Abstract: A device may receive, from a first vehicle, video data for video captured of a location associated with an accident for a second vehicle, and may process the video data, with a first model, to generate a sparse point cloud of the location associated with the accident. The device may process the video data, with a second model, to generate depth maps for frames of the video data, and may utilize the depth maps with the sparse point cloud to generate a dense point cloud. The device may process the video data, with a third model, to generate a dense semantic point cloud, and may process the dense semantic point cloud, with a fourth model, to determine a dense semantic overhead view of the location associated with the accident. The device may perform actions based on the dense semantic overhead view.

Abstract: A method and system for classifying a vehicle based on low frequency GPS tracks. The method and system comprise retrieving a low frequency GPS track having a sampling interval of at least 20 seconds; deriving additional data from the low frequency GPS track, the additional data including interval speed and instantaneous acceleration of the vehicle; extracting a plurality of data sets from the low frequency GPS track and the additional data; generating a plurality of features from the extracted data sets; and providing the plurality of generated features to a classifier that classifies the vehicle into a predetermined class.

Abstract: A load planning platform generates a preliminary packing solution based on loading constraints for a three-dimensional container and parameters for a set of items to be loaded into the three-dimensional container, wherein the preliminary packing solution simulates placing unpacked items into the three-dimensional container according to one or more loading rules based on a sequence in which the set of items are to be unloaded from the three-dimensional container. The load planning platform generates a set of packing solutions by applying one or more available moves changing a simulated placement for one or more items in the set of items. The load planning platform selects a final packing solution from the set of packing solutions based on one or more optimization criteria and provides access to a three-dimensional rendering of the final packing solution and instructions for implementing the final packing solution.

Abstract: A device receives location data that identifies geographic locations of a vehicle at corresponding times, and speed data that identifies respective speeds of the vehicle at the set of corresponding times. The device identifies, based on the location data, speed limit data that identifies respective speed limits at the geographic locations. The device determines, based on the respective speeds and the respective speed limits, a set of respective relative speed values associated with the vehicle. The device identifies respective relative speed values, of the set of respective relative speed values, that exceed a threshold. The device determines, based on the respective relative speed values, a univocal speed indicator that represents an overall degree to which the respective relative speed values exceed the threshold, during a time interval that includes the corresponding times. The device performs a set of actions based on the univocal speed indicator.