TH99358A - Motion monitoring equipment - Google Patents

Abstract

------October 22, 2020------(OCR) This invention, DC60, is a device for detecting the movement of objects such as humans or vehicles. It relies on both frequency and temporal analysis of signals to differentiate between human walking and vehicle movement. It uses a small, low-power microcontroller and employs Fast Fourier Transform (FFT) frequency classification, eliminating the need for electronic filters. This provides flexibility in defining the frequency range and allows for the selection and analysis of multiple frequency bands, resulting in more detailed signal analysis. The analysis is compared to a database containing data on human walking and vehicle movement on various surfaces such as sand and cement. The movement of vehicles on various surfaces such as sand and cement is monitored by this invention. The device, designed to detect the movement of objects like humans or vehicles, relies on both frequency and temporal signal analysis to differentiate between human stepping and vehicle movement. It utilizes a small, low-power microcontroller and employs Fast Fourier Transform for frequency classification. This requires an electronic filter, offering flexibility in defining frequency ranges and allowing for the selection and analysis of multiple frequency bands. Consequently, more detailed signal analysis is achieved by comparing data to a database containing information on human stepping and vehicle movement on various surfaces.

Claims (5)

------October 22, 2020------(OCR) 1. Surface motion monitoring device consisting of: a vibration sensor (Geophone) that measures the level of vibration on the detected surface, providing an electrical signal with a frequency and voltage level corresponding to the vibration; an amplifier that amplifies the voltage received from the vibration sensor; a band-pass filter that filters frequencies within a predetermined range to reduce noise; and a control unit with a database containing samples of human gait patterns, vehicle movement, and surface types. This unit receives the amplified and filtered electrical signal from the vibration sensor to classify the type of detected object. Its specific characteristics include: 0. A signal level detection path that makes an initial decision whether the received vibration signal is actual vibration of an object within the detection radius or is due to environmental disturbance. 0. A temporal analysis path that performs temporal analysis to classify whether the signal from the seismic sensor represents a specific type of movement or another event. In addition to the required methods, the patent includes: 1. A Fast Fourier Transform (FFT) method for converting the received signal into signal strength levels separated by different frequency ranges. 2. A frequency analysis method for frequency analysis that uses frequency calculation data from the aforementioned Fast Fourier Transform method to compare with reference frequency patterns to find the probability of various data patterns occurring. 3. A decision method for classifying objects by weighing data obtained from Time Domain Analysis and Frequency Domain Analysis and the aforementioned database table to determine the overall probability of the data occurring. 4. A device according to claim 1 that also includes an analog-to-digital converter circuit for converting the filtered electrical signal from the vibration sensor into a digital signal. 5. A device according to claim 2 where the calculated digital signal is compared to a threshold value of the signal voltage level. If it exceeds the set value, it is considered a signal generated by vibration. and will trigger other functions as well. 4. The device according to claim 3, where the control unit automatically sets the threshold value. If no movement or signal level is detected on the ground for a certain period of time, the control unit will set the threshold lower. However, if a high signal level is detected on the ground for an extended period, the threshold will be set higher. 5. The device according to claim 1, where the control unit analyzes the frequency to find the difference between signals generated by human walking and vehicle movement, using the Fast Fourier Transform (FFT) mathematical calculation to separate the frequencies and normalize the strength of each frequency against values stored in a database table. This also incorporates characteristics such as walking time, vehicle movement, and soil type properties into the decision-making process. 6. The device according to claim 1, where the band-pass filter filters frequencies in the range of 10 Hz to 100 Hz. 7. The device according to claim 1, where the temporal analysis method determines the type of signal movement. Or it may originate from events other than those desired, such as other types of movement not considered walking or vehicles, like falling branches, fruit, or the vibration of tree roots due to wind. These types of signals, in addition to frequency analysis, can also be analyzed using temporal analysis for decision-making, as they have different occurrence periods and durations (length and intensity change per unit time) compared to signals from walking or vehicles. 8. An apparatus under claim 1 where the Fast Fourier Transform path operates in the frequency ranges of 16.7 Hz, 33.3 Hz, 50.0 Hz, 66.7 Hz, 83.3 Hz, and 100.0 Hz. 9. An apparatus under claim 1 where the frequency analysis path compares the received frequency pattern to a predefined reference pattern to determine the probability of various data patterns occurring, namely walking, vehicle movement, and environmental disturbances such as rain, falling objects, wind, and tree roots swaying. These will have different spectral patterns. 1. Surface motion monitoring device, consisting of: • A geophone sensor that measures vibration levels on the detected surface, outputting an electrical signal with a frequency and voltage corresponding to the vibration. • An amplifier that amplifies the voltage received from the geophone sensor. • A band-pass filter that filters frequencies within a predetermined range to reduce noise. • A control unit with a database containing samples of human gait, vehicle movement, and surface type. This unit receives the amplified and filtered electrical signals from the geophone sensor to classify the type of detected object. Its specific characteristics include: O A signal detection path that makes an initial decision whether the received vibration signal is actual vibration from an object within the detection radius or is due to environmental disturbance. O A temporal analysis path that performs temporal analysis to determine whether the signal from the seismic sensor represents a specific type of movement or is caused by another event. Beyond the required methods, there are: O A method for using the Fast Fourier Transform (FFT) to transform received signals into signal strength levels separated by different frequency ranges. O A frequency analysis method for frequency analysis that uses frequency calculation data from the aforementioned Fast Fourier Transform method to compare with a reference frequency pattern to find the probability of various data patterns occurring. And O A decision-making method for classifying objects by weighing data obtained from Time Domain Analysis (DDO) and Frequency Domain Analysis (FDO) and the aforementioned database to determine the overall probability of the data occurring. 2. The device under claim 1, which also includes an analog-to-digital converter circuit for converting the filtered electrical signal from the aforementioned vibration sensor into a digital signal. 3. Device: Under claim 2, the calculated digital signal value is compared to a threshold value of the signal voltage level. If it exceeds the set value, it is considered a vibration signal and will trigger other functions. 4. The device under claim 3, controlled by the said control unit, will automatically set the threshold value. If no movement or signal level is detected on the ground for a certain period of time, the control unit will lower the threshold value. If a high signal level is detected on the ground for an extended period, the threshold value will be set higher. 5. The device under Claim 1, where the control unit performs frequency analysis to determine the difference between signals generated by human walking and vehicle movement, uses Fast Fourier Transform (FFT) mathematical calculations to separate frequencies and normalize the strength of each frequency against values stored in a database. It also incorporates characteristics such as walking time, vehicle movement, and soil type properties into the decision-making process.