The invention introduces a method for data synchronization between a sensor hub and an application processor, which contains at least the following steps: generating and adding a plurality of absolute time stamps in a sensor-data stream; and generating and adding a plurality of pieces of sensor data and a plurality of relative time stamps in the sensor-data stream between the moments of generating each two adjacent absolute time stamps, wherein each relative time stamp is associated with one piece of sensor data.

Systems, apparatuses, and methods described herein are configured for monitoring and managing a plurality of sensors. The plurality of sensors may be fixed, mobile, or a combination thereof. In some embodiments, the monitoring and management of the sensors is facilitated via a graphical user interface.

A system learns to automatically identify, and detect, contextual conditions that may serve as action triggers to help please a user (or avoid annoying a user). Among other features, a simple sensor arrangement is detailed which, in addition to producing a customary stream of high bandwidth sensor data, provides an output of low bandwidth data. This low-bandwidth data serves to identify a particular reference pattern with which the high-bandwidth sensor data is found to correspond. Such a sensor can employ reference patterns discovered through pseudo-random trials. A great number of other advantageous features and arrangements are also detailed.

A method of analyzing signal quality in order to determine the operational characteristics of a measuring device uses a sampling device to monitor and analyze signal data that is generates by a measuring device or encoder. The sampling device is used to calculate and transmit data that characterizes the signals being generated by the measuring device. The method enables a user to interact with the sampling device, and this user interaction is mediated by a remote server. The method employs the sampling device to constantly monitor the signal data and then generate alerts whenever the measuring device is exhibiting characteristics that do not meet predefined thresholds. The sampling device periodically publishes the calculated characteristic data. Thus, enabling the user to understand the operational characteristics of the measuring device and predict when maintenance should be performed. The method enables the user to execute specific signal analysis processes when performing diagnostic tests.

A method of analyzing signal quality in order to determine the operational characteristics of a measuring device uses a sampling device to monitor and analyze signal data that is generates by a measuring device or encoder. The sampling device is used to calculate and transmit data that characterizes the signals being generated by the measuring device. The method enables a user to interact with the sampling device, and this user interaction is mediated by a remote server. The method employs the sampling device to constantly monitor the signal data and then generate alerts whenever the measuring device is exhibiting characteristics that do not meet predefined thresholds. The sampling device periodically publishes the calculated characteristic data. Thus, enabling the user to understand the operational characteristics of the measuring device and predict when maintenance should be performed. The method enables the user to execute specific signal analysis processes when performing diagnostic tests.

The invention introduces a method for data synchronization between a sensor hub and an application processor, which contains at least the following steps: generating and adding a plurality of absolute time stamps in a sensor-data stream; and generating and adding a plurality of pieces of sensor data and a plurality of relative time stamps in the sensor-data stream between the moments of generating each two adjacent absolute time stamps, wherein each relative time stamp is associated with one piece of sensor data.

Systems, apparatuses, and methods described herein are configured for monitoring and managing a plurality of sensors. The plurality of sensors may be fixed, mobile, or a combination thereof. In some embodiments, the monitoring and management of the sensors is facilitated via a graphical user interface.

Provided are embodiments for method and system for performing an integrated ice protection with prognostics and health management using fiber optic sensors. Embodiments can include reading a signal from each sensor of an array of sensors installed on a surface of a structure or equipment, wherein each sensor is a fiber optic sensor, and generating a map based on reading the signal from each sensor, wherein the map monitors a condition of the surface detected by each sensor. Embodiments can also include determining at least one of an abnormal condition or a failure based at least in part on reading the signal from each sensor; and performing at least one of adjusting power control for the structure or equipment or communicating the abnormal condition or failure of the structure or equipment.

Provided are embodiments for method and system for performing an integrated ice protection with prognostics and health management using fiber optic sensors. Embodiments can include reading a signal from each sensor of an array of sensors installed on a surface of a structure or equipment, wherein each sensor is a fiber optic sensor, and generating a map based on reading the signal from each sensor, wherein the map monitors a condition of the surface detected by each sensor. Embodiments can also include determining at least one of an abnormal condition or a failure based at least in part on reading the signal from each sensor; and performing at least one of adjusting power control for the structure or equipment or communicating the abnormal condition or failure of the structure or equipment.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for enhanced sensors. One of the methods includes accessing i) data for a detected event that was detected using first sensor data captured by a first sensor at a property and ii) second sensor data captured by a second sensor for the property, the first sensor having a different type than the second sensor; providing, to an artificial intelligence model trained to determine whether to provide a notification about the detected event, the data for the detected event and the second sensor data to cause the artificial intelligence model to generate output; receiving, from the artificial intelligence model, the output that indicates whether to provide a notification about the detected event; and performing one or more actions using the output that indicates whether to provide a notification about the detected event.