Abstract: Systems and methods for transferring learning in sensor devices. Historical time-series measurement samples of one or more parameters associated with a biological function being monitored by the sensor device are received and assigned to clusters. Feature data extracted from the historical time-series measurement samples are used to generate cluster-specific source-domain classifiers for each cluster. Unlabeled time-series measurement samples of the one or more parameters associated with the biological function are received. A cluster-identifier is assigned to each unlabeled target-domain sample, the cluster-identifier including information identifying a cluster-specific source-domain classifier associated with the unlabeled target-domain sample.

Abstract: A product authentication system includes one or more image capture devices that provide video data representative of an enhanced safety environment. The product authentication system can determine the continuous presence of a designated product during a time period, for example, during performance of a task in an enhanced safety environment. The video data can be spatiotemporally sliced according to multiple orientations with respect to the time axis and the two spatial axes. A plurality of data streams are created In where the slices of each respective data stream have the same orientation. The data streams are processed according to one or more machine learning models, such as convolutional neural networks trained to determine whether the designated product is continuously present in the video data. An indicator of the continuous presence of the designated product can be provided to a downstream system and used to indicate whether functions of the downstream system are to be performed.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: Systems and methods for monitoring the condition of an air filter installed in an HVAC system and for monitoring the condition of the HVAC system. The monitoring system includes a processing unit configured to receive data representative of at least a first temporal parameter of the HVAC system. The processing unit can process the data to obtain an indication of the condition of the air filter and can also process the data to obtain an indication of the condition of the HVAC system.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: Systems and methods for detecting the quality of signals captured by a sensor device monitoring a biological function. Sensor data associated with the sensor device is received, the sensor data representing time-series measurement samples of one or more parameters associated with the biological function, the sensor data including usable and unusable samples of the time-series measurements. Data representing two or more features of samples of the time-series measurements is extracted and filtered to reduce outliers in the extracted data based on an expected outlier ratio. A machine learning algorithm is then trained to identify events based on the filtered extracted data.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: In an example, a system comprises at least one body-worn tracking device (BWTD) configured to transmit location data that indicates a location of the BWTD and a computing system configured to communicate with the at least one BWTD. The computing system is configured to receive the location data from the at least one BWTD, determine, based on a set of weighted filters associated with at least one monitoring attribute, at least one gradient value corresponding to the location data, where the at least one gradient value represents a level of the at least one monitoring attribute, and perform at least one operation based on the at least one gradient value.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.