Abstract: Methods and devices for asset tracking are provided. An example method involves obtaining a stream of raw data, adding data points from the stream of raw data to a data buffer in a first cycle of data, performing a dataset simplification algorithm on the first cycle of data to determine whether one or more data points from the first cycle of data are to be recorded, preparing the data buffer for a second cycle of data, including determining a group of carry-over data points to be included in the second cycle of data, and continuing to add data points from the stream of raw data to the data buffer in the second cycle of data.

Abstract: Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Abstract: Disclosed are systems and methods relating to defining a road network used by vehicles for movement and/or parking. A classifier may be employed for identifying portions of the road network via machine learning techniques and processing of historical telematic data.

Abstract: Disclosed are systems and methods relating to defining a road network used by vehicles for movement and/or parking. A classifier may be employed for identifying portions of the road network via machine learning techniques and processing of historical telematic data.

Abstract: Systems, devices, and methods for asset tracking through specialized connectors and specialized casing units are provided. An example system includes an asset tracking device and a specialized casing unit to house the asset tracking device and to connect the asset tracking device to a communication port of an asset. The asset tracking device includes a communication port interface to interface with the communication port of the asset directly, and to interface with the communication port of the asset through the specialized casing unit. The asset tracking device further includes a controller to determine whether the asset tracking device is interfaced with the communication port of the asset directly or through the specialized casing unit, and when it is determined that the asset tracking device is interfaced with the communication port of the asset through the specialized casing unit, configure the asset tracking device to operate in a specialized operating mode.

Abstract: A traffic analysis system analyzes location data from a plurality of vehicles to determine journeys made by the vehicles. Vehicles may make one or more rest stops during a journey. The traffic analysis system compares rest periods to journey criteria to determine whether a rest period delineates the end of a journey, or whether a rest period is still within the journey. In this way, a plurality of trips can be chained together into a journey to provide more accurate analysis of traffic patterns.

Abstract: A method for inferring a status asset information from data of a first type gathered by a first asset tracking device is provided. The method includes determining that a first asset tracking device coupled to a first asset and a second asset tracking device coupled to a second asset are travelling together, that the first asset tracking device has a first operating mode, and that the second asset tracking device has a second operating mode, which is different from the first operating mode of the first asset tracking device. In response, the second asset tracking device enters into a low-power mode in which it either does not gather data of the first type or does so at a reduced rate. Status information related to the second asset may be inferred from data of the first type gathered by the first asset tracking device.

Abstract: A wire-management module is configured to be installable to a vehicle having an operable system configured to be energized in response to operative connection between a first wire and a second wire. A user-authentication module is configured to transmit a wire-management signal including a wire-inhibit signal configured to indicate lack of authorization to use the operable system of the vehicle. The wire-management module is configured to be operatively coupled to the first wire and the second wire. The wire-management module has a signal input port configured to receive the wire-inhibit signal that is transmittable from the user-authentication module. The wire-management module is also configured to inhibit operative connection between the first wire and the second wire.

Abstract: Methods for asset type fingerprinting are provided. An example method involves an asset tracking system failing to identify an asset type fingerprint and requesting an asset type fingerprint from an asset data analysis system. The asset data analysis system generates a proposed asset type fingerprint, links the asset type fingerprint to a set of signal definitions that indicate how to decode data messages from the asset. The asset data analysis system transmits the proposed asset type fingerprint to the asset data analysis system, which then decodes at least some data messages from the asset thus obtaining asset information. The method may be used to identify vehicle types and decode proprietary or non-standard data messages via a vehicle's diagnostic port.

Abstract: System, apparatus, device and methods relating to a telematic vehicle sharing platform ecosystem and a telematic vehicle share I/O expander to automate sharing and management of a vehicle that is shared by more than one operator.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: Described herein are techniques for addressing queries regarding vehicles without sharing of individually identifiable information regarding individual vehicles. Aggregate analysis data resulting from performance of statistical operation(s) on vehicle information regarding the individual vehicles may be used to address the queries without requiring an exchange of individually identifiable information obtained from the individual vehicles.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for monitoring vehicle components and providing indications towards the condition of the vehicle components and providing optimal indications towards replacement or maintenance of vehicle components before vehicle component failure.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for monitoring vehicle components and providing indications towards the condition of the vehicle components and providing optimal indications towards replacement or maintenance of vehicle components before vehicle component failure.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for the for identifying in real time unpredictable network communication faults based upon pre-processed raw telematics big data logs that may include GPS data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for identifying in real time unpredictable network communication faults based upon pre-processed raw telematics big data logs that may include gps data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

Abstract: Methods and systems for identifying manufacturer-specific controller-area (CAN) data for a vehicle type are provided. Manufacturer-specific CAN data may be identified by processing defined CAN data having a correlation relationship with the target data and undefined manufacturer-specific CAN data for determining if there is a correlation relationship therebetween. Also provided are methods and systems for identifying and automatically collecting manufacturer-specific CAN data for a vehicle type.

Abstract: Methods and systems for identifying manufacturer-specific controller-area (CAN) data for a vehicle type are provided. Manufacturer-specific CAN data may be identified by processing defined CAN data having a correlation relationship with the target data and undefined manufacturer-specific CAN data for determining if there is a correlation relationship therebetween. Also provided are methods and systems for identifying and automatically collecting manufacturer-specific CAN data for a vehicle type.