Abstract: A video summary device may determine, based on video data, a plurality of events that occurred during a period of time. The video summary device may determine first measures of relevance of a plurality of portions of the period of time. A first measure of relevance of a portion of time may be determined based on one or more events of the plurality of events. The video summary device may determine second measures of relevance of a plurality of ranges of time between different portions of time of the plurality of portions of the period of time. The second measures of relevance is determined based on the first measures of relevance determined for the different portions of time. The video summary device may determine particular frames of the video data, as a video summary of the video data, based on the second measures of relevance.

Abstract: A device may receive schedule data identifying schedules of appointments for drivers of vehicles and may receive location data identifying geographical locations of the vehicles. The device may receive traffic data identifying traffic conditions, and may process the received data, with a first model, to determine status data identifying estimated statuses of the appointments. The device may process the received data, with a second model, to generate sets of isochrones for destinations of the appointments, and may calculate, based on the sets of isochrones and the location data, estimated travel time data identifying estimated travel times for the appointments. The device may process the status data, the estimated travel time data, and the schedule data, with a third model, to calculate estimated time of arrival data identifying estimated times of arrival for the appointments, and may perform actions based on the estimated time of arrival data.

Abstract: Embodiments described herein provide for the generation of models, which may predict or otherwise model road safety conditions. For example, embodiments may determine attributes of roads and/or segments of roads based on sensor data, statistical data, and/or other suitable data to determine road safety models associated with the roads or road segments. Such models may be used when determining navigation routes, controlling autonomous vehicles, city planning, and/or other suitable operations that may take road safety into account.

Abstract: A device may receive schedule data identifying schedules of appointments for drivers of vehicles and may receive location data identifying geographical locations of the vehicles. The device may receive traffic data identifying traffic conditions, and may process the received data, with a first model, to determine status data identifying estimated statuses of the appointments. The device may process the received data, with a second model, to generate sets of isochrones for destinations of the appointments, and may calculate, based on the sets of isochrones and the location data, estimated travel time data identifying estimated travel times for the appointments. The device may process the status data, the estimated travel time data, and the schedule data, with a third model, to calculate estimated time of arrival data identifying estimated times of arrival for the appointments, and may perform actions based on the estimated time of arrival data.