Methods, systems, kits and apparatuses for monitoring and managing industrial settings in an industrial internet of things data collection environment

Patent metadata

Field	Value
Publication number	US-2020225655-A1
Application number	US-202016741470-A
Country	US
Kind code	A1
Filing date	Jan 13, 2020
Priority date	May 9, 2016
Publication date	Jul 16, 2020
Grant date	—

Abstract

The present disclosure includes a method for receiving, by the processing system, reporting packets from one or more respective sensors of the plurality of sensors. Each reporting packet is sent from a respective sensor and indicates sensor data captured by the respective sensor; performing, by the processing system, one or more edge operations on one or more instances of sensor data received in the reporting packets. Generating one or more sensor kit packets based on the instances of sensor data. Each sensor kit packet includes at least one instance of sensor data. Outputting the sensor kit packets to the data handling platform. Receiving the sensor kit packets from the edge device. Generating the digital twin of said industrial setting including a digital replica of at least one industrial component of said industrial setting and being at least partially based on the sensor kit packets.

First claim

What is claimed is:

1 . An Internet of Things (IoT) system configured for monitoring and creating a digital twin of an industrial setting, the IoT system comprising:
an edge device; a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network; a data handling platform in communication with the edge device and configured to generate a digital twin of said industrial setting, wherein the plurality of sensors includes one or more sensors of a first sensor type and one or more sensors of a second sensor type, wherein at least one sensor of the plurality of sensors comprises:
a sensing component that captures sensor measurements and outputs instances of sensor data;
a processing unit that generates reporting packets based on one or more instances of sensor data and outputs the reporting packets, wherein each reporting packet includes routing data and one or more instances of sensor data; and
a communication device configured to receive reporting packets from the processing unit and to transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol; and, wherein the edge device comprises:
one or more storage devices that store a model data store that stores a plurality of machine-learned models that are each trained to predict or classify a condition of an industrial component of said industrial setting or of said industrial setting based on a set of features that are derived from instances of sensor data captured by one or more of the plurality of sensors;
a communication system that receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and that transmits sensor kit packets to the data handling platform; and
a processing system having one or more processors that execute computer-executable instructions that cause the processing system to:
receive the reporting packets from the communication system;
generate a set of feature vectors based on one or more respective instances of sensor data received in the reporting packets;
for each respective feature vector, input the respective feature vector into a respective machine-learned model that corresponds to the feature vector to obtain a respective prediction or classification relating to a condition of a respective industrial component of said industrial setting or said industrial setting and a degree of confidence corresponding to the respective prediction or classification;
selectively encode the one or more instances of sensor data prior to transmission to the data handling platform based on the respective predictions or classifications outputted by the machine-learned models in response to the respective feature vector to obtain one or more sensor kit packets; and
output the sensor kit packets to the communication system, wherein the communication system transmits the sensor kit packets to the data handling platform;

wherein the data handling platform is configured to:
receive the sensor kit packets from the edge device; and
generate the digital twin of said industrial setting, the digital twin of said industrial setting including a digital replica of at least one industrial component of said industrial setting and being at least partially based on the sensor kit packets.

2 . The IoT system of claim 1 , further comprising a dashboard configured to display the digital twin to a user of the IoT system and the data handling platform is configured to update the digital twin based on sensor kit packets received subsequent to generation of the digital twin such that the displayed digital twin includes a substantially real-time digital replica of said at least one industrial component of said industrial setting.

3 . The IoT system of claim 1 , further comprising a gateway device, wherein the gateway device is configured to receive sensor kit packets from the edge device via a wired communication link and transmit the sensor kit packets to the data handling platform on behalf of the edge device.

4 . The IoT system of claim 3 , wherein the gateway device includes a satellite terminal device that is configured to transmit the sensor kit packets to a satellite that routes the sensor kit packets to the public network.

5 . The IoT system of claim 3 , wherein the gateway device includes a cellular chipset that is pre-configured to transmit the sensor kit packets to a cellphone tower of a preselected cellular provider.

6 . The IoT system of claim 1 , wherein the second communication device of the edge device is a satellite terminal device that is configured to transmit the sensor kit packets to a satellite that routes the sensor kits to the public network.

7 . The IoT system of claim 1 , wherein the one or more storage devices store a sensor data store that stores instances of sensor data captured by the plurality of sensors of the sensor kit.

8 . The IoT system of claim 1 , wherein selectively encoding the one or more instances of sensor data includes: in response to obtaining one or more predictions or classifications relating to conditions of respective industrial components of said industrial setting and said industrial setting that collectively indicate that there are likely no issues relating to any industrial component of said industrial setting and said industrial setting, compressing the one or more instances of sensor data using a lossy codec.

9 . The IoT system of claim 8 , wherein compressing the one or more instances of sensor data using the lossy codec includes:
normalizing the one or more instances of sensor data into respective pixel values; encoding the respective pixel values into a video frame; and compressing a block of video frames using the lossy codec, wherein the lossy codec is a video codec and the block of video frames includes the video frame and one or more other video frames that include normalized pixel values of other instances of sensor data.

10 . The IoT system of claim 8 , wherein selectively encoding the one or more instances of sensor data includes: in response to obtaining a prediction or classification relating to a condition of a particular industrial component or said industrial setting that indicates that there is likely an issue relating to the particular industrial component or said industrial setting, compressing the one or more instances of sensor data using a lossless codec.

11 . The IoT system of claim 8 , wherein selectively encoding the one or more instances of sensor data includes: in response to obtaining a prediction or classification relating to a condition of a particular industrial component or said industrial setting that indicates that there is likely an issue relating to the particular industrial component or said industrial setting, refraining from compressing the one or more instances of sensor data.

12 . The IoT system of claim 1 , wherein the computer-executable instructions further cause the one or more processors of the edge device to selectively store the one or more instances of sensor data in the one or more storage devices of the edge device based on the respective predictions or classifications.

13 . The IoT system of claim 12 , wherein selectively storing the one or more instances of sensor data includes: in response to obtaining one or more predictions or classifications relating to conditions of respective industrial components of said industrial setting and said industrial setting that collectively indicate that there are likely no issues relating to any industrial component of said industrial setting and said industrial setting, sto

Assignees

• Strong Force Iot Portfolio 2016 Llc

Inventors

• Cella Charles
• El-Tahry Teymour
• Spitz Richard
• Mcguckin Jeffrey P
• Duffy Jr Gerald William

Classifications

• G05B23/0294 Primary

  Optimizing process, e.g. process efficiency, product quality · CPC title

• G05B19/4184 Primary

  characterised by fault tolerance, reliability of production system · CPC title

• G06V10/95

  structured as a network, e.g. client-server architectures · CPC title

• G06F18/2178

  based on feedback of a supervisor · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title