A driving pattern regenerative braking method of a vehicle includes: collecting and inputting driving data, extracting deceleration data through preprocessing the driving data, clustering the deceleration data and removing outliers, calculating a deceleration rate change and an inter-vehicle distance to a vehicle in front from clustered data, deriving a quadratic equation of the deceleration rate change and the distance to the vehicle in front through polynomial regression, determining whether a predetermined condition is satisfied, and if so, modifying a regenerative braking system of the vehicle based on the quadratic equation, all of the above steps being performed by a controller. The method may further include calculating orthogonal distances and removing deceleration data furthest away in orthogonal distance from the quadratic equation if the predetermined condition is not satisfied.

A computing system implements a telematics service that obtains a set of vehicle telematics data for each vehicle of a population. Within each set of vehicle telematics data, a set of time-based measurements for a measurement type is identified. The set of time-based measurements identified for each vehicle are combined to obtain a combined set of time-based observations for the measurement type across the population of vehicles or a sub-set of the population defined by vehicle make, model, and/or year of production. An outlier observation is identified from among the combined set of time-based observations. A determination is made whether the outlier observation is part of a temporary deviation or a persistent deviation. For a temporary deviation, an impact of the outlier observation on the set of time-based measurements is reduced. For a persistent deviation, the outlier observation is programmatically characterized.

A sensor system and method includes first and second sensing elements, digital sensors, a host computer and a digital bus. The first sensing element is configured to collect first sensor data and the second sensing element is configured to collect second sensor data. The digital sensor includes a controller that is configured to receive the first and second sensor data and process the first sensor data together with the second sensor data to generate processed data. The host computer is configured to receive the processed data from the digital sensor over the digital bus.

An example method includes receiving, at a computing system, a first user input from a user interface during operation of a vehicle and responsive to receiving the first user input, determining a time of reception for the first user input. The method further includes receiving a first set of parameters from the vehicle that correspond to a first parameter identifier (PID). The method also includes determining a time of reception for each parameter, and based on the time of reception for the first user input and the time of reception for each parameter of the first set of parameters, determining a first temporal position for an indicator configured to represent the first user input on a graph of the parameters corresponding to the first PID. The method further includes displaying, on a display interface, the graph of the parameters corresponding to the first PID with the indicator in the first temporal position.

A method and a system for monitoring an aircraft engine (2), including: acquisition and processing part (11) configured to collect a time signal of the exhaust gas temperature residual margin of the aircraft engine (2), acquisition and processing part (11) configured to smooth the time signal thus forming a first curve representing the temperature residual margin, acquisition and processing part (11) configured to identify decreasing pieces in the first curve, acquisition and processing part (11) configured to construct a second curve by concatenation of the decreasing pieces, the second curve being continuous while being restricted to the decreasing pieces of the first curve, acquisition and processing part (11) configured to construct a prediction model from the second curve to determine at least one failure forecast indicator.

A method, system, and device for diagnosing an anomaly of a monitored component in a drive train, the method including: obtaining original data based on samples of a tachometer signal; processing the original data to obtain rotational information; processing the original data to produce a sine spectrum; determining complex magnitudes of the sine spectrum; removing dominate torsional mode residuals from the complex magnitudes of the sine spectrum to produce a frequency spectrum; and determining a condition indicator from the frequency spectrum.

Systems, methods and non-transitory computer readable storage medium are provided for task-based health data monitoring relating to aircraft components of aircraft within an aircraft fleet. One method includes establishing a review item with a first data review state to create a review task relating to health data of an aircraft component, generating images relating to the review item for display on a display device, retaining the review item for monitoring responsive to receiving user input changing the first data review state of the review item to a second data review state, receiving new health data relating to the aircraft component and automatically resetting the review item from the second data review state to the first data review state responsive to receiving the new health data to create a new review task.

A computing system implements a telematics service that obtains a set of vehicle telematics data for each vehicle of a population. Within each set of vehicle telematics data, a set of time-based measurements for a measurement type is identified. The set of time-based measurements identified for each vehicle are combined to obtain a combined set of time-based observations for the measurement type across the population of vehicles or a sub-set of the population defined by vehicle make, model, and/or year of production. An outlier observation is identified from among the combined set of time-based observations. A determination is made whether the outlier observation is part of a temporary deviation or a persistent deviation. For a temporary deviation, an impact of the outlier observation on the set of time-based measurements is reduced. For a persistent deviation, the outlier observation is programmatically characterized.

Systems, methods and non-transitory computer readable storage medium are provided for task-based health data monitoring relating to aircraft components of aircraft within an aircraft fleet. One method includes establishing a review item with a first data review state to create a review task relating to health data of an aircraft component, generating images relating to the review item for display on a display device, retaining the review item for monitoring responsive to receiving user input changing the first data review state of the review item to a second data review state, receiving new health data relating to the aircraft component and automatically resetting the review item from the second data review state to the first data review state responsive to receiving the new health data to create a new review task.

Systems and methods are provided for task-based health data monitoring relating to aircraft components of aircraft within an aircraft fleet. One method includes identifying health data of an aircraft component for potential monitoring based upon a condition indicator provided by a health and usage monitoring system, establishing a Review Item for the health data of the aircraft component having an initial data review state of New Data, thereby creating a Review Task, generating images of the Review Item for display and receiving an indication to change the data review state of the Review Item from New Data to Watch Data, receiving new health data relating to the aircraft component from the health and usage monitoring system and automatically resetting the data review state of the Review Item from Watch Data to New Data responsive to the receipt of the new health data, thereby creating a new Review Task.