Machine learning system for natural gas leak detection

A leak identification system configured to detect gaseous leaks in a natural gas extraction environment, the leak identification system comprising:

• a machine learning interface configured to generate feature vectors based on video data that depicts a natural gas storage facility and provide the feature vectors as input to a motion detection machine learning model, a background detection machine learning model, an object detection machine learning model, and a gas leak detection machine learning model;
• the motion detection machine learning model configured to ingest the feature vectors and generate a motion detection output that indicates the presence of motion in the video data;
• the background detection machine learning model configured to ingest the feature vectors and generate a background detection output that indicates background portions of the video data;
• the object detection machine learning model configured to ingest the feature vectors and generate an object detection output that indicates natural gas extraction, storage, or transfer equipment in the video data;
• the gas leak detection machine learning model configured to ingest the feature vectors and generate a gas leak detection output that indicates portions of the video data that depict a gas leak;
• a non-linear function machine learning model configured to ingest the motion detection output, the background detection output, the object detection output, and the gas leak detection output and utilize a non-linear function machine learning algorithm to generate a non-linear function output that indicates a likelihood of the presence of the gas leak in the natural gas storage facility;
• and
• the machine learning interface configured to receive the non-linear function output that indicates the likelihood of the presence of the gas leak in the natural gas storage facility, generate data for rendering a user interface that comprises the indication, and transfer the data.

A non-transitory computer-readable medium stored thereon instructions to detect gaseous leaks in a natural gas extraction environment, that, in response to execution, cause a system comprising a processor to perform operations, the operations comprising:

• generating feature vectors based on video data that depicts a natural gas storage facility;
• providing the feature vectors as input to a motion detection machine learning model, a background detection machine learning model, an object detection machine learning model, and a gas leak detection machine learning model, wherein:
• the motion detection machine learning model indicates a presence or lack thereof of motion in the video data;
• the background detection machine learning model indicates a presence or lack thereof of background environment in the video data;
• the object detection machine learning model indicates a presence or lack thereof of natural gas extraction, storage, or transfer equipment in the video data;
• the gas leak detection machine learning model indicates a presence or lack thereof of a gas leak;
• providing a motion detection indication, a background detection indication, an object detection indication, and a gas leak detection indication to a non-linear function machine learning model, wherein the non-linear function machine learning model indicates a likelihood of the presence or lack thereof of the gas leak in the natural gas storage facility;
• and
• in response to an indication of the likelihood of the presence or lack thereof of the gas leak in the natural gas storage facility, generating and transferring data for rendering a user interface that comprises the indication.