A movement distance calculation device includes: a first movement distance calculation unit which calculates a first movement distance of a movable body based on plural rotation speeds of plural wheels of the movable body and a steering angle of the movable body; a vector detection unit which detects a movement vector of an object included in the acquired images as defined herein; a second movement distance calculation unit which calculates a second movement distance of the movable body based on the movement vector; a first reliability determining unit which determines reliability of the calculated first movement distance as defined herein; a second reliability determining unit which determines reliability of the calculated second movement distance as defined herein; and a movement distance determining unit which determines a movement distance using at least one of the calculated first movement distance and the calculated second movement distance as defined herein.

Speed and acceleration calculation and measuring methods and devices based on a regularization algorithm are disclosed. Speed and acceleration are calculated using the following steps: (1) acquiring position data or displacement data; and (2) using the position data or displacement data to calculate the speed and the acceleration with a disclosed regularization method. The disclosed methods and systems avoid the issue of noise amplification that arises when speed and acceleration are measured by existing speed and acceleration devices at high sampling rates. Noise amplification is prevented by first expressing the relationship between position data or displacement data and speed or acceleration into a typical Volterra integral equation of the first kind, and then using the disclosed regularization method to calculate speed and acceleration, thus suppressing noise amplification and accurately extracting speed and acceleration signal values.

Speed and acceleration calculation and measuring methods and devices based on a regularization algorithm are disclosed. Speed and acceleration are calculated using the following steps: (1) acquiring position data or displacement data; and (2) using the position data or displacement data to calculate the speed and the acceleration with a disclosed regularization method. The disclosed methods and systems avoid the issue of noise amplification that arises when speed and acceleration are measured by existing speed and acceleration devices at high sampling rates. Noise amplification is prevented by first expressing the relationship between position data or displacement data and speed or acceleration into a typical Volterra integral equation of the first kind, and then using the disclosed regularization method to calculate speed and acceleration, thus suppressing noise amplification and accurately extracting speed and acceleration signal values.

Earthquake detector is a solid-state device that detects the motion of a building or structure and initiates an alarm when the motion of a building or structure rises above a certain base level or threshold level of motion that is automatically calibrated or manually entered for the specific building or structure and the specific location of the building or structure. Earthquake detector measures the amplitude of movement and the magnitude of acceleration of the actual building or structure caused by a seismic event, earthquake, or other external force because this is the primary cause of damage to the building or structure and the associated potential for collapse of the building or structure. Earthquake detector has a circuit board; a microprocessor, integrated circuit, or chip; an accelerometer integrated circuit or chip; an alarm module; a connection to a power source; and a calibration control.

An exemplary method includes vehicle-mounted sensors continuously detecting vehicle speed and vehicle tire and steering vibrations; a processor implementing a machine-learning program that continuously monitors signals from the vehicle-mounted sensors and compares detected vehicle tire and steering vibrations to upper bounds corresponding to detected vehicle speed; and the processor alerting a vehicle driver that wheel or tire service is required based on the detected vehicle tire and steering vibrations exceeding the upper bounds. An exemplary apparatus includes a vehicle; tires mounted to the vehicle; a speed sensor mounted to the vehicle; a vibration sensor mounted to the vehicle; and a processor connected in communication with the speed sensor and the vibration sensor. The processor is adapted to implement any of the method steps above.

An exemplary method includes vehicle-mounted sensors continuously detecting vehicle speed and vehicle tire and steering vibrations; a processor implementing a machine-learning program that continuously monitors signals from the vehicle-mounted sensors and compares detected vehicle tire and steering vibrations to upper bounds corresponding to detected vehicle speed; and the processor alerting a vehicle driver that wheel or tire service is required based on the detected vehicle tire and steering vibrations exceeding the upper bounds. An exemplary apparatus includes a vehicle; tires mounted to the vehicle; a speed sensor mounted to the vehicle; a vibration sensor mounted to the vehicle; and a processor connected in communication with the speed sensor and the vibration sensor. The processor is adapted to implement any of the method steps above.

A measurement apparatus is equipped with a processor. The processor acquires first velocity data, which is data on a velocity in a first direction, and second velocity data, which is data on a velocity in a second direction orthogonal to the first direction, on the basis of accelerations acquired at an acceleration sensor. The processor calculates a first coefficient on the basis of the acquired first velocity data and the acquired second velocity data. The processor determines whether the measurement apparatus is installed in normal orientation on the basis of the calculated first coefficient.

A measurement apparatus is equipped with a processor. The processor acquires first velocity data, which is data on a velocity in a first direction, and second velocity data, which is data on a velocity in a second direction orthogonal to the first direction, on the basis of accelerations acquired at an acceleration sensor. The processor calculates a first coefficient on the basis of the acquired first velocity data and the acquired second velocity data. The processor determines whether the measurement apparatus is installed in normal orientation on the basis of the calculated first coefficient.

A device of or attached to a roller body determines a rotational frequency of the roller body (or other object) rotating about an axis of rotation includes an acceleration sensor that detects an acceleration signal of an acceleration in a first direction extending in a radial or tangential direction to the axis of rotation of the roller body; and an electronic processing unit and configured to low-pass and high-pass, particularly adaptively high-pass filter, the detected acceleration signal, perform a derivation, with respect to time, of the filtered signal, optimize the signal with a subsequent absolute-amount generation and with moving averaging, and ascertain a frequency of the filtered acceleration signal, which corresponds to the rotational frequency of the roller body.

A motion measurement apparatus according to an embodiment of the present technology includes a detector unit, a controller unit, and an output unit. The detector unit is to be attached to a detection target and detects velocity-related information, the velocity-related information being related to temporal changes in velocities in three-axis directions of the detection target being in motion in a space. The controller unit extracts a motion feature amount including one or a plurality of kinematic physical quantities of the detection target on the basis of the velocity-related information. The output unit generates a perceivable measurement signal that changes depending on the motion feature amount.