Abstract:
Among other things, information generated by sensors of a mobile phone and indicative of motion of the mobile phone and state information indicative of a state of operation of the mobile phone are monitored. Based on the monitoring, distraction by a user of the mobile phone who is a driver of a vehicle is determined.
Abstract:
A sensor tag which in use will be affixed to a vehicle for obtaining vehicle telematics data includes a battery for powering the tag and a processor running executable code to process accelerometer data. An accelerometer measures the acceleration of the tag and thereby of the vehicle, and also controls the operation of the processor. A memory is used for storing a unique tag identifier of the tag and for storing trip data including information about trips and acceleration data. Finally, a communication module is used for short range wireless communication with a mobile communications device located in the vehicle via a short range wireless communications protocol, the communication module transmitting the tag's unique identifier and a sequence of time stamped acceleration data. The mobile communications device obtains GPS data, combines this with the acceleration date and transmits this to a server for analysis.
Abstract:
An approach to determining vehicle usage makes use of a sensor that provides a vibration signal associated with the vehicle, and that vibration signal is used to infer usage. Usage can include distance traveled, optionally associated with particular ranges of speed or road type. In a calibration phase, auxiliary measurements, for instance based on GPS signals, are used to determine a relationship between the vibration signal and usage. In a monitoring phase, the determined relationship is used to infer usage from the vibration signal.
Abstract:
Among other things, information generated by sensors of a mobile phone and indicative of motion of the mobile phone and state information indicative of a state of operation of the mobile phone are monitored. Based on the monitoring, distraction by a user of the mobile phone who is a driver of a vehicle is determined.
Abstract:
Data processing techniques and systems for processing telematics data associated with a vehicle, such as an automobile, to classify how the vehicle is being operated by a driver. The telematics data can include the use of image data captured by a camera of the vehicle. The image data is processed in conjunction with vehicular telematics data such as position, speed, and acceleration data of the vehicle obtained from, for example, smartphone sensors. The image data is processed and used by a processing system to provide a context for the telematics data. The image data and the telematics data are classified by the processing system to identify driving behavior of the driver, determine driving maneuvers that have occurred, scoring driving quality of the driver, or a combination of them.
Abstract:
Among other aspects, information is received at or from a mobile device. The information is derived from one or more position or motion sensors of the mobile device. The derived information is indicative of a position or a velocity of the mobile device. The position or the velocity of the mobile device conforms to a position or a velocity of a vehicle. The derived information is used to identify a dangerous situation involving the vehicle and a person on foot or a bicyclist. A notification is provided of the dangerous situation.
Abstract:
Customize safe speeds for vehicles are determined from information that is collected from multiple trips and multiple drivers across many road segments. The information collected includes the speed traveled along the road segment, possibly along with additional information, such as (for example) driver, time of day, day of week, weather and road conditions, angle of the sun or other factors. Given information from a new trip, the driver's speed can be compared on each road segment with relevant data from previous trips (from e.g., similar roads, weather conditions, drivers). The comparison yields a score representing the safety of the driver's speed.
Abstract:
A system for tracking objects includes tracking devices each attached to an object to be tracked and including a short range communications module. A server includes a processor and a memory. A mobile communications device (typically a mobile telephone) includes memory for storing an identification of the mobile device, a long range communication module for communication over a cellular communication network and a short range communications module for receiving short range signals transmitted from tracking devices. The mobile telephone also includes a location determination module to determine the location of the mobile telephone. On receipt of a short range distress signal from a tracking device, a location is obtained from the location module and a signal transmitted to the server including at least the identification of the tracking device, a time of receipt of the short range signal from the tracking device and the determined location of the tracking device when the short range signal was received.
Abstract:
Accurate longitudinal acceleration, lateral acceleration (perpendicular to the principal direction of motion, and velocity, is inferred by processing raw data from a commodity three-axis accelerometer that may be oriented arbitrarily in a moving vehicle (or carried by a moving user), and whose orientation and position may change arbitrarily during the motion. The approach is applicable to a range of applications, including insurance telematics, driver behavior and risk assessment, and road surface quality assessment.
Abstract:
An approach to telematics using mobile devices provides battery-efficient trajectory and mileage inference from inaccurate and intermittent location data. Accurate trajectories of how users or vehicles move in the physical world are formed by processing raw position estimates obtained from noisy, inaccurate, and error-prone position sensors on mobile devices, where the position data may also arrive intermittently with long time gaps. The trajectory is formed using the process of map matching, which determines the trajectory on a map that best explains the sequence of position observations.