Abstract: Methods and systems for predicting electromechanical device failure are disclosed. In an example method, an analytic model, configured to implement predictive diagnostics for an electromechanical device, may be provided. Sensor data may be received from the electromechanical device, which may comprise a plurality of time series for a sensor-measurable parameter associated with operation of the electromechanical device. One or more machine learning processes may be used to update the analytic model. The one or more machine learning processes may comprise determining one or more data anomalies in the plurality of time series. The updated analytic method may be deployed to implement updated predictive diagnostics for the electromechanical device.

Abstract: An apparatus and system are provided for delivering communication services such as video, data and telephony services to individual residential units. According to one embodiment, an optical network terminal (ONT) for providing communication services to a single residential unit comprises a passive optical network interface (PI) circuit, a residential service interface (RSI) circuit, and a power unit. The PI circuit receives optical signals from an optical fiber and transmits optical signals onto the optical fiber. The PI circuit is adapted to convert received optical signals containing voice information to electrical voice ATM cells, received optical signals containing data information to electrical data ATM cells, and received optical signals containing video signals to electrical video signals. The PI circuit is also adapted to convert electrical voice ATM cells and electrical data ATM cells to optical signals for transmission over the optical fiber.