In one illustrative configuration, an air quality monitoring system may enable wide-scale deployment of multiple air quality monitors with high-confidence and actionable data is provided. Further, the air quality monitoring system may enable identifying a target emission from a plurality of potential sources at a site based on simulating plume models. The simulation of plume models may take into consideration various simulation parameters including wind speed and direction. Further, methods of determining a plume flux of a plume of emissions at a site, and methods of transmitting data from an air quality monitor are disclosed.

Methods for reversing determination for a vehicle asset are provided. The methods include capturing by a telematics device coupled to the vehicle acceleration data from a three-axis accelerometer, determining by a reversing-determination machine learning mode, a machine-learning-determined reversing indication for the vehicle asset. The reversing-determination machine-learning model being trained by a vehicle reversing indication comprising a vehicle speed and a reverse gear indication.

An electronic rotary encoder is configured to be disposed on a vertical rotary shaft in a rotary object to obtain two encoded signals: a phase A signal and a phase B signal for calculating a rotational speed and a position. The electronic rotary encoder includes: at least one Hall element outputting Hall signals used as a square wave of the phase A signal; two capacitors, to respectively obtain a first voltage and a second voltage; two buffer gates, to respectively output waveform signals of a first X voltage and a second X voltage; two comparators outputting, a control signal through a latch; and an exclusive OR gate, where a direction signal and the control signal outputted through the latch are inputted to the exclusive OR gate, to obtain the phase B signal.

The inventive concept provides a wafer type sensor unit which acquires data on a wind direction and a wind velocity of an air flow during processing, the wafer type sensor unit supported by a supporting unit of a substrate processing apparatus. The unit comprising a wafer-shaped circuit board and a hot-wired wind velocity sensor placed apart from an upper surface of the circuit board.

Systems, devices, and methods for: an unmanned aerial vehicle (UAV); at least one sensorless motor of the UAV, the at least one sensorless motor comprising a set of windings and a rotor; at least one propeller connected to the at least one sensorless motor; a microcontroller in communication with the at least one sensorless motor, wherein the microcontroller is configured to: determine a rotation rate of the at least one propeller; determine a rotation direction of the at least one propeller; provide an output to stop the at least one propeller if at least one of: the determined rotation rate is not a desired rotation rate and the determined rotation direction is not a desired rotation direction; and provide an output to start the at least one propeller if the at least one propeller is stopped at the desired rotation rate and the desired rotation direction.

An electronic watch includes a housing and a crown assembly including a rotatable actuation member. The rotatable actuation member includes a knob external to the housing and configured to receive a rotational input and a shaft assembly coupled to the knob and positioned at least partially within the housing, the shaft assembly defining a sensing surface configured to rotate in response to the rotational input. The electronic watch further includes an optical sensing system configured to detect the rotational input, the detecting including directing light onto the sensing surface, receiving reflected light from the sensing surface, and producing a signal corresponding to a rotational motion of the sensing surface, the signal based at least in part on an interference between the light directed onto the sensing surface and the reflected light.

Methods for reversing determination for a vehicle asset are provided. The methods include capturing by a telematics device coupled to the vehicle acceleration data from a three-axis accelerometer, determining by an edge reversing-determination machine learning mode, a machine-learning-determined reversing indication for the vehicle asset. The edge reversing-determination machine-learning model being updated based on a centralized reversing-determination machine-learning model trained using a vehicle-provided reversing indication.

In one embodiment, a method includes receiving, by a controller, one or more signals from the one or more pressure transducers. The one or more pressure transducers are coupled to one or more pressure lines, the one or more pressure lines are coupled to one or more probes, and the one or more probes coupled to a vehicle. The method also includes converting, by the controller, the one or more signals to one or more digital signals. The method further includes calculating, by the controller, a wind velocity relative to the vehicle using the one or more digital signals.

A rotation sensor system includes a rotatable target object configured to rotate about a rotational axis in a rotation direction; a first millimeter-wave (mm-wave) metamaterial track coupled to the rotatable target object, where the first mm-wave metamaterial track is arranged around the rotational axis, and where the first mm-wave metamaterial track includes a first array of elementary structures having at least one first characteristic that changes around a perimeter of the first mm-wave metamaterial track; at least one transmitter configured to transmit a first electro-magnetic transmit signal towards the first mm-wave metamaterial track, where the first mm-wave metamaterial track converts the first electro-magnetic transmit signal into a first electro-magnetic receive signal; at least one receiver configured to receive the first electro-magnetic receive signal; and at least one processor configured to determine a rotational parameter of the rotatable target object based on the received first electro-magnetic receive signal.

A method for determining a speed using a measurement-sensor in a vehicle, the measurement-sensor including at least one coil and a ferromagnetic-transmitter-element, including: changing the inductance of the coil, using an inductive-speed-sensor having at least the coil and the ferromagnetic-transmitter-element; recording a change in the coil inductance, and determining the speed based on the changed coil inductance; in which in each case one inductive-speed-sensor is a wheel-speed-sensor for at least two vehicle wheels, and in which a reversal of the direction of movement of the ferromagnetic-transmitter-element as to the coil or a reversal of the direction of travel of the vehicle from forward travel to reverse travel or from reverse travel to forward travel is recognized based on at least one temporal-phase-offset of the temporal-profiles of the inductances recorded by the wheel-speed-sensors of the at least two wheels. Also described is a related driver assistance system and vehicle.