Elliptical edge-blurred rfid communication area modeling method and system

Abstract

This invention relates to the field of RFID communication technology, specifically disclosing a method and system for modeling RFID communication regions with elliptical edge blurring. The invention acquires initial communication data returned by RFID tags; performs identification and analysis of communication stability and distribution to construct an initial elliptical communication model; analyzes the signal attenuation trend at the elliptical edges to plan edge blurring intervals; performs confidence level stratification of the RFID communication region to generate an RFID communication region model; and adaptively updates the RFID communication region model. This invention enables the identification and analysis of communication stability and distribution, the construction of an initial elliptical communication model, the planning of edge blurring intervals, and the generation of an RFID communication region model through confidence level stratification. This ensures that the spatial distribution of RFID communication signals matches the gradual change characteristics of real communication, avoiding misjudgments and improving the realism and reliability of communication region modeling.

Description

Technical Field

[0001] This invention belongs to the field of RFID communication technology, and in particular relates to a method and system for modeling RFID communication regions with blurred elliptical edges. Background Technology

[0002] RFID communication is a communication technology that uses radio frequency signals to achieve contactless information transmission and automatic identification. By attaching RFID tags to target objects, readers transmit radio frequency signals within a certain distance to establish a wireless communication link with the tags, thereby completing the reading, writing, and interaction of the target object's identity information or related data. It is widely used in logistics management, asset tracking, intelligent manufacturing, access control systems, and smart cities, and is one of the important basic communication technologies of the Internet of Things (IoT) sensing layer.

[0003] In existing technologies, RFID communication area modeling methods typically use fixed thresholds or simple geometric boundaries to describe the communication coverage area, dividing the communication area into communicable and non-communicable areas. This simple division does not match the gradual distribution characteristics of RFID communication signals in space, and therefore does not reflect the actual communication situation, which can easily lead to misjudgments. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for modeling RFID communication regions with blurred elliptical edges, aiming to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: A method for modeling RFID communication regions with blurred elliptical edges, the method specifically includes the following steps: The RFID reader is activated to continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data. The standard communication data is analyzed for communication stability and distribution to determine the center point, principal axis, and secondary axis, and an initial elliptical communication model is constructed. Based on the standard communication data, the signal attenuation trend analysis of the elliptical edge of the initial elliptical communication model is performed, the edge blurring interval is planned, and multiple blurring position weights are generated. By combining the standard communication data and multiple fuzzy location weights, the RFID communication area is layered with confidence levels to generate an RFID communication area model. RFID communication data is continuously collected, and the RFID communication area model is adaptively updated.

[0006] As a further limitation of the technical solution of this embodiment of the invention, the step of activating the RFID reader to continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data specifically includes the following steps: Start the RFID reader / writer to continuously scan the RFID communication area and obtain the initial communication data returned by the RFID tags; The initial communication data is formatted and recorded to include the communication point location, signal strength, and communication success status, generating formatted communication data. The formatted communication data is time-consistently aligned to generate aligned communication data; The aligned communication data is processed to identify and remove abnormal communication data, and standard communication data is generated.

[0007] As a further limitation of the technical solution of this invention, the step of identifying and analyzing the communication stability and distribution of the standard communication data, determining the center point, principal axis, and secondary axis, and constructing an initial elliptical communication model specifically includes the following steps: Perform spatial clustering analysis on the standard communication data to determine the range of stable regions; The spatial center of the stable region is selected as the center point; The standard communication data is subjected to communication distribution extension direction identification to determine the main axis direction and the secondary axis direction; Based on the main axis direction and the secondary axis direction, the standard communication data is effectively distributed to determine the main axis length and the secondary axis length; An initial elliptical communication model is constructed based on the center point, the direction of the principal axis, the direction of the secondary axis, the length of the principal axis, and the length of the secondary axis.

[0008] As a further limitation of the technical solution of this embodiment of the invention, the step of performing signal attenuation trend analysis on the initial elliptical communication model based on the standard communication data, planning the edge blurring interval, and generating multiple blurring position weights specifically includes the following steps: Based on the standard communication data, the signal attenuation trend analysis of the elliptical edge of the initial elliptical communication model is performed to determine the signal attenuation rate in different directions. Plan the edge blurring interval according to the signal attenuation rate in different directions; According to the aforementioned edge blurring interval, a blurred edge region is constructed at the edge of the initial elliptical communication model; For different locations in the blurred edge region, continuously varying blur weights are configured to obtain multiple blurred position weights.

[0009] As a further limitation of the technical solution of this embodiment of the invention, the step of integrating the standard communication data and multiple fuzzy position weights to perform confidence level stratification of the RFID communication area and generate an RFID communication area model specifically includes the following steps: From the standard communication data, extract communication success rate data and signal strength data; By combining the communication success rate data, the signal strength data, and multiple fuzzy location weights, the location confidence level of different locations in the RFID communication area is analyzed and determined. Based on the multiple location confidence levels, the RFID communication area is divided into high, medium, and low confidence levels to obtain the confidence level stratification results; The confidence level stratification result, the fuzzy edge region, and the initial elliptical communication model are fused to form an RFID communication region model with fuzzy edges and confidence level distribution.

[0010] As a further limitation of the technical solution of this embodiment of the invention, the continuous collection of RFID communication data and the adaptive updating of the RFID communication area model specifically includes the following steps: Continuously collect RFID communication data; The RFID communication data is monitored and analyzed to determine whether there are changes in the elliptic parameters; When the ellipse parameters change, the ellipse parameters of the RFID communication area model are adjusted. The confidence level stratification results and fuzzy edge regions are updated synchronously to achieve adaptive updates of the RFID communication area model.

[0011] An RFID communication region modeling system with elliptical edge blurring, the system comprising an initial communication processing unit, an ellipse parameter analysis unit, an edge blurring analysis unit, a confidence level layering processing unit, and a model automatic update unit, wherein: An initial communication processing unit is used to start the RFID reader / writer, continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data. The elliptic parameter analysis unit is used to identify and analyze the communication stability and communication distribution of the standard communication data, determine the center point, principal axis and secondary axis, and construct an initial elliptic communication model. The edge fuzzing analysis unit is used to perform signal attenuation trend analysis on the edge of the initial elliptical communication model based on the standard communication data, plan the edge fuzzing interval, and generate multiple fuzzy position weights. The confidence level processing unit is used to integrate the standard communication data and multiple fuzzy location weights to perform confidence level layering on the RFID communication area and generate an RFID communication area model. The model automatic update unit is used to continuously collect RFID communication data and adaptively update the RFID communication area model.

[0012] As a further limitation of the technical solution of this embodiment of the invention, the initial communication processing unit specifically includes: The initial communication module is used to start the RFID reader / writer, continuously scan the RFID communication area, and obtain the initial communication data returned by the RFID tag. The formatted record module is used to format and record the initial communication data, including the communication point location, signal strength, and communication success status, to generate formatted communication data. The time alignment module is used to perform time consistency alignment on the formatted communication data to generate aligned communication data. An anomaly handling module is used to identify and remove abnormal communication data from the aligned communication data, and generate standard communication data.

[0013] As a further limitation of the technical solution of this embodiment of the invention, the ellipse parameter analysis unit specifically includes: The spatial clustering analysis module is used to perform spatial clustering analysis on the standard communication data to determine the stable region range. The center point selection module is used to select the spatial center of the stable region as the center point; The extension direction identification module is used to identify the extension direction of the communication distribution of the standard communication data and determine the main axis direction and the secondary axis direction. An effective distribution analysis module is used to perform effective distribution analysis on the standard communication data based on the main axis direction and the secondary axis direction to determine the main axis length and the secondary axis length. The initial model construction module is used to construct an initial elliptical communication model based on the center point, the direction of the principal axis, the direction of the secondary axis, the length of the principal axis, and the length of the secondary axis.

[0014] As a further limitation of the technical solution of this embodiment of the invention, the edge blurring analysis unit specifically includes: The signal attenuation trend analysis module is used to perform signal attenuation trend analysis on the edge of the initial elliptical communication model based on the standard communication data, and to determine the signal attenuation rate in different directions. The fuzzy interval planning module is used to plan the edge fuzzification interval according to the signal attenuation rate in different directions; A blurred edge region construction module is used to construct blurred edge regions at the edges of the initial elliptical communication model according to the blurred edge interval; The weight configuration module is used to configure continuously changing fuzzy weights for different locations in the fuzzy edge region, thereby obtaining multiple fuzzy position weights.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention, through obtaining initial communication data returned by RFID tags, performs identification and analysis of communication stability and distribution to construct an initial elliptical communication model; analyzes the signal attenuation trend at the edges of the ellipse and plans edge ambiguity intervals; performs confidence level stratification of the RFID communication region to generate an RFID communication region model; and adaptively updates the RFID communication region model. This allows for the identification and analysis of communication stability and distribution, the construction of an initial elliptical communication model, the planning of edge ambiguity intervals, and the generation of an RFID communication region model through confidence level stratification. This ensures that the spatial distribution of RFID communication signals matches the gradual changes in real communication, avoiding misjudgments and improving the realism and reliability of the communication region modeling. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0017] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0018] Figure 2 A flowchart illustrating the method for acquiring standard communication data provided in an embodiment of the present invention is shown.

[0019] Figure 3 A flowchart illustrating the construction of an initial elliptic communication model in the method provided by an embodiment of the present invention is shown.

[0020] Figure 4 A flowchart illustrating the planning of edge blurring intervals in the method provided by an embodiment of the present invention is shown.

[0021] Figure 5 A flowchart illustrating the generation of an RFID communication area model in the method provided by an embodiment of the present invention is shown.

[0022] Figure 6 A flowchart of RFID communication area model updating in the method provided by an embodiment of the present invention is shown.

[0023] Figure 7 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0024] Figure 8 A structural block diagram of the initial communication processing unit in the system provided by an embodiment of the present invention is shown.

[0025] Figure 9 A structural block diagram of the elliptic parameter analysis unit in the system provided by an embodiment of the present invention is shown.

[0026] Figure 10 A structural block diagram of the edge fuzzy analysis unit in the system provided by an embodiment of the present invention is shown. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0028] Understandably, in existing technologies, RFID communication area modeling methods typically use fixed thresholds or simple geometric boundaries to describe the communication coverage area, dividing the communication area into communicable and non-communicable areas. This simple division does not match the gradual distribution characteristics of RFID communication signals in space, and therefore does not reflect the actual communication situation, making it prone to misjudgment.

[0029] To address the aforementioned issues, this invention employs an RFID reader / writer to continuously scan the RFID communication area, acquiring initial communication data returned by RFID tags. This initial data is then processed to obtain standard communication data. The standard communication data undergoes communication stability and distribution identification analysis to determine the center point, principal axis, and secondary axis, constructing an initial elliptical communication model. Based on the standard communication data, signal attenuation trend analysis is performed on the elliptical edges of the initial elliptical communication model, planning edge fuzzification intervals and generating multiple fuzzy position weights. By integrating the standard communication data and multiple fuzzy position weights, the RFID communication area is layered with confidence levels to generate an RFID communication area model. RFID communication data is continuously collected, and the RFID communication area model is adaptively updated. This approach enables the identification and analysis of communication stability and distribution, the construction of an initial elliptical communication model, the planning of edge fuzzification intervals, and the layering of confidence levels to generate an RFID communication area model. This ensures that the spatial distribution of RFID communication signals matches the gradual changes in real communication, avoiding misjudgments and improving the realism and reliability of the communication area modeling.

[0030] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0031] Specifically, the method for modeling RFID communication regions with blurred elliptical edges includes the following steps: Step S101: Start the RFID reader / writer to continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data.

[0032] In this embodiment of the invention, the RFID reader is activated to continuously scan the RFID communication area, thereby acquiring the initial communication data returned by the RFID tag. The initial communication data is then formatted and recorded to include the communication point location, signal strength, and communication success status, generating formatted communication data. Subsequently, the formatted communication data is time-consistently aligned to generate aligned communication data, avoiding the impact of communication delays or momentary interference. Finally, the aligned communication data is processed to identify and remove abnormal communication data, suppressing abnormal communication samples and generating standard communication data.

[0033] Specifically, Figure 2 A flowchart illustrating the method for acquiring standard communication data provided in an embodiment of the present invention is shown.

[0034] In a preferred embodiment of the present invention, the steps of activating the RFID reader to continuously scan the RFID communication area, acquiring the initial communication data returned by the RFID tag, and processing the initial communication data to obtain standard communication data specifically include the following steps: Step S1011: Start the RFID reader / writer to continuously scan the RFID communication area and obtain the initial communication data returned by the RFID tag; Step S1012: Format and record the initial communication data, including communication point location, signal strength, and communication success status, to generate formatted communication data; Step S1013: Perform time consistency alignment on the formatted communication data to generate aligned communication data; Step S1014: Identify and remove abnormal communication data from the aligned communication data to generate standard communication data.

[0035] Furthermore, the RFID communication region modeling method with blurred elliptical edges also includes the following steps: Step S102: Identify and analyze the communication stability and communication distribution of the standard communication data, determine the center point, principal axis and secondary axis, and construct an initial elliptical communication model.

[0036] In this embodiment of the invention, by performing spatial clustering analysis on standard communication data to determine the most stable communication region, the spatial center of the stable region is selected as the center point of the ellipse. Then, the extension direction of the communication distribution of the standard communication data is identified to determine the principal axis direction and the secondary axis direction. Based on the principal axis direction and the secondary axis direction, an effective distribution analysis is performed on the standard communication data to determine the principal axis length and the secondary axis length. Finally, based on the center point, principal axis direction, secondary axis direction, principal axis length, and secondary axis length, an initial elliptical communication model is constructed.

[0037] Specifically, Figure 3 A flowchart illustrating the construction of an initial elliptic communication model in the method provided by an embodiment of the present invention is shown.

[0038] In a preferred embodiment of the present invention, the step of identifying and analyzing the communication stability and distribution of the standard communication data, determining the center point, principal axis, and secondary axis, and constructing an initial elliptical communication model specifically includes the following steps: Step S1021: Perform spatial clustering analysis on the standard communication data to determine the stable region range; Step S1022: Select the spatial center of the stable region as the center point; Step S1023: Identify the extension direction of the communication distribution of the standard communication data to determine the main axis direction and the secondary axis direction; Step S1024: Based on the main axis direction and the secondary axis direction, perform effective distribution analysis on the standard communication data to determine the main axis length and the secondary axis length; Step S1025: Construct an initial elliptical communication model based on the center point, the direction of the principal axis, the direction of the secondary axis, the length of the principal axis, and the length of the secondary axis.

[0039] Specifically, the standard communication data is subjected to communication distribution extension direction identification to determine the main axis direction and the secondary axis direction. The specific steps are as follows: Extract the location coordinates of each communication point and the corresponding instantaneous signal strength value from the standard communication data, and associate the location coordinates of the communication point with the corresponding instantaneous signal strength value to obtain the location-signal strength set; A signal strength threshold is preset based on the formatted communication data; the instantaneous signal strength values ​​in the location-signal strength set are filtered using the signal strength threshold to select the communication point location coordinates corresponding to signal strength values ​​higher than the signal strength threshold, thus obtaining a set of filtered communication points; Identify and statistically analyze the principal eigenvector directions of the covariance matrix of all communication point locations in the communication point set to obtain the straight line direction representing the maximum extension trend of the point; mark the straight line direction representing the maximum extension trend of the point as the initial main extension direction. In a two-dimensional plane, the direction orthogonal to the initial extension main direction is marked as the initial vertical secondary direction; the initial extension main direction and the initial vertical secondary direction are adjusted by using the overall distribution pattern of the communication points in the filtered communication point set to obtain the adjusted main and secondary directions; The degree of fit between the adjusted primary and secondary directions and the distribution of all communication points in the standard communication data is verified one by one, and the adjusted primary and secondary directions with the highest degree of fit with the spatial distribution of communication points are selected as the primary axis direction and the secondary axis direction.

[0040] Furthermore, this invention screens reliable locations with high signal strength from communication data, extracts the dominant extension direction based on their distribution covariance matrix, and then performs fine-tuning and verification in conjunction with the overall distribution pattern, thereby accurately identifying the main axis and secondary axis directions of the communication point distribution, providing a reliable directional basis for subsequent data analysis and spatial optimization.

[0041] Furthermore, the RFID communication region modeling method with blurred elliptical edges also includes the following steps: Step S103: Based on the standard communication data, perform signal attenuation trend analysis on the edge of the initial elliptical communication model, plan the edge blurring interval, and generate multiple blurry position weights.

[0042] In this embodiment of the invention, based on standard communication data, the signal attenuation trend analysis of the edge of the initial elliptical communication model is performed to identify the trend of signal change from stable to unstable, determine the signal attenuation rate in different directions, and then plan the edge fuzzification interval according to the signal attenuation rate in different directions. According to the edge fuzzification interval, a fuzzy edge region is constructed at the edge of the initial elliptical communication model. For different positions in the fuzzy edge region, continuously changing fuzzy weights are configured to obtain multiple fuzzy position weights, which are used to represent the degree of possibility that different positions belong to the RFID communication area.

[0043] Specifically, Figure 4 A flowchart illustrating the planning of edge blurring intervals in the method provided by an embodiment of the present invention is shown.

[0044] In a preferred embodiment of the present invention, the step of performing signal attenuation trend analysis on the elliptical edge of the initial elliptical communication model based on the standard communication data, planning the edge blurring interval, and generating multiple blurring position weights specifically includes the following steps: Step S1031: Based on the standard communication data, perform signal attenuation trend analysis on the edge of the ellipse of the initial elliptical communication model to determine the signal attenuation rate in different directions; Step S1032: Plan the edge blurring interval according to the signal attenuation rate in different directions; Step S1033: Construct a blurred edge region at the edge of the initial elliptical communication model according to the edge blurring interval; Step S1034: Configure continuously changing fuzzy weights for different positions in the fuzzy edge region to obtain multiple fuzzy position weights.

[0045] Specifically, based on the signal attenuation rate in different directions, the edge blurring interval is planned, and the specific steps are as follows: By using the principal axis and secondary axis directions, the boundary lines of the initial elliptical communication model in two dimensions are identified to obtain the edge direction of the signal propagation trend; For each direction in the edge direction of the signal propagation trend, a record of the signal strength change with position in that direction is obtained from standard communication data to obtain the signal strength change result; Based on the signal strength change results, the gradient of signal strength decrease during the signal strength change process is calculated to obtain the signal descent gradient; the signal descent gradients in each direction are compared, and the signal attenuation directions are sorted in descending order according to the signal descent gradients to obtain the comparison and judgment results; Each direction in the comparison and judgment results is assigned a level parameter to obtain the mapping relationship between direction and level parameter; the direction with the fastest signal attenuation is assigned the highest level parameter, and the direction with the slowest signal attenuation is assigned the lowest level parameter. Based on the mapping relationship between direction and grade parameters, preset the range values ​​of each direction interval; on the edge contour of the initial elliptical communication model, extend outward along each direction, and the distance of the extension is equal to the range value of each direction interval, to obtain the local fuzzy transition zone of each direction. Connect the local fuzzy transition zones in each direction to construct and plan the edge fuzzification interval.

[0046] Furthermore, by distinguishing the attenuation rate of the signal in different directions and assigning appropriate fuzzy extension ranges to each direction accordingly, the present invention constructs an adaptive, non-uniform edge fuzzification interval, which effectively improves the fitting accuracy and realism of the communication propagation model boundary to the actual signal attenuation characteristics.

[0047] Specifically, continuously varying fuzzy weights are configured for different locations within the fuzzy edge region to obtain fuzzy position weights. The specific steps are as follows: By combining the level parameters corresponding to each direction in the mapping relationship between direction and level parameters, as well as the outer boundary position of the local fuzzy transition zone in each direction, the correspondence between level and outer boundary of transition zone is obtained. Based on the comparison and judgment results and the correspondence between the level and the outer boundary of the transition zone, the range values ​​of each direction are assigned to the corresponding level parameters to obtain the correspondence between the level and the range values. For each local fuzzy transition zone, the level parameter is extracted through the correspondence between the level and the outer boundary of the transition zone, and then the corresponding interval range value is extracted from the correspondence between the level and the interval range value through the level parameter to obtain the associated interval range value. Within each local fuzzy transition zone, the space from the edge of the initial elliptical communication model to the outer boundary of the transition zone is uniformly divided using associated interval range values ​​to obtain a continuously divided space; Based on the level parameters and the continuous division space, a position weight value is preset for each position in the local fuzzy transition zone; the preset principle for the weight value is: within the same local fuzzy transition zone, the position closer to the edge of the initial elliptical communication model has a higher weight value. The location information and status parameters of each historical communication point within the fuzzy edge region are obtained based on standard communication data. Using the location information and status parameters of each historical communication point within the fuzzy edge region, the location weight values ​​are configured and adjusted so that the change trend of the location weight values ​​is consistent with the reliability trend of the status parameters of the historical communication points while maintaining continuous spatial change, and thus the fuzzy location weights are obtained.

[0048] Furthermore, based on the signal attenuation levels in each direction and historical communication data, this invention dynamically generates a continuously changing weight distribution within the fuzzy transition zone, enabling the fuzziness of the model edges to precisely match the spatial changes in the actual communication state, thereby improving the realism and reliability of the boundary region characterization of the communication model.

[0049] Furthermore, the RFID communication region modeling method with blurred elliptical edges also includes the following steps: Step S104: Based on the standard communication data and multiple fuzzy location weights, the RFID communication area is layered with confidence level to generate an RFID communication area model.

[0050] In this embodiment of the invention, communication success rate data and signal strength data are extracted from standard communication data. Through communication success rate data, signal strength data, and multiple fuzzy location weights, a comprehensive confidence analysis is performed on different locations in the RFID communication area to determine the location confidence of different locations in the RFID communication area. Then, according to multiple location confidence levels, the RFID communication area is divided into high, medium, and low confidence levels to obtain the confidence level stratification results. Finally, the confidence level stratification results, fuzzy edge regions, and the initial elliptical communication model are fused to form an RFID communication area model with fuzzy edges and confidence level distribution.

[0051] Specifically, Figure 5 A flowchart illustrating the generation of an RFID communication area model in the method provided by an embodiment of the present invention is shown.

[0052] In a preferred embodiment of the present invention, the step of integrating the standard communication data and multiple fuzzy location weights to perform confidence level stratification on the RFID communication area and generate an RFID communication area model specifically includes the following steps: Step S1041: Extract communication success rate data and signal strength data from the standard communication data; Step S1042: By combining the communication success rate data, the signal strength data, and multiple fuzzy location weights, the location confidence of different locations in the RFID communication area is analyzed and determined. Step S1043: According to the multiple location confidence levels, the RFID communication area is divided into high, medium and low confidence levels to obtain the confidence level stratification results; Step S1044: The confidence level layering result, the fuzzy edge region, and the initial elliptical communication model are fused to form an RFID communication region model with fuzzy edges and confidence level distribution.

[0053] Specifically, by combining the communication success rate data, the signal strength data, and the fuzzy location weights, the location confidence level of different locations in the RFID communication area is analyzed and determined. The specific steps are as follows: Based on the communication success status corresponding to each communication point location in the standard communication data, calculate the ratio of the number of successful communications at the current location to the total number of communications to obtain the communication success rate baseline value; based on the signal strength data, calculate the arithmetic mean of all signal strength values ​​at the current location to obtain the signal strength baseline value; The communication success rate benchmark value and the signal strength benchmark value at a unified location are combined according to a preset weight to obtain the initial communication reliability. For each communication point location in the RFID communication area, the fuzzy location weights of the corresponding locations are extracted according to the edge fuzzification intervals. The fuzzy location weights are then multiplied by the corresponding initial communication reliability to obtain the weighted reliability. Based on standard communication data, the number of communication state switching events at each location is obtained to obtain the number of communication fluctuations. Based on abnormal communication data, a fluctuation threshold is preset, and the number of communication fluctuations at each location is compared with the fluctuation threshold. For locations where the number of communication fluctuations exceeds the fluctuation threshold, the corresponding weighted reliability is reduced according to the excess ratio to obtain the corrected reliability. Based on the current location of the communication point, the adjacent communication points are determined through the range of the stable region, and the average value of the corrected reliability of the adjacent communication points is calculated to obtain the adjacent reliability reference value. The absolute difference between the corrected reliability of each communication point location and the adjacent reliability reference value is calculated. The corrected reliability is then corrected using a preset allowable difference value and the absolute difference to obtain the final reliability. The correction rule is as follows: if the absolute difference is within the preset allowable difference range, the corrected reliability is taken as the final reliability; otherwise, the corrected reliability is linearly adjusted based on the adjacent reliability reference value to obtain the final reliability. The final reliability values ​​are divided into three intervals: high, medium, and low. The final reliability of each communication point location is assigned to the corresponding interval to obtain the confidence level. Based on the mapping relationship between each communication point location and the confidence level, the location confidence of each communication point is obtained.

[0054] Furthermore, this invention integrates multi-dimensional data such as communication success rate, signal strength, and fuzzy position weights, and introduces communication fluctuation correction and adjacent area consistency adjustment to achieve a refined and dynamic assessment of the reliability of each location within the RFID communication area. Ultimately, it outputs three levels of confidence: high, medium, and low, thereby improving the spatial accuracy and practical guidance value of regional communication quality characterization.

[0055] Furthermore, the RFID communication region modeling method with blurred elliptical edges also includes the following steps: Step S105: Continuously collect RFID communication data and adaptively update the RFID communication area model.

[0056] In this embodiment of the invention, by continuously collecting RFID communication data and monitoring and analyzing the RFID communication data, it is determined whether there are changes in the elliptic parameters of the center point, principal axis length and / or secondary axis length. If it is determined that there are changes in the elliptic parameters, the elliptic parameters of the RFID communication area model are adjusted accordingly, and the confidence level stratification results and fuzzy edge regions are updated synchronously to achieve adaptive updating of the RFID communication area model.

[0057] Specifically, Figure 6 A flowchart of RFID communication area model updating in the method provided by an embodiment of the present invention is shown.

[0058] In a preferred embodiment of the present invention, the continuous collection of RFID communication data and the adaptive updating of the RFID communication area model specifically include the following steps: Step S1051: Continuously collect RFID communication data; Step S1052: Monitor and analyze the RFID communication data to determine whether there is a change in elliptic parameters; Step S1053: When there is a change in the ellipse parameter, adjust the ellipse parameter of the RFID communication area model; Step S1054: Synchronously update the confidence level stratification results and fuzzy edge regions to achieve adaptive updates of the RFID communication area model.

[0059] Furthermore, Figure 7 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0060] In another preferred embodiment of the present invention, the RFID communication region modeling system with blurred elliptical edges includes: The initial communication processing unit 101 is used to start the RFID reader / writer, continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data.

[0061] In this embodiment of the invention, the initial communication processing unit 101 starts the RFID reader / writer to continuously scan the RFID communication area, thereby acquiring the initial communication data returned by the RFID tag. Then, the initial communication data is formatted and recorded to include the communication point location, signal strength, and communication success status, generating formatted communication data. After that, the formatted communication data is time-consistently aligned to generate aligned communication data, avoiding the impact of communication delays or momentary interference. Then, the aligned communication data is processed to identify and remove abnormal communication data, thereby suppressing abnormal communication samples and generating standard communication data.

[0062] Specifically, Figure 8 A structural block diagram of the initial communication processing unit 101 in the system provided by an embodiment of the present invention is shown.

[0063] In a preferred embodiment of the present invention, the initial communication processing unit 101 specifically includes: The initial communication module 1011 is used to start the RFID reader / writer, continuously scan the RFID communication area, and obtain the initial communication data returned by the RFID tag. The formatted record module 1012 is used to format and record the initial communication data, including the communication point location, signal strength, and communication success status, to generate formatted communication data. Time alignment module 1013 is used to perform time consistency alignment on the formatted communication data to generate aligned communication data; The exception handling module 1014 is used to identify and remove abnormal communication data from the aligned communication data and generate standard communication data.

[0064] Furthermore, the RFID communication region modeling system with blurred elliptical edges also includes: Ellipse parameter analysis unit 102 is used to identify and analyze the communication stability and communication distribution of the standard communication data, determine the center point, principal axis and secondary axis, and construct an initial ellipse communication model.

[0065] In this embodiment of the invention, the ellipse parameter analysis unit 102 determines the most stable stable region range by performing spatial aggregation analysis on the standard communication data, then selects the spatial center of the stable region range as the center point of the ellipse, then identifies the extension direction of the communication distribution of the standard communication data to determine the principal axis direction and the secondary axis direction, and then performs effective distribution analysis on the standard communication data based on the principal axis direction and the secondary axis direction to determine the principal axis length and the secondary axis length, and finally constructs an initial elliptical communication model based on the center point, principal axis direction, secondary axis direction, principal axis length and secondary axis length.

[0066] Specifically, Figure 9 A structural block diagram of the elliptic parameter analysis unit 102 in the system provided in an embodiment of the present invention is shown.

[0067] In a preferred embodiment of the present invention, the elliptic parameter analysis unit 102 specifically includes: Spatial clustering analysis module 1021 is used to perform spatial clustering analysis on the standard communication data to determine the stable region range; The center point selection module 1022 is used to select the spatial center of the stable region as the center point; The extension direction identification module 1023 is used to identify the extension direction of the communication distribution of the standard communication data and determine the main axis direction and the secondary axis direction. The effective distribution analysis module 1024 is used to perform effective distribution analysis on the standard communication data based on the main axis direction and the secondary axis direction to determine the main axis length and the secondary axis length; The initial model construction module 1025 is used to construct an initial elliptical communication model based on the center point, the direction of the principal axis, the direction of the secondary axis, the length of the principal axis, and the length of the secondary axis.

[0068] Furthermore, the RFID communication region modeling system with blurred elliptical edges also includes: The edge fuzzing analysis unit 103 is used to perform signal attenuation trend analysis on the edge of the initial elliptical communication model based on the standard communication data, plan the edge fuzzing interval, and generate multiple fuzzy position weights.

[0069] In this embodiment of the invention, the edge fuzzy analysis unit 103 analyzes the signal attenuation trend of the initial elliptical communication model based on standard communication data, identifies the trend of signal change from stable to unstable, determines the signal attenuation rate in different directions, and then plans the edge fuzzification interval according to the signal attenuation rate in different directions. According to the edge fuzzification interval, a fuzzy edge region is constructed at the edge of the initial elliptical communication model. For different positions in the fuzzy edge region, continuously changing fuzzy weights are configured to obtain multiple fuzzy position weights, which are used to represent the degree of possibility that different positions belong to the RFID communication area.

[0070] Specifically, Figure 10 The diagram shows the structural block diagram of the edge blur analysis unit 103 in the system provided in the embodiment of the present invention.

[0071] In a preferred embodiment of the present invention, the edge blurring analysis unit 103 specifically includes: The signal attenuation trend analysis module 1031 is used to perform signal attenuation trend analysis on the edge of the ellipse of the initial elliptical communication model based on the standard communication data, and to determine the signal attenuation rate in different directions. The fuzzy interval planning module 1032 is used to plan the edge fuzzification interval according to the signal attenuation rate in different directions; The blurred edge region construction module 1033 is used to construct blurred edge regions at the edges of the initial elliptical communication model according to the blurred edge interval; The weight configuration module 1034 is used to configure continuously changing fuzzy weights for different positions in the fuzzy edge region to obtain multiple fuzzy position weights.

[0072] Furthermore, the RFID communication region modeling system with blurred elliptical edges also includes: The confidence level stratification processing unit 104 is used to integrate the standard communication data and multiple fuzzy location weights to perform confidence level stratification on the RFID communication area and generate an RFID communication area model.

[0073] In this embodiment of the invention, the confidence level processing unit 104 extracts communication success rate data and signal strength data from standard communication data. Through the communication success rate data, signal strength data, and multiple fuzzy position weights, it performs a comprehensive confidence analysis on different positions in the RFID communication area to determine the position confidence of different positions in the RFID communication area. Then, according to the multiple position confidence levels, the RFID communication area is divided into high, medium, and low confidence levels to obtain the confidence level stratification results. Finally, the confidence level stratification results, fuzzy edge regions, and the initial elliptical communication model are fused to form an RFID communication area model with fuzzy edges and confidence distribution.

[0074] The model automatic update unit 105 is used to continuously collect RFID communication data and adaptively update the RFID communication area model.

[0075] In this embodiment of the invention, the model automatic update unit 105 continuously collects RFID communication data and monitors and analyzes the RFID communication data to determine whether there are changes in the elliptic parameters of the center point, principal axis length and / or secondary axis length. If it is determined that there are changes in the elliptic parameters, the elliptic parameters of the RFID communication area model are adjusted accordingly, and the confidence level stratification results and fuzzy edge regions are updated synchronously to achieve adaptive updates of the RFID communication area model.

[0076] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0077] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0078] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0079] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0080] 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, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for modeling RFID communication regions with blurred elliptical edges, characterized in that, The method specifically includes the following steps: The RFID reader is activated to continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data. The standard communication data is analyzed for communication stability and distribution to determine the center point, principal axis, and secondary axis, and an initial elliptical communication model is constructed. Based on the standard communication data, the signal attenuation trend analysis of the elliptical edge of the initial elliptical communication model is performed, the edge fuzzification interval is planned, and fuzzy position weights are generated. By combining the standard communication data and the fuzzy location weights, the RFID communication area is layered with confidence levels to generate an RFID communication area model. RFID communication data is continuously collected, and the RFID communication area model is adaptively updated.

2. The RFID communication region modeling method with elliptical edge blurring according to claim 1, characterized in that, The process of activating the RFID reader / writer, continuously scanning the RFID communication area, acquiring the initial communication data returned by the RFID tags, and processing the initial communication data to obtain standard communication data specifically includes the following steps: Start the RFID reader / writer to continuously scan the RFID communication area and obtain the initial communication data returned by the RFID tags; The initial communication data is formatted and recorded to include the communication point location, signal strength, and communication success status, generating formatted communication data. The formatted communication data is time-consistently aligned to generate aligned communication data; The aligned communication data is processed to identify and remove abnormal communication data, and standard communication data is generated.

3. The RFID communication region modeling method with elliptical edge blurring according to claim 2, characterized in that, The process of identifying and analyzing the communication stability and distribution of the standard communication data, determining the center point, principal axis, and secondary axis, and constructing an initial elliptical communication model specifically includes the following steps: Perform spatial clustering analysis on the standard communication data to determine the range of stable regions; The spatial center of the stable region is selected as the center point; The standard communication data is subjected to communication distribution extension direction identification to determine the main axis direction and the secondary axis direction; Based on the main axis direction and the secondary axis direction, the standard communication data is effectively distributed to determine the main axis length and the secondary axis length; An initial elliptical communication model is constructed based on the center point, the direction of the principal axis, the direction of the secondary axis, the length of the principal axis, and the length of the secondary axis.

4. The RFID communication region modeling method with elliptical edge blurring according to claim 3, characterized in that, The standard communication data is subjected to communication distribution extension direction identification to determine the main axis direction and the secondary axis direction. The specific steps are as follows: Extract the location coordinates of each communication point and the corresponding instantaneous signal strength value from the standard communication data, and associate the location coordinates of the communication point with the corresponding instantaneous signal strength value to obtain the location-signal strength set; Preset signal strength thresholds based on the formatted communication data; The instantaneous signal strength values ​​in the location-signal strength set are filtered using a signal strength threshold to identify the location coordinates of communication points corresponding to signal strength values ​​higher than the threshold, thus obtaining a filtered set of communication points. Identify and statistically analyze the principal eigenvector directions of the covariance matrix of all communication point locations in the communication point set to obtain the direction of the straight line representing the maximum extension trend of the point. Mark the direction of the line representing the maximum extension trend of the point as the initial main extension direction; In a two-dimensional plane, the direction orthogonal to the initial extension main direction is marked as the initial vertical secondary direction; the initial extension main direction and the initial vertical secondary direction are adjusted by using the overall distribution pattern of the communication points in the filtered communication point set to obtain the adjusted main and secondary directions; The degree of fit between the adjusted primary and secondary directions and the distribution of all communication points in the standard communication data is verified one by one, and the adjusted primary and secondary directions with the highest degree of fit with the spatial distribution of communication points are selected as the primary axis direction and the secondary axis direction.

5. The RFID communication region modeling method with elliptical edge blurring according to claim 4, characterized in that, The steps of performing signal attenuation trend analysis on the elliptical edge of the initial elliptical communication model based on the standard communication data, planning the edge blurring interval, and generating fuzzy position weights specifically include the following: Based on the standard communication data, the signal attenuation trend analysis of the elliptical edge of the initial elliptical communication model is performed to determine the signal attenuation rate in different directions. Plan the edge blurring interval according to the signal attenuation rate in different directions; According to the aforementioned edge blurring interval, a blurred edge region is constructed at the edge of the initial elliptical communication model; For different locations in the blurred edge region, continuously varying blur weights are configured to obtain blurred position weights.

6. The RFID communication region modeling method with elliptical edge blurring according to claim 4, characterized in that, Based on the signal attenuation rate in different directions, the edge blurring interval is planned. The specific steps are as follows: By using the principal axis and secondary axis directions, the boundary lines of the initial elliptical communication model in two dimensions are identified to obtain the edge direction of the signal propagation trend; For each direction in the edge direction of the signal propagation trend, a record of the signal strength change with position in that direction is obtained from standard communication data to obtain the signal strength change result; Based on the signal strength change results, the gradient of signal strength decrease during the signal strength change process is calculated to obtain the signal descent gradient; the signal descent gradients in each direction are compared, and the signal attenuation directions are sorted in descending order according to the signal descent gradients to obtain the comparison and judgment results; Each direction in the comparison and judgment results is assigned a level parameter to obtain the mapping relationship between direction and level parameter; the direction with the fastest signal attenuation is assigned the highest level parameter, and the direction with the slowest signal attenuation is assigned the lowest level parameter. Based on the mapping relationship between direction and grade parameters, preset the range values ​​of each direction interval; on the edge contour of the initial elliptical communication model, extend outward along each direction, and the distance of the extension is equal to the range value of each direction interval, to obtain the local fuzzy transition zone of each direction. Connect the local fuzzy transition zones in each direction to construct and plan the edge fuzzification interval.

7. The RFID communication region modeling method with elliptical edge blurring according to claim 6, characterized in that, To obtain the fuzzy position weights, continuously varying fuzzy weights are configured for different locations within the fuzzy edge region. The specific steps are as follows: By combining the level parameters corresponding to each direction in the mapping relationship between direction and level parameters, as well as the outer boundary position of the local fuzzy transition zone in each direction, the correspondence between level and outer boundary of transition zone is obtained. Based on the comparison and judgment results and the correspondence between the level and the outer boundary of the transition zone, the range values ​​of each direction are assigned to the corresponding level parameters to obtain the correspondence between the level and the range values. For each local fuzzy transition zone, the level parameter is extracted through the correspondence between the level and the outer boundary of the transition zone, and then the corresponding interval range value is extracted from the correspondence between the level and the interval range value through the level parameter to obtain the associated interval range value. Within each local fuzzy transition zone, the space from the edge of the initial elliptical communication model to the outer boundary of the transition zone is uniformly divided using associated interval range values ​​to obtain a continuously divided space; Based on the level parameters and the continuous division space, a position weight value is preset for each position in the local fuzzy transition zone; the preset principle for the position weight value is: within the same local fuzzy transition zone, the position weight value is higher the closer it is to the edge of the initial elliptical communication model. The location information and status parameters of each historical communication point within the fuzzy edge region are obtained based on standard communication data. Using the location information and status parameters of each historical communication point within the fuzzy edge region, the location weight values ​​are configured and adjusted so that the change trend of the location weight values ​​is consistent with the reliability change trend derived from the analysis of the status parameters of historical communication points while maintaining continuous spatial change, and thus the fuzzy location weights are obtained.

8. The RFID communication region modeling method with elliptical edge blurring according to claim 7, characterized in that, The process of integrating the standard communication data and the fuzzy location weights to perform confidence-level stratification of the RFID communication area and generate an RFID communication area model specifically includes the following steps: From the standard communication data, extract communication success rate data and signal strength data; By combining the communication success rate data, the signal strength data, and the fuzzy location weights, the location confidence level of different locations in the RFID communication area is analyzed and determined. Based on the location confidence level, the RFID communication area is divided into high, medium, and low confidence levels to obtain the confidence level stratification results; The confidence level stratification result, the fuzzy edge region, and the initial elliptical communication model are fused to form an RFID communication region model with fuzzy edges and confidence level distribution.

9. The RFID communication region modeling method with elliptical edge blurring according to claim 8, characterized in that, By combining the communication success rate data, the signal strength data, and the fuzzy location weights, the location confidence level of different locations in the RFID communication area is analyzed and determined. The specific steps are as follows: Based on the communication success status corresponding to each communication point location in the standard communication data, calculate the ratio of the number of successful communications at the current location to the total number of communications to obtain the communication success rate baseline value; based on the signal strength data, calculate the arithmetic mean of all signal strength values ​​at the current location to obtain the signal strength baseline value; The communication success rate benchmark value and the signal strength benchmark value at a unified location are combined according to a preset weight to obtain the initial communication reliability. For each communication point location in the RFID communication area, the fuzzy location weights of the corresponding locations are extracted according to the edge fuzzification intervals. The fuzzy location weights are then multiplied by the corresponding initial communication reliability to obtain the weighted reliability. Based on standard communication data, the number of communication state switching events at each location is obtained to obtain the number of communication fluctuations. Based on abnormal communication data, a fluctuation threshold is preset, and the number of communication fluctuations at each location is compared with the fluctuation threshold. For locations where the number of communication fluctuations exceeds the fluctuation threshold, the corresponding weighted reliability is reduced according to the excess ratio to obtain the corrected reliability. Based on the current location of the communication point, the adjacent communication points are determined through the range of the stable region, and the average value of the corrected reliability of the adjacent communication points is calculated to obtain the adjacent reliability reference value. The absolute difference between the corrected reliability of each communication point location and the adjacent reliability reference value is calculated. The corrected reliability is then corrected using a preset allowable difference value and the absolute difference to obtain the final reliability. The correction rule is as follows: if the absolute difference is within the preset allowable difference range, the corrected reliability is taken as the final reliability; otherwise, the corrected reliability is linearly adjusted based on the adjacent reliability reference value to obtain the final reliability. The final reliability values ​​are divided into three intervals: high, medium, and low. The final reliability of each communication point location is assigned to the corresponding interval to obtain the confidence level. Based on the mapping relationship between each communication point location and the confidence level, the location confidence of each communication point is obtained.

10. The RFID communication region modeling method with elliptical edge blurring according to claim 9, characterized in that, The continuous collection of RFID communication data and the adaptive updating of the RFID communication area model specifically include the following steps: Continuously collect RFID communication data; The RFID communication data is monitored and analyzed to determine whether there are changes in the elliptic parameters; When the ellipse parameters change, the ellipse parameters of the RFID communication area model are adjusted. The confidence level stratification results and fuzzy edge regions are updated synchronously to achieve adaptive updates of the RFID communication area model.

11. A system for modeling RFID communication regions with blurred elliptical edges, characterized in that, The system employs the RFID communication region modeling method with elliptical edge blurring as described in any one of claims 1-10, and the system includes: An initial communication processing unit is used to start the RFID reader / writer, continuously scan the RFID communication area, obtain the initial communication data returned by the RFID tag, and process the initial communication data to obtain standard communication data. The elliptic parameter analysis unit is used to identify and analyze the communication stability and communication distribution of the standard communication data, determine the center point, principal axis and secondary axis, and construct an initial elliptic communication model. The edge fuzzing analysis unit is used to perform signal attenuation trend analysis on the edge of the initial elliptical communication model based on the standard communication data, plan the edge fuzzification interval, and generate fuzzy position weights. The confidence level processing unit is used to integrate the standard communication data and the fuzzy location weights to perform confidence level layering on the RFID communication area and generate an RFID communication area model. The model automatic update unit is used to continuously collect RFID communication data and adaptively update the RFID communication area model.

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