Synchronization method and system based on spatio-temporal data of moving object

Abstract

The invention discloses a synchronization method and system based on spatio-temporal data of a moving object. The method relates to the technical field of moving object spatio-temporal data processing, and comprises the following steps: acquiring a spatio-temporal data module; analyzing the spatio-temporal data of the moving object; and comprehensively analyzing, optimizing and adjusting the spatio-temporal data synchronization method of the moving object. The mobile object time synchronization risk assessment index and the mobile object image quality assessment index are obtained by collecting and processing the mobile object time-space data and analyzing the mobile object time-space data, and synchronization of the mobile object time-space data is comprehensively analyzed, optimized and adjusted. The accuracy of the synchronization method based on the spatio-temporal data of the moving object is improved, and the problem of insufficient accuracy of the synchronization method based on the spatio-temporal data of the moving object in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of moving object spatiotemporal data processing, and in particular to a synchronization method and system based on moving object spatiotemporal data. Background Art

[0002] With the popularization of the Internet and the development of mobile communication technology, the speed and capacity of information transmission have been greatly improved, providing a basis for the real-time synchronization of spatiotemporal data of mobile objects. The Internet of Things technology enables various devices to connect to each other and exchange data, thereby promoting the data collection and synchronization of mobile objects. In order to solve traffic congestion and improve road safety, intelligent transportation systems need to synchronize and analyze the spatiotemporal data of a large number of mobile objects in real time. Synchronizing the spatiotemporal data of moving objects is helpful to monitor environmental changes, such as animal migration, pollution diffusion, etc. Synchronized spatiotemporal data will help urban planners better understand urban dynamics and achieve more efficient and humane urban planning.

[0003] Existing synchronization methods and systems based on spatiotemporal data of moving objects are used to process and predict sequence data through machine learning and deep learning technologies, which are suitable for dynamic analysis of spatiotemporal data; through high spatiotemporal fusion methods, high spatial resolution and high temporal resolution data are combined to solve the spatiotemporal contradictions of remote sensing images; through spatiotemporal databases and data processing platforms, database systems are specially designed for storing and managing spatiotemporal data; through trajectory data processing technology, complex spatiotemporal trajectory data are simplified for easy storage and analysis.

[0004] For example, the invention patent with announcement number: CN107577822B announces a data synchronization method, a data synchronization device and a mobile terminal, including: based on the result of the previous synchronization of the file system of the mobile terminal, detecting the current file system of the mobile terminal; obtaining the first data of the current file system, wherein the first data includes the newly added files, newly added folders, newly deleted files and newly deleted folders in the current file system; synchronizing the media library according to the first data; and recording the result of this synchronization of the file system of the mobile terminal.

[0005] For example, the invention patent application with publication number: CN116303355A discloses a method for synchronous migration of data in heterogeneous databases, including: S1, using a driver to connect a source database and a target database; S2, inputting SQL query parameters in the driver, then querying the required data in the source database and storing it in a target table in the driver; S3, writing the data in the target table into the target database to realize data synchronous migration.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the prior art, the synchronization method based on the spatiotemporal data of moving objects is applied in the scenario of monitoring traffic violations. Due to the time synchronization between different monitoring devices, the time deviation leads to inaccurate recording of violations, and the light intensity affects the image quality, resulting in the inability to recognize license plate numbers and vehicle types. Therefore, the synchronization method based on the spatiotemporal data of moving objects has the problem of insufficient accuracy. Summary of the invention

[0007] The embodiments of the present application solve the problem of insufficient accuracy of synchronization methods based on spatiotemporal data of moving objects in the prior art by providing a synchronization method and system based on spatiotemporal data of moving objects, thereby improving the accuracy of synchronization methods based on spatiotemporal data of moving objects.

[0008] An embodiment of the present application provides a synchronization method based on spatiotemporal data of a moving object, comprising the following steps: collecting and processing the spatiotemporal data of a moving object; analyzing the spatiotemporal data of a moving object to obtain a time synchronization risk assessment index of a moving object and an image quality assessment index of a moving object; comprehensively analyzing to obtain an accuracy assessment index of the spatiotemporal data of a moving object; comparing and analyzing the time synchronization risk assessment index of a moving object with a first threshold of the time synchronization risk assessment index of a moving object, and optimizing and adjusting the time synchronization method of a moving object; comparing and analyzing the image quality assessment index of a moving object with a second threshold of the image quality assessment index of a moving object, and optimizing the image quality method of a moving object; comparing and analyzing the accuracy assessment index of a moving object spatiotemporal data with a comprehensive threshold of the accuracy assessment index of a moving object spatiotemporal data, and optimizing and adjusting the synchronization method of a moving object spatiotemporal data.

[0009] Furthermore, the specific steps of collecting and processing the spatiotemporal data of moving objects are: collecting the original spatiotemporal data of moving objects through cameras and sensor devices; cleaning and denoising the original spatiotemporal data of moving objects to obtain the spatiotemporal data of moving objects, and the spatiotemporal data of moving objects include time synchronization risk data of moving objects and image quality data of moving objects.

[0010] Furthermore, the specific steps for obtaining the mobile object time synchronization risk assessment index are: recording the mobile object time synchronization risk detection time as the first preset time mobile object time synchronization risk detection point; obtaining the electromagnetic strength of the mobile object time synchronization risk detection point at the first preset time through a current probe; obtaining the network jitter of the mobile object time synchronization risk detection point at the first preset time through a network protocol analyzer; obtaining the clock drift rate of the mobile object time synchronization risk detection point at the first preset time through a high-precision clock source; obtaining the clock deviation of the mobile object time synchronization risk detection point at the first preset time through a frequency counter; obtaining the image transmission rate of the mobile object time synchronization risk detection point at the first preset time through a network bandwidth testing device; the mobile object time synchronization risk data includes electromagnetic strength, network jitter, clock drift rate, clock deviation and image transmission rate; and obtaining the mobile object time synchronization risk assessment index based on the mobile object time synchronization risk data analysis.

[0011] Furthermore, the specific steps for obtaining the moving object image quality assessment index are: recording the moving object image quality detection time as the second preset time moving object image quality detection point; obtaining the image resolution of the moving object image quality detection point at the second preset time through a camera; obtaining the image contrast of the moving object image quality detection point at the second preset time through image processing software; obtaining the image color depth of the moving object image quality detection point at the second preset time through an image sensor; obtaining the electromagnetic intensity of the moving object image quality detection point at the second preset time through a current probe; obtaining the light intensity of the moving object image quality detection point at the second preset time through a light intensity sensor; the moving object image quality data includes image resolution, image contrast, image color depth, electromagnetic intensity and light intensity; and obtaining the moving object image quality assessment index based on the analysis of the moving object image quality data.

[0012] Furthermore, the specific steps for obtaining the moving object spatiotemporal data accuracy assessment index are: recording the moving object spatiotemporal data accuracy detection time as the moving object spatiotemporal data accuracy detection point at the third preset time; obtaining the image upload rate of the moving object spatiotemporal data accuracy detection point at the third preset time through data transmission monitoring software; and obtaining the moving object spatiotemporal data accuracy assessment index through comprehensive analysis of the moving object time synchronization risk assessment index, the moving object image quality assessment index and the image upload rate.

[0013] Furthermore, the specific steps of the method for optimizing and adjusting the time synchronization of mobile objects are: if the time synchronization risk assessment index of the mobile object is lower than or equal to the first threshold value of the time synchronization risk assessment index of the mobile object, there is no need to optimize and adjust the time synchronization of the mobile object; if the time synchronization risk assessment index of the mobile object is greater than the first threshold value of the time synchronization risk assessment index of the mobile object, then the difference between the time synchronization risk assessment index of the mobile object and the first threshold value of the time synchronization risk assessment index of the mobile object is used to match the corresponding adjustment plan in the mobile object spatiotemporal database.

[0014] Furthermore, the specific steps of the method for optimizing the moving object image quality are: if the moving object image quality assessment index is greater than or equal to the second threshold value of the moving object image quality assessment index, there is no need to optimize the moving object image quality method; if the moving object image quality assessment index is less than the second threshold value of the moving object image quality assessment index, then the difference between the moving object image quality assessment index and the second threshold value of the moving object image quality assessment index is used to match the corresponding adjustment plan stored in the moving object spatiotemporal database.

[0015] Furthermore, the specific steps of the method for optimizing and adjusting the synchronization of moving object spatiotemporal data are: extracting the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index in the moving object spatiotemporal database, comparing the moving object spatiotemporal data accuracy assessment index with the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index; if the moving object spatiotemporal data accuracy assessment index is greater than or equal to the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is synchronized; if the moving object spatiotemporal data accuracy assessment index is less than the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is not synchronized.

[0016] Furthermore, the method for optimizing and adjusting the synchronization of the spatiotemporal data of a moving object also includes: if the spatiotemporal data of the moving object is synchronized, no optimization and adjustment is required; if the spatiotemporal data of the moving object is not synchronized, image noise is reduced by using Kalman filtering, and is identified and corrected by using a data cleaning tool.

[0017] The embodiment of the present application provides a synchronization system based on the spatiotemporal data of mobile objects, including a spatiotemporal data acquisition module, a spatiotemporal data analysis module for mobile objects, a comprehensive analysis module and a module for optimizing and adjusting the spatiotemporal data synchronization method for mobile objects: the spatiotemporal data acquisition module is used to acquire and process the spatiotemporal data of mobile objects; the spatiotemporal data analysis module for mobile objects is used to analyze the spatiotemporal data of mobile objects to obtain a time synchronization risk assessment index for mobile objects and a mobile object image quality assessment index; the comprehensive analysis module is used to comprehensively analyze and obtain an accuracy assessment index for spatiotemporal data of mobile objects; the module for optimizing and adjusting the spatiotemporal data synchronization method for mobile objects is used to compare and analyze the time synchronization risk assessment index of mobile objects with a first threshold value of the time synchronization risk assessment index of mobile objects, and optimize and adjust the time synchronization method for mobile objects; compare and analyze the image quality assessment index of mobile objects with a second threshold value of the image quality assessment index of mobile objects, and optimize the image quality method for mobile objects; compare and analyze the spatiotemporal data accuracy assessment index of mobile objects with a comprehensive threshold value of the spatiotemporal data accuracy assessment index of mobile objects, and optimize and adjust the spatiotemporal data synchronization method for mobile objects.

[0018] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By collecting and processing the spatiotemporal data of moving objects, analyzing the spatiotemporal data of moving objects, obtaining the time synchronization risk assessment index of moving objects and the image quality assessment index of moving objects, comprehensively analyzing and optimizing the synchronization of spatiotemporal data of moving objects, reducing the spatiotemporal image noise of moving objects through Kalman filtering, improving the accuracy of the synchronization method based on the spatiotemporal data of moving objects, and solving the problem of insufficient accuracy of the synchronization method based on the spatiotemporal data of moving objects in the prior art.

[0019] 2. Analyze the spatiotemporal data of moving objects, and adjust the exposure time through the Web interface based on the analysis results to improve the accuracy of the spatiotemporal images of moving objects. Use data cleaning tools to identify and correct errors and outliers in the spatiotemporal data of moving objects, improve the accuracy of the spatiotemporal data of moving objects, and adjust the frequency and phase of the hardware clock through software control of the hardware clock, adjust the network bandwidth and transmission rate, thereby improving the processing efficiency of the spatiotemporal data of moving objects.

[0020] 3. Through comprehensive analysis and optimization of the synchronization of the spatiotemporal data of moving objects, the positioning accuracy of moving objects can be improved by adjusting the filter parameters, thereby improving the performance of the entire system, and then improving the data processing efficiency, and by adjusting the image contrast, brightness and image compression ratio, the reliability of the synchronization system based on the spatiotemporal data of moving objects can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1A flow chart of a synchronization method based on spatiotemporal data of a moving object provided in an embodiment of the present application; Figure 2 A schematic diagram of an exponential function for evaluating the accuracy of spatiotemporal data of a moving object provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a synchronization system based on spatiotemporal data of moving objects provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application solve the problem of insufficient accuracy of synchronization methods based on spatiotemporal data of moving objects in the prior art by providing a synchronization method and system based on spatiotemporal data of moving objects. By collecting and processing spatiotemporal data of moving objects, analyzing the spatiotemporal data of moving objects, obtaining a time synchronization risk assessment index for moving objects and an image quality assessment index for moving objects, the synchronization of spatiotemporal data of moving objects is comprehensively analyzed and optimized, thereby improving the accuracy of the synchronization method based on spatiotemporal data of moving objects.

[0023] The technical solution in the embodiment of the present application is to solve the above problem that the synchronization method based on the spatiotemporal data of moving objects is not accurate enough. The overall idea is as follows: The spatiotemporal data of moving objects are collected and processed, and the spatiotemporal data of moving objects are analyzed to obtain the time synchronization risk assessment index of moving objects and the image quality assessment index of moving objects. The synchronization of the spatiotemporal data of moving objects is comprehensively analyzed and optimized, thereby improving the accuracy of the synchronization method based on the spatiotemporal data of moving objects.

[0024] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0025] like Figure 1 As shown, it is a flow chart of the synchronization method based on the spatiotemporal data of a moving object provided in an embodiment of the present application. The method is applied to a synchronization device based on the spatiotemporal data of a moving object, and the method includes the following steps: collecting and processing the spatiotemporal data of a moving object; analyzing the spatiotemporal data of a moving object to obtain a time synchronization risk assessment index of a moving object and an image quality assessment index of a moving object; comprehensively analyzing to obtain an accuracy assessment index of the spatiotemporal data of a moving object; comparing and analyzing the time synchronization risk assessment index of a moving object with a first threshold value of the time synchronization risk assessment index of a moving object, and optimizing and adjusting the time synchronization method of a moving object; comparing and analyzing the image quality assessment index of a moving object with a second threshold value of the image quality assessment index of a moving object, and optimizing and adjusting the image quality method of a moving object; comparing and analyzing the accuracy assessment index of a moving object spatiotemporal data with a comprehensive threshold value of the accuracy assessment index of a moving object spatiotemporal data, and optimizing and adjusting the synchronization method of a moving object spatiotemporal data.

[0026] Furthermore, the specific steps of collecting and processing the spatiotemporal data of moving objects are: collecting the original spatiotemporal data of moving objects through cameras and sensor devices; cleaning and denoising the original spatiotemporal data of moving objects to obtain the spatiotemporal data of moving objects, and the spatiotemporal data of moving objects include time synchronization risk data of moving objects and image quality data of moving objects.

[0027] Furthermore, the specific steps for obtaining the mobile object time synchronization risk assessment index are as follows: recording the mobile object time synchronization risk detection time as the first preset time mobile object time synchronization risk detection point; obtaining the electromagnetic strength of the mobile object time synchronization risk detection point at the first preset time through a current probe; obtaining the network jitter of the mobile object time synchronization risk detection point at the first preset time through a network protocol analyzer; obtaining the clock drift rate of the mobile object time synchronization risk detection point at the first preset time through a high-precision clock source; obtaining the clock deviation of the mobile object time synchronization risk detection point at the first preset time through a frequency counter; obtaining the image transmission rate of the mobile object time synchronization risk detection point at the first preset time through a network bandwidth testing device; the mobile object time synchronization risk data includes electromagnetic strength, network jitter, clock drift rate, clock deviation and image transmission rate; and obtaining the mobile object time synchronization risk assessment index based on the mobile object time synchronization risk data analysis.

[0028] In this embodiment, the specific method of analyzing and obtaining the moving object time synchronization risk assessment index is as follows: ; ; ; ; ; The preset moving object time synchronization risk detection points are numbered in sequence. Indicates The number of the moving object time synchronization risk detection point under the moving object time synchronization risk detection segment, , Indicates the total number of moving object time synchronization risk detection points.

[0029] Divide the preset moving object time synchronization risk time into moving object time synchronization risk detection segments of the same length, Indicates the number of the moving object time synchronization risk detection segment, , Indicates the total number of moving object time synchronization risk detection segments.

[0030] Indicates The moving object time synchronization risk assessment index under the moving object time synchronization risk detection point.

[0031] Indicates The electromagnetic intensity influence coefficient of the moving object time synchronization risk detection point.

[0032] Indicates The network jitter impact coefficient of the time synchronization risk detection point of a moving object.

[0033] Indicates The clock drift rate at the time synchronization risk detection point of a moving object, the clock drift rate refers to the rate of change of the clock frequency relative to its nominal value, for example, the signal frequency is accurately measured by a frequency meter, and the clock drift rate is calculated by continuously measuring the frequency of the clock signal and comparing it with the nominal frequency.

[0034] It represents the standard value of the clock drift rate, which is the preset standard value of the clock drift rate obtained from the moving object spatiotemporal database. It is used to describe the error or drift of the clock within the time synchronization range of the moving object under a certain moving object time synchronization risk detection point within a period of time.

[0035] Indicates The clock deviation under the time synchronization risk detection section of a moving object is measured. The clock deviation refers to the time difference of a clock relative to a reference clock. For example, the time interval between two events is accurately measured by a time interval counter, and the time difference between the local clock and the reference clock is measured to calculate the clock deviation.

[0036] It represents the standard value of clock deviation, which is the preset standard value of clock deviation obtained from the moving object spatiotemporal database, and can be the average value of clock deviation at the preset moving object time synchronization risk detection point in the historical data.

[0037] Indicates The image transmission rate under the time synchronization risk detection points of moving objects.

[0038] It represents the standard value of image transmission rate, which is the preset standard value of image transmission rate obtained from the moving object spatiotemporal database, and can be the average value of image transmission rate at the preset moving object time synchronization risk detection point in the historical data.

[0039] Indicates Electromagnetic intensity at the time-synchronized risk detection points of a moving object.

[0040] It represents the standard value of electromagnetic field strength, which is the preset standard value of electromagnetic field strength obtained from the moving object spatiotemporal database, and can be the average value of electromagnetic field strength at the preset moving object time synchronization risk detection point in the historical data.

[0041] Indicates The network jitter under the time synchronization risk detection point of a moving object is measured. Network jitter is the fluctuation of the arrival time of data packets in network transmission. For example, the network traffic is simulated by Spirent network tester, and the transmission delay and jitter of the data packet are measured.

[0042] It represents the network jitter standard value, which is the preset network jitter standard value obtained from the mobile object spatiotemporal database, and can be the network jitter value at the preset mobile object time synchronization risk detection point in the historical data.

[0043] The preset clock drift rate obtained from the moving object spatiotemporal database affects the weighting factor.

[0044] The preset clock bias impact weight factor obtained from the moving object spatiotemporal database.

[0045] The preset image transmission rate obtained from the moving object spatiotemporal database affects the weighting factor.

[0046] It is the preset electromagnetic field intensity influencing factor obtained from the moving object spatiotemporal database.

[0047] is the preset network jitter impact factor obtained from the moving object spatiotemporal database.

[0048] The preset clock drift rate influence weight factor, the preset clock deviation influence weight factor and the image transmission rate influence weight factor respectively represent the numerical values ​​of the influence degree of temperature change on the clock drift rate, clock deviation and image transmission rate on the moving object time synchronization risk assessment index.

[0049] When in use, the preset clock drift rate influence weight factor, the preset clock deviation influence weight factor and the image transmission rate influence weight factor can be directly obtained from the moving object spatiotemporal database according to the value of temperature change, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of temperature changes and their corresponding preset clock drift rate influence weight factors, preset clock deviation influence weight factors and image transmission rate influence weight factors is constructed, and the real-time temperature change value is input into the mapping set to obtain the preset clock drift rate influence weight factor, the preset clock deviation influence weight factor and the image transmission rate influence weight factor, and the mapping relationship can be one-to-one or many-to-one.

[0050] The preset electromagnetic field strength influence factor and the preset network jitter influence factor respectively represent the numerical values ​​of the influence of antenna gain on the electromagnetic field strength and network jitter on the mobile object time synchronization risk assessment index.

[0051] When in use, the preset electromagnetic field strength influence factor and the preset network jitter influence factor can be directly obtained from the mobile object spatiotemporal database according to the antenna gain value, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the antenna gain value and its corresponding preset electromagnetic field strength influence factor and preset network jitter influence factor is constructed, and the real-time antenna gain value is input into the mapping set to obtain the preset electromagnetic field strength influence factor and the preset network jitter influence factor. The mapping relationship can be one-to-one or many-to-one.

[0052] The electromagnetic field strength affects network transmission. The higher the electromagnetic field strength, the stronger the interference to the wireless signal transmission, resulting in increased network jitter. The clock drift rate refers to the rate of change of the clock frequency over time. The clock deviation refers to the time difference between two clocks. The higher the clock drift rate, the greater the clock deviation will be over time. The greater the clock drift rate, the slower the clock will run, resulting in a difference between the time displayed by the clock and the real time. As time goes by, this difference will gradually increase, forming a clock deviation, which increases the clock deviation. The clock deviation affects the image transmission rate. The clock deviation causes inaccurate sending and receiving times of data packets. If the clock deviation is large, the receiving end cannot process the received data packets in time, resulting in a decrease in the image transmission rate. Network jitter affects the image transmission quality. The higher the network jitter, the more packet loss, delay or incoherent images will appear in the video stream. The higher the image transmission rate, the smaller the network jitter. The electromagnetic field strength affects the transmission distance and transmission quality of the signal. The lower the electromagnetic field strength, the more signal attenuation, resulting in a lower image transmission rate and worse image quality.

[0053] The electromagnetic field strength interferes with the transmission of wireless signals. The absolute difference between the electromagnetic field strength and the standard value of the electromagnetic field strength is positively correlated with the time synchronization risk assessment index of the moving object. The greater the absolute difference between the electromagnetic field strength and the standard value of the electromagnetic field strength, the higher the time synchronization risk assessment index of the moving object. Network jitter will increase the uncertainty of data transmission. The absolute difference between the electromagnetic field strength and the standard value of the electromagnetic field strength is positively correlated with the time synchronization risk assessment index of the moving object. The greater the absolute difference between the network jitter and the standard value of the network jitter, the higher the time synchronization risk assessment index of the moving object. The clock drift rate leads to an increase in clock deviation, affecting time synchronization. The absolute difference between the clock drift rate and the standard value of the clock drift rate is positively correlated with the time synchronization risk assessment index of the moving object. The greater the absolute difference between the clock drift rate and the standard value of the clock drift rate, the higher the time synchronization risk assessment index of the moving object; the clock deviation reflects the accuracy of time synchronization. The greater the absolute value of the clock deviation and the standard value of the clock deviation, the higher the time synchronization risk assessment index of the moving object. The absolute value of the clock deviation and the standard value of the clock deviation are positively correlated with the time synchronization risk assessment index of the moving object; the higher the image transmission rate, the higher the requirement for time synchronization. The image transmission rate is unstable, resulting in time synchronization problems. The absolute difference between the image transmission rate and the standard value of the image transmission rate is positively correlated with the time synchronization risk assessment index of the moving object. The higher the absolute difference between the image transmission rate and the standard value of the image transmission rate, the higher the time synchronization risk assessment index of the moving object.

[0054] Furthermore, the specific steps for obtaining the moving object image quality assessment index are as follows: recording the moving object image quality detection time as the second preset time moving object image quality detection point; obtaining the image resolution of the moving object image quality detection point at the second preset time through a camera; obtaining the image contrast of the moving object image quality detection point at the second preset time through image processing software; obtaining the image color depth of the moving object image quality detection point at the second preset time through an image sensor; obtaining the electromagnetic intensity of the moving object image quality detection point at the second preset time through a current probe; obtaining the light intensity of the moving object image quality detection point at the second preset time through a light intensity sensor; the moving object image quality data includes image resolution, image contrast, image color depth, electromagnetic intensity and light intensity; and obtaining the moving object image quality assessment index based on the analysis of the moving object image quality data.

[0055] In this embodiment, the specific method of obtaining the moving object image quality assessment index by analysis is as follows: ; ; ; ; The preset moving object image quality detection points are numbered in sequence. Indicates the number of the moving object image quality detection point, , Indicates the total number of moving object image quality detection points.

[0056] Indicates The moving object image quality assessment index of the moving object image quality detection points.

[0057] Indicates The image resolution at the moving object image quality detection point.

[0058] It represents the image resolution threshold, which is the preset image resolution threshold obtained from the moving object spatiotemporal database, and can be the average image resolution at the preset moving object image quality detection point in the historical data.

[0059] Indicates Image contrast at the image quality detection point of a moving object.

[0060] It represents the image contrast threshold, which is a preset image resolution threshold obtained from the moving object spatiotemporal database, and can be the average image contrast value at a preset moving object image quality detection point in the historical data.

[0061] Indicates The image color depth at the moving object image quality detection point.

[0062] represents the image color depth threshold, which is a preset image color depth threshold obtained from the moving object spatiotemporal database, and can be the average image color depth value at a preset moving object image quality detection point in the historical data.

[0063] Indicates The electromagnetic intensity influence coefficient of the moving object image quality detection point.

[0064] Indicates The light intensity influence coefficient at the image quality detection point of a moving object.

[0065] Indicates The electromagnetic intensity at the image quality detection point of a moving object.

[0066] It represents the standard value of electromagnetic intensity, which is the preset standard value of electromagnetic intensity obtained from the moving object spatiotemporal database, and represents the standard value of electromagnetic intensity at a moving object image quality detection point.

[0067] Indicates The light intensity at the image quality detection point of a moving object.

[0068] It represents the standard value of light intensity, which is the preset standard value of light intensity obtained from the moving object spatiotemporal database, and represents the standard value of light intensity at a moving object image quality detection point.

[0069] The preset image resolution influence weight factor obtained from the moving object spatiotemporal database.

[0070] is the preset image contrast impact weight factor obtained from the moving object spatiotemporal database.

[0071] It is the preset image color depth impact weight factor obtained from the moving object spatiotemporal database.

[0072] It is the preset electromagnetic intensity influence coefficient influence weight factor obtained from the moving object spatiotemporal database.

[0073] It is the preset illumination intensity influence coefficient influence weight factor obtained from the moving object spatiotemporal database.

[0074] It is the preset electromagnetic field intensity influencing factor obtained from the moving object spatiotemporal database.

[0075] It is the preset light intensity influencing factor obtained from the moving object spatiotemporal database.

[0076] The preset image resolution influence weight factor, the preset image contrast influence weight factor, the preset image color depth influence weight factor, the preset electromagnetic intensity influence coefficient influence weight factor and the preset light intensity influence coefficient influence weight factor respectively represent the numerical values ​​of the influence of network delay on image resolution, image contrast, image color depth, electromagnetic intensity influence coefficient and light intensity influence coefficient on the moving object image quality assessment index.

[0077] When in use, the preset image resolution influence weight factor, preset image contrast influence weight factor, preset image color depth influence weight factor, preset electromagnetic intensity influence coefficient influence weight factor and preset illumination intensity influence coefficient influence weight factor can be directly obtained from the moving object spatiotemporal database according to the value of network delay, and the corresponding relationship can be a preset mapping relationship. For example, a mapping set of network delay and its corresponding preset image resolution influence weight factor, preset image contrast influence weight factor, preset image color depth influence weight factor, preset electromagnetic intensity influence coefficient influence weight factor and preset illumination intensity influence coefficient influence weight factor is constructed, and the real-time network delay value is input into the mapping set to obtain the preset image resolution influence weight factor, preset image contrast influence weight factor, preset image color depth influence weight factor, preset electromagnetic intensity influence coefficient influence weight factor and preset illumination intensity influence coefficient influence weight factor, wherein the mapping relationship can be one-to-one or many-to-one.

[0078] The preset electromagnetic field intensity influence factor and the preset illumination intensity influence factor respectively represent the numerical values ​​of the influence degree of the packet loss rate on the electromagnetic field intensity and the illumination intensity on the moving object image quality evaluation index.

[0079] When in use, the preset electromagnetic field intensity influence factor and the preset light intensity influence factor can be directly obtained from the moving object spatiotemporal database according to the value of the packet loss rate, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the packet loss rate and its corresponding preset electromagnetic field intensity influence factor and preset light intensity influence factor is constructed, and the real-time packet loss rate value is input into the mapping set to obtain the preset electromagnetic field intensity influence factor and the preset light intensity influence factor, wherein the mapping relationship can be one-to-one or many-to-one.

[0080] Image resolution refers to the number of pixels in an image, and image contrast refers to the difference between dark and light areas in an image. Images with higher image resolution can provide more details and increase image contrast. The higher the image resolution, the higher the image clarity and the higher the image color depth. The stronger the electromagnetic intensity, the higher the image noise and the lower the image contrast. The stronger the light intensity, the more exposed the image and the lower the image contrast and image color depth.

[0081] The higher the image resolution, the clearer the image details of the moving object, which is positively correlated with the moving object image quality assessment index, and the higher the moving object image quality assessment index; the greater the absolute difference between the image contrast and the image contrast threshold, the more obvious the difference between the moving object and the background, the greater the absolute difference between the image contrast and the image contrast threshold, and the negative correlation between the moving object image quality assessment index, and the lower the moving object image quality assessment index; the increased image color depth provides rich color information, and the greater the absolute difference between the image color depth and the image color depth is negatively correlated with the moving object image quality assessment index, and the lower the moving object image quality assessment index; the greater the absolute difference between the electromagnetic intensity and the electromagnetic intensity standard value leads to increased image noise, reducing the recognizability of the moving object, which is negatively correlated with the moving object image quality assessment index, and the smaller the moving object image quality assessment index; the greater the absolute difference between the light intensity and the light intensity leads to overexposure, which is negatively correlated with the moving object image quality assessment index, and the smaller the moving object image quality assessment index.

[0082] Furthermore, the specific steps for obtaining the moving object spatiotemporal data accuracy assessment index are as follows: recording the moving object spatiotemporal data accuracy detection time as the moving object spatiotemporal data accuracy detection point at the third preset time; obtaining the image upload rate of the moving object spatiotemporal data accuracy detection point at the third preset time through data transmission monitoring software; and obtaining the moving object spatiotemporal data accuracy assessment index through comprehensive analysis of the moving object time synchronization risk assessment index, the moving object image quality assessment index and the image upload rate.

[0083] In this embodiment, the specific method for analyzing and obtaining the moving object spatiotemporal data accuracy evaluation index is as follows: ; ; The preset moving object spatiotemporal data accuracy detection points are numbered in sequence. Indicates the number of the moving object's spatiotemporal data accuracy detection point, , Indicates the total number of points where the spatiotemporal data accuracy of a moving object is checked.

[0084] Represents the accuracy assessment index of spatiotemporal data of moving objects.

[0085] Indicates The moving object image quality assessment index of the moving object image quality detection points.

[0086] Indicates The image upload rate at the spatiotemporal data accuracy detection point of a moving object.

[0087] It represents the standard value of image upload rate, which is the preset standard value of image upload rate obtained from the moving object spatiotemporal database, and can be the average value of image upload rate at the preset moving object image quality detection point in the historical data.

[0088] Indicates The moving object time synchronization risk assessment index under the moving object time synchronization risk detection point.

[0089] It is the influencing weight factor of the preset moving object image quality assessment index obtained from the moving object spatiotemporal database.

[0090] The preset image upload rate obtained from the moving object spatiotemporal database affects the weight factor.

[0091] It is the influence weight factor of the preset moving object time synchronization risk assessment index obtained from the moving object spatiotemporal database.

[0092] The preset moving object image quality assessment index influence weight factor, the preset image upload rate influence weight factor and the preset moving object time synchronization risk assessment index influence weight factor respectively represent the numerical values ​​of the influence of network bandwidth on the moving object image quality assessment index, the image upload rate and the moving object time synchronization risk assessment index on the moving object spatiotemporal data accuracy assessment index.

[0093] When in use, the preset moving object image quality assessment index influencing weight factor, the preset image upload rate influencing weight factor and the preset moving object time synchronization risk assessment index influencing weight factor can be directly obtained from the moving object spatiotemporal database according to the value of the network bandwidth, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the network bandwidth and its corresponding preset moving object image quality assessment index influencing weight factor, the preset image upload rate influencing weight factor and the preset moving object time synchronization risk assessment index influencing weight factor is constructed, and the real-time network bandwidth value is input into the mapping set to obtain the preset moving object image quality assessment index influencing weight factor, the preset image upload rate influencing weight factor and the preset moving object time synchronization risk assessment index influencing weight factor, wherein the mapping relationship can be one-to-one or many-to-one.

[0094] Table 1 is an example table of the evaluation index of the spatiotemporal data accuracy of moving objects. The example parameters in Table 1 only take the parameters of one spatiotemporal data accuracy detection point of a moving object as an example. The weight factor Set to 0.3, weight factor Set to 0.4, weight factor Set to 0.3, The standard value of the image upload rate is 3, as shown in Table 1.

[0095] Table 1 Example table of moving object spatiotemporal data accuracy evaluation index

[0096] As shown in Table 1 and Figure 2 As shown, the higher the moving object image quality assessment index is, the higher the image resolution is, and a higher image upload rate is required. A low image upload rate affects the image transmission quality, resulting in packet loss or delay during image transmission, thereby affecting the image quality; the image upload rate affects the accuracy of moving object time synchronization, unstable upload rate or large delay leads to inaccurate timestamp, affecting the accuracy of time synchronization, and the larger the moving object time synchronization risk assessment index is; the accuracy of time synchronization affects image quality assessment, inaccurate time synchronization leads to misalignment of image sequence, affecting the coherence and quality of the image, and the larger the moving object time synchronization risk assessment index is, the lower the moving object image quality assessment index is; Curve a indicates that if the image upload rate is set to a fixed value of 1, the moving object time synchronization risk assessment index is set to a fixed value of 1, the moving object image quality assessment index is x, and the moving object spatiotemporal data accuracy assessment index is y, the moving object spatiotemporal data accuracy assessment index increases as the moving object image quality assessment index increases.

[0097] Curve b indicates that if the moving object image quality assessment index is set to a fixed value of 1, the moving object time synchronization risk assessment index is set to a fixed value of 1, the image upload rate is x, and the moving object spatiotemporal data accuracy assessment index is y, if x is greater than or equal to 0 and less than or equal to 3, the moving object spatiotemporal data accuracy assessment index increases with the increase of the image upload rate; if x is greater than 3, the moving object spatiotemporal data accuracy assessment index decreases with the increase of the image upload rate.

[0098] Curve c indicates that if the moving object image quality assessment index is set to a fixed value of 1, the image upload rate is set to a fixed value of 1, the moving object time synchronization risk assessment index is x, and the moving object spatiotemporal data accuracy assessment index is y, the moving object spatiotemporal data accuracy assessment index decreases as the moving object time synchronization risk assessment index increases.

[0099] The higher the moving object image quality assessment index, the higher the image quality, which is positively correlated with the moving object spatiotemporal data accuracy assessment index, and the larger the moving object spatiotemporal data accuracy assessment index; the higher the image upload rate, the more frequent data updates are provided, which is positively correlated with the moving object spatiotemporal data accuracy assessment index, and the larger the moving object spatiotemporal data accuracy assessment index; the higher the time synchronization risk, the lower the accuracy of the spatiotemporal data, and the inaccurate timestamp will cause the data to be misaligned in time. The larger the moving object time synchronization risk assessment index, the negatively correlated with the moving object spatiotemporal data accuracy assessment index, and the smaller the moving object spatiotemporal data accuracy assessment index.

[0100] Furthermore, the specific steps of the method for optimizing and adjusting the time synchronization of mobile objects are as follows: if the time synchronization risk assessment index of the mobile object is lower than or equal to the first threshold value of the time synchronization risk assessment index of the mobile object, there is no need to optimize and adjust the time synchronization of the mobile object; if the time synchronization risk assessment index of the mobile object is greater than the first threshold value of the time synchronization risk assessment index of the mobile object, the difference between the time synchronization risk assessment index of the mobile object and the first threshold value of the time synchronization risk assessment index of the mobile object is used to match the corresponding adjustment plan in the mobile object spatiotemporal database.

[0101] For example, assuming that the mobile object time synchronization risk assessment index is 0.9, the first threshold of the mobile object time synchronization risk assessment index obtained from the mobile object spatiotemporal database is 0.7, and the corresponding difference is 0.2, then the adjustment scheme corresponding to the difference between the mobile object time synchronization risk assessment index and the first threshold of the mobile object time synchronization risk assessment index is 0.2 is obtained from the database. The adjustment scheme is: increase the hardware clock frequency by 0.1MHz; increase the current hardware clock by 5 degrees; increase the current network bandwidth by 50Mbps, adjust the transmission rate to 1.5Gbps, adjust the cutoff frequency to 150Hz, and adjust the filter gain to 1.5. Through the above calculation, the parameter values ​​that need to be adjusted are obtained. The frequency and phase of the hardware clock are adjusted by software control of the hardware clock, the network bandwidth and transmission rate are adjusted by the wireless access point, and the bandwidth or rate limit of the wireless network is configured to optimize the flow of mobile object time synchronization risk data. When processing data, the filter parameters of the Kalman filter are adjusted, and the filter is used to reduce noise and smooth data, so as to reduce the mobile object time synchronization risk assessment index.

[0102] Furthermore, the specific steps of optimizing the moving object image quality method are as follows: if the moving object image quality assessment index is greater than or equal to the second threshold value of the moving object image quality assessment index, there is no need to optimize the moving object image quality method; if the moving object image quality assessment index is less than the second threshold value of the moving object image quality assessment index, then the difference between the moving object image quality assessment index and the second threshold value of the moving object image quality assessment index is used to match the corresponding adjustment plan stored in the moving object spatiotemporal database.

[0103] For example, assuming that the moving object image quality assessment index is 1, the second threshold of the moving object image quality assessment index obtained from the moving object spatiotemporal database is 2, and the corresponding difference is -1, then the adjustment scheme corresponding to the difference between the moving object image quality assessment index and the second threshold of the moving object image quality assessment index is -1, which is matched from the database. The adjustment scheme is: double the exposure time, increase the image enhancement parameter by 0.5, increase the denoising parameter by 0.3, increase the contrast by 0.2, adjust the brightness to 0.7, and adjust the compression ratio to 70%. Through the above calculation, the parameter values ​​that need to be adjusted are obtained. The exposure time is adjusted through the Web interface, the image enhancement and denoising are performed through the script, the contrast and brightness of the image are adjusted through image processing software such as OpenCV, and the compression ratio of the image is adjusted by adjusting the compression quality parameters of the image encoding such as JPEG quality factor, WebP compression quality, etc., so as to improve the moving object image quality assessment index.

[0104] Furthermore, the specific steps of optimizing and adjusting the synchronization method of the moving object spatiotemporal data are as follows: extracting the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index in the moving object spatiotemporal database, comparing the moving object spatiotemporal data accuracy assessment index with the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index; if the moving object spatiotemporal data accuracy assessment index is greater than or equal to the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is synchronized; if the moving object spatiotemporal data accuracy assessment index is less than the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is not synchronized.

[0105] Furthermore, the method for optimizing and adjusting the synchronization of the spatiotemporal data of a moving object also includes: if the spatiotemporal data of the moving object is synchronized, no optimization and adjustment is required; if the spatiotemporal data of the moving object is not synchronized, image noise is reduced by using Kalman filtering, and is identified and corrected by using a data cleaning tool.

[0106] In this embodiment, it is assumed that we have an image in which the position information of the moving object is (x, y) = (10, 20). Due to the presence of noise, the actual measurement value is (x', y') = (12, 22). The real position information is estimated by the prediction equation and update equation of the Kalman filter. It is assumed that there is a series of position information data, some of which are erroneous. Data cleaning tools can be used to identify and correct these errors. For example, outliers can be identified by OpenRefine, and statistical features of position information, such as mean and standard deviation, can be calculated. Outliers can be identified by Trifacta Wrangler, and errors can be corrected by DataCleaner. For identified outliers, interpolation or other methods can be used to correct the errors. Through the above steps, image noise can be reduced, and errors in the data can be identified and corrected, thereby improving the accuracy of the spatiotemporal data of moving objects.

[0107] like Figure 3 As shown, it is a structural schematic diagram of a synchronization system based on spatiotemporal data of a mobile object provided in an embodiment of the present application. The synchronization system based on spatiotemporal data of a mobile object provided in an embodiment of the present application includes: a spatiotemporal data acquisition module, a spatiotemporal data analysis module for a mobile object, a comprehensive analysis module and a module for optimizing and adjusting the spatiotemporal data synchronization method for a mobile object: a spatiotemporal data acquisition module: used for acquiring and processing the spatiotemporal data of a mobile object; a spatiotemporal data analysis module for a mobile object: used for analyzing the spatiotemporal data of a mobile object, obtaining a time synchronization risk assessment index for a mobile object and obtaining a mobile object image quality assessment index; a comprehensive analysis module: used for comprehensively analyzing and obtaining a spatiotemporal data accuracy assessment index for a mobile object; a module for optimizing and adjusting the spatiotemporal data synchronization method for a mobile object: used for comparing and analyzing the time synchronization risk assessment index of a mobile object with a first threshold value of the time synchronization risk assessment index of a mobile object, and optimizing and adjusting the time synchronization method for a mobile object; comparing and analyzing the image quality assessment index of a mobile object with a second threshold value of the image quality assessment index of a mobile object, and optimizing the image quality method for a mobile object; comparing and analyzing the spatiotemporal data accuracy assessment index of a mobile object with a comprehensive threshold value of the spatiotemporal data accuracy assessment index of a mobile object, and optimizing and adjusting the spatiotemporal data synchronization method for a mobile object.

[0108] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0112] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0113] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A synchronization method based on spatiotemporal data of moving objects, characterized in that: The following steps are involved: Collect and process spatiotemporal data of moving objects; Analyze the spatiotemporal data of moving objects to obtain a moving object time synchronization risk assessment index and a moving object image quality assessment index; Comprehensive analysis is used to obtain the temporal and spatial data accuracy assessment index of moving objects; Compare and analyze the moving object time synchronization risk assessment index with the first threshold of the moving object time synchronization risk assessment index, and optimize and adjust the moving object time synchronization method; Compare and analyze the moving object image quality assessment index with the second threshold of the moving object image quality assessment index to optimize the moving object image quality method; The moving object spatiotemporal data accuracy assessment index and the moving object spatiotemporal data accuracy assessment index comprehensive threshold are compared and analyzed to optimize and adjust the synchronization method of the moving object spatiotemporal data.

2. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of collecting and processing the spatiotemporal data of moving objects are: Collecting spatiotemporal raw data of moving objects through cameras and sensor devices; The original spatiotemporal data of the moving object are cleaned and denoised to obtain the spatiotemporal data of the moving object, wherein the spatiotemporal data of the moving object include the time synchronization risk data of the moving object and the image quality data of the moving object.

3. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of obtaining the moving object time synchronization risk assessment index are: Recording the moving object time synchronization risk detection time as the first preset time moving object time synchronization risk detection point; Obtaining the electromagnetic intensity of a time synchronization risk detection point of a moving object at a first preset time through a current probe; Obtaining the network jitter of the time synchronization risk detection point of the moving object at the first preset time through a network protocol analyzer; Obtaining a clock drift rate of a time synchronization risk detection point of a moving object at a first preset time through a high-precision clock source; Obtaining a clock deviation of a time synchronization risk detection point of a moving object at a first preset time through a frequency counter; Obtaining, by means of a network bandwidth testing device, an image transmission rate of a time synchronization risk detection point of a moving object at a first preset time; The mobile object time synchronization risk data includes electromagnetic intensity, network jitter, clock drift rate, clock deviation and image transmission rate; The moving object time synchronization risk assessment index is obtained based on the moving object time synchronization risk data analysis.

4. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of obtaining the moving object image quality assessment index are: Recording the moving object image quality detection time as the second preset time moving object image quality detection point; Obtaining, by means of a camera, an image resolution of an image quality detection point of a moving object at a second preset time; Obtaining the image contrast of the image quality detection point of the moving object at a second preset time by using image processing software; Obtaining, by means of an image sensor, an image color depth at an image quality detection point of the moving object at a second preset time; Obtaining the electromagnetic intensity of the image quality detection point of the moving object at a second preset time by means of a current probe; Obtaining the light intensity at the image quality detection point of the moving object at a second preset time through a light intensity sensor; The moving object image quality data includes image resolution, image contrast, image color depth, electromagnetic intensity and light intensity; The moving object image quality assessment index is obtained based on the moving object image quality data analysis.

5. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of obtaining the moving object spatiotemporal data accuracy evaluation index are as follows: Recording the moving object spatiotemporal data accuracy detection time as the third preset time moving object spatiotemporal data accuracy detection point; The image upload rate of the spatiotemporal data accuracy detection point of the moving object at the third preset time is obtained through the data transmission monitoring software; The moving object spatiotemporal data accuracy assessment index is obtained through comprehensive analysis of the moving object time synchronization risk assessment index, the moving object image quality assessment index and the image upload rate.

6. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of the method for optimizing and adjusting the time synchronization of a moving object are as follows: If the moving object time synchronization risk assessment index is lower than or equal to the first threshold value of the moving object time synchronization risk assessment index, there is no need to optimize and adjust the moving object time synchronization; If the moving object time synchronization risk assessment index is greater than the first threshold of the moving object time synchronization risk assessment index, the corresponding adjustment plan in the moving object spatiotemporal database is matched through the difference between the moving object time synchronization risk assessment index and the first threshold of the moving object time synchronization risk assessment index.

7. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of the method for optimizing the image quality of moving objects are: If the moving object image quality assessment index is greater than or equal to the moving object image quality assessment index second threshold value, there is no need to optimize the moving object image quality method; If the moving object image quality assessment index is less than the moving object image quality assessment index second threshold, the adjustment plan corresponding to it stored in the moving object spatiotemporal database is matched through the difference between the moving object image quality assessment index and the moving object image quality assessment index second threshold.

8. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The specific steps of the method for optimizing and adjusting the synchronization of spatiotemporal data of moving objects are as follows: The comprehensive threshold of the moving object spatiotemporal data accuracy assessment index is extracted from the moving object spatiotemporal database, and the moving object spatiotemporal data accuracy assessment index is compared with the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index. If the moving object spatiotemporal data accuracy assessment index is greater than or equal to the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is synchronized; if the moving object spatiotemporal data accuracy assessment index is less than the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index, the moving object spatiotemporal data is not synchronized.

9. The synchronization method based on spatiotemporal data of a moving object as claimed in claim 1, characterized in that: The method for optimizing and adjusting the synchronization of spatiotemporal data of a moving object further includes: If the spatiotemporal data of the moving object are synchronized, no optimization adjustment is required; If the spatiotemporal data of a moving object are not synchronized, the image noise is reduced through Kalman filtering and identified and corrected through data cleaning tools.

10. A synchronization system based on spatiotemporal data of moving objects, characterized in that: It includes a module for collecting spatiotemporal data, a module for analyzing spatiotemporal data of moving objects, a comprehensive analysis module, and a module for optimizing and adjusting the synchronization method of spatiotemporal data of moving objects: Collection of spatiotemporal data module: used to collect and process spatiotemporal data of moving objects; Moving object spatiotemporal data analysis module: used to analyze the spatiotemporal data of moving objects, obtain the moving object time synchronization risk assessment index and the moving object image quality assessment index; Comprehensive analysis module: used to comprehensively analyze and obtain the accuracy evaluation index of spatiotemporal data of moving objects; Optimizing and adjusting the moving object spatiotemporal data synchronization method module: used to compare and analyze the moving object time synchronization risk assessment index with the first threshold of the moving object time synchronization risk assessment index, and optimize and adjust the moving object time synchronization method; Compare and analyze the moving object image quality assessment index with the second threshold of the moving object image quality assessment index to optimize the moving object image quality method; compare and analyze the moving object spatiotemporal data accuracy assessment index with the comprehensive threshold of the moving object spatiotemporal data accuracy assessment index to optimize and adjust the synchronization method of the moving object spatiotemporal data.

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