Abstract: Systems, methods, and other embodiments associated with off-duty-cycle-robust machine learning for anomaly detection in assets with random downtimes are described. In one embodiment, a method includes inferring ranges of asset downtime from spikes in a numerical derivative of a time series signal for an asset; extracting an asset downtime signal from the time series signal based on the inferred ranges of asset downtime; determining that the asset downtime signal carries telemetry based on the variance of the asset downtime signal; training a first machine learning model for the asset downtime signal; detecting a first spike in the numerical derivative of the time signal that indicates a transition to asset downtime; and in response to detection of the first spike, monitoring the time series signal for anomalous activity with the trained first machine learning model.

Abstract: A system is provided that detects a card skimmer in a target system, wherein the card skimmer surreptitiously gathers credit/debit card information during operation of the target system. This system first gathers target electromagnetic interference (EMI) signals by monitoring EMI signals generated by the target system through an external scanner with a directional antenna. Next, the system generates a target EMI fingerprint from the target EMI signals. The system then compares the target EMI fingerprint against a reference EMI fingerprint for the target system to determine whether the target system contains a card skimmer.

Abstract: A user interface having a plurality of user interface elements including: background, passive elements such as frames and borders, information display elements that present information from application software operating on the control unit, and control elements that cause application software operating on the control unit to initiate programmed behaviors. The user interface as a whole is contextually sensitive in that the appearance of user interface elements (e.g., color, size, font, contrast, order, grouping, arrangement, etc.) and/or the behavior of user interface elements are varied in a manner that is dependent on the context of the control unit. The context of the control unit is represented by state information known to the control unit, which includes context-specific state information known to a particular control unit as well as global context information known to multiple or all control units in a system.

Abstract: A home automation and control architecture that includes one or more controlled devices and one or more control panels coupled by a communication network. Each of the controlled devices is directly coupled to at least one control panel and configured to communicate control information with the coupled panel. The control panels comprise sufficient computing resources for implementing a user interface and executing application software to generate control messages based on user input and/or context information of which the control panel is aware. A message broker implemented within the pone or more control panels conveys control messages from a first control panel that initiates the control message to one or more other control panels that implement the control message.

Abstract: A user interface having a plurality of user interface elements including: background, passive elements such as frames and borders, information display elements that present information from application software operating on the control unit, and control elements that cause application software operating on the control unit to initiate programmed behaviors. The user interface as a whole is contextually sensitive in that the appearance of user interface elements (e.g., color, size, font, contrast, order, grouping, arrangement, etc.) and/or the behavior of user interface elements are varied in a manner that is dependent on the context of the control unit. The context of the control unit is represented by state information known to the control unit, which includes context-specific state information known to a particular control unit as well as global context information known to multiple or all control units in a system.