公开(公告)号：US12204543B2

公开(公告)日：2025-01-21

申请号：US17942073

申请日：2022-09-09

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew Cardno ,  Jenna Parenti ,  Andrew S. Locke ,  Teymour S. El-Tahry

IPC: G06F16/24 ,  G05D1/00 ,  G06F16/182 ,  G06F16/2453 ,  G06F16/2455 ,  G06F16/2458 ,  G06F16/27 ,  G06Q10/0631 ,  G06Q10/0833 ,  G06Q10/087 ,  G06Q20/38 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06V10/774 ,  H04N23/67

Abstract: A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.

公开(公告)号：US20230289340A1

公开(公告)日：2023-09-14

申请号：US18180069

申请日：2023-03-07

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew Cardno

IPC: G06F16/2453 ,  G06F16/27

CPC classification number: G06F16/24537 ,  G06F16/27

Abstract: A computer-implemented method for optimizing a distributed database includes receiving, at an aggregator, one or more query logs comprising past queries received by the distributed database. The computer-implemented method includes determining, by the aggregator, common queries received by one or more edge devices. The computer-implemented method includes determining, by the aggregator, that at least one edge device was not able to respond to a common query received by the at least one edge device. The computer-implemented method includes causing, by the aggregator, data for responding to the common query to be transmitted to the at least one edge device.

公开(公告)号：US20230103078A1

公开(公告)日：2023-03-30

申请号：US17942058

申请日：2022-09-09

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Brent Bliven ,  Kunal Sharma ,  Teymour S. El-Tahry

IPC: G06Q10/0631 ,  G06Q10/0633 ,  G06Q20/14

Abstract: A distributed manufacturing network includes a distributed ledger system and an artificial intelligence system. The distributed ledger system is integrated with digital threads of a set of distributed manufacturing network entities for storing information on event, activities and transactions related to the distributed manufacturing network entities. The artificial intelligence system is configured to learn on a training set of outcomes, parameters, and data collected from the distributed manufacturing network entities to optimize manufacturing and value chain workflows.

公开(公告)号：US20230102048A1

公开(公告)日：2023-03-30

申请号：US17942079

申请日：2022-09-09

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Brad Kell ,  Teymour S. El-Tahry ,  Leon Fortin, Jr.

IPC: B25J9/16 ,  B25J19/00

Abstract: A robot fleet management platform includes a resources data store that maintains a robot inventory indicating robots that can be assigned to a robot fleet and, for each respective robot, a set of baseline features of the robot and a respective status. The resources data store maintains a components inventory indicating different components that can be provisioned to one or more multi-purpose robots and, for each component, a respective set of extended capabilities corresponding to the component and a respective status. The robot fleet management platform receives a request for a robotic fleet to perform a job, determines a job definition data structure based on the request, determines a robot fleet configuration data structure corresponding to the job based on the set of tasks and the robot inventory, determines a respective configuration for each assigned robot based on the components inventory, configures the assigned robots, and deploys the robotic fleet.

公开(公告)号：US20230090334A1

公开(公告)日：2023-03-23

申请号：US17942065

申请日：2022-09-09

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Brent Bliven ,  Kunal Sharma ,  Teymour S. El-Tahry

IPC: G05B13/02 ,  G05B13/04 ,  G06F30/27 ,  G06Q30/0201

Abstract: An information technology system for supporting additive manufacturing and value chain workflows includes a cloud-based metal additive manufacturing management platform including an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from one or more additive manufacturing nodes to optimize additive manufacturing and value chain processes and workflows. The information technology system includes a distributed ledger system configured to store data related to the manufacturing nodes.

公开(公告)号：US20210356157A1

公开(公告)日：2021-11-18

申请号：US17332450

申请日：2021-05-27

Applicant: STRONG FORCE VCN PORTFOLIO 2019, LLC

Inventor： Stephen Paul Elias ,  Eric Roger Giler ,  Katherine Lavin Hall ,  Charles Howard Cella

IPC: F24F11/49 ,  G01S13/00 ,  G06K9/62 ,  G06N20/00

Abstract: A sensor system for determining occupancy in a space generally includes a transmitter radio device that transmits radio signals over a channel in the space; a receiver radio device that receives the transmitted radio signals that have traveled through the space; and at least one processor implementing an occupancy-centric algorithm that determines occupancy in the space based on the radio signals. The at least one processor determines channel state information based on the radio signals transmitted over the channel, determines occupancy in the space based on the channel state information, and outputs an occupancy signal based on the determined occupancy.

公开(公告)号：US12271382B2

公开(公告)日：2025-04-08

申请号：US18180065

申请日：2023-03-07

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew Cardno

IPC: G06F16/2455 ,  G05D1/00 ,  G05D1/69 ,  G06F16/182 ,  G06F16/2453 ,  G06F16/2458 ,  G06F16/27 ,  G06Q10/0631 ,  G06Q10/0833 ,  G06Q10/087 ,  G06Q20/38 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06V10/774 ,  H04N23/67

Abstract: A computer-implemented method for optimizing a distributed database includes receiving, at an aggregator, one or more query logs comprising past queries received by the distributed database. The method includes generating, by the aggregator, a query prediction model based on the one or more query logs. The method includes predicting, by the aggregator, a future query using the query prediction model. The predicted future query is predicted to be received by an edge device. The method includes causing, by the aggregator, data for responding to the predicted future query to be transmitted to the edge device.

公开(公告)号：US12039559B2

公开(公告)日：2024-07-16

申请号：US18179914

申请日：2023-03-07

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew S. Locke

IPC: G06Q30/0201 ,  G05B13/04 ,  G06F9/48 ,  G06N5/043 ,  G06N10/60 ,  G06N10/80 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q10/087 ,  G06Q30/0601 ,  G06Q40/04

CPC classification number: G06Q30/0206 ,  G05B13/048 ,  G06F9/4881 ,  G06N5/043 ,  G06N10/60 ,  G06N10/80 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q10/06315 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0625 ,  G06Q40/04

Abstract: A digital product network system includes a set of digital products each having a product processor, a product memory, and a product network interface. The digital product network system includes a product network control tower having a control tower processor, a control tower memory, and a control tower network interface. The product processor and the control tower processor collectively include non-transitory instructions that program the digital product network system to generate product level data at the product processor, transmit the product level data from the product network interface, receive the product level data at the control tower network interface, encode the product level data as a product level data structure configured to convey parameters indicated by the product level data across the set of digital products, and write the product level data structure to at least one of the product memory and the control tower memory.

公开(公告)号：US20230325766A1

公开(公告)日：2023-10-12

申请号：US18179981

申请日：2023-03-07

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew S. Locke

IPC: G06Q10/087

CPC classification number: G06Q10/087

Abstract: A system for product replacement includes a product logistics system for a product in a product condition. The system includes an exposure data collection system configured to collect exposure data indicating at least one of an event or an environmental condition that capable of impacting the product condition of the product. The system includes a replacement determination system programmed to calculate a probability for the need to replace the product based on the at least one of the event or the environmental condition. The system includes a replacement procurement system programmed to autonomously configure an option-type futures contract for replacement of the product based on the probability for the need to replace the product.

公开(公告)号：US20230252776A1

公开(公告)日：2023-08-10

申请号：US18180053

申请日：2023-03-07

Applicant: Strong Force VCN Portfolio 2019, LLC

Inventor： Charles Howard Cella ,  Andrew Cardno ,  Brent Bliven ,  Brad Kell ,  Sava Marinkovich ,  Kunal Sharma ,  Joshua Dobrowitsky

IPC: G06V10/82 ,  G06N10/40 ,  G06N3/0464 ,  G06N3/08

CPC classification number: G06V10/82 ,  G06N10/40 ,  G06N3/0464 ,  G06N3/08

Abstract: A dynamic vision system for a robotic system includes an optical assembly including a lens containing a liquid. The lens is deformable to generate variable focus for the lens. The optical assembly is configured to capture optical data. A robotic system is configured to simulate human or animal species capabilities having a control system configured to adjust one or more optical parameters. The one or more optical parameters modify the variable focus of the lens while the optical assembly captures current optical data relating to the robotic system. A processing system is configured to train a machine learning model to recognize an object relating to the robotic system from training data generated from the optical data captured by the optical assembly. The optical data includes the current optical data relating to the robotic system.