Abstract: The present disclosure is directed to a device configured to detect whether the device is in a bag or outside of the bag. The device determines whether the device is in or outside of the bag based on distance measurements generated by at least one proximity sensor and motion measurements generated by at least one motion sensor. By using both distance measurements and motion measurements, the device is able to detect whether the device is in the bag or outside of the bag with high accuracy and robustness.

Abstract: A device includes a charge variation sensor having at one or more electrodes. The charge variation sensor, in operation, generates a charge variation signal indicative of changes in an electric or electrostatic charge induced on the one or more electrodes by an alternating current power source. Processing circuitry, coupled to the charge variation sensor, generates a frequency spectrum signal based on the charge variation signal and identifies a frequency of operation associated with the alternating current power source based on the generated frequency spectrum signal. A control signal is generated based on the identified frequency of operation. An image acquisition device sets an image acquisition frequency based on the control signal.

Abstract: A system includes inertial sensors and a GPS. The system generates a first estimated vehicle velocity based on motion data and positioning data, generates a second estimated vehicle velocity based on the processed motion data and the first estimated vehicle velocity, and generates fused datasets indicative of position, velocity and attitude of a vehicle based on the processed motion data, the positioning data and the second estimated vehicle velocity. The generating the second estimated vehicle velocity includes: filtering the motion data, transforming the filtered motion data in a frequency domain based on the first estimated vehicle velocity, generating spectral power density signals, generating an estimated wheel angular frequency and an estimated wheel size based on the spectral power density signals, and generating the second estimated vehicle velocity as a function of the estimated wheel angular frequency and the estimated wheel size.

Abstract: An electronic device has sensing circuitry and control circuitry. The control circuitry generates, based on generated sensor data, information indicative of movement of the electronic device. The control circuitry generates control signals to control operation of the electronic device in a plurality of power states, including a working-power state, an intermediate-power state and a low-power state, based on the information indicative of movement.

Abstract: A microelectromechanical weather pattern recognition system includes: at least one movement sensor, of a MEMS type, which generates a movement signal, in the presence and as a function of at least one weather pattern to be recognized; and a recognition circuitry, which is coupled to the movement sensor and which receives the movement signal; extracts given features of the movement signal; and perform processing operations, based on the given features of the movement signal, in order to recognize the weather pattern by executing at least one, appropriately trained, machine-learning algorithm.

Abstract: A device for generating a control signal based on the linear movement of a linear member is provided. The device includes a linear member, a rotatable member, a first inertial measurement unit (IMU) coupled to the rotatable member and a second IMU having a fixed position. The device also includes a processing circuit which uses sensing signals from the IMUS to determine an attitude of the first IMU referenced to the second IMU and generate a control signal based on the attitude.

Abstract: A device including microelectromechanical systems (MEMS) sensors are used in dead reckoning in conditions where Global Positioning System (GPS) signals or Global Navigation Satellite System (GNSS) signals are lost. The device is capable of tracking the location of the device after the GPS/GNSS signals are lost by using MEMS sensors such as accelerometers and gyroscopes. By calculating a misalignment angle between a forward axis of a sensor frame of the device and a forward axis of a vehicle frame using the data received from the MEMS sensors, the device can accurately calculate the location of a user or the vehicle of the device even without the GPS/GNSS signals. Accordingly, a device capable of tracking the location of the user riding in the vehicle in GPS/GNSS signals absent environment can be provided.