Abstract: Disclosed in certain embodiments are methods of removing methanol from a gas feed stream comprising methanol and water during an adsorption step of an adsorption cycle.

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

Abstract: Disclosed in certain embodiments are methods of removing water from a gas feed stream comprising hydrocarbons and water during an adsorption step of an adsorption cycle.

Abstract: Disclosed in certain embodiments are methods of removing methanol from a natural gas stream comprising methanol during an adsorption step of an adsorption cycle.

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

Abstract: Disclosed in certain embodiments are processes for heavy hydrocarbon removal that implement a regeneration loop to reduce an amount of liquid hydrocarbons exposed by the separator to the regeneration stream over one or more durations for which an average C5+ hydrocarbon content of the regeneration stream is reduced or minimal.

Abstract: An improved system and method of selectively transmitting asset data from one or more sensors associated with the vehicle to a backend server, which is configured to analyze the asset data and, if necessary for further analysis of the asset data (e.g., to determine whether a safety event has occurred) and/or to provide actionable data for review by a safety analyst, requests further asset data from a vehicle device.

Abstract: Disclosed in certain embodiments are methods of removing water from a gas feed stream comprising hydrocarbons and water during an adsorption step of an adsorption cycle.

Abstract: A device orientation calibration system to perform operations that include: accessing inertial measurement unit (IMU) data generated by an IMU mounted upon an object that corresponds with a first reference frame, the IMU data indicating a second reference frame that comprises a Z-axis, a Y-axis, and an X-axis; performing a calibration of the IMU data to align the second reference frame of the IMU with the first reference frame of the object, the performing the calibration comprising: determining a gravitational vector based on a first portion of the IMU data; applying a first rotation to the IMU data to align the Z-axis of the second reference frame with the gravitational vector; determining a forward motion vector based on a second portion of the IMU data; and applying a second rotation to the IMU data to align the X-axis of the second reference frame with the forward motion vector.

Abstract: Disclosed in certain embodiments are processes for heavy hydrocarbon removal that implement a regeneration loop to reduce an amount of liquid hydrocarbons exposed by the separator to the regeneration stream over one or more durations for which an average C5+ hydrocarbon content of the regeneration stream is reduced or minimal.

Abstract: Disclosed in certain embodiments are processes for heavy hydrocarbon removal that implement a regeneration loop that introduces an absorbent into a regeneration gas stream, and systems for implementing the same.

Abstract: Disclosed in certain embodiments are methods of removing water, mercaptans, C5+ or C6+ hydrocarbons, or any combination thereof from a gas feed stream during an adsorption step of an adsorption cycle.

Abstract: Disclosed in certain embodiments are processes for heavy hydrocarbon removal that implement a regeneration loop to reduce an amount of liquid hydrocarbons exposed by the separator to the regeneration stream over one or more durations for which an average C5+ hydrocarbon content of the regeneration stream is reduced or minimal.

Abstract: An improved system and method of selectively transmitting asset data from one or more sensors associated with the vehicle to a backend server, which is configured to analyze the asset data and, if necessary for further analysis of the asset data (e.g., to determine whether a safety event has occurred) and/or to provide actionable data for review by a safety analyst, requests further asset data from a vehicle device.

Abstract: Disclosed in certain embodiments are methods of removing water from a gas feed stream comprising mercaptans and water during an adsorption step of an adsorption cycle.

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

Abstract: An improved system and method of selectively transmitting asset data from one or more sensors associated with the vehicle to a backend server, which is configured to analyze the asset data and, if necessary for further analysis of the asset data (e.g., to determine whether a safety event has occurred) and/or to provide actionable data for review by a safety analyst, requests further asset data from a vehicle device.

Abstract: Disclosed in certain embodiments are methods of removing water from a gas feed stream comprising hydrocarbons and water during an adsorption step of an adsorption cycle.

Abstract: A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

Abstract: An improved system and method of selectively transmitting asset data from one or more sensors associated with the vehicle to a backend server, which is configured to analyze the asset data and, if necessary for further analysis of the asset data (e.g., to determine whether a safety event has occurred) and/or to provide actionable data for review by a safety analyst, requests further asset data from a vehicle device.