Incucomm, Inc.

Eric Haney

Steven D Roemerman

John P Volpi

Matthew Bowers

Randal Allen

Shane Poage

James Robinson

Christopher Niblo

Mark James Volpi

Randall Allen

Systems and methods for the automatic routing of data packets in dynamic networks, wherein at least a portion of a route for a data packet is modeled as a fluid dynamics potential flow characterized by an irrotational velocity field. Each data packet is the analogue of a flow particle, an originating node of the data packet is the analogue of a source, and a destination node of the data packet is the analogue of a sink. Each of one or more nodes intermediate to the originating node and the destination node for a data packet are defined as a stream function (Ψ) which adheres to the definition of irrotational and incompressible potential flow that independently represents a flow phenomenon that can influence the route of the data packet. A route for a data packet is calculated based on its current location and the aggregate stream function comprising the sum of each of the flow phenomena acting on the data packet.

System and method for the automatic routing of information in dynamic networks

A distributed analytics system to control an operation of a monitored system, and method of operation thereof, including an architect subsystem and an edge processing device. The edge subsystem includes an edge processing device associated with the monitored system. The architect subsystem is configured to deploy an analytic model to the edge processing device based on characteristics of the monitored system. The edge processing device is configured to receive the analytic model and independently perform predictive and prescriptive analytics on dynamic input data associated with the monitored system, provide control signals to the monitored system according to the predictive and prescriptive analytics, and provide information to the architect subsystem, including monitored system responses to the control signals. The architect subsystem is configured to modify the analytic model to improve system performance of the monitored system.

Adaptive distributed analytics system

An operations and maintenance (O&M) system, and related method, for a plurality of unique objects characterized by distinct digital twins. The O&M system includes: a database subsystem for storing at least first and second distinct digital twins for each of the plurality of unique objects; at least one of the digital twins has an identifier that uniquely associates it with one of the plurality of unique objects and defines a unique virtual representation thereof. The system further includes a virtual sensor subsystem operative to emulate operational data for ones of the plurality of objects; the virtual sensor subsystem is not dependent on sensors physically associated with ones of the plurality of unique objects. A digital twin comparison subsystem is operative to compare outputs of the at least first and second distinct digital twins for each of the plurality of unique objects; the output of at least one of the first and second digital twins is a function of the emulated operational data for its associated object, and the O&M system makes an operational or maintenance decision with respect to an object as a function of the comparison.

Operations and maintenance systems and methods employing sensor-less digital twins

An aggregation layer subsystem, and method of operation thereof, for use with an architect subsystem and a plurality of edge processing devices in a distributed analytics system, wherein each edge processing device is adapted to monitor and control the operation of at least one monitored system according to a first analytic model, the aggregation layer subsystem comprising: a processor and memory, the memory containing instructions which, when executed by the processor, enables the aggregation layer subsystem to: receive a second analytic model from the architect subsystem, the second analytic model based on characteristics of at least one monitored system associated with at least one of the plurality of edge processing devices; receive monitored system information from each of the plurality of edge processing devices; and, provide control signals to the at least one monitored system, via one of the edge processing devices, according to the second analytic model in response to the monitored system information.

Distributed analytics system used to control the operation of at least one monitored system; the system includes an architect subsystem and an edge subsystem, wherein the edge subsystem comprises at least one edge processing device associated with at least one monitored system. The architect subsystem deploys at least one analytic model to an edge processing device based on characteristics of a monitored system associated with the edge processing device, the analytic model to be used by the edge processing device to provide control signals to a monitored system; and, receives information related to the monitored system from the edge processing device, the information utilized by the architect subsystem to modify the analytic model deployed to the at least one edge processing device to improve system performance of the monitored system. An edge processing device receives an analytic model from the architect subsystem; provides control signals to the monitored system according to the analytic model; and, sends information related to the monitored system to the architect subsystem, the information to be used by the architect subsystem to modify the analytic model to improve system performance of the monitored system.

A communication system and method that provides predictive and prescriptive analytics for a system running at an edge. In one embodiment, the communication system includes an architect subsystem configured to build, test and deploy a model based on sensor characteristics of the system. The sensor characteristics are from at least one of an operator input, a historical input, a specification input, and a subject-matter expert input. The communication system also includes an edge subsystem configured to receive said model and perform predictive and prescriptive analytics on sensor data from said system running on said model deployed at said edge.

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Dallas, TX, United States of America

Eric Haney