01); H04L 9/06 (2006.01); H04L 67/12 (2022.01)
CPC G06Q 10/04 (2013.01) [G05B 19/00 (2013.01); G05B 19/41865 (2013.01); G05B 19/4188 (2013.01); G06F 9/3836 (2013.01); G06F 9/3891 (2013.01); G06F 9/466 (2013.01); G06F 9/4806 (2013.01); G06F 9/4881 (2013.01); G06F 9/50 (2013.01); G06F 9/5005 (2013.01); G06F 9/5016 (2013.01); G06F 9/5027 (2013.01); G06F 9/5072 (2013.01); G06F 9/541 (2013.01); G06F 16/182 (2019.01); G06F 16/1865 (2019.01); G06F 16/23 (2019.01); G06F 16/2365 (2019.01); G06F 16/2379 (2019.01); G06F 16/24 (2019.01); G06F 16/27 (2019.01); G06F 16/951 (2019.01); G06F 18/2148 (2023.01); G06F 18/2155 (2023.01); G06F 21/105 (2013.01); G06F 30/27 (2020.01); G06N 3/02 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/0631 (2013.01); G06Q 10/06314 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/067 (2013.01); G06Q 20/06 (2013.01); G06Q 20/065 (2013.01); G06Q 20/0655 (2013.01); G06Q 20/29 (2013.01); G06Q 20/367 (2013.01); G06Q 20/38215 (2013.01); G06Q 20/389 (2013.01); G06Q 20/4016 (2013.01); G06Q 20/405 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0202 (2013.01); G06Q 30/0205 (2013.01); G06Q 30/0206 (2013.01); G06Q 30/0247 (2013.01); G06Q 30/0273 (2013.01); G06Q 30/06 (2013.01); G06Q 40/04 (2013.01); G06Q 40/10 (2013.01); G06Q 50/04 (2013.01); G06Q 50/06 (2013.01); G06Q 50/184 (2013.01); H02J 3/008 (2013.01); H02J 3/14 (2013.01); H02J 3/28 (2013.01); H02J 3/388 (2020.01); H04L 9/50 (2022.05); H04L 12/14 (2013.01); H04L 47/783 (2013.01); H04L 47/788 (2013.01); H04L 47/83 (2022.05); G05B 2219/36542 (2013.01); G06F 9/3838 (2013.01); G06F 16/2457 (2019.01); G06N 3/0418 (2013.01); G06N 3/044 (2023.01); G06N 3/047 (2023.01); G06Q 20/4015 (2020.05); G06Q 30/0254 (2013.01); G06Q 30/0276 (2013.01); G06Q 50/01 (2013.01); G06Q 2220/00 (2013.01); G06Q 2220/12 (2013.01); G06Q 2220/18 (2013.01); H02J 3/003 (2020.01); H04L 9/0643 (2013.01); H04L 67/12 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A transaction-enabling system, comprising:
an interface configured to communicate with a fleet of machines, each one of the fleet of machines having a resource requirement comprising a plurality of machine-related resources, the plurality of machine-related resources comprising at least two of: a compute resource, a spectrum resource, or a network bandwidth resource, the resource requirement including a first resource among the plurality of machine-related resources; and
a controller in communication with the fleet of machines via the interface, the controller comprising:
an intelligent agent circuit structured to aggregate data corresponding to the plurality of machine-related resources from a plurality of data sources comprising at least an external data source, the external data source comprising at least a behavioral data source;
an expert system circuit structured to configure a purchase of at least one of the plurality of machine-related resources, the configuring the purchase comprising:
maintaining a training data set comprising feedback data indicating respective outcomes of previous purchases and, for each respective outcome, at least one of: a facility parameter, a yield parameter, a profit parameter, a resource optimization parameter, a user satisfaction parameter, or an operator satisfaction parameter;
training an artificial intelligence system based on the training data set to self-adjust forecasts for a forward market price of the at least one of the plurality of machine-related resources based on the training data set that includes the feedback data, the forward market price being for at least one of:
the first resource; and
a second resource, among the at least one of the plurality of machine-related resources, that can be substituted for the first resource,
wherein the first resource and the second resource are distinct instances of the same type of resource; and
determining a substitution cost of the second resource; and
a machine resource acquisition circuit structured to:
determine a machine-related resource acquisition value; and
automatically solicit the configured purchase of the at least one of the first resource or the second resource in a forward market for the at least one of the first resource or the second resource based on the machine-related resource acquisition value and the substitution cost of the second resource,
wherein the expert system circuit is further structured to update the training data set with additional feedback data corresponding to the configured purchase and reinforce the artificial intelligence system based on the additional feedback data.