Abstract: Methods and systems may provide for receiving a set of voltage samples corresponding to a line voltage of a leg in an electrical system and conducting a time domain analysis to identify one or more loads in the electrical system. Additionally, the time domain analysis may be used to identify one or more loads in the electrical system. In one example, conducting the time domain analysis involves classifying events with respect to cross correlation, shape magnitude, transient amplitude, transient duration, run delta and/or standard deviation.

Abstract: Methods and systems may provide for identifying, and distinguishing between electrical loads using time and frequency domain analysis of at least one property of an alternating current during a transient event. In one example, time and frequency domain features may be computed from the voltage signatures of an ON event. A support vector machine classifier may then be trained using the feature vectors (including the time and frequency domain features) for known devices. The trained support vector machine may classify or identify an unknown electrical device using a feature vector as input.

Abstract: Methods and systems may provide for identifying, and distinguishing between electrical loads using time and frequency domain analysis of at least one property of an alternating current during a transient event. In one example, time and frequency domain features may be computed from the voltage signatures of an ON event. A support vector machine classifier may then be trained using the feature vectors (including the time and frequency domain features) for known devices. The trained support vector machine may classify or identify an unknown electrical device using a feature vector as input.

Abstract: Methods and systems may provide for receiving a set of voltage samples corresponding to a line voltage of a leg in an electrical system and conducting a time domain analysis to identify one or more loads in the electrical system. Additionally, the time domain analysis may be used to identify one or more loads in the electrical system. In one example, conducting the time domain analysis involves classifying events with respect to cross correlation, shape magnitude, transient amplitude, transient duration, run delta and/or standard deviation.

Abstract: Methods and devices capable of measuring, analyzing, and monitoring electrical energy consumption of appliances and devices within a building are provided. Voltage sensors that are optionally connected to electrical socket outlets are employed within a building or section of a building to infer the identity of electricity-consuming devices and the amount of power the devices are consuming individually and collectively. Energy use inferencing devices according to embodiments of the invention provide ease of installation, simplicity, manageability, and ease-of-use that can engender deployment by electricity consumers, such as, home owners and businesses.

Abstract: Methods and devices capable of measuring, analyzing, and monitoring electrical energy consumption of appliances and devices within a building are provided. Voltage sensors that are optionally connected to electrical socket outlets are employed within a building or section of a building to infer the identity of electricity-consuming devices and the amount of power the devices are consuming individually and collectively. Energy use inferencing devices according to embodiments of the invention provide ease of installation, simplicity, manageability, and ease-of-use that can engender deployment by electricity consumers, such as, home owners and businesses.