Abstract: A biosensor system determines analyte concentration from an output signal generated from a light-identifiable species or a redox reaction of the analyte. The biosensor system compensates at least 50% of the total error in the output signal with a primary function and compensates a portion of the remaining error with a residual function. The amount of error compensation provided by the primary and residual functions may be adjusted with a weighing coefficient. The compensation method including a primary function and a residual function may be used to determine analyte concentrations having improved accuracy from output signals including components attributable to error.

Abstract: Waveform analysis is performed to identify and characterize power-consuming devices operating on a building electrical circuit. Current waveforms are measured from the building circuit with electrical devices operating thereon. The waveforms are separated into wavelets and analyzed to identify a representative wavelet model which is transmitted to a server for analysis. The server compares the representative wavelet model to a predictive model built from waveform signatures of known electrical devices operating on a circuit. When the predictive model matches the representative wavelet model, the electrical devices contributing to the representative wavelet, their operating mode(s) (e.g., “on”, “off”, “paused”, “hibernating”) and/or their performance state(s) (e.g., normal operation, deterioration, or failure modes) can be identified. This information can be communicated as feedback to the consumer to facilitate more efficient and more cost-effective energy usage.

Abstract: Waveform analysis is performed to identify and characterize power-consuming devices operating on a building electrical circuit. Current waveforms are measured from the building circuit with electrical devices operating thereon. The waveforms are separated into wavelets and analyzed to identify a representative wavelet model which is transmitted to a server for analysis. The server compares the representative wavelet model to a predictive model built from waveform signatures of known electrical devices operating on a circuit. When the predictive model matches the representative wavelet model, the electrical devices contributing to the representative wavelet, their operating mode(s) (e.g., “on”, “off”, “paused”, “hibernating”) and/or their performance state(s) (e.g., normal operation, deterioration, or failure modes) can be identified. This information can be communicated as feedback to the consumer to facilitate more efficient and more cost-effective energy usage.