Settlement method based on intelligent fusion terminal, terminal, medium and program product

Abstract

The invention discloses a settlement method based on an intelligent fusion terminal, a terminal, a medium and a program product, and the method comprises the steps: determining the maximum radio frequency signal intensity value of a new commodity in a settlement region as the reference signal intensity; judging whether the commodity weight of the settled area is increased or not; if not, determining the maximum radio frequency signal intensity value of the new commodity in the settled area as settled signal intensity; judging whether the ratio of the settled signal strength to the reference signal strength is smaller than a preset threshold value or not; if yes, constructing a continuous distribution curved surface of the radio frequency signal intensity of the new commodity; calculating a curved surface peak value position of the continuously distributed curved surface, and judging whether the curved surface peak value position is within a preset range of the settled area; if yes, determining the new commodity as a normatively placed commodity; if not, determining the new commodity as a non-standard placement commodity; starting a preset alarm mode; and if the weight of the commodity is increased, determining the new commodity as a normatively placed commodity. According to the invention, the efficiency of intelligent settlement is improved.

Description

Technical Field

[0001] The present application belongs to the field of identification and settlement, and in particular, relates to a settlement method, terminal, medium and program product based on an intelligent fusion terminal. Background Art

[0002] With the rapid development of the smart retail industry, the traditional manual cashier model can no longer meet the modern business environment's demand for efficiency and service quality. With the increasing variety of goods and the increasing customer flow, the traditional cashier method has problems such as low settlement efficiency, high labor costs, and high error rates, which affects the business's operating efficiency and customers' shopping experience.

[0003] To address the above issues, the industry currently uses an intelligent identification and settlement system that integrates multi-source sensors. This system simultaneously deploys RFID readers, visual cameras, and weight sensors, and uses multi-dimensional data fusion to identify and verify goods. It can accurately complete automatic identification and settlement of goods, significantly improving the accuracy and efficiency of settlement.

[0004] However, when the weight of a certain product is too light, it may not be recorded in the settled area after settlement. When it is scanned by the RFID reader, the terminal does not monitor the weight change in the settled area, resulting in an erroneous judgment that the product is not operated in accordance with the rules, causing settlement to be interrupted. The administrator needs to authorize to continue settlement, which reduces the efficiency of smart settlement. Summary of the invention

[0005] The present application provides a settlement method, terminal, medium and program product based on an intelligent fusion terminal, which are used to improve the efficiency of intelligent settlement.

[0006] In a first aspect, the present application provides a settlement method based on an intelligent fusion terminal. After determining that the barcode information of a new product has been scanned, the maximum radio frequency signal strength value of the new product in the settlement area is calculated, and the maximum radio frequency signal strength value is determined as the reference signal strength. The terminal includes a settlement area and a settled area. Several radio frequency antennas are arranged in the settlement area and the settled area to obtain the radio frequency signal strength of the product. Determine whether the weight of the goods in the settled area has increased; If the weight of the product has not increased, the maximum RF signal strength value of the new product in the settled area is calculated to obtain the settled signal strength; When it is determined that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, all the radio frequency signal data in the settled area are spatially interpolated to construct a continuous distribution surface of the radio frequency signal strength of the new product; Calculate the peak position of the continuous distribution surface, and determine whether the peak position of the surface is within a preset range of the settled area; If it is within the preset range, the new product is confirmed as a standard placement product; If it is not within the preset range, the new product is confirmed as a non-standard placement product; Turning on a preset alarm mode, and after the preset alarm mode ends, executing a step of calculating the maximum radio frequency signal strength value of the new product in the settled area to obtain the settled signal strength; If the weight of the product increases, the new product will be confirmed as a standard placement product.

[0007] By adopting the above technical solution, the baseline signal strength of the new product in the settlement area is calculated, and compared and analyzed with the signal strength in the settled area. Combined with the weight change information of the product, the accuracy of judging whether the product is placed in a standardized manner can be improved. When the ratio is less than the preset threshold, a continuous distribution surface is constructed through spatial interpolation operation, and the compliance of the product placement position is judged based on the peak position of the surface, which can effectively identify the spatial position of the product. The dual verification mechanism of signal strength and weight reduces the risk of misjudgment caused by relying solely on a single sensor. When non-standard placement is detected, the system will start the preset alarm mode and re-verify after the alarm ends, realizing timely reminders and re-inspections of abnormal situations, improving the accuracy and reliability of the settlement process, and thus improving the efficiency of intelligent settlement.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the maximum radio frequency signal strength value of the new product in the settlement area specifically includes: Obtaining a sequence of radio frequency signal strengths collected by each radio frequency antenna in a settlement area within a preset time window; Perform wavelet transform on the RF signal strength sequence to obtain signal characteristic coefficients at different scales; Calculate the entropy value of the signal based on the signal characteristic coefficient, and remove abnormal data with entropy values ​​greater than a preset threshold; constructing an analytical representation based on the signal strength values ​​excluding the anomalous data; Calculate the instantaneous envelope of the analytical representation and obtain the local maximum point; Perform linear regression on the local maximum point to obtain the change trend of signal strength; The maximum value of the signal strength in the changing trend is taken as the benchmark signal strength.

[0009] By adopting the above technical solution, wavelet transform is used to perform multi-scale analysis on the RF signal strength sequence, and abnormal data is eliminated by judging the signal entropy value, which can reduce the impact of environmental interference and measurement noise. By analyzing the signal and extracting the instantaneous envelope, the dynamic change characteristics of the signal strength can be accurately captured. Linear regression is performed on the local maximum points to obtain the signal strength change trend, which reduces the impact of instantaneous fluctuations on the judgment of the reference signal strength and improves the stability and reliability of the reference signal strength calculation. Through data analysis of the preset time window, it not only guarantees the real-time requirements, but also reflects the overall change law of the signal, making the determination of the reference signal strength more accurate and representative.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the step of performing spatial interpolation operation on all radio frequency signal data in the settled area to construct a continuous distribution surface of the radio frequency signal strength of the new product specifically includes: Divide the settled area into a first number of grid cells, and record the radio frequency signal strength value of the center point of each grid cell to obtain a discrete spatial sampling data set; Calculating the signal strength change rate of each grid unit based on the spatial sampling data set, and adaptively subdividing the grid unit according to the magnitude of the signal strength change rate to obtain a second number of subdivided grid units, where the second number is greater than the first number; Constructing an interpolation basis function system in the form of a tensor product, the interpolation basis function system satisfies the interpolation condition at the nodes of the grid unit; Solve the interpolation coefficients that satisfy global smoothness based on the interpolation basis function system; Constructing a global system of equations containing boundary continuity constraints for the subdivided mesh cells; A continuous distribution surface of the radio frequency signal strength of new products is constructed based on the global equations and interpolation coefficients.

[0011] By adopting the above technical solution, the spatial resolution is dynamically adjusted according to the rate of change of signal strength, and more precise sampling points are provided in areas where the signal changes dramatically, thereby improving the interpolation accuracy. The interpolation basis function system in the form of tensor product is adopted and the boundary continuity constraint is introduced to improve the smoothness and continuity of the interpolation result in the entire area. This interpolation method reduces the information loss that may be caused by traditional equidistant sampling, and improves the description accuracy of key areas through adaptive subdivision. The constructed continuous distribution surface can truly reflect the spatial distribution characteristics of the RF signal strength, making the subsequent judgment based on the peak position of the surface more accurate.

[0012] In combination with some embodiments of the first aspect, in some embodiments, before determining that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, the method further includes: Obtain the three-dimensional spatial coordinate information of the settlement area and the settled area, and establish a spatial coordinate system including the location of the radio frequency antenna, the boundary of the commodity placement area, and the distribution of metal objects; The arrival time difference and arrival angle of the received signal of each RF antenna are collected based on the spatial coordinate system, and a multipath propagation path map is constructed in combination with the real-time signal strength; Based on the multipath propagation path diagram, the geometric loss, dielectric loss and reflection loss of each path are calculated to obtain the path transmission characteristic parameters; Establish a signal propagation compensation matrix based on path transmission characteristic parameters; Perform amplitude and phase compensation on the radio frequency signal based on the signal propagation compensation matrix to obtain a corrected signal strength distribution; According to the corrected signal strength distribution, the false detection rate and missed detection rate are calculated; Update the preset threshold value according to the false detection rate, missed detection rate and preset detection reliability requirements.

[0013] By adopting the above technical solution, a three-dimensional spatial coordinate system including the position of the RF antenna, the boundary of the product placement area and the distribution of metal objects is established, and a multipath propagation path map is constructed by combining the arrival time difference and arrival angle information, thereby realizing accurate modeling of the RF signal propagation environment. The loss parameters of each propagation path are calculated and a signal propagation compensation matrix is ​​established to compensate for the amplitude and phase of the RF signal, thereby reducing the signal distortion caused by multipath propagation. The false detection rate and missed detection rate are calculated based on the corrected signal strength distribution, and the preset threshold is dynamically updated, so that the system has adaptive adjustment capabilities, reduces the impact of complex electromagnetic environments on signal propagation, and improves the accuracy of signal strength measurement. By updating the preset threshold in real time, the system can automatically optimize the judgment criteria based on the actual detection effect, thereby improving the reliability of the judgment of the standardization of product placement.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the step of collecting the arrival time difference and arrival angle of the signal received by each radio frequency antenna based on the spatial coordinate system specifically includes: A phase synchronization trigger signal is used to control the sampling timing of each radio frequency antenna to obtain a sampling signal; Extracting the in-phase component and the orthogonal component of the sampled signal, and calculating the instantaneous phase and envelope of the sampled signal according to the in-phase component and the orthogonal component; Based on the instantaneous phase, the generalized cross-correlation algorithm is used to calculate the arrival time difference between any two RF antennas; An overdetermined set of equations is constructed according to the arrival time difference, and the arrival angle of the sampled signal is determined according to the overdetermined set of equations.

[0015] By adopting the above technical solution and using a phase synchronization trigger signal to control the sampling timing of the RF antenna, it can be ensured that all antennas start sampling at the same time, reducing the error caused by the sampling timing deviation. The in-phase component and the orthogonal component are extracted from the sampled signal, and the instantaneous phase and envelope information are calculated, which can accurately reflect the phase change characteristics of the signal during the propagation process. The generalized cross-correlation algorithm is used to calculate the arrival time difference between antennas, which can suppress the influence of noise and multipath interference on the time difference estimation. The overdetermined equations constructed based on the arrival time difference contain redundant information, and the arrival angle obtained by solving the overdetermined equations has higher accuracy and reliability.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, before calculating the geometric loss, dielectric loss, and reflection loss of each path based on the multipath propagation path graph, the method further includes: Calculate the propagation speed and attenuation coefficient of electromagnetic waves in different media based on real-time environmental status data; Simulate the propagation characteristics of electromagnetic waves and obtain the main propagation path; Establish an electromagnetic field simulation model based on the main propagation path; The electromagnetic field simulation model is used to predict the signal propagation loss of different paths and obtain a path loss estimation database.

[0017] By adopting the above technical solution, the electromagnetic wave propagation parameters are calculated according to the real-time environmental status data, so that the propagation model can dynamically adapt to environmental changes. By simulating the propagation characteristics of electromagnetic waves to obtain the main propagation path, the calculation complexity can be reduced and the computing resources can be concentrated on the path that has the most significant impact on signal propagation. The established electromagnetic field simulation model takes into account various influencing factors in the actual environment, making the prediction of signal propagation loss more in line with the actual situation. By pre-establishing a path loss estimation database, the loss information of different propagation paths can be quickly queried, which reduces the time consumption of real-time calculations, improves the accuracy of signal propagation characteristic predictions, and provides a reliable theoretical basis for signal strength compensation, so that the accuracy of product location judgment is improved.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, predicting signal propagation losses of different paths using an electromagnetic field simulation model specifically includes: The electromagnetic field distribution is obtained based on the electromagnetic field simulation model; The electromagnetic field distribution is simplified to the superposition of several main propagation modes, and a superposition representation is obtained; Based on the superposition representation, the electromagnetic wave transmission equation including frequency dispersion and spatial attenuation characteristics is established; Calculate the geometric attenuation, dielectric absorption and scattering loss of each main propagation path to obtain the loss characteristic vector; Constructing a path characteristic parameter matrix according to the loss characteristic vector, wherein the characteristic dimensions of the path characteristic parameter matrix include path length, incident angle, number of reflections and loss component; A recursive neural network is used to train the path loss prediction model, and the path characteristic parameter matrix is ​​used as input to predict the signal propagation loss of different paths.

[0019] By adopting the above technical solutions, the field distribution obtained by electromagnetic field simulation is simplified to the superposition of the main propagation modes, which not only retains the important propagation characteristics but also reduces the computational complexity. The established electromagnetic wave transmission equation takes into account the frequency dispersion and spatial attenuation characteristics, and can accurately describe the propagation law of electromagnetic waves in complex environments. The calculated loss characteristic vector fully reflects the characteristics of the propagation path, and the constructed path characteristic parameter matrix contains the key factors affecting signal propagation. The recursive neural network is used to train the path loss prediction model, and the correlation between the characteristic parameters is utilized to improve the accuracy of loss prediction.

[0020] In the second aspect, an embodiment of the present application provides a settlement terminal based on a smart fusion terminal, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the terminal to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a terminal, causes the terminal to execute the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a terminal, the terminal executes the method described in any possible implementation manner in the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The present application provides a settlement method based on an intelligent fusion terminal, which calculates the baseline signal strength of new goods in the settlement area, and compares and analyzes it with the signal strength in the settled area. Combined with the weight change information of the goods, it can improve the accuracy of judging whether the goods are placed in a standardized manner. When the ratio is less than the preset threshold, a continuous distribution surface is constructed through spatial interpolation operations, and the compliance of the placement of the goods is judged based on the peak position of the surface, which can effectively identify the spatial position of the goods. The dual verification mechanism of signal strength and weight reduces the risk of misjudgment caused by relying solely on a single sensor. When non-standard placement is detected, the system will start the preset alarm mode and re-verify after the alarm ends, realizing timely reminders and re-inspections of abnormal situations, improving the accuracy and reliability of the settlement process, and thus improving the efficiency of intelligent settlement.

[0024] 2. The present application provides a settlement method based on an intelligent fusion terminal, establishes a three-dimensional spatial coordinate system including the position of the RF antenna, the boundary of the commodity placement area, and the distribution of metal objects, and constructs a multipath propagation path map in combination with the arrival time difference and arrival angle information, thereby realizing accurate modeling of the RF signal propagation environment. The loss parameters of each propagation path are calculated and a signal propagation compensation matrix is ​​established to perform amplitude and phase compensation on the RF signal, thereby reducing the signal distortion caused by multipath propagation. The false detection rate and missed detection rate are calculated based on the corrected signal strength distribution, and the preset threshold is dynamically updated, so that the system has adaptive adjustment capabilities, reduces the impact of complex electromagnetic environments on signal propagation, and improves the accuracy of signal strength measurement. By updating the preset threshold in real time, the system can automatically optimize the judgment criteria based on the actual detection effect, thereby improving the reliability of the judgment of the standardization of commodity placement.

[0025] 3. The present application provides a settlement method based on an intelligent fusion terminal. By adopting the above-mentioned technical solution, the electromagnetic wave propagation parameters are calculated according to the real-time environmental status data, so that the propagation model can dynamically adapt to environmental changes. By simulating the propagation characteristics of electromagnetic waves to obtain the main propagation path, the calculation complexity can be reduced and the computing resources can be concentrated on the path that has the most significant impact on signal propagation. The established electromagnetic field simulation model takes into account various influencing factors in the actual environment, so that the prediction of signal propagation loss is more in line with the actual situation. By pre-establishing a path loss estimation database, the loss information of different propagation paths can be quickly queried, which reduces the time consumption of real-time calculations, improves the accuracy of signal propagation characteristic predictions, and provides a reliable theoretical basis for signal strength compensation, so that the accuracy of product location judgment is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a settlement method based on an intelligent fusion terminal in an embodiment of the present application.

[0027] Figure 2It is a flow chart of a signal preprocessing method in an embodiment of the present application.

[0028] Figure 3 It is a schematic diagram of the physical device structure of a settlement terminal based on an intelligent fusion terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0031] The following uses an embodiment and combines Figure 1 , a settlement method based on an intelligent fusion terminal in an embodiment of the present application is described: See also Figure 1 , which is a flow chart of a settlement method based on an intelligent fusion terminal in an embodiment of the present application.

[0032] S101, calculating the maximum radio frequency signal strength value of the new product in the settlement area, and determining the maximum radio frequency signal strength value as the reference signal strength; After determining that the barcode information of the new product has been scanned, the intelligent fusion terminal calculates the maximum RF signal strength value of the new product in the settlement area, and determines the maximum RF signal strength value as the reference signal strength. The terminal includes a settlement area and a settled area, and a number of RF antennas are set in the settlement area and the settled area to obtain the RF signal strength of the product. Specifically: obtain the RF signal strength sequence collected by each RF antenna in the settlement area within a preset time window; perform wavelet transform on the RF signal strength sequence to obtain signal characteristic coefficients at different scales; calculate the entropy value of the signal based on the signal characteristic coefficient, and remove abnormal data with entropy values ​​greater than the preset threshold; construct an analytical representation based on the signal strength values ​​other than the abnormal data; calculate the instantaneous envelope of the analytical representation to obtain the local maximum point; perform linear regression on the local maximum point to obtain the change trend of the signal strength; and use the maximum value of the signal strength in the change trend as the reference signal strength.

[0033] In this step, the intelligent fusion terminal first determines the barcode information of the new product scanned, then calculates the maximum RF signal strength value of the new product in the settlement area, and determines the maximum value as the reference signal strength. The intelligent fusion terminal includes a settlement area and a settled area, and multiple RF antennas are set in these two areas to obtain the RF signal strength of the product.

[0034] Specifically, the intelligent fusion terminal can calculate the benchmark signal strength of the new product in the following way: first, obtain the RF signal strength sequence collected by each RF antenna in the settlement area within a preset time window; then, perform wavelet transform on the RF signal strength sequence to obtain signal characteristic coefficients at different scales; then, calculate the entropy value of the signal according to the signal characteristic coefficient, and remove abnormal data with entropy values ​​greater than a preset threshold; then, construct an analytical representation based on the signal strength values ​​​​except for the abnormal data; finally, calculate the instantaneous envelope of the analytical representation to obtain the local maximum points, and perform linear regression on the local maximum points to obtain the changing trend of the signal strength, and take the maximum value of the signal strength in the changing trend as the benchmark signal strength.

[0035] S102, determining whether the weight of the goods in the settled area has increased; In this step, the intelligent fusion terminal needs to determine whether the weight of the goods in the settled area has increased. This step is to determine whether the new goods have been placed in the settled area by the customer.

[0036] In order to determine the weight of goods, the intelligent fusion terminal can set a weight sensor in the settled area to monitor the weight change of goods in the settled area in real time. When the weight increase is detected, it can be considered that the new goods have been placed in the settled area.

[0037] S103, calculating the maximum radio frequency signal strength value of the new product in the settled area to obtain the settled signal strength; If the weight of the product has not increased, the maximum radio frequency signal strength value of the new product in the settled area is calculated to obtain the settled signal strength.

[0038] In this step, if the intelligent fusion terminal determines that the weight of the goods in the settled area has not increased, it is necessary to calculate the maximum radio frequency signal strength value of the new goods in the settled area as the settled signal strength.

[0039] In order to obtain the settled signal strength, the intelligent fusion terminal can adopt a method similar to the calculation of the reference signal strength, that is, first obtain the RF signal strength sequence of the new product received by each RF antenna in the settled area, and then through a series of processing steps such as wavelet transform, abnormal data elimination, analytical representation construction and instantaneous envelope calculation, finally obtain the maximum RF signal strength value of the new product in the settled area as the settled signal strength.

[0040] In the process of calculating the settled signal strength, the intelligent fusion terminal may encounter the problem that the RF signal strength distribution changes due to the change in the location of the new product. In order to adapt to this change, the intelligent fusion terminal can introduce an adaptive positioning algorithm to estimate the location of the new product in real time based on the spatial distribution characteristics of the RF signal strength, and dynamically adjust the working parameters of the RF antenna according to the change in location, such as transmission power, receiving gain, etc., to ensure the calculation accuracy of the settled signal strength.

[0041] S104: when it is determined that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, perform spatial interpolation operation on all radio frequency signal data in the settled area to construct a continuous distribution surface of the radio frequency signal strength of the new product; When determining that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, the intelligent fusion terminal performs spatial interpolation operations on all the radio frequency signal data in the settled area to construct a continuous distribution surface of the radio frequency signal strength of the new product. Specifically: the settled area is divided into a first number of grid units, and the center point of each grid unit records the radio frequency signal strength value of the center point to obtain a discrete spatial sampling data set; the signal strength change rate of each grid unit is calculated based on the spatial sampling data set, and the grid unit is adaptively subdivided according to the size of the signal strength change rate to obtain a second number of subdivided grid units, and the second number is greater than the first number; an interpolation basis function system in the form of a tensor product is constructed, and the interpolation basis function system satisfies the interpolation condition at the nodes of the grid unit; the interpolation coefficients that satisfy global smoothness are solved according to the interpolation basis function system; a global equation group containing boundary continuity constraints of the subdivided grid units is constructed; and a continuous distribution surface of the radio frequency signal strength of the new product is constructed based on the global equation group and the interpolation coefficients.

[0042] In this step, the intelligent fusion terminal first determines whether the ratio of the settled signal strength to the reference signal strength is less than a preset threshold. If the ratio is less than the threshold, it indicates that the new product may not be correctly placed in the settled area. At this time, it is necessary to further analyze the spatial distribution characteristics of the RF signal strength in the settled area to determine the specific location of the new product.

[0043] In order to construct a continuous distribution surface of the RF signal strength of new products, the intelligent fusion terminal can adopt a spatial interpolation operation method. The specific steps are as follows: first, the settled area is divided into several grid cells, and the center point of each grid cell records the RF signal strength value of the center point to obtain a discrete spatial sampling data set; then, the signal strength change rate of each grid cell is calculated based on the spatial sampling data set, and the grid cells are adaptively subdivided according to the size of the change rate to obtain subdivided grid cells with higher resolution; then, an interpolation basis function system in the form of a tensor product is constructed to ensure that the interpolation basis function satisfies the interpolation condition at the nodes of the grid cells; then, the interpolation coefficients that satisfy global smoothness are solved according to the interpolation basis function system, and a global equation group containing continuity constraints on the boundaries of the subdivided grid cells is constructed; finally, a continuous distribution surface of the RF signal strength of new products is constructed based on the global equation group and the interpolation coefficients.

[0044] S105, performing spatial interpolation operation on all radio frequency signal data in the settled area to construct a continuous distribution surface of radio frequency signal strength of new products; From step S104, it can be seen that when the intelligent fusion terminal determines that the ratio of the settled signal strength to the reference signal strength is less than the preset threshold, it needs to perform spatial interpolation operation on the RF signal data of the settled area to construct a continuous distribution surface of the RF signal strength of the new product. This step reiterates the process.

[0045] In order to realize the spatial interpolation of RF signal strength, the intelligent fusion terminal can use various interpolation algorithms, such as linear interpolation, spline interpolation, Kriging interpolation, etc. Among them, Kriging interpolation is a spatial interpolation method based on the theory of variogram. By modeling the spatial correlation of RF signal strength, the optimal unbiased estimation result can be obtained, so it is widely used in the field of RF signal processing.

[0046] When performing spatial interpolation operations, the intelligent fusion terminal needs to comprehensively consider factors such as interpolation accuracy, computational efficiency, and memory overhead, and select appropriate interpolation algorithms and parameter settings. For example, for areas where the RF signal strength changes dramatically, the intelligent fusion terminal can use a high-order interpolation algorithm to improve interpolation accuracy; while for areas where the signal strength changes gently, a low-order interpolation algorithm can be used to reduce the amount of calculation. In addition, the intelligent fusion terminal can also introduce adaptive data compression technology, which significantly reduces memory overhead and data transmission volume while ensuring interpolation accuracy by reducing the dimension and sparsely representing the RF signal data.

[0047] S106, calculating the peak position of the continuous distribution surface, and determining whether the peak position of the surface is within a preset range of the settled area; In this step, the intelligent fusion terminal needs to calculate the peak position of the continuous distribution surface of the new commodity radio frequency signal strength obtained in step S105, and determine whether the peak position is within the preset range of the settled area.

[0048] In order to calculate the peak position of the surface, the intelligent fusion terminal can use numerical optimization algorithms, such as gradient descent method, Newton method, etc., to find the maximum value point on the surface through iterative search. At the same time, in order to improve the efficiency and reliability of peak search, the intelligent fusion terminal can introduce a heuristic search strategy, pre-estimate the possible position of the peak according to the distribution characteristics of the RF signal strength, and then perform a fine search in the local area, thereby accelerating the convergence speed and avoiding falling into the local extreme value.

[0049] S107, confirming the new product as a non-standardly placed product, and starting a preset alarm mode; If it is not within the preset range, the new product is confirmed as a non-standardly placed product, and after the preset alarm mode ends, the step of calculating the maximum radio frequency signal strength value of the new product in the settled area to obtain the settled signal strength is executed, and the process returns to step S101 and is repeated until the peak position of the surface is within the preset range of the settled area.

[0050] In this step, if the intelligent fusion terminal determines that the surface peak position of the radio frequency signal strength of the new product is not within the preset range of the settled area, the new product is confirmed as a non-standardly placed product and the preset alarm mode is turned on.

[0051] In order to remind customers to correctly place new products in the settled area, the intelligent fusion terminal can use a variety of alarm methods, such as voice prompts, flashing lights, screen displays, etc. At the same time, in order to guide customers to complete the standardized placement operation, the intelligent fusion terminal can also use a visual method to display the current location and target location of the new product on the screen in real time, and use arrows and other indicator marks to guide customers to move the product to the correct location.

[0052] After the preset alarm mode is turned on, the intelligent fusion terminal needs to continuously monitor the position change of the new product until it is confirmed that the new product has been correctly placed. In order to prevent customers from failing to complete the placement operation for a long time, the intelligent fusion terminal can set an alarm timeout mechanism. If the change of the new product position is still not detected within the preset time, the manual intervention process will be automatically triggered to request staff to assist in handling.

[0053] In addition, when the alarm mode is turned on, the intelligent fusion terminal can also record relevant information of non-standard placement events, such as the time of occurrence, duration, customer behavior characteristics, etc., for subsequent user behavior analysis and optimization. By mining and modeling these data, the intelligent fusion terminal can learn and predict the customer's non-standard placement behavior pattern, so as to take measures in advance to reduce the frequency of non-standard placement events and improve settlement efficiency and customer experience.

[0054] S108. Confirm the new product as a standard placement product.

[0055] When the judgment result of step S102 is that the weight of the commodity increases, the new commodity is confirmed as a standard placement commodity. At the same time, if the peak position of the curved surface is within the preset range of the settled area, this step is also performed.

[0056] For new products placed in a standardized manner, the intelligent fusion terminal can automatically update the list and amount of settled products, and display the settlement information on the screen for customers to check and confirm. At the same time, in order to improve the customer's shopping experience, the intelligent fusion terminal can also recommend related products or preferential activities based on the customer's purchase history and preferences to encourage customers to make additional purchases.

[0057] After confirming that the new product is a standard placed product, the intelligent fusion terminal needs to continue to monitor the status of the settled area until the customer completes the settlement and payment of all products. In order to prevent customers from taking or missing products by mistake during the settlement process, the intelligent fusion terminal can use visual recognition technology to track the quantity and location changes of products in the settled area in real time, and compare them with the settlement list to promptly discover and correct errors. In addition, the intelligent fusion terminal can also guide customers to correctly operate the settlement equipment through human-computer interaction functions, such as prompting customers to place products in designated areas and guiding customers to complete the payment process, thereby improving the accuracy and efficiency of settlement.

[0058] In the above embodiment, the baseline signal strength of the new product in the settlement area is calculated, and compared with the signal strength in the settled area. Combined with the weight change information of the product, the accuracy of judging whether the product is placed in a standardized manner can be improved. When the ratio is less than the preset threshold, a continuous distribution surface is constructed through spatial interpolation operations, and the compliance of the product placement position is judged based on the peak position of the surface, so that the spatial position of the product can be effectively identified. The dual verification mechanism of signal strength and weight reduces the risk of misjudgment caused by relying solely on a single sensor. When non-standard placement is detected, the system will start the preset alarm mode and re-verify after the alarm ends, realizing timely reminders and re-inspections of abnormal situations, improving the accuracy and reliability of the settlement process, and thus improving the efficiency of intelligent settlement.

[0059] In order to further improve the accuracy and reliability of the system's judgment, before executing the above settlement method, this application also provides a signal preprocessing solution. This solution compensates and corrects the radio frequency signal by establishing an accurate spatial electromagnetic environment model, providing a more reliable signal basis for the judgment of the normativeness of product placement. On this basis, the system can dynamically adjust the judgment threshold so that the above dual verification mechanism based on signal strength and weight can operate more stably. Figure 2 , a signal preprocessing method in an embodiment of the present application is described: See also Figure 2 , which is a flow chart of a signal preprocessing method in an embodiment of the present application.

[0060] S201, obtaining the three-dimensional spatial coordinate information of the settlement area and the settled area, and establishing a spatial coordinate system including the location of the radio frequency antenna, the boundary of the commodity placement area, and the distribution of metal objects; The intelligent fusion terminal obtains the three-dimensional spatial coordinate information of the settlement area and the settled area, and establishes a spatial coordinate system that includes the location of the RF antenna, the boundary of the commodity placement area, and the distribution of metal objects. This step obtains the three-dimensional spatial information of the settlement area and the settled area to establish a three-dimensional spatial coordinate system that includes the specific location information of the RF antenna, the boundary information of the commodity placement area, and the distribution information of metal objects. By establishing such a complete three-dimensional spatial coordinate system, the intelligent fusion terminal can accurately grasp the spatial position relationship between various objects, providing a coordinate basis for subsequent signal processing and judgment of commodity placement norms.

[0061] In specific implementation, the intelligent fusion terminal can obtain the three-dimensional spatial coordinate information of the settlement area and the settled area in a variety of ways. For example, the intelligent fusion terminal can use a three-dimensional visual sensor to collect the three-dimensional point cloud data of the settlement area and the settled area, and then generate a complete three-dimensional space model through point cloud stitching and three-dimensional reconstruction technology. In addition, the intelligent fusion terminal can also use multiple two-dimensional visual sensors to collect images of the settlement area and the settled area from different angles, and then use binocular stereo vision technology or structured light technology to extract three-dimensional space information. For the acquisition of the RF antenna position and the distribution of metal objects, the intelligent fusion terminal can use manual calibration to enter the position information of the RF antenna and the metal object into the system.

[0062] S202, collecting the arrival time difference and arrival angle of the signal received by each radio frequency antenna based on the spatial coordinate system, and constructing a multipath propagation path map in combination with the real-time signal strength; The arrival time difference and arrival angle of the received signal of each RF antenna are collected based on the spatial coordinate system, and a multipath propagation path diagram is constructed in combination with the real-time signal strength. Specifically: a phase synchronization trigger signal is used to control the sampling timing of each RF antenna to obtain a sampling signal; the in-phase component and the orthogonal component of the sampling signal are extracted, and the instantaneous phase and envelope of the sampling signal are calculated based on the in-phase component and the orthogonal component; based on the instantaneous phase, a generalized cross-correlation algorithm is used to calculate the arrival time difference between any two RF antennas; an overdetermined set of equations is constructed based on the arrival time difference, and the arrival angle of the sampling signal is determined based on the overdetermined set of equations.

[0063] The intelligent fusion terminal collects the arrival time difference and arrival angle of the signal received by each RF antenna based on the spatial coordinate system, and builds a multipath propagation path diagram based on the real-time signal strength. This step uses the established three-dimensional spatial coordinate system to collect information such as the arrival time difference and arrival angle of the signal received by each RF antenna, and combines the real-time measured signal strength data to build a graph model describing the signal multipath propagation path. The multipath propagation path diagram can reflect the propagation of the signal in space, including the direct path and reflection path of the signal, and provide important reference information for subsequent signal compensation and correction.

[0064] In specific implementation, the intelligent fusion terminal can construct a multipath propagation path map in a variety of ways. First, the intelligent fusion terminal can use the phase synchronization trigger signal to control the sampling timing of each RF antenna to ensure that the signal samples collected by each antenna are synchronized in time. Then, the intelligent fusion terminal can extract the in-phase component and the orthogonal component of the sampled signal, and calculate the characteristic parameters such as the instantaneous phase and envelope of the sampled signal based on these components. Using these characteristic parameters, the intelligent fusion terminal can use the generalized cross-correlation algorithm to calculate the arrival time difference between any two RF antennas, and construct an overdetermined set of equations based on the arrival time difference, and then solve the arrival angle of the sampled signal. Finally, the intelligent fusion terminal can conduct a comprehensive analysis of the location information of each RF antenna, the arrival time difference and arrival angle of the signal, and the real-time signal strength data to construct a complete multipath propagation path map.

[0065] Before executing step S203, the propagation speed and attenuation coefficient of electromagnetic waves in different media are calculated according to the real-time environmental status data; the propagation characteristics of electromagnetic waves are simulated to obtain the main propagation path; based on the main propagation path, an electromagnetic field simulation model is established; the signal propagation loss of different paths is predicted using the electromagnetic field simulation model to obtain a path loss estimation database. Among them, the signal propagation loss of different paths is predicted using the electromagnetic field simulation model, specifically including: obtaining the electromagnetic field distribution based on the electromagnetic field simulation model; simplifying the electromagnetic field distribution into the superposition of several main propagation modes to obtain a superposition representation; establishing an electromagnetic wave transmission equation containing frequency dispersion and spatial attenuation characteristics based on the superposition representation; calculating the geometric attenuation, medium absorption and scattering loss of each main propagation path to obtain a loss characteristic vector; constructing a path characteristic parameter matrix according to the loss characteristic vector, the characteristic dimensions in the path characteristic parameter matrix include path length, incident angle, number of reflections and loss components; using a recursive neural network to train the path loss prediction model, and using the path characteristic parameter matrix as input to predict the signal propagation loss of different paths.

[0066] S203, calculating the geometric loss, dielectric loss and reflection loss of each path based on the multipath propagation path diagram to obtain path transmission characteristic parameters; The intelligent fusion terminal calculates the geometric loss, dielectric loss and reflection loss of each path based on the multipath propagation path map to obtain the path transmission characteristic parameters. This step uses the constructed multipath propagation path map to analyze and calculate the signal loss on each propagation path to obtain a set of parameters that reflect the path transmission characteristics. These transmission characteristic parameters include the geometric diffusion loss, dielectric absorption loss, and reflection and refraction loss suffered by the signal during the propagation process, which are crucial for subsequent signal compensation and correction.

[0067] In specific implementation, the intelligent fusion terminal can obtain the loss parameters of each propagation path by combining theoretical calculation and empirical estimation. For geometric loss, the intelligent fusion terminal can use the free space propagation model to calculate the distance attenuation and diffusion loss of the signal based on the distance between the RF antenna and the product in the spatial coordinate system and the geometric characteristics of the propagation path. For dielectric loss, the intelligent fusion terminal can calculate the propagation speed and attenuation coefficient of electromagnetic waves in media such as air and shelves based on environmental parameters such as temperature, humidity, and air pressure in the settlement area, and estimate the dielectric absorption loss based on the length of the propagation path. For reflection loss, the intelligent fusion terminal can calculate the reflection loss based on parameters such as the material, roughness, and incident angle of reflective surfaces such as shelves, floors, and ceilings using a simplified electromagnetic theoretical model (such as the Fresnel reflection model). In addition, the intelligent fusion terminal can also use electromagnetic field simulation software to perform three-dimensional modeling and grid division on the settlement area, simulate and calculate the signal loss on each propagation path, and generate an estimated database for path loss.

[0068] S204, establishing a signal propagation compensation matrix according to the path transmission characteristic parameters, and performing amplitude and phase compensation on the radio frequency signal based on the signal propagation compensation matrix to obtain a corrected signal strength distribution; The intelligent fusion terminal establishes a signal propagation compensation matrix according to the path transmission characteristic parameters, and performs amplitude and phase compensation on the RF signal based on the signal propagation compensation matrix to obtain the corrected signal strength distribution. This step uses the estimated path transmission characteristic parameters to construct a matrix model that describes the signal propagation compensation rule, and uses the matrix to correct the amplitude and phase of the received RF signal, and finally obtains the compensated signal strength spatial distribution. The purpose of this step is to suppress the impact of multipath effects on signal strength measurement and improve the accuracy and reliability of signal strength distribution.

[0069] In specific implementation, the intelligent fusion terminal can establish a signal propagation compensation matrix based on the theoretical basis of signal processing and the estimated path transmission characteristic parameters. The row and column dimensions of the matrix correspond to the number of RF antennas, and the element values ​​of the matrix reflect the signal compensation coefficients between different antennas. These compensation coefficients need to comprehensively consider factors such as the amplitude attenuation and phase delay of the RF signal on each propagation path, and are calculated using the geometric characteristics and loss parameters of the propagation path. After obtaining the compensation matrix, the intelligent fusion terminal can multiply the matrix with the original signal received by each RF antenna to obtain the compensated signal amplitude and phase value. Finally, the intelligent fusion terminal can use the compensated signal amplitude to recalculate the signal strength distribution map at each location in the space as a basis for subsequent judgment of the normativeness of product placement.

[0070] S205, calculating the false detection rate and missed detection rate according to the corrected signal strength distribution; The intelligent fusion terminal calculates the false detection rate and missed detection rate based on the corrected signal strength distribution. This step uses the compensated and corrected signal strength distribution diagram to analyze and calculate the false detection rate and missed detection rate indicators of the system's judgment on the standardization of product placement. The false detection rate refers to the probability of misjudging a product that meets the placement specifications as not meeting the specifications, while the missed detection rate refers to the probability of misjudging a product that does not meet the placement specifications as meeting the specifications. These two indicators reflect the accuracy and reliability of the judgment on the standardization of product placement and are important bases for evaluating system performance.

[0071] In specific implementation, the intelligent fusion terminal can use statistical hypothesis testing methods to calculate the false detection rate and missed detection rate. First, the intelligent fusion terminal needs to divide the corrected signal strength distribution map into two areas that meet the placement specifications and do not meet the placement specifications according to the pre-set judgment threshold. Then, the intelligent fusion terminal can select a group of commodity samples with known placement specifications, and according to the position of these samples in the signal strength distribution map, statistically judge the difference between the result and the actual placement specification. By calculating the proportion of samples that meet the specifications that are misjudged as not meeting the specifications, the false detection rate of the system can be obtained. Similarly, by calculating the proportion of samples that do not meet the specifications that are missed as meeting the specifications, the missed detection rate of the system can be obtained.

[0072] S206: Update the preset threshold value according to the false detection rate, the missed detection rate and the preset detection reliability requirement.

[0073] The intelligent fusion terminal updates the preset threshold value according to the false detection rate, missed detection rate and preset detection reliability requirements. This step uses the calculated false detection rate and missed detection rate indicators, combined with the system's preset detection reliability requirements, to dynamically adjust the threshold parameters for the normative judgment of product placement. Through the adaptive update of the threshold, the sensitivity of the judgment threshold can be improved while meeting the detection reliability requirements, reducing the false detection rate and missed detection rate, and further improving the overall performance of the system.

[0074] In specific implementation, the intelligent fusion terminal can adopt a closed-loop control method to achieve automatic adjustment of the judgment threshold. First, the intelligent fusion terminal needs to preset an initial detection reliability target based on business needs and operational experience, such as controlling the false detection rate and missed detection rate within 5% at the same time. Then, the intelligent fusion terminal can compare the difference between the current false detection rate and missed detection rate and the preset target, and calculate the adjustment amount of the threshold according to the size and sign of the difference. For example, if the false detection rate is higher than expected and the missed detection rate is lower than expected, the intelligent fusion terminal can appropriately lower the judgment threshold to reduce the occurrence of false detection. Conversely, if the missed detection rate is higher than expected and the false detection rate is lower than expected, the intelligent fusion terminal needs to increase the judgment threshold to reduce the occurrence of missed detection. Through multiple consecutive threshold adjustments and performance evaluations, the intelligent fusion terminal can continuously approach the optimal judgment threshold and achieve adaptive optimization of detection performance.

[0075] In the above embodiment, a three-dimensional spatial coordinate system including the position of the RF antenna, the boundary of the commodity placement area, and the distribution of metal objects is established, and a multipath propagation path diagram is constructed in combination with the arrival time difference and arrival angle information, thereby realizing accurate modeling of the RF signal propagation environment. The loss parameters of each propagation path are calculated and a signal propagation compensation matrix is ​​established to perform amplitude and phase compensation on the RF signal, thereby reducing the signal distortion caused by multipath propagation. The false detection rate and missed detection rate are calculated based on the corrected signal strength distribution, and the preset threshold is dynamically updated, so that the system has adaptive adjustment capabilities, reduces the impact of complex electromagnetic environments on signal propagation, and improves the accuracy of signal strength measurement. By updating the preset threshold in real time, the system can automatically optimize the judgment criteria according to the actual detection effect, thereby improving the reliability of the judgment of the standardization of commodity placement.

[0076] The following describes the terminal in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a settlement terminal based on an intelligent fusion terminal provided in an embodiment of the present application.

[0077] It should be noted that Figure 3 The structure of the terminal shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0078] like Figure 3 As shown, the terminal includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method in the above embodiment. Various programs and data required for terminal operation are also stored in RAM 303. CPU 301, ROM 302 and RAM 303 are connected to each other through a bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0079] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD) and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0080] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0081] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0082] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the terminal, method and computer program product according to various embodiments of the present invention. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based terminal that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0083] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the terminal described in the above embodiment; or may exist independently without being assembled into the terminal. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a terminal, the terminal implements the method provided in the above embodiment.

[0084] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0085] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0086] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0087] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A settlement method based on an intelligent fusion terminal, characterized in that: include: After determining that the barcode information of the new product has been scanned, calculating the maximum radio frequency signal strength value of the new product in the settlement area, and determining the maximum radio frequency signal strength value as the reference signal strength, the terminal includes the settlement area and the settled area, and a plurality of radio frequency antennas are arranged in the settlement area and the settled area to obtain the radio frequency signal strength of the product; Determining whether the weight of the goods in the settled area increases; If the weight of the commodity has not increased, then calculating the maximum radio frequency signal strength value of the new commodity in the settled area to obtain the settled signal strength; When it is determined that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, performing a spatial interpolation operation on all radio frequency signal data in the settled area to construct a continuous distribution surface of the radio frequency signal strength of the new product; Calculating the peak position of the continuous distribution surface, and determining whether the peak position of the surface is within a preset range of the settled area; If the new product is within the preset range, the new product is confirmed as a standard placement product; If the new product is not within the preset range, the new product is confirmed as a non-standardly placed product; Turning on a preset alarm mode, and after the preset alarm mode ends, executing the step of calculating the maximum radio frequency signal strength value of the new commodity in the settled area to obtain the settled signal strength; If the weight of the commodity increases, the new commodity is confirmed as a standard placement commodity.

2. The method according to claim 1, characterized in that The step of calculating the maximum radio frequency signal strength value of the new product in the settlement area specifically includes: Obtaining a sequence of radio frequency signal strengths collected by each radio frequency antenna in a settlement area within a preset time window; Performing wavelet transform on the radio frequency signal strength sequence to obtain signal characteristic coefficients at different scales; Calculating the entropy value of the signal according to the signal characteristic coefficient, and removing abnormal data whose entropy value is greater than a preset threshold; constructing an analytical representation based on the signal strength values ​​excluding the abnormal data; Calculating the instantaneous envelope of the analytical representation to obtain a local maximum point; Performing linear regression on the local maximum point to obtain a change trend of the signal strength; The maximum value of the signal strength in the change trend is used as the reference signal strength.

3. The method according to claim 1, characterized in that The step of performing spatial interpolation operation on all radio frequency signal data of the settled area to construct a continuous distribution surface of the radio frequency signal strength of the new product specifically includes: Dividing the settled area into a first number of grid units, recording the radio frequency signal strength value of the center point of each grid unit, and obtaining a discrete spatial sampling data set; Calculating a signal strength change rate of each of the grid cells based on the spatial sampling data set, and adaptively subdividing the grid cells according to the magnitude of the signal strength change rate to obtain a second number of subdivided grid cells, where the second number is greater than the first number; constructing an interpolation basis function system in the form of a tensor product, wherein the interpolation basis function system satisfies an interpolation condition at the nodes of the grid unit; Solving interpolation coefficients that satisfy global smoothness according to the interpolation basis function system; constructing a global system of equations including boundary continuity constraints for the subdivided grid cells; A continuous distribution surface of the radio frequency signal strength of the new product is constructed based on the global equation group and the interpolation coefficients.

4. The method according to claim 1, characterized in that: Before determining that the ratio of the settled signal strength to the reference signal strength is less than a preset threshold, the method further includes: Acquire the three-dimensional spatial coordinate information of the settlement area and the settled area, and establish a spatial coordinate system including the location of the radio frequency antenna, the boundary of the commodity placement area, and the distribution of metal objects; Based on the spatial coordinate system, the arrival time difference and arrival angle of the signal received by each of the radio frequency antennas are collected, and a multipath propagation path diagram is constructed in combination with the real-time signal strength; Calculating the geometric loss, dielectric loss and reflection loss of each path based on the multipath propagation path diagram to obtain path transmission characteristic parameters; Establishing a signal propagation compensation matrix according to the path transmission characteristic parameters; Performing amplitude and phase compensation on the radio frequency signal based on the signal propagation compensation matrix to obtain a corrected signal strength distribution; Calculating the false detection rate and missed detection rate according to the corrected signal strength distribution; The preset threshold is updated according to the false detection rate, the missed detection rate and the preset detection reliability requirement.

5. The method according to claim 4, characterized in that The step of collecting the arrival time difference and arrival angle of the signal received by each of the radio frequency antennas based on the spatial coordinate system specifically includes: Using a phase synchronization trigger signal to control the sampling timing of each of the radio frequency antennas to obtain a sampling signal; Extracting the in-phase component and the quadrature component of the sampled signal, and calculating the instantaneous phase and envelope of the sampled signal according to the in-phase component and the quadrature component; Based on the instantaneous phase, a generalized cross-correlation algorithm is used to calculate the arrival time difference between any two of the radio frequency antennas; An overdetermined set of equations is constructed according to the arrival time difference, and the arrival angle of the sampling signal is determined according to the overdetermined set of equations.

6. The method according to claim 4, characterized in that Before calculating the geometric loss, dielectric loss and reflection loss of each path based on the multipath propagation path graph, the method further includes: Calculate the propagation speed and attenuation coefficient of electromagnetic waves in different media based on real-time environmental status data; Simulating the propagation characteristics of the electromagnetic wave to obtain a main propagation path; Based on the main propagation path, establishing an electromagnetic field simulation model; The electromagnetic field simulation model is used to predict signal propagation losses of different paths to obtain a path loss estimation database.

7. The method according to claim 6, characterized in that The method of using the electromagnetic field simulation model to predict signal propagation losses of different paths specifically includes: Simulating the electromagnetic field distribution based on the electromagnetic field simulation model; Simplifying the electromagnetic field distribution into a superposition of several main propagation modes to obtain a superposition representation; Establishing an electromagnetic wave transmission equation including frequency dispersion and spatial attenuation characteristics based on the superposition representation; Calculating the geometric attenuation, dielectric absorption and scattering loss of each of the main propagation paths to obtain a loss characteristic vector; Constructing a path characteristic parameter matrix according to the loss characteristic vector, wherein the characteristic dimensions in the path characteristic parameter matrix include path length, incident angle, number of reflections and loss component; A recursive neural network is used to train a path loss prediction model, and the path characteristic parameter matrix is ​​used as input to predict signal propagation losses of different paths.

8. A settlement terminal based on an intelligent fusion terminal, characterized in that: The terminal comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the terminal to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a terminal, the terminal is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is executed on a terminal, the terminal is enabled to execute the method according to any one of claims 1 to 7.

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