Neural network circuit for vehicle sensor signal processing

An electronic device, comprising:

• a sensor that is a tire pressure sensor or an accelerometer, wherein the sensor is physically coupled to a tire of a vehicle and configured to collect a temporal sequence of sensor data samples used to provide a plurality of first parallel data items;
• and
• a neural network circuit coupled to the sensor, wherein:
• the neural network circuit is configured to receive the plurality of first parallel data items via a plurality of first inputs and generate one or more output data items based on the plurality of first parallel data items;
• the one or more output data items indicate a condition of a road, the vehicle, or a component of the vehicle;
• and
• the neural network circuit further comprises:
• a digital-to-analog converter (DAC) configured to receive the plurality of first parallel data items via the plurality of first inputs and convert the plurality of first parallel data items into a plurality of analog input signals;
• a neural network core coupled to the DAC, the neural network core configured to convert the plurality of analog input signals to one or more analog output signals;
• and
• an analog-to-digital converter (ADC) coupled to the neural network core, the ADC configured to convert the one or more analog output signals to the one or more output data items.

A method for processing vehicle data, comprising:

• measuring, by a sensor, a temporal sequence of sensor data samples within a first temporal window having a temporal width and according to a sampling rate, wherein the sensor is physically coupled to a tire of a vehicle and includes a tire pressure sensor and/or an accelerometer;
• obtaining the temporal sequence of sensor data samples collected by the sensor;
• converting the temporal sequence of sensor data samples into a plurality of first parallel data items;
• applying the plurality of first parallel data items to a plurality of first inputs of a neural network circuit;
• and
• generating, by the neural network circuit, one or more output data items based on the plurality of first parallel data items, wherein:
• the one or more output data items correspond to the first temporal window;
• and
• the one or more output data items indicate a condition of a road, the vehicle, or a component of the vehicle.

An electronic device, comprising:

• a sensor that is a tire pressure sensor or an accelerometer, wherein the sensor is physically coupled to a tire of a vehicle and configured to collect a temporal sequence of sensor data samples used to provide a plurality of first parallel data items;
• and
• a neural network circuit that is coupled to the sensor and includes a plurality of operational amplifiers and a plurality of resistors, wherein:
• each amplifier of the neural network circuit forms a respective neuron circuit with a subset of resistors to implement a respective neuron of a neural network;
• resistances of the plurality of resistors depend on weights associated with neuron inputs of the respective neuron of the neural network;
• the neural network circuit is configured to receive the plurality of first parallel data items via a plurality of first inputs and generate one or more output data items based on the plurality of first parallel data items;
• and
• the one or more output data items indicate a condition of a road, the vehicle, or a component of the vehicle.