von Zmuda-Trzebiatowski, Margarethe

Methods by a telematics device and a telematics device for simplifying captured telematics data and providing near real-time data points to a telematics server. Simplifying the data uses an algorithm that prioritizes primary data while providing timely secondary data under various conditions. In some implementations, a data simplification method is applied to partially filled data captured buffers containing secondary data. In some implementations, partially filled data capture buffers are processed if data points of that data type have not been selected for sending or if the data capture buffers are filled over a particular threshold. In some implementations, data points having an estimate error greater than an estimate error threshold are selected for sending to the telematics server.

The present disclosure relates to systems and methods for identifying commercial domiciles. An example of one such method includes operating at least one processor to: receive telematics data originating from a plurality of telematics devices installed in a plurality of vehicles; identify, using the telematics data, a vehicle stop zone, each vehicle stop zone comprising a vehicle stop cluster; and identify the vehicle stop zone as a commercial domicile by applying to the vehicle stop cluster of the vehicle stop zone at least one machine learning model trained to classify vehicle stop zones based on one or more vehicle stop features thereof.

Systems, methods, devices, and models for identifying preventable idling in vehicles are described. Preventable idling events are identified which are outside of acceptability criteria, such as idling duration. Preventable idling events can be associated with drivers and/or vehicles to provide avenues to curb preventable idling. Fuel consumption and/or carbon emissions for preventable idling events are identified to quantify efficacy of curbing preventable idling. Histograms and concentration maps are generated to identify high-concentration idling events, and take targeted action.

A method in a telematics system is provided. The method is for identifying an asset category of a plurality of asset categories. The method includes executing category identifying asset data queries after excluding error causing asset data requests from a main list and excluding asset categories from the main list based on the result of executing category identifying asset data queries. The steps are repeated until a single asset category remains in the main list. A telematics system including a telematics server, a telematics database coupled to the telematics server, a network, and a telematics device is provided, the telematics system configured for carrying out the method.

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Systems, methods, models, and training for collision detection and near miss detection are discussed. Models are trained to identify collisions and near misses between two vehicles, based on how quickly a bounding box size changes for a vehicle represented in image data. Rapidly changing bounding box size is indicative of extreme proximity between vehicles, and thus indicative of collision or near-miss scenarios. Identifications of collisions or near misses can be reported to a remote operator, to send emergency assistance, perform driver evaluation, or alert other drivers in the area of risks.

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