Positioning data sensing method and device based on identifier analysis and medium

Abstract

The invention relates to the technical field of identification signal compensation, in particular to a positioning data sensing method and device based on identification analysis and a medium, and the method comprises the steps: obtaining the identification data and signal intensity of each agricultural product when the agricultural product passes through each region, and the humidity of each region at each sampling moment; obtaining an environment constraint coefficient of the current region; counting the missing number of the identification data at the same sampling moment, and obtaining an environment positioning error in combination with an environment constraint coefficient; counting missing conditions of the identification data at different sampling moments to obtain identification loss frequency; obtaining signal coverage completeness according to the signal intensity; obtaining a positioning coverage attenuation degree according to the consistency of the covariant relationship between the identification loss frequency and the signal coverage completeness; generating a compensation parameter of the current region; and performing sampling compensation by using the compensation parameter. The invention aims to solve the problem of identification data missing caused by the influence of the environment and the signal intensity on the identification data, and improves the sensing accuracy of the positioning data.

Description

Technical Field

[0001] The present invention relates to the technical field of identification signal compensation, and in particular to a positioning data perception method, device and medium based on identification resolution. Background Art

[0002] With the rapid development of information technology and the Internet of Things, the number of devices and application scenarios based on the Internet of Things is increasing, and positioning technology is playing an increasingly important role in the fields of intelligent manufacturing, logistics management, smart cities, and Internet of Vehicles. In order to meet diverse business needs, efficient and accurate perception and acquisition of positioning data has become one of the core supporting technologies for the application of the Internet of Things. Among them, the identity resolution system, as a key infrastructure of the Internet of Things, provides important support for device positioning, resource tracking, and information management by giving physical objects unique identifiers and associating their related attributes and service resources.

[0003] However, in the complex and changing environment, the existing identification resolution method is affected by factors such as multipath effects, obstacles, and changes in environmental media during the signal propagation process, resulting in nonlinear and uncertain signal attenuation rates. Traditional static signal propagation models, such as path loss models, cannot accurately reflect the attenuation characteristics of actual signals under environmental influences, resulting in errors in the perception of positioning data. Summary of the invention

[0004] The present invention provides a positioning data perception method, device and medium based on identification resolution to solve the existing problems.

[0005] The present invention provides a positioning data perception method, device and medium based on identification resolution, which adopts the following technical solutions: In a first aspect, an embodiment of the present invention provides a method for sensing positioning data based on identity resolution, the method comprising the following steps: Collect the identification of all agricultural products in the same batch, obtain the identification data and signal strength of each agricultural product at different sampling times when passing through each region, and the humidity at each sampling time in each region; When the same batch of agricultural products passes through the current area, the environmental constraint coefficient of the current area is obtained, and the environmental constraint coefficient is positively correlated with the humidity fluctuation of the agricultural products in the current area; the number of missing identification data of all agricultural products at the same sampling time is counted, and the environmental positioning error of the current area is obtained by combining the environmental constraint coefficient; the missing identification data of all agricultural products at different sampling times are counted to obtain the frequency of identification loss in the current area; according to the signal strength of the same batch of agricultural products at different sampling times, the signal coverage completeness of the current area is obtained; Obtain the identification loss frequency and signal coverage completeness of each region; obtain the positioning coverage attenuation of the current region based on the consistency of the covariant relationship between the identification loss frequency and signal coverage completeness of the current region and the previous region passed through; The compensation parameters of the current area are generated by using the positioning coverage attenuation and the environmental positioning error; and the compensation parameters are used to perform sampling compensation on the identification data of the next batch of agricultural products passing through the current area.

[0006] Preferably, the specific steps of obtaining the environmental constraint coefficient include: Construct a humidity curve for the current region based on the humidity at each sampling time in the current region, where the horizontal axis of the humidity curve is the sampling time and the vertical axis is the humidity value; Take all the maximum and minimum values ​​in the humidity curve of the current area; record the range between each maximum value and the previous minimum value as the positive increment of the maximum value; calculate the mean of all positive increments in the humidity curve of the current area; The product of the mean of all positive increments in the humidity curve of the current region and the variance of all humidity in the humidity curve of the current region is recorded as the environmental constraint coefficient of the current region.

[0007] Preferably, the specific steps of obtaining the environmental positioning error include: The number of identification data marked as missing in all agricultural products at the same sampling time in the current region is recorded as the missing amount of identification data at the sampling time in the current region; The ratio of the mean of the missing amount of identification data at all sampling moments in the current region to the amount of agricultural products is recorded as the missing rate of the current region; The product of the missing rate and the environmental constraint coefficient of the current area is recorded as the environmental positioning error of the current area.

[0008] Preferably, the specific steps of obtaining the frequency of loss of the identifier include: When the same batch of agricultural products passes through the current area, the identification data of each agricultural product marked as missing is recorded as a missing sampling point of the agricultural product at all sampling moments; According to the continuous missing situation of all missing sampling points of each agricultural product, the identification perception failure rate of each agricultural product in the current area is obtained; Classifying all agricultural products in the current region according to the identification perception failure rate to obtain agricultural products that are prone to missing in the current region; The frequency of label loss in the current region is obtained based on the proportion of easily missing agricultural products in the current region and their label perception failure rate; The product of the ratio of the number of easily missing agricultural products in the same batch to the total number of agricultural products in the same batch and the identification perception failure rate of all easily missing agricultural products in the same batch is recorded as the identification loss frequency in the current area.

[0009] Preferably, the specific steps of obtaining the identification perception failure rate include: For the current region agricultural products, The missing sampling points of agricultural products are merged to obtain the Several persistent missing segments for agricultural products; No. When agricultural products pass through the current region, Failure rate of perceived labeling of agricultural products The calculation method is:

[0010] in, For the The total number of identification data of agricultural products passing through the current region, For the The total number of missing sampling points when agricultural products pass through the current area; For the Total number of persistent missing segments for agricultural products; is the preset sampling interval time length, No. The agricultural product the length of time that the missing segment persists; is the prior fault tolerance multiple.

[0011] Preferably, the specific steps of obtaining the easily missing agricultural products include: The identification perception failure rate when obtaining all agricultural products passing through the current region; Arrange the identification perception failure rates of all agricultural products when passing through the current area in descending order to obtain a descending sequence of identification perception failure rates of the agricultural products when passing through the current area, calculate the difference between two adjacent sequence values ​​in the descending sequence of identification perception failure rates, record the smaller sequence number of the two sequence values ​​corresponding to the maximum difference in the difference between the two adjacent sequence values ​​as the separation sequence number, and record the agricultural products corresponding to all sequence values ​​from the first sequence number to the separation sequence number and including the first sequence number in the descending sequence of identification perception failure rates as easily missing agricultural products in the current area.

[0012] Preferably, the specific steps of obtaining the signal coverage completeness include: When the same batch of agricultural products passes through the current area, the mean signal strength of the identification data of all agricultural products at the same sampling time is calculated, and recorded as the mean signal strength of the same batch of agricultural products at each sampling time; The signal mean intensity of the same batch of agricultural products at all sampling times is mapped into a two-dimensional space, where the horizontal axis is the sampling time and the vertical axis is the signal mean intensity, and the signal intensity fluctuation curve of the same batch of agricultural products passing through the current area is obtained; The ratio of the minimum value of the signal mean strength to the average value of the signal mean strength at all sampling moments of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region is recorded as the downward range of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region; The signal coverage completeness of the current area is obtained by combining the downward amplitude of the signal strength fluctuation curve of the same batch of agricultural products when passing through the current area and the average of the amplitudes of all negative increments, wherein the downward amplitude is directly proportional to the signal coverage completeness, and the average of the amplitudes of the negative increments is inversely proportional to the signal coverage completeness.

[0013] Preferably, the specific steps of obtaining the positioning coverage attenuation include: According to the frequency of label loss and signal coverage completeness of the same batch of agricultural products in different regions, the label loss frequency sequence and signal coverage completeness sequence of the batch of agricultural products are constructed; The mean square error of the label loss frequency sequence and signal coverage completeness sequence of the same batch of agricultural products is obtained, which is recorded as the subjective deviation degree of the label of the same batch of agricultural products; Record the batch of agricultural products that has recently passed through the current area as the current batch of agricultural products; The positioning coverage attenuation of the current area is obtained by comprehensively considering the frequency of identification loss and the completeness of signal coverage in the current area and combining the degree of subjective deviation of the labels of the current batch of agricultural products. The frequency of identification loss and the degree of subjective deviation of the labels are directly proportional to the positioning coverage attenuation, and the signal coverage completeness is inversely proportional to the positioning coverage attenuation.

[0014] In the second aspect, the present invention also proposes a positioning data perception device based on identity resolution, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the memory is used to store the computer program, and the processor runs the computer program to implement the steps of the aforementioned positioning data perception method based on identity resolution.

[0015] In a third aspect, the present invention further proposes a positioning data perception medium based on identity resolution, on which computer instructions are stored, and when the computer instructions are executed by a processor, the steps of the aforementioned method are implemented.

[0016] The beneficial effects of the technical solution of the present invention are: obtaining the identification data and signal strength of each agricultural product of the same batch at different sampling times when passing through each region, as well as the humidity at each sampling time in each region; obtaining the environmental constraint coefficient of the current region when the same batch of agricultural products passes through the current region; counting the number of missing identification data of all agricultural products at the same sampling time, and obtaining the environmental positioning error of the current region in combination with the environmental constraint coefficient; quantifying the impact of humidity on signal strength, and combining the missing situation of agricultural product identification data, quantifying the error caused by environmental interference in the current region; counting the missing situation of identification data of all agricultural products at different sampling times, and obtaining the frequency of identification loss in the current region; obtaining the frequency of loss of agricultural products in the current region by quantifying the loss situation of the same batch of agricultural products when passing through the current region; obtaining the signal coverage completeness of the current region according to the signal strength of the same batch of agricultural products at different sampling times, and using the signal strength of different identification data to reflect the signal coverage of the current region. The invention discloses a method for obtaining the positioning coverage of a product of a certain area by analyzing the covariation relationship between the frequency of identification loss and the completeness of signal coverage of the current area and the area before the current area. The method comprises the following steps: obtaining the positioning coverage attenuation of the current area according to the consistency of the covariation relationship between the frequency of identification loss and the completeness of signal coverage of the current area and the area before the current area; analyzing the covariation relationship between the frequency of identification loss and the completeness of signal coverage of the current batch of agricultural products when passing through all areas, reflecting the relationship between the missing of the current batch of agricultural products and the signal strength, and then using it as the weight for obtaining the compensation parameter to obtain the positioning coverage attenuation of the current area; using the positioning coverage attenuation and the environmental positioning error to generate the compensation parameter of the current area; using the compensation parameter to sample and compensate the identification data of the next batch of agricultural products passing through the current area; the present invention obtains the compensation parameter for sampling and compensating the identification data of the next batch of agricultural products when passing through the current area by analyzing the relationship between the signal strength and the missing of identification data when a batch of agricultural products passes through all areas, and the interference of the environment on the identification data, so as to improve the sampling precision and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 The present invention is a flowchart of the steps of a positioning data perception method based on identity resolution. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a positioning data perception method based on identification resolution proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0020] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0021] The following is a detailed description of a specific solution of a positioning data perception method, device and medium based on identity resolution provided by the present invention in conjunction with the accompanying drawings.

[0022] First, see Figure 1 , which shows a flowchart of a method for sensing positioning data based on identity resolution provided by an embodiment of the present invention, the method comprising the following steps: Step S001: Collect the identification of all agricultural products in the same batch, obtain the identification data and signal strength of each agricultural product at different sampling times when passing through each region, and the humidity of each region at each sampling time.

[0023] There are strict requirements on environmental factors such as temperature, humidity, and obstacles in the logistics and transportation of agricultural products. If they do not meet the requirements, the agricultural products may deteriorate, the quality may decline, etc., affecting the efficiency and economic benefits of the agricultural product circulation link. Therefore, it is necessary to grasp the location information and environmental data of agricultural products in real time; during the logistics and transportation of agricultural products, each batch of agricultural products will be assigned a unique identification. When arriving at each region, the identification data of the agricultural product status will be transmitted to the logistics and transportation system through the identification. However, during transmission, the agricultural products need to be kept in a humid environment, and the agricultural products are stacked and stored. The transmission of the identification data is interfered with, resulting in signal attenuation or even loss. Therefore, this embodiment analyzes the identification data of the agricultural products in various regions, and then compensates for the signals of subsequent agricultural products passing through the area and collects them, thereby improving the validity of the identification data.

[0024] First of all, agricultural products are usually transported in batches of multiple types at the same time. It is necessary to collect the identification data, humidity and signal strength of the same batch of agricultural products at different sampling times when passing through various regions; the identification data contains the information of the agricultural products, which serves as the data support for agricultural product traceability, identification, resource tracking and other links; the signal strength is the wireless signal strength of the receiving sensing device of the logistics transmission system when collecting the identification data.

[0025] Specifically, unique labels are assigned to all types of agricultural products in the same batch to carry the identification data of each agricultural product. In this embodiment, the identification data of agricultural products is collected through radio frequency identification (RFID) technology. The labels are installed on the packaging of different types of agricultural products by attachment or other means. The logistics and transportation systems in various regions transmit wireless radio frequencies to the labels of all agricultural products through radio frequency equipment installed in the field, so as to read the identification information in the labels, and the receiving device receives the identification data, thereby achieving the purpose of identifying agricultural product targets and data exchange by the logistics and transportation systems in various regions; the receiving device is described using a receiving reader as an example.

[0026] It should be noted that the area described in this embodiment is the same environment of the agricultural products' route. As an example, the starting station through which the agricultural products pass is the first area, the journey from the starting station to the first transfer station is the second area, and the agricultural products arriving at the first transfer station is the third area.

[0027] As a preferred example, the specific steps of obtaining identification data, humidity and signal strength of each agricultural product at different sampling times when passing through various regions include: Radio frequency equipment and receiving readers are installed in each area, and a fixed sampling interval is set. Every other sampling interval is used as a sampling moment. The radio frequency equipment continuously transmits wireless radio frequency signals to the area. After the tags of each agricultural product of the same batch enter the range of the radio frequency signal emitted by the radio frequency equipment, the tags transmit the product information stored in the tags by means of the energy obtained by the induced current, which is received by the receiving reader of the logistics transportation system, and the identification data of each agricultural product of the same batch at different sampling moments when passing through each area are obtained, and the signal strength of the identification data is recorded; While collecting identification data and signal strength, the logistics and transportation system installs humidity sensors in each area. The humidity at each sampling moment obtained by the humidity sensors is recorded as the humidity at each sampling moment in each area.

[0028] It should be noted that the identification data described in this embodiment includes basic information of agricultural products, such as product identification number, product name, production batch number, specifications, storage temperature, shelf life, raw material batch number, origin, foreign matter detection results, etc. This embodiment does not limit the content of the basic information, and other embodiments may modify the content of the basic information; At the same time, the signal of the identification data may be interfered or weakened during the sampling process, resulting in the collection results being unrecognizable or unable to be sampled. At this time, the identification data of the agricultural products that cannot be identified or sampled are marked as missing, and the identification data are filled with null values. It is particularly important to note that as long as the label of the agricultural product receives the radio frequency signal emitted by the receiving reader, it can passively send the product information stored in the label. The product information is received by the receiving reader and then identified and read. The signal marked as missing cannot be fully identified and read, but the receiving reader can still receive the signal strength, so the signal strength of the identification data marked as missing is not all zero.

[0029] It should be noted that the agricultural products analyzed in this embodiment are agricultural products from the same batch. This embodiment divides different types of agricultural products in the same batch based on different identification data. Agricultural products with the same identification data are regarded as the same type of agricultural products, and agricultural products with different identification data are regarded as different types of agricultural products. The types of agricultural products described in this embodiment are not consistent with the species of agricultural products.

[0030] Among them, the radio frequency identification (RFID) technology and its specific transmission and reception of wireless radio frequency are existing well-known technologies and will not be described in detail in this embodiment.

[0031] Step S002: when the same batch of agricultural products passes through the current area, the environmental constraint coefficient of the current area is obtained, the number of missing identification data of all agricultural products at the same sampling time is counted, and the environmental positioning error of the current area is obtained in combination with the environmental constraint coefficient.

[0032] The moisture in the air will interfere with the transmission of wireless signals. Fluctuating humidity has a greater impact on the transmission of constant wireless RF signals than stable humidity. Increased humidity will cause scattering of wireless signals, and high humidity will increase the absorption effect of wireless signals, which will significantly weaken the signal strength. Therefore, the higher the humidity and the greater the fluctuation, the greater the demand for signal compensation. This embodiment obtains the environmental constraint coefficient of the current area according to the humidity fluctuation.

[0033] The last region that the same batch of agricultural products passes through in time sequence is recorded as the current region, and there are identification data, humidity and signal strength at several sampling moments in the current region; Preferably, the specific steps of obtaining the environmental constraint coefficient of the current area include: Construct a humidity curve for the current region based on the humidity at each sampling moment in the current region; After obtaining all positive increments in the humidity curve of the current area, the average value of the positive increments is obtained; The fluctuation of the humidity curve of the current area is analyzed and combined with the mean value of the positive increment to obtain the environmental constraint coefficient of the current area.

[0034] Specifically, a humidity curve of the current region is constructed according to the humidity at each sampling time in the current region, wherein the horizontal axis of the humidity curve is the sampling time and the vertical axis is the humidity value; Further, all the maximum and minimum values ​​in the humidity curve of the current area are obtained, and the maximum and minimum values ​​appear alternately; the range difference between each maximum value and the previous minimum value is recorded as the positive increment of the maximum value; the mean value of all the positive increments in the humidity curve of the current area is calculated; Furthermore, the method for obtaining the environmental constraint coefficient of the current area is: multiplying the mean of all positive increments in the humidity curve of the current area by the variance of all humidity in the humidity curve of the current area, and recording it as the environmental constraint coefficient of the current area; wherein, the variance of all humidity in the humidity curve of the current area is used to represent the fluctuation of the humidity curve of the current area.

[0035] It should be noted that after obtaining the interference of humidity on wireless signal propagation, agricultural products of the same batch need to be transported and moved in the same area. Therefore, the positions of agricultural products are different at different sampling times. Factors such as the obstruction of obstacles in the area and the distance between the tag and the receiving reader cause different numbers of agricultural product identifications that can be collected at different sampling times. Therefore, this embodiment obtains the environmental positioning error by counting the number of identification data of all agricultural products at the same sampling time and combining the environmental constraint coefficient.

[0036] Preferably, the specific steps of counting the number of missing identification data of all agricultural products at the same sampling time and obtaining the environmental positioning error of the current area in combination with the environmental constraint coefficient are: The number of identification data marked as missing in all agricultural products at the same sampling time in the current region is recorded as the missing amount of identification data at the sampling time in the current region; The ratio of the mean of the missing amount of identification data at all sampling moments in the current region to the amount of agricultural products is recorded as the missing rate of the current region; the product of the missing rate and the environmental constraint coefficient of the current region is recorded as the environmental positioning error of the current region.

[0037] Step S003: When the same batch of agricultural products passes through the current area, statistics are collected on the missing identification data of all agricultural products at different sampling times to obtain the frequency of identification loss in the current area; and the signal coverage completeness of the current area is obtained based on the signal strength of the same batch of agricultural products at different sampling times.

[0038] For the same agricultural product from the same batch, when it passes through the current area, if the label of the agricultural product fails, is blocked by other agricultural products and is in a signal blind spot, or the amount of information contained in the label of the agricultural product exceeds the processing bottleneck of the logistics transportation system, a large amount of identification data collected by the agricultural product when passing through the current area will be marked as missing, and there will be a continuous long period of missing data. This means that the identification data of the agricultural product is more likely to be missing. Therefore, this embodiment obtains the frequency of identification loss in the current area by counting the missing status of identification data of all agricultural products at different sampling times.

[0039] Preferably, the specific steps of counting the missing status of identification data of all agricultural products at different sampling times and obtaining the identification loss frequency of the current region include: When the same batch of agricultural products passes through the current area, the identification data of each agricultural product marked as missing is recorded as a missing sampling point of the agricultural product at all sampling moments; According to the continuous missing situation of all missing sampling points of each agricultural product, the identification perception failure rate of each agricultural product in the current area is obtained; Classifying all agricultural products in the current region according to the identification perception failure rate to obtain agricultural products that are prone to missing in the current region; The frequency of label loss in the current area is obtained based on the proportion of easily missing agricultural products in the current area and their label perception failure rate.

[0040] Specifically, according to the continuous missing of all missing sampling points of each agricultural product, the specific method of obtaining the identification perception failure rate of each agricultural product in the current area is as follows: For the current region agricultural products, The missing sampling points of agricultural products are merged to obtain the Several persistent missing segments for agricultural products; It should be noted that the above continuous representation means that the interval between the sampling moments corresponding to two adjacent missing sampling points in time sequence is equal to one sampling interval, and a missing sampling point segment consisting of a plurality of consecutive missing sampling points separated by only one sampling interval is recorded as a continuous missing segment; when the interval between a missing sampling point and other adjacent missing sampling points is greater than one sampling interval, a single missing sampling point also constitutes a continuous missing segment.

[0041] It should be particularly noted that the continuity described in this embodiment is described by taking an interval equal to a sampling interval as an example, and other embodiments may use other sampling interval lengths as conditions for judging continuity. This embodiment does not specifically limit the conditions for continuity.

[0042] Further, When agricultural products pass through the current region, Failure rate of perceived labeling of agricultural products The calculation method is:

[0043] in, For the The total number of identification data of agricultural products passing through the current region, For the The total number of missing sampling points when agricultural products pass through the current area; For the Total number of persistent missing segments for agricultural products; is the preset sampling interval time length, No. The agricultural product the length of time that the missing segment persists; is a priori fault tolerance multiple, which is greater than or equal to 1, and is used to avoid misjudging a continuous loss when the duration of a continuous missing segment is equal to the duration of the sampling interval. This article takes the example as an example and does not specifically limit the fault tolerance multiple.

[0044] in, Indicates The proportion of missing sampling points of agricultural products in all identification data. The larger the value, the The identification data of agricultural products in the current region are more likely to be missing, and The label of an agricultural product may be in a blind spot or blocked by other agricultural products, resulting in signal obstruction; at the same time, The larger the value, the The more continuous the missing sampling points of agricultural products are, the less likely they are to be sporadic signal missing.

[0045] Furthermore, the identification perception failure rate of all agricultural products passing through the current region is obtained.

[0046] Specifically, as an example, all agricultural products in the current region are divided according to the identification perception failure rate, and the specific method of obtaining the easily missing agricultural products in the current region is: Arrange the identification perception failure rates of all agricultural products when passing through the current area in descending order to obtain a descending sequence of identification perception failure rates of the agricultural products when passing through the current area, calculate the difference between two adjacent sequence values ​​in the descending sequence of identification perception failure rates, record the smaller sequence number of the two sequence values ​​corresponding to the maximum difference in the difference between the two adjacent sequence values ​​as the separation sequence number, and record the agricultural products corresponding to all sequence values ​​from the first sequence number to the separation sequence number and including the first sequence number in the descending sequence of identification perception failure rates as easily missing agricultural products in the current area.

[0047] It should be noted that the above classification method is based on great differences, so that the identification perception failure rate of easily missing agricultural products is much higher than that of other agricultural products. Easy to miss agricultural products represent agricultural products in the current area that are prone to signal loss.

[0048] As another example, all agricultural products in the current region are divided according to the identification perception failure rate, and the specific method for obtaining the easily missing agricultural products in the current region is: Arrange the identification perception failure rates of all agricultural products when passing through the current area in descending order to obtain a descending sequence of identification perception failure rates of the agricultural products when passing through the current area; divide the descending sequence of identification perception failure rates into two equal parts, and record the agricultural products corresponding to the serial number values ​​with larger identification perception failure rates as easily missing agricultural products.

[0049] Specifically, the specific method of obtaining the frequency of label loss in the current region according to the proportion of easily missing agricultural products in the current region and their label perception failure rate is as follows: When the same batch of agricultural products passes through the current area, the ratio of the number of easily missing agricultural products in the same batch to the total number of agricultural products in the same batch, and the product of the label perception failure rate of all easily missing agricultural products in the same batch, is recorded as the frequency of label loss in the current area.

[0050] Among them, the larger the ratio of the number of easily missing agricultural products in the same batch to the total number of agricultural products in the same batch, the more likely it is that this batch of agricultural products will have missing identification data due to reasons such as labels or sensing devices when passing through the current area.

[0051] It should be noted that, while obtaining the frequency of identification loss in the current area, in order to prove that the frequency of identification loss is caused by the tag or the receiving end in the area, such as the tag is blocked by other agricultural products, or the receiving end is far away from the tag, resulting in a significant weakening of the signal strength, it is necessary to compensate for the signal strength received by the receiving end, so that the radio frequency signal received by the receiving end after passive reflection by the tag has sufficient signal strength to be recognized. Therefore, this embodiment obtains the signal coverage completeness of the current area according to the signal strength of the same batch of agricultural products at different sampling times.

[0052] Preferably, the specific steps of obtaining the signal coverage completeness of the current area according to the signal strength of the same batch of agricultural products at different sampling times are: When the same batch of agricultural products passes through the current area, a signal strength fluctuation curve when the same batch of agricultural products passes through the current area is constructed according to the signal strength of all agricultural products at each moment; The signal coverage completeness of the current area is obtained by quantifying the downward amplitude of the signal strength fluctuation curve and the amplitude of all negative increments.

[0053] Specifically, the specific method of constructing the signal strength fluctuation curve of the same batch of agricultural products passing through the current region is: When the same batch of agricultural products passes through the current area, the mean signal strength of the identification data of all agricultural products at the same sampling time is calculated, and recorded as the mean signal strength of the same batch of agricultural products at each sampling time; The signal mean intensity of the same batch of agricultural products at all sampling times is mapped into a two-dimensional space, where the horizontal axis is the sampling time and the vertical axis is the signal mean intensity, to obtain the signal intensity fluctuation curve of the same batch of agricultural products when passing through the current area.

[0054] Furthermore, quantifying the downward amplitude of the signal strength fluctuation curve and the amplitude of all negative increments to obtain the signal coverage completeness of the current area specifically includes: The ratio of the minimum value of the signal mean strength to the average value of the signal mean strength at all sampling moments of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region is recorded as the downward range of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region; The signal coverage completeness of the current area is obtained by combining the downward amplitude of the signal strength fluctuation curve when the same batch of agricultural products passes through the current area and the average of the amplitudes of all negative increments, wherein the downward amplitude is in direct proportion to the signal coverage completeness, and the average of the amplitudes of the negative increments is in inverse proportion to the signal coverage completeness; As an example, the coverage of the current area is complete. The calculation method is:

[0055] in, is the downward range of the signal strength fluctuation curve of the same batch of agricultural products passing through the current area, It is the average of the amplitudes of all negative increments in the signal strength fluctuation curve of the same batch of agricultural products when passing through the current area.

[0056] It should be noted that in the signal strength fluctuation curve when the same batch of agricultural products passes through the current area, the difference between the signal mean strength at the next sampling moment and the previous moment is taken as the increment. When the increment is less than 0, it is recorded as the negative increment of the signal strength fluctuation curve, which is used to indicate the decrease in signal strength at adjacent sampling moments. The greater the decrease, the more likely it is that the tag is blocked by the environment, and the less complete the signal coverage. At the same time, the downward amplitude surface shows the degree of decrease of the minimum value of the signal strength in the current area compared with other sampling moments. The larger the value, the more sampling nodes with incomplete signal coverage there are in the current area, that is, incomplete coverage will cause the inability to identify and perceive agricultural products when they are transported to some areas.

[0057] Step S004, obtaining the identification loss frequency and signal coverage completeness of each region; obtaining the positioning coverage attenuation of the current region based on the consistency of the covariant relationship between the identification loss frequency and signal coverage completeness of the current region and the previous region passed through.

[0058] The above obtains the signal coverage completeness of the current area and the frequency of identification loss in the current area when the same batch of agricultural products passes through the current area. Similarly, when the batch of agricultural products passes through various areas, the frequency of identification loss and signal coverage completeness of each area will be obtained; It should be noted that the above-mentioned regions represent the regions passed by the current region, and do not include the regions after the current region.

[0059] It should be noted that the frequency of identification loss indicates the loss of agricultural products when passing through the area, while the signal coverage indicates the signal coverage of the area when collecting the identification of agricultural products; when the signal loss is due to the stacking of agricultural products during transportation, which causes the identification to be blocked, or the increase in the number of agricultural products in the same batch causes the number of identifications to exceed the perception load of the perception system, the signal coverage of the same batch of agricultural products in different areas is correlated with the frequency of identification loss. Therefore, this embodiment analyzes the covariant relationship between the signal coverage and the frequency of identification loss of the same batch of agricultural products in all areas along the way, and uses the covariant relationship as a weight to obtain the positioning coverage attenuation of the current area.

[0060] Preferably, according to the consistency of the covariance relationship between the identification loss frequency and the signal coverage completeness of the current area and the area before the current area, the specific steps of obtaining the positioning coverage attenuation of the current area include: According to the frequency of identification loss and signal coverage completeness of each region of the same batch of agricultural products, the identification loss frequency sequence and signal coverage completeness sequence of the batch of agricultural products are constructed, where the sequence number value represents the regional order of the route; The mean square error of the label loss frequency sequence and signal coverage completeness sequence of the same batch of agricultural products is obtained, which is recorded as the subjective deviation degree of the label of the same batch of agricultural products; The degree of subjective deviation of the label is used to reflect the constant performance of the label of this batch of agricultural products in regions with different perception accuracy. The larger the value, the more the missing identification data of this batch of agricultural products is affected by the regional perception accuracy. When the label of agricultural products is not affected by the perception accuracy, there is no longer a relationship between the frequency of identification loss and the completeness of signal coverage, that is, the more obvious the perception accuracy of a batch of agricultural products, the stronger the compensation effect. Therefore, the degree of subjective deviation of the label of this batch of agricultural products can be used as a compensation weight for signal compensation.

[0061] Furthermore, a batch of agricultural products that has recently passed through the current region is recorded as the current batch of agricultural products; The positioning coverage attenuation of the current area is obtained by comprehensively considering the frequency of identification loss and the completeness of signal coverage in the current area and combining the degree of subjective deviation of the labels of the current batch of agricultural products. The frequency of identification loss and the degree of subjective deviation of the labels are directly proportional to the positioning coverage attenuation, and the signal coverage completeness is inversely proportional to the positioning coverage attenuation.

[0062] As an example, the positioning coverage attenuation of the current area is obtained as follows: The frequency of identity loss in the current region is recorded as ; The degree of subjective deviation of the label of the current batch of agricultural products is recorded as ; Positioning coverage attenuation in the current area The calculation method is:

[0063] in, The completeness of signal coverage in the current area.

[0064] Step S005: Generate compensation parameters for the current area using the positioning coverage attenuation and the environmental positioning error; and use the compensation parameters to perform sampling compensation on identification data of the next batch of agricultural products passing through the current area.

[0065] It should be noted that the purpose of this embodiment is to analyze the collection results of the identification data of the current batch of agricultural products after the current batch of agricultural products passes through the current area, so as to compensate for the signal strength of the tag sensing device in the current area, and improve the identification sensing accuracy of the tag sensing device for the next batch of agricultural products after the next batch of agricultural products enters the current area.

[0066] It should be further explained that the above method obtains the positioning coverage attenuation and environmental positioning error of the current area, wherein the larger the environmental positioning error, the greater the impact of environmental interference in the current area, and the more signal strength needs to be compensated to reduce the number of identification data marked as missing; at the same time, the larger the value of the positioning coverage attenuation of the current area, the greater the impact of other factors in the current area, such as the greater the distance between the agricultural products and the identification sensing device, etc., on the accuracy of identification data collection; therefore, this embodiment uses the positioning coverage attenuation and the environmental positioning error to generate compensation parameters for the current area; and uses the compensation parameters to perform sampling compensation on the identification data of the next batch of agricultural products passing through the current area.

[0067] Preferably, the specific steps of generating the compensation parameters of the current area by using the positioning coverage attenuation and the environmental positioning error of the current area are: As an example, the compensation parameters for the current region are calculated as: The environmental positioning error of the current area is recorded as ;

[0068] in, is the compensation parameter of the current region, The positioning coverage attenuation of the current area; is a sigmoid function, which is used to normalize the positioning coverage attenuation and the environmental positioning error to , eliminating the impact of different magnitudes.

[0069] As another example, the compensation parameter for the current region is calculated as: The environmental positioning error of the current area is recorded as ;

[0070] in, is the compensation parameter of the current region, The positioning coverage attenuation of the current area.

[0071] Furthermore, using the compensation parameter to perform sampling compensation on the identification data of the next batch of agricultural products passing through the current region specifically includes: As an example, the present embodiment uses the pre-emphasis technology to perform signal compensation, wherein the tag sensing device takes a receiving reader as an example, and the tag sensing technology takes the radio frequency identification technology as an example; When the next batch of agricultural products passes through the current area, a radio frequency signal is transmitted to the current area through the radio frequency transmitting device. The label on the next batch of agricultural products sends out the product information stored in the label by means of the energy obtained by the induced current. After being received by the receiving reader of the logistics transportation system, an identification signal to be processed is obtained. The identification signal to be processed is an analog signal. The identification signal to be processed is compensated by the compensation parameter of the current area in combination with the pre-emphasis technology to obtain a processed identification signal. The compensation result is that the high-frequency signal of the processed representation signal is 1 of the high-frequency signal of the identification signal to be processed plus a multiple of the compensation parameter; the processed representation signal is converted into digital-to-analog format to obtain identification data of each agricultural product of the next batch at different sampling times when passing through each area.

[0072] It should be noted that the above-mentioned sampling compensation for the identification data of the next batch of agricultural products passing through the current area is an example compensation method proposed in this embodiment, wherein the pre-emphasis technology utilized is an existing well-known technology, and other embodiments may adopt other compensation methods for sampling compensation. This embodiment does not specifically limit the sampling compensation method.

[0073] In the second aspect, another embodiment of the present invention also provides a positioning data perception device based on identity resolution, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the memory is used to store the computer program, and the processor executes the computer program to implement the steps of the aforementioned positioning data perception method based on identity resolution.

[0074] In a third aspect, another embodiment of the present invention further provides a positioning data perception medium based on identity resolution, on which a computer instruction is stored, and when the computer instruction is executed by a processor, the following operations are performed: Collect the identification of all agricultural products in the same batch, obtain the identification data and signal strength of each agricultural product at different sampling times when passing through each region, and the humidity at each sampling time in each region; When the same batch of agricultural products passes through the current area, the environmental constraint coefficient of the current area is obtained, and the environmental constraint coefficient is positively correlated with the humidity fluctuation of the agricultural products in the current area; the number of missing identification data of all agricultural products at the same sampling time is counted, and the environmental positioning error of the current area is obtained by combining the environmental constraint coefficient; the missing identification data of all agricultural products at different sampling times are counted to obtain the frequency of identification loss in the current area; according to the signal strength of the same batch of agricultural products at different sampling times, the signal coverage completeness of the current area is obtained; Obtain the identification loss frequency and signal coverage completeness of each region; obtain the positioning coverage attenuation of the current region based on the consistency of the covariant relationship between the identification loss frequency and signal coverage completeness of the current region and the previous region passed through; The compensation parameters of the current area are generated by using the positioning coverage attenuation and the environmental positioning error; and the compensation parameters are used to perform sampling compensation on the identification data of the next batch of agricultural products passing through the current area.

[0075] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A positioning data perception method based on identity resolution, characterized in that: The method comprises the following steps: Collect the identification of all agricultural products in the same batch, obtain the identification data and signal strength of each agricultural product at different sampling times when passing through each region, and the humidity at each sampling time in each region; When the same batch of agricultural products passes through the current area, the environmental constraint coefficient of the current area is obtained, and the environmental constraint coefficient is positively correlated with the humidity fluctuation of the agricultural products in the current area; the number of missing identification data of all agricultural products at the same sampling time is counted, and the environmental positioning error of the current area is obtained by combining the environmental constraint coefficient; the missing identification data of all agricultural products at different sampling times are counted to obtain the frequency of identification loss in the current area; according to the signal strength of the same batch of agricultural products at different sampling times, the signal coverage completeness of the current area is obtained; Obtain the identification loss frequency and signal coverage completeness of each region; obtain the positioning coverage attenuation of the current region based on the consistency of the covariant relationship between the identification loss frequency and signal coverage completeness of the current region and the previous region passed through; The compensation parameters of the current area are generated by using the positioning coverage attenuation and the environmental positioning error; and the compensation parameters are used to perform sampling compensation on the identification data of the next batch of agricultural products passing through the current area.

2. According to claim 1, a positioning data perception method based on identity resolution is characterized in that: The specific steps of obtaining the environmental constraint coefficient include: Construct a humidity curve for the current region based on the humidity at each sampling time in the current region, where the horizontal axis of the humidity curve is the sampling time and the vertical axis is the humidity value; Take all the maximum and minimum values ​​in the humidity curve of the current area; record the range between each maximum value and the previous minimum value as the positive increment of the maximum value; calculate the mean of all positive increments in the humidity curve of the current area; The product of the mean of all positive increments in the humidity curve of the current region and the variance of all humidity in the humidity curve of the current region is recorded as the environmental constraint coefficient of the current region.

3. According to claim 1, a positioning data perception method based on identity resolution is characterized in that: The specific steps of obtaining the environmental positioning error include: The number of identification data marked as missing in all agricultural products at the same sampling time in the current region is recorded as the missing amount of identification data at the sampling time in the current region; The ratio of the mean of the missing amount of identification data at all sampling moments in the current region to the amount of agricultural products is recorded as the missing rate of the current region; The product of the missing rate and the environmental constraint coefficient of the current area is recorded as the environmental positioning error of the current area.

4. According to claim 1, a positioning data perception method based on identity resolution is characterized in that: The specific steps of obtaining the frequency of identification loss include: When the same batch of agricultural products passes through the current area, the identification data of each agricultural product marked as missing is recorded as a missing sampling point of the agricultural product at all sampling moments; According to the continuous missing situation of all missing sampling points of each agricultural product, the identification perception failure rate of each agricultural product in the current area is obtained; Classifying all agricultural products in the current region according to the identification perception failure rate to obtain agricultural products that are prone to missing in the current region; The frequency of label loss in the current region is obtained based on the proportion of easily missing agricultural products in the current region and their label perception failure rate; The product of the ratio of the number of easily missing agricultural products in the same batch to the total number of agricultural products in the same batch and the identification perception failure rate of all easily missing agricultural products in the same batch is recorded as the identification loss frequency in the current area.

5. The positioning data perception method based on identity resolution according to claim 4 is characterized in that: The specific steps of obtaining the identification perception failure rate include: For the current region agricultural products, The missing sampling points of agricultural products are merged to obtain the Several persistent missing segments for agricultural products; No. When agricultural products pass through the current region, Failure rate of perceived labeling of agricultural products The calculation method is: in, For the The total number of identification data of agricultural products passing through the current region, For the The total number of missing sampling points when agricultural products pass through the current area; For the Total number of persistent missing segments for agricultural products; is the length of the preset sampling interval. No. The agricultural product the length of time that the missing segments persist; is the prior fault tolerance multiple.

6. The positioning data perception method based on identity resolution according to claim 4 is characterized in that: The specific steps for obtaining the easily missing agricultural products include: The identification perception failure rate when obtaining all agricultural products passing through the current region; Arrange the identification perception failure rates of all agricultural products when passing through the current area in descending order to obtain a descending sequence of identification perception failure rates of the agricultural products when passing through the current area, calculate the difference between two adjacent sequence values ​​in the descending sequence of identification perception failure rates, record the smaller sequence number of the two sequence values ​​corresponding to the maximum difference in the difference between the two adjacent sequence values ​​as the separation sequence number, and record the agricultural products corresponding to all sequence values ​​from the first sequence number to the separation sequence number and including the first sequence number in the descending sequence of identification perception failure rates as easily missing agricultural products in the current area.

7. The positioning data perception method based on identity resolution according to claim 1 is characterized in that: The specific steps of obtaining the signal coverage completeness include: When the same batch of agricultural products passes through the current area, the mean signal strength of the identification data of all agricultural products at the same sampling time is calculated, and recorded as the mean signal strength of the same batch of agricultural products at each sampling time; The signal mean intensity of the same batch of agricultural products at all sampling times is mapped into a two-dimensional space, where the horizontal axis is the sampling time and the vertical axis is the signal mean intensity, and the signal intensity fluctuation curve of the same batch of agricultural products passing through the current area is obtained; The ratio of the minimum value of the signal mean strength to the average value of the signal mean strength at all sampling moments of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region is recorded as the downward range of the signal strength fluctuation curve when the same batch of agricultural products passes through the current region; The signal coverage completeness of the current area is obtained by combining the downward amplitude of the signal strength fluctuation curve of the same batch of agricultural products when passing through the current area and the average of the amplitudes of all negative increments, wherein the downward amplitude is directly proportional to the signal coverage completeness, and the average of the amplitudes of the negative increments is inversely proportional to the signal coverage completeness.

8. The positioning data perception method based on identity resolution according to claim 1, characterized in that: The specific steps of obtaining the positioning coverage attenuation include: According to the frequency of label loss and signal coverage completeness of the same batch of agricultural products in different regions, the label loss frequency sequence and signal coverage completeness sequence of the batch of agricultural products are constructed; The mean square error of the label loss frequency sequence and signal coverage completeness sequence of the same batch of agricultural products is obtained, which is recorded as the subjective deviation degree of the label of the same batch of agricultural products; Record the batch of agricultural products that has recently passed through the current area as the current batch of agricultural products; The positioning coverage attenuation of the current area is obtained by comprehensively considering the frequency of identification loss and the completeness of signal coverage in the current area and combining the degree of subjective deviation of the labels of the current batch of agricultural products. The frequency of identification loss and the degree of subjective deviation of the labels are directly proportional to the positioning coverage attenuation, and the signal coverage completeness is inversely proportional to the positioning coverage attenuation.

9. A positioning data perception device based on identity resolution, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of a positioning data perception method based on identity resolution as described in any one of claims 1 to 8 are implemented.

10. A positioning data sensing medium based on identification resolution, on which computer instructions are stored, characterized in that: When the computer instruction is executed by a processor, the steps of a positioning data perception method based on identity resolution as described in any one of claims 1 to 8 are implemented.

Images