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: 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: An event detection system to operations that include: detecting an event based on at least a portion of the sensor data, the event comprising a plurality of event attributes; determining one or more event attributes from the plurality of event attributes of the event transgress a threshold value; and causing display of a notification that includes a presentation of at least the portion of the sensor data in response to the determining that the one or more event attributes from among the plurality of event attributes of the event transgress the threshold value.

Abstract: A baseline event detection system to detect events by performing operations that include: generating a baseline data set; accessing a data stream; performing a comparison of the baseline data set and the data stream; and detecting an event based on the comparison.

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: 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: 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 are systems, methods, and non-transitory computer-readable media for configuration of optical sensor devices in vehicles based on thermal data. To manage the temperature of an optical sensor device, temperature data describing the current temperature of the optical sensor is used to determine whether the current temperature meets or exceeds a predetermined threshold temperature. If the current temperature meets or exceeds the threshold temperature, the optical sensor device may be configured into a modified operating mode to reduce the current temperature of the optical sensor device. For example, the operating mode of the optical sensor device may be modified to terminate one or more processes, reduce a frame rate at which image/video data is captured, and the like.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for configuration of optical sensor devices in vehicles based on thermal data. To manage the temperature of an optical sensor device, temperature data describing the current temperature of the optical sensor is used to determine whether the current temperature meets or exceeds a predetermined threshold temperature. If the current temperature meets or exceeds the threshold temperature, the optical sensor device may be configured into a modified operating mode to reduce the current temperature of the optical sensor device. For example, the operating mode of the optical sensor device may be modified to terminate one or more processes, reduce a frame rate at which image/video data is captured, and the like.

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: An event detection system to operations that include: detecting an event based on at least a portion of the sensor data, the event comprising a plurality of event attributes; determining one or more event attributes from the plurality of event attributes of the event transgress a threshold value; and causing display of a notification that includes a presentation of at least the portion of the sensor data in response to the determining that the one or more event attributes from among the plurality of event attributes of the event transgress the threshold value.

Abstract: A baseline event detection system to detect events by performing operations that include: generating a baseline data set; accessing a data stream; performing a comparison of the baseline data set and the data stream; and detecting an event based on the comparison.