Disclosed is a method including receiving a depth map estimated using data based on image and data received from a movement sensor as input, generating an alignment parameter based on the depth map, adding the alignment parameter to a pre-calibration state to define a user operational calibration state, generating scale parameters and shift parameters based on features associated with the data received from the image and movement sensor, and calibrating the image and movement sensor based on the user operational calibration state, the scale parameters and the shift parameters.

Disclosed is a method including receiving a depth map estimated using data based on image and data received from a movement sensor as input, generating an alignment parameter based on the depth map, adding the alignment parameter to a pre-calibration state to define a user operational calibration state, generating scale parameters and shift parameters based on features associated with the data received from the image and movement sensor, and calibrating the image and movement sensor based on the user operational calibration state, the scale parameters and the shift parameters.

The present disclosure relates to a contextual service device and method of use to identify an operator's needs, such as in the event a vehicle crash, vehicle breakdown, theft, and/or vehicle related quarry in real time. In various aspects, the device is self-sufficient and may be installed and activated in a single step. Furthermore, the device is not reliant upon external systems of components of the vehicle to operate and may be updated over the air to improve cash detection accuracy.

The present disclosure relates to a contextual service device and method of use to identify an operator's needs, such as in the event a vehicle crash, vehicle breakdown, theft, and/or vehicle related quarry in real time. In various aspects, the device is self-sufficient and may be installed and activated in a single step. Furthermore, the device is not reliant upon external systems of components of the vehicle to operate and may be updated over the air to improve cash detection accuracy.

Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification. A computing platform may receive first source data comprising driving data associated with a vehicle over a time period. Based on the first source data, the computing device may determine that the vehicle experienced an event, resulting in an event output. In response to determining the event output, the computing device may generate a request for second source data associated with the vehicle over the time period. The computing device may receive, from a sensor device, the second source data. Based on a comparison of the first source data to the second source data, the computing platform may determine an event comparison output. The computing platform may determine that the event comparison output exceeds a predetermined comparison threshold, and may send an indication of an event in response.

A thermal regulation system includes a sensor, one or more temperature adjusting devices, and a filler provided in a space between the sensor and at least one of the one or more temperature adjusting devices. The one or more temperature adjusting devices are (1) in thermal communication with the sensor, and (2) configured to adjust a temperature of the sensor from an initial temperature to a predetermined temperature at a rate of temperature change that meets or exceeds a threshold value.

A thermal regulation system includes a sensor, one or more temperature adjusting devices, and a filler provided in a space between the sensor and at least one of the one or more temperature adjusting devices. The one or more temperature adjusting devices are (1) in thermal communication with the sensor, and (2) configured to adjust a temperature of the sensor from an initial temperature to a predetermined temperature at a rate of temperature change that meets or exceeds a threshold value.

A signal processing method includes receiving a signal that rises in response to a physical change and falls in response to an opposite physical change that is opposite to the physical change from a sensor that is a stretchable sensor and outputs the signal, and correcting a signal lag as either a rising of a received signal that has been received from the sensor lags with respect to a falling of the received signal, or the falling of the received signal lags with respect to the rising of the received signal.

An example system comprising: a microelectromechanical system (MEMS) vibrating beam accelerometer (VBA) comprising: a proof mass; and a first resonator mechanically coupled to the proof mass; a first electrode configured to apply a force to the proof mass.

An example system comprising: a microelectromechanical system (MEMS) vibrating beam accelerometer (VBA) comprising: a proof mass; and a first resonator mechanically coupled to the proof mass; a first electrode configured to apply a force to the proof mass.