Abstract: A data classification engine includes an interface configured to interface with an input source, where the input source includes sequential data points representative of a time-varying input signal and one or more processors adapted to receive a temporal sequence of data points at a time T, where the one or more processors are further adapted to receive a next sequential data point and facilitate discarding an oldest data point of the temporal sequence at a time T+1. The data classification engine further includes a matrix adapted to align, at time T, to successive temporal portions of the temporal sequence to generate a set of successive outputs from the temporal sequence and one or more memory modules adapted to store the set of successive outputs from the temporal sequence.

Abstract: A sensor apparatus includes an interface configured to interface and communicate with a network, a sensor unit configured to measure and report an output representative of a motion state for the sensor apparatus, memory and processing circuitry configured to execute operational instructions to receive the output signal from the sensor unit, where the output signal is representative of one of a plurality of motion states for the sensor unit and the output signal includes information sufficient to determine one or more changes to an environment associated with the sensor apparatus. The processing circuitry is configured to classify, via an artificial intelligence model, the output signal according to previously classified events to produce a classified output determine whether to transmit a notification to the network.

Abstract: An audio processing circuit includes an audio front end (AFE) configured to generate audio data in response to audio signals received from one or more microphones. One or more special purpose engines (SPEs) are configured to: generate prediction data via a usage model; generate bias adjustment data based on the prediction data; adjust a threshold of an audio event recognition engine based on the prediction data; and determine, via the audio event recognition engine and based on audio data, when an audio event is detected.