Commodity replenishment counting method and device and computer readable storage medium

Abstract

The invention discloses a commodity replenishment counting method and device and a computer readable storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a pulse signal fed back by a roller counting sensor in a replenishment process and a weight signal fed back by a weight sensor in a cache region in response to a replenishment completion operation; calculating replenishment length information of a target commodity according to the pulse signal, and determining first commodity quantity data according to standard length information of the target commodity and the replenishment length information; determining replenishment weight information of the target commodity based on the weight signal, and determining second commodity quantity data according to standard weight information of the target commodity; and if the first commodity quantity data is not matched with the preset replenishment quantity, correcting the first commodity quantity data based on the second commodity quantity data. The technical effect of improving the accuracy of commodity replenishment quantity statistics is achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a commodity replenishment counting method, device, and computer-readable storage medium. Background Art

[0002] Currently, roller counting sensors are commonly used to count the number of goods during the replenishment process. However, these sensors are prone to signal interference, which can cause pulse signal loss and lead to errors in replenishment quantity counting.

[0003] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of this application is to provide a commodity replenishment counting method, device and computer-readable storage medium, aiming to solve the technical problem of replenishment quantity counting errors caused by sensor signal loss.

[0005] To achieve the above objectives, the present application proposes a commodity replenishment counting method, which includes: In response to the replenishment completion operation, a pulse signal fed back by the roller counting sensor and a weight signal fed back by the weight sensor during the replenishment process are acquired in the buffer area; Calculating replenishment length information of the target product according to the pulse signal, and determining quantity data of the first product according to the standard length information of the target product and the replenishment length information; determining replenishment weight information of the target product based on the weight signal, and determining quantity data of the second product based on the standard weight information of the target product; If the first product quantity data does not match the preset replenishment quantity, the first product quantity data is corrected based on the second product quantity data.

[0006] In one embodiment, after the steps of determining the replenishment weight information of the target product based on the weight signal and determining the quantity data of the second product based on the standard weight information of the target product, the product replenishment counting method further includes: Get the preset replenishment quantity; If the first product quantity data and the second product quantity data do not match the preset replenishment quantity, a replenishment product type error message is generated; Render the replenishment product type error information to the corresponding electronic price tag.

[0007] In one embodiment, the step of calculating the replenishment length information of the target product according to the pulse signal, and determining the quantity data of the first product according to the standard length information of the target product and the replenishment length information includes: Counting the pulse signal to obtain the number of pulses; Calculating the roller rotation distance based on the number of pulses and the unit pulse length corresponding to the pulse signal as replenishment length information of the target product; Based on a pre-established commodity information database, standard length information corresponding to the target commodity is obtained, and the first commodity quantity data is calculated according to a quotient of the replenishment length information and the standard length information.

[0008] In one embodiment, the step of calculating the roller rotation distance based on the number of pulses and the unit pulse length corresponding to the pulse signal as the replenishment length information of the target product includes: Acquiring the operating status data of the roller counting sensor and calculating the dynamic correction coefficient of the roller rotation distance of the roller counting sensor; Based on the number of pulses, the unit pulse length, and the dynamic correction coefficient, the roller rotation distance is calculated to obtain the corresponding replenishment length information of the target product.

[0009] In one embodiment, after the steps of determining the replenishment weight information of the target product based on the weight signal and determining the quantity data of the second product according to the standard weight information of the target product, the following steps are included: Based on the pulse signal of the roller counting sensor, the standard deviation of the pulse interval time is calculated, the pulse stability coefficient is determined, and normalized to the counting dimension confidence; Based on the weight signal of the weight sensor, calculating the weight average absolute difference, determining the weight fluctuation rate, and normalizing it into a quality dimension confidence; Establishing a two-dimensional confidence evaluation system for commodity quantity data based on the counting dimension confidence and the quality dimension confidence; Based on the two-dimensional confidence evaluation system and in combination with the environmental factor correction coefficient, the weight coefficient of the first commodity quantity data corresponding to the counting dimension confidence and the weight coefficient of the second commodity quantity data corresponding to the quality dimension confidence are dynamically adjusted; The actual quantity of the replenished goods is calculated based on the weight coefficient of the first commodity quantity data and the weight coefficient of the second commodity quantity data.

[0010] In one embodiment, after the step of correcting the first product quantity data based on the second product quantity data if the first product quantity data does not match the preset replenishment quantity, the method further includes: If there is a discrepancy between the corrected quantity data of the first product and the preset replenishment quantity, it is determined that the replenishment product is lost; Calculating the difference between the corrected quantity data of the first product and the preset replenishment quantity; Generate replenishment commodity missing information based on the difference, and render the replenishment commodity missing information on the corresponding electronic price tag.

[0011] In one embodiment, before the step of acquiring, in the buffer area, the pulse signal fed back by the roller counting sensor during the replenishment process and the weight signal fed back by the weight sensor in response to the replenishment completion operation, the method further includes: In response to a user-triggered replenishment start operation, entering a replenishment mode for the target product; Based on the replenishment mode, the pulse signal output by the roller counting sensor is received in real time and stored in a buffer area; The weight sensor detects the weight change of the goods on the shelf in real time, and converts the weight signal into a digital signal and stores it in the buffer area. In response to the replenishment completion operation, the replenishment mode is exited, and the reception of the signals output by the roller counting sensor and the weight sensor is stopped.

[0012] In one embodiment, before the step of acquiring, in the buffer area, a pulse signal fed back by the roller counting sensor and a weight signal fed back by the weight sensor during the replenishment process in response to the replenishment completion operation, the commodity replenishment counting method further comprises: In response to a replenishment start operation, identifying a type of target commodity for replenishment; If the target commodity is an irregular commodity, obtaining characteristic parameters corresponding to the target commodity type and calculating a pulse signal compensation value and a weight signal compensation value; compensating the pulse signal based on the pulse signal compensation value, and compensating the weight signal based on the weight signal compensation value; If the difference between the value after compensation and the value before compensation is greater than the compensation threshold, the vibration signal and pressure distribution of the shelf are analyzed; If an abnormal vibration signal or pressure distribution is detected, the shelf structure is determined to be abnormal, and manual review information is generated and displayed on the electronic price tag corresponding to the shelf.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes a commodity replenishment counting device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the commodity replenishment counting method described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium and stores a computer program. When the computer program is executed by a processor, the steps of the product replenishment counting method described above are implemented.

[0015] The present application provides a method for counting replenishment of goods. The present application first responds to the replenishment completion operation and obtains the pulse signal fed back by the roller counting sensor and the weight signal fed back by the weight sensor during the replenishment process in the buffer area; calculates the replenishment length information of the target product based on the pulse signal, and determines the first product quantity data based on the standard length information and the replenishment length information of the target product; determines the replenishment weight information of the target product based on the weight signal, and determines the second product quantity data based on the standard weight information of the target product; if the first product quantity data does not match the preset replenishment quantity, the first product quantity data is corrected based on the second product quantity data. The present application performs a double verification of the replenishment quantity by combining the pulse signal of the roller counting sensor and the weight signal of the weight sensor, thereby improving the accuracy of the replenishment quantity calculation. When the pulse signal is abnormal, it is automatically determined that the signal is lost and the correction mechanism is triggered. The abnormality of the pulse signal is corrected based on the weight sensor data to ensure the accuracy of the replenishment quantity. The present application achieves the technical effect of improving the accuracy of the statistics of the replenishment quantity of goods. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A flowchart of the first embodiment of the method for counting replenishment of goods in this application is provided; Figure 2 A flowchart of the second embodiment of the method for counting replenishment of goods in this application is provided; Figure 3 A flowchart of the third embodiment of the method for counting replenishment of goods in this application is provided; Figure 4 A flowchart of the fourth embodiment of the method for counting replenishment of goods in this application is provided; Figure 5 A flowchart of the fifth embodiment of the method for counting replenishment of goods in this application is provided; Figure 6A flowchart of Example 6 of the commodity replenishment counting method of this application is provided; Figure 7 A brief flowchart of Example 6 of the product replenishment counting method of this application is provided; Figure 8 This is a structural diagram of a commodity replenishment counting device in an embodiment of the present application.

[0019] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0020] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0021] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0022] The main solutions of the embodiments of this application are: Currently, during the product replenishment process, roller counting sensors are usually used to count the number of goods. However, roller counting sensors are prone to pulse signal loss due to mechanical failure, signal interference or physical obstruction, resulting in errors in replenishment quantity statistics.

[0023] This application combines the pulse signal of the roller counting sensor and the weight signal of the weight sensor to perform double verification of the replenishment quantity, thereby improving the accuracy of the replenishment quantity calculation. When the pulse signal is abnormal, it automatically determines that the signal is lost and triggers the correction mechanism to correct the abnormality of the pulse signal based on the weight sensor data to ensure the accuracy of the replenishment quantity.

[0024] It should be noted that the execution entity of this embodiment can be a product replenishment and counting system, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or a control device for a product replenishment and counting system capable of implementing the above functions, etc. This embodiment does not specifically limit this. The following uses the product replenishment and counting system as an example to illustrate this embodiment and the following embodiments.

[0025] Example 1 Based on this, this application proposes a commodity replenishment counting method of the first embodiment, please refer to Figure 1 , the commodity replenishment counting method includes: In step S10 , in response to the replenishment completion operation, a pulse signal fed back by the roller counting sensor and a weight signal fed back by the weight sensor during the replenishment process are acquired in the buffer area.

[0026] By simultaneously acquiring data from the roller counting sensor and weight sensor, a double verification basis is provided for subsequent replenishment quantity calculations, thereby improving data reliability.

[0027] In this embodiment, the replenishment completion operation is a confirmation action triggered by the replenishment personnel after the product is put on the shelf, including operations such as clicking a button, scanning a barcode, or triggering a mechanical switch. A roller counting sensor is a sensor that generates a pulse signal through the rotation of a roller, including a magnetic, electrode, or grating sensor, and is used to calculate the distance or quantity of goods moved. The pulse signal is an electrical signal generated every time the roller rotates a certain angle, and the frequency is proportional to the speed of the goods moving. A weight sensor is a sensor that measures the weight of goods based on the piezoresistive effect, capacitance change, or electromagnetic induction principles. The weight signal is the electrical signal output by the weight sensor, and the value is proportional to the weight of the goods.

[0028] It should be noted that the roller counting sensor is deployed at the end of the shelf, the other end of the shelf is equipped with an electronic price tag, and the weight sensor is deployed at the bottom of the shelf. The roller counting sensor can be compared to a mouse wheel, sending a pulse signal when rolling, and one unit of pulse signal represents a fixed scroll distance. The roller counting sensor is connected to a spring rope, the other end of which is connected to a push plate. When an item is placed on the shelf, the push plate pushes toward the roller, causing the spring rope to loosen, and the roller counting sensor retracts the excess spring rope. The distance the roller counting sensor's roller rotates while retracting the spring rope can be used to determine the length of the item placed, and thus the quantity of the item placed.

[0029] Optionally, the pulse signal of the roller counting sensor is received and the corresponding information is transmitted to the electronic price tag and the backend server respectively. The electronic price tag will update the displayed data, and the backend server can count and manage the replenishment of the goods.

[0030] Optionally, a grating roller sensor is used, in which a grating disk with equidistant light-transmitting holes is distributed on the surface of the roller. The grating disk rotates synchronously with the roller. An infrared lamp is used to emit a parallel light beam to vertically illuminate the grating disk. The light on and off is detected by a receiver, and a pulse signal is output to solve the counting error problems caused by fluctuations in the magnetic field intensity of the magnetic sensor and poor contact of the electrodes of the electrode-type sensor.

[0031] Step S20 , calculating the replenishment length information of the target product according to the pulse signal, and determining the quantity data of the first product according to the standard length information of the target product and the replenishment length information.

[0032] In this embodiment, replenishment length information is the length of the target product along the shelf during the replenishment process, calculated from the pulse signal of the roller counting sensor. Standard length information is a pre-set standard length value corresponding to the target product. It serves as benchmark data for comparison with the actual measured replenishment length information and calculation of product quantity. Standard length information corresponding to the target product can be obtained from a pre-established product information database based on the product type corresponding to the shelf. First product quantity data refers to preliminary data on the replenished product quantity, calculated based on the replenishment length information and standard length information.

[0033] As an optional implementation, the length corresponding to each pulse signal is determined based on the calibration parameters of the roller counting sensor. The number of pulses is then converted to the actual replenishment length using the formula: "Replenishment length = number of pulses × length corresponding to each pulse." A database is then queried to obtain the standard length of the target product. The replenishment length is then divided by the standard length to obtain the first product quantity using the formula: "First product quantity = replenishment length / standard length."

[0034] As another alternative, a high-precision linear guide is installed on the replenishment track or shelf, along with a grating ruler. A roller counting sensor is linked to the grating ruler. As the roller rotates, the grating ruler simultaneously measures the linear displacement of the replenishment push plate. The ruler collects the displacement pulse signal feedback, calculates the actual displacement of the replenishment push plate based on its resolution, and divides this displacement by the standard length of the target product to obtain the first product quantity data.

[0035] Optionally, step S20 includes: Step S21: Count the pulse signal to obtain the number of pulses.

[0036] Exemplarily, the state of the stored pulse signal of the roller counting sensor is read, and when it is detected that the signal jumps from a low level to a high level, the pulse number count is increased by 1.

[0037] Optionally, upon receiving a replenishment start signal, a hardware counter connected to the output of the roller counting sensor is started, and the hardware counter counts the pulse signals in real time and stores the count result in a register. Upon receiving a replenishment end signal, the hardware counter stops counting and the number of pulses during the replenishment process is obtained by reading the value of the register.

[0038] Step S22: Calculate the roller rotation distance based on the number of pulses and the unit pulse length corresponding to the pulse signal as replenishment length information of the target product.

[0039] It should be noted that the roller rotation distance is the linear displacement length corresponding to the rotation of the roller during the replenishment process, reflecting the actual length occupied by the replenished goods on the shelf.

[0040] For example, the number of pulse signals N generated per rotation of the roller is obtained, and the unit pulse length is calculated based on the measured roller circumference L. , which is the arc length corresponding to the roller rotation angle corresponding to each pulse signal. Multiply the number of pulses by the unit pulse length to get the total distance the roller rotates.

[0041] Optionally, step S22 includes: Step A10: Acquire the operating status data of the roller counting sensor and calculate the dynamic correction coefficient of the roller rotation distance of the roller counting sensor.

[0042] The purpose of acquiring the operating status data of the roller counting sensor and calculating the dynamic correction coefficient for the roller rotation distance is to correct and optimize the roller rotation distance measured by the roller counting sensor. During actual operation, the roller counting sensor may be affected by various factors, such as roller wear, sensor accuracy deviations, and signal interference caused by environmental factors. This can cause a certain error between the measured roller rotation distance and the actual value. By calculating the dynamic correction coefficient, the measured value can be dynamically adjusted based on the current operating status of the sensor, thereby improving the accuracy of the roller rotation distance measurement.

[0043] It should be noted that a roller counting sensor measures the distance or amount of an object's movement by detecting the rotation of a roller. It consists of a roller, an encoder, and other components. When the roller contacts the object being measured and rotates as the object moves, the encoder converts the roller's rotation into a pulse signal. By counting and processing the pulse signal, information such as the number of roller rotations can be obtained, and the distance the object has moved can be calculated. Operating status data refers to various data generated by the roller counting sensor during operation, reflecting the sensor's operating status. This includes parameters such as the roller's speed, acceleration, vibration, and the frequency, amplitude, and stability of the pulse signal output by the sensor. The dynamic correction coefficient is a coefficient used to make real-time corrections to the measured value of the roller's rotation distance. It is calculated based on the current operating status data of the roller counting sensor, and different operating states correspond to different correction coefficients.

[0044] Optionally, corresponding sensors are installed in the shelf where the roller counting sensor is located, including a rotation speed sensor, a pressure sensor, a current sensor, a temperature sensor, a humidity sensor, and the like.

[0045] Optionally, based on the physical characteristics and actual operating conditions of the roller counting sensor, a mathematical model is established to describe the relationship between the pulse signal and the actual rotation distance during roller rotation. The characteristic quantities of the roller counting sensor are used as the model's input variables, and the dynamic correction coefficients are used as the model's output variables. The model is trained and optimized using experimental data or historical data to determine the model's parameters.

[0046] For example, sensors collect real-time operating status data such as roller speed, load pressure, motor current, ambient temperature, and humidity. This data is then preprocessed, including data cleaning, smoothing, and feature extraction, to extract key features that effectively reflect the roller's operating status, namely operating status data. This includes the average speed, standard deviation of load pressure, and peak motor current. This extracted operating status data is then fed into a trained calibration model, which then calculates a dynamic calibration coefficient in real time based on the current operating status data and trained parameters.

[0047] Step A20: Calculate the roller rotation distance based on the pulse quantity, the unit pulse length, and the dynamic correction coefficient to obtain the corresponding replenishment length information of the target product.

[0048] The pulse signal generated by the roller counting sensor is converted into the actual replenishment length, providing accurate data support for inventory management and replenishment decisions. Because the roller's rotation is affected by various factors, resulting in deviations between the pulse signal and the actual rotation distance, calculations based solely on the number of pulses and unit pulse length can result in errors. By introducing a dynamic correction factor, the calculated roller rotation distance can be corrected in real time, bringing it closer to the actual replenishment length, thereby improving replenishment counting accuracy.

[0049] For example, pulse signals generated during the replenishment process are read from a buffer, the number of pulses is counted, and a pre-set unit pulse length parameter is obtained. The number of pulses is multiplied by the unit pulse length to obtain the uncorrected roller rotation distance. The uncorrected roller rotation distance is then multiplied by the dynamic correction coefficient to obtain the corrected roller rotation distance. Based on the size parameters and arrangement of the target products, the corrected roller rotation distance is converted into the corresponding replenishment length information.

[0050] Step S23 : Based on a pre-established commodity information database, obtain the standard length information corresponding to the target commodity, and calculate the quantity data of the first commodity according to the quotient of the replenishment length information and the standard length information.

[0051] It should be noted that the product information database stores information such as product type, standard length, standard weight, and price. Standard length information is a pre-set standard length value corresponding to the target product, determined based on the product's packaging specifications and dimensions, and stored in the product information database.

[0052] Exemplarily, according to the commodity type corresponding to the replenished shelf, the corresponding standard length information is searched in the commodity information database, and then the calculated replenishment length information is divided by the standard length information to obtain the first commodity quantity data.

[0053] Step S30: determining the replenishment weight information of the target product based on the weight signal, and determining the quantity data of the second product according to the standard weight information of the target product.

[0054] In this embodiment, replenishment weight information refers to the total weight change of the target product after it is placed on the shelf, as measured by the weight sensor during the replenishment process. Standard weight information refers to the pre-set standard individual product weight value corresponding to the target product, which is used to compare with the actual measured replenishment weight information and calculate the product quantity. Secondary product quantity data refers to the replenished product quantity data calculated based on the replenishment weight information and the standard weight information.

[0055] As an optional embodiment, upon receiving a start replenishment instruction, the initial weight (i.e., the weight of the goods on the shelf before replenishment) is recorded based on the weight signal. Upon receiving a stop replenishment instruction, the final weight is recorded. The initial weight is subtracted from the final weight to obtain replenishment weight information. The standard weight information corresponding to the target goods is retrieved from the goods information database. The replenishment weight information is divided by the standard weight information to obtain the second product quantity data.

[0056] As another optional implementation, during the replenishment process, the weight signal output by the weight sensor is collected and the weight value at each moment is recorded to generate a weight change trend curve. The standard weight information of the target product is obtained from the product information database. The weight change trend curve and the standard weight information are combined to calculate the quantity data of the second product. The weight change trend curve is analyzed. If the weight change curve is relatively stable, the stabilized weight value is directly used for calculation. If the weight change curve has small fluctuations, a filtering algorithm is used to process the weight signal before calculating the product quantity.

[0057] Optionally, after replenishment is completed, the weight sensor is controlled to collect weight signals at multiple different time points, and the weight values ​​corresponding to the collected multiple weight signals are arithmetic averaged. The obtained average weight value is used as the total weight after replenishment to reduce measurement errors caused by environmental interference and other factors.

[0058] For example, after replenishment is complete, the weight sensor continuously collects weight signals, and the system monitors the collected weight signals in real time. The weight value corresponding to the weight signal is the total weight after replenishment. The pre-replenishment weight is obtained from the database cache, and the pre-replenishment weight is subtracted from the post-replenishment weight to obtain the replenishment weight information. Based on the shelf information, the corresponding product type is obtained. Based on the target product, the product information database is queried to obtain the corresponding standard weight information. The obtained replenishment weight information is divided by the standard weight information to obtain the second product quantity data.

[0059] It should be noted that the pre-replenishment weight is the total weight of the target products on the shelf before the replenishment operation begins. When the replenishment start signal is received, the signal of the weight sensor is read and the corresponding weight data is obtained by parsing, which is the pre-replenishment weight, and the pre-replenishment weight is stored in the database.

[0060] Step S40: If the first product quantity data does not match the preset replenishment quantity, the first product quantity data is corrected based on the second product quantity data.

[0061] In this embodiment, the preset replenishment quantity refers to the planned replenishment quantity of goods before the replenishment operation begins, or the replenishment quantity entered by the replenishment personnel at the beginning of the replenishment operation. Correction is the process of adjusting and correcting the first product quantity data using the second product quantity data through an algorithm or rule to eliminate counting deviations caused by loss of the roller counting sensor signal or other error factors, thereby making the final determined product replenishment quantity more accurate.

[0062] As an optional implementation, when the system detects that the difference between the first product quantity data and the preset replenishment quantity exceeds a preset range, the second product quantity data is directly used to replace the first product quantity data as the final product replenishment quantity, and the corrected product replenishment quantity is updated to the inventory management system.

[0063] As another optional implementation, historical replenishment data is analyzed to establish a replenishment quantity trend model. When it is found that the first product quantity data does not match the preset replenishment quantity, a comprehensive judgment is made based on the current replenishment trend and the second product quantity data. If the second product quantity data is consistent with the replenishment trend, but the first product quantity data significantly deviates from the trend, the trend model and the second product quantity data are used to adjust the first product quantity data.

[0064] Optionally, when it is detected that the difference between the quantity data of the first product and the preset replenishment quantity exceeds a preset range, it can be determined that the signal of the roller counting sensor is lost, and a signal loss prompt message can be displayed on the electronic price tag corresponding to the shelf where the roller counting sensor is located, so that the management personnel can repair it in time.

[0065] Optionally, after the replenishment item count is completed, the current inventory quantity of the target shelf is read from the database, the corrected first item quantity is added to the current inventory quantity to obtain the updated inventory quantity, and the updated result is written to the database, triggering an inventory update event. A product display template is obtained, and fields such as the product name, price, and inventory quantity are filled into the template to generate the final product display information. The product display information is transmitted to the electronic price tag, and the electronic price tag's display content is updated according to preset rules and logic to display the latest product information.

[0066] This embodiment provides a method for counting and replenishing goods. This embodiment first performs a double verification of the replenishment quantity by combining the pulse signal of the roller counting sensor and the weight signal of the weight sensor, thereby improving the accuracy of the replenishment quantity calculation. When the pulse signal is abnormal, it is automatically determined that the signal is lost, and a correction mechanism is triggered to correct the abnormality of the pulse signal based on the weight sensor data to ensure the accuracy of the replenishment quantity.

[0067] Based on Example 1, Example 2 of this application proposes a commodity replenishment counting method, referring to Figure 2 After step S20, the commodity replenishment counting method further includes: Step B10: Obtain the preset replenishment quantity.

[0068] As an optional implementation, the preset replenishment quantity is determined based on the replenishment quantity input by the replenishment personnel when triggering the replenishment start operation.

[0069] As another optional implementation, based on historical replenishment data of the target product, the average replenishment quantity in the historical replenishment data is further analyzed to determine the preset replenishment quantity.

[0070] Step B20: If the first product quantity data and the second product quantity data do not match the preset replenishment quantity, a replenishment product type error message is generated.

[0071] By comparing the first product quantity data with the preset replenishment quantity, it is determined whether the replenishment quantity meets the expectation, ensuring the accuracy of the replenishment operation. If the first product quantity data does not match the preset replenishment quantity, the second product quantity data is further compared with the preset replenishment quantity to verify the accuracy of the replenishment quantity and ensure the reliability of the replenishment operation. If both the first and second product quantity data do not match the preset replenishment quantity, a replenishment product type error message is generated to ensure the correctness of the replenishment operation.

[0072] Exemplarily, the difference between the first product quantity data and the preset replenishment quantity is calculated. If the absolute value of the difference is less than or equal to a preset determination threshold, and the first product quantity data is less than the preset replenishment quantity, then a match is determined. The difference between the second product quantity data and the preset replenishment quantity is calculated. If the absolute value of the difference is less than or equal to the preset determination threshold, and the second product quantity data is less than the preset replenishment quantity, then a match is determined.

[0073] Step B30: Render the replenishment product type error information to the corresponding electronic price tag.

[0074] The error information will be displayed on the electronic price tag in time to remind the replenishment staff to deal with it in time to ensure the correctness of the replenishment operation.

[0075] Exemplarily, the replenishment product type error information is transmitted to the electronic price tag and displayed in real time through a graphical interface.

[0076] Optionally, the replenishment commodity type error information and the corresponding shelf information are sent to the inventory management personnel. After confirmation by the inventory management personnel, the replenishment commodity type error information is sent to the corresponding replenishment personnel to remind the replenishment personnel to correct the replenishment type of the corresponding commodity.

[0077] Optionally, to determine whether the product type is correct, the scanner on the shelf can be used to scan the product label and compare it with the shelf-bound type when replenishing; or, a camera installed on the shelf can be used to identify the product packaging features through images and match them with standard images in a database; or, the built-in NFC tag of the product can be sensed at a designated location on the shelf to confirm type consistency.

[0078] This embodiment provides a commodity replenishment counting method. This embodiment first ensures the accuracy of the replenishment quantity through dual verification of a roller counting sensor and a weight sensor, promptly discovers and handles the problem of replenishment quantity mismatch, avoids errors and losses in inventory management, and displays error information in real time through electronic price tags to ensure that problems can be discovered and handled in a timely manner.

[0079] Based on Example 1, Example 3 of this application proposes a commodity replenishment counting method, referring to Figure 3 , after step S30, including: Step S50: Based on the pulse signal of the roller counting sensor, the standard deviation of the pulse interval time is calculated, the pulse stability coefficient is determined, and the coefficient is normalized to the counting dimension confidence.

[0080] The pulse stability coefficient is determined by calculating the standard deviation of the pulse interval time and normalized to the counting dimension confidence, thereby quantitatively evaluating the counting reliability of the roller counting sensor in the replenishment process.

[0081] It should be noted that the pulse interval standard deviation is the standard deviation of the time intervals between adjacent pulse signals generated by the roller counting sensor, reflecting the temporal stability of the pulse signal. The smaller the standard deviation, the more stable the pulse signal and the more reliable the counting. The pulse stability coefficient is calculated based on the pulse interval standard deviation and is used to measure the stability of the roller counting sensor's pulse signal. The counting dimension confidence is the value obtained by normalizing the pulse stability coefficient. It indicates the degree of confidence in the roller counting sensor's counting results and ranges from 0 to 1.

[0082] As an optional embodiment, when receiving the output signal of the roller counting sensor, the timestamp of each pulse signal output by the roller counting sensor is recorded. Based on the recorded timestamps, the time intervals between adjacent pulses are calculated. The standard deviation of the obtained pulse intervals is calculated using statistical methods. Based on the magnitude of the standard deviation, a pulse stability coefficient is determined using a preset mapping relationship. The pulse stability coefficient is normalized to a range of 0-1 to obtain the counting dimension confidence.

[0083] For example, the time interval between two adjacent pulse signals is calculated based on the timestamp of the collected pulse signal. The timestamp of the first pulse signal is , the timestamp of the second pulse signal is , then the pulse interval time Calculate the average of all pulse intervals , according to the formula Calculate the variance of the interpulse intervals, where n is the number of interpulse intervals, is the i-th pulse interval time, and the square root of the variance is used to obtain the standard deviation of the pulse interval time. .

[0084] Step S60: Calculate the weight average absolute difference based on the weight signal of the weight sensor, determine the weight fluctuation rate, and normalize it into the quality dimension confidence.

[0085] The mean absolute difference in weight is calculated to determine the weight fluctuation rate and normalized to the quality dimension confidence level to evaluate the stability of the weight sensor's measurement results during the replenishment process.

[0086] It should be noted that the average absolute difference in weight is the average of the absolute differences between the weight sensor measurement and the average weight value within a time window, reflecting the fluctuation in weight measurements. The weight volatility is an indicator determined based on the average absolute difference in weight, indicating the degree of fluctuation in weight sensor measurement results. The quality dimension confidence is the confidence level corresponding to the normalized weight volatility, reflecting the level of confidence in the weight sensor measurement results, ranging from 0 to 1.

[0087] As an optional implementation, the analog weight signal output by the weight sensor is converted into a digital signal. The collected digital weight signals are averaged within a preset time window to obtain an average weight value. The absolute difference between each weight measurement and the average weight value is calculated, and all absolute differences are averaged to obtain an average absolute weight difference. The weight fluctuation rate is determined based on the ratio of the average absolute difference to a preset baseline value. The weight fluctuation rate is normalized to a range of 0-1 to obtain the quality dimension confidence level.

[0088] For example, for the collected weight signal sequence , calculate the absolute difference between two adjacent weight signal values , where i = 1, 2, ..., n-1. Calculate the average of all absolute differences, that is, the weighted average absolute difference .

[0089] Step S70: establishing a two-dimensional confidence evaluation system for commodity quantity data based on the counting dimension confidence and the quality dimension confidence.

[0090] Integrating the confidence of the counting dimension and the confidence of the quality dimension to construct a two-dimensional confidence evaluation system for commodity quantity data will help to comprehensively evaluate the reliability of the two sensor data during the replenishment process.

[0091] It should be noted that the two-dimensional confidence assessment system is an assessment framework that comprehensively considers the confidence of the counting dimension and the quality dimension, and is used to comprehensively measure the reliability of commodity quantity data.

[0092] As an optional implementation, a two-dimensional coordinate system is established with the count dimension confidence as the horizontal axis and the quality dimension confidence as the vertical axis. The count and quality dimension confidence levels are marked as coordinate points. Confidence assessment rules for different regions are developed based on historical data.

[0093] Step S80, based on the two-dimensional confidence evaluation system and combined with the environmental factor correction coefficient, dynamically adjust the weight coefficient of the first commodity quantity data corresponding to the counting dimension confidence and the weight coefficient of the second commodity quantity data corresponding to the quality dimension confidence.

[0094] By combining a two-dimensional confidence assessment system and environmental factor correction coefficients, the weight coefficients of the two commodity quantity data are dynamically adjusted. Based on actual conditions, the weights of the roller counting sensor and weight sensor data in the replenishment quantity calculation are reasonably allocated to improve the accuracy of the calculation results.

[0095] It should be noted that the environmental factor correction coefficient is calculated based on the impact of environmental factors such as temperature, humidity, and electromagnetic interference on sensor data. It is used to adjust the weight of sensor data. The weight coefficient indicates the proportion of different data in the fusion calculation. The larger the weight coefficient, the greater the impact of the data on the final result.

[0096] As an optional implementation, sensors are used to monitor environmental factors in real time. Based on the monitored environmental factor values, environmental factor correction coefficients are calculated using a preset model or formula. Weight adjustment rules are developed based on the two-dimensional confidence assessment system and the environmental factor correction coefficients.

[0097] For example, if the confidence of the counting dimension is high and the environmental factors have little impact on the roller counting sensor, the weight coefficient of the first commodity quantity data is increased; if the confidence of the quality dimension is low and the environmental factors have a large impact on the weight sensor, the weight coefficient of the second commodity quantity data is reduced.

[0098] Optionally, during the replenishment process, the weight coefficient is dynamically calculated and updated in real time according to the current confidence level and environmental factor correction coefficient and in accordance with the weight adjustment rule.

[0099] Step S90: Calculate the actual quantity of goods to be replenished based on the weight coefficient of the first commodity quantity data and the weight coefficient of the second commodity quantity data.

[0100] By using the adjusted weight coefficient and integrating the first product quantity data and the second product quantity data, a more accurate calculation of the actual replenishment product quantity is obtained. By reasonably allocating weights, the advantages of the two sensor data are fully utilized to improve the accuracy of replenishment quantity calculation.

[0101] For example, a weighted average method is used to combine the two data sets based on weight coefficients. The actual product quantity is calculated as (first product quantity data × first weight coefficient + second product quantity data × second weight coefficient) / (first weight coefficient + second weight coefficient). The calculated actual product quantity is output as the final replenishment quantity.

[0102] This embodiment provides a commodity replenishment counting method. This embodiment first determines the pulse stability coefficient by calculating the standard deviation of the pulse interval time and normalizes it into the counting dimension confidence. This embodiment can accurately quantify the reliability of the roller counting sensor data. The weight fluctuation rate is determined by calculating the average absolute difference of weight and normalized into the quality dimension confidence. This embodiment can accurately evaluate the stability of the weight sensor data. Based on the two-dimensional confidence evaluation system and the environmental factor correction coefficient, the weight coefficient is dynamically adjusted to improve the accuracy of the replenishment quantity calculation.

[0103] Based on Example 1, Example 4 of this application proposes a commodity replenishment counting method, referring to Figure 4 , after step S40, including: Step S100: If there is a difference between the corrected quantity data of the first product and the preset replenishment quantity, it is determined that the replenishment product is lost.

[0104] By comparing the corrected first product quantity data with the preset replenishment quantity, when there is a difference between the two, it means that there is a deviation between the actual product quantity and the expected replenishment quantity, and there is a situation where the replenishment product is lost.

[0105] It should be noted that the loss of replenished goods occurs when the corrected first product quantity data is less than the preset replenishment quantity, which means that the actual number of goods replenished to the shelf does not reach the expected number, and there is a phenomenon of goods being lost during the replenishment process.

[0106] Step S110 , calculating the difference between the corrected first commodity quantity data and the preset replenishment quantity.

[0107] After determining that the replenishment product is lost, the difference between the corrected first product quantity data and the preset replenishment quantity is calculated to accurately quantify the quantity of the lost product.

[0108] Exemplarily, the difference amount is obtained by directly subtracting the corrected first product quantity data from the preset replenishment quantity.

[0109] Step S120 : generating replenishment product missing information based on the difference, and rendering the replenishment product missing information on a corresponding electronic price tag.

[0110] When it is determined that the replenishment product is lost, the replenishment product loss information is generated and rendered on the corresponding electronic price tag so that relevant personnel can be notified of the replenishment anomaly in a timely manner and take measures to solve the problem.

[0111] It should be noted that the missing replenishment product information includes specific details about the missing replenishment product, such as product name, product type, missing quantity, missing time, and missing shelf number. An electronic shelf tag is an electronic display device installed on a shelf that displays product information. The display content can be remotely controlled by the backend system. It uses an ink screen and is powered by a button battery. When the electronic shelf tag receives a signal, it connects to the battery and updates the information displayed on the ink screen.

[0112] Exemplarily, replenishment product loss information including the quantity and type of lost products is generated based on the difference amount, the replenishment product loss information is formatted according to the display format of the electronic price tag, the text information is converted into a data format recognizable by the electronic price tag, and the formatted replenishment product loss information is sent to the corresponding electronic price tag via wireless communication technology. The electronic price tag renders and displays the information after receiving it.

[0113] This embodiment provides a commodity replenishment counting method. This embodiment first determines the difference between the corrected first commodity quantity data and the preset replenishment quantity, thereby promptly detecting the loss of commodities during the replenishment process, calculating the specific quantity lost, and displaying it on the electronic price tag, so that the replenishment staff can immediately take corresponding remedial measures.

[0114] Based on Example 1, Example 5 of this application proposes a commodity replenishment counting method, referring to Figure 5 , before step S10, including: Step S130 , in response to the replenishment start operation triggered by the user, enter the replenishment mode of the target product.

[0115] It should be noted that the replenishment start operation is a replenishment command initiated by the user through the user interface, which may include a touch screen, buttons, or mobile device application. The replenishment mode is a system-defined operating mode for replenishment operations. In this mode, replenishment-related functions are enabled and replenishment-related data is received and processed.

[0116] As an optional implementation, a "start replenishment" button is set on the operation interface of the replenishment management system. Based on the user's click operation on the button, a replenishment start signal is triggered, and the replenishment mode is entered after receiving the replenishment start signal.

[0117] As another optional implementation, a pressure sensor or a photoelectric sensor provided in the replenishment area detects the replenishment action of placing the goods in the replenishment area, automatically triggers the replenishment start operation, and enters the replenishment mode.

[0118] Step S140: Based on the replenishment mode, the pulse signal output by the roller counting sensor is received in real time and stored in a buffer area.

[0119] The roller counting sensor records the movement of goods during the replenishment process and calculates the number of goods replenished by counting the pulse signals. Storing the pulse signals in a buffer ensures the timeliness and integrity of the data, allowing for accurate counting of replenishment quantities later.

[0120] As an optional implementation, in the replenishment mode, the output state of the roller counting sensor is polled at a set time interval, and when a change in the pulse signal is detected, the pulse count in the buffer area is updated.

[0121] Step S150: Detect the weight change of the goods on the shelf in real time through the weight sensor, and convert the weight signal into a digital signal and store it in the buffer area.

[0122] Weight changes can reflect the increase or decrease in the number of goods on the shelf. Converting the weight signal into a digital signal and storing it in the cache area can facilitate the system to monitor and verify the number of goods during the replenishment process to ensure the accuracy of the replenishment quantity.

[0123] As an optional implementation, a weight sensor is used to detect the weight changes of goods on the shelf in real time and output a weight signal. An analog-to-digital converter is used to convert the analog weight signal output by the weight sensor into a digital signal. The output value of the analog-to-digital converter is read according to the set sampling frequency, and the digital signal is stored in a cache area.

[0124] Step S160 , in response to the replenishment completion operation, exiting the replenishment mode, and stopping receiving the signals output by the roller counting sensor and the weight sensor.

[0125] After the replenishment operation is completed, stop receiving the signals output by the roller counting sensor and the weight sensor in time and exit the replenishment mode to avoid data confusion, so that the data of this replenishment process can be accurately extracted and analyzed in the future to complete the calculation of the replenishment quantity.

[0126] For example, when a replenishment completion operation is received, the mode is switched back to the normal mode from the "replenishment mode", the data acquisition channels with the roller counting sensor and the weight sensor are closed, and the reception of the signals output by the sensors is stopped.

[0127] Optionally, release system resources related to the replenishment mode, close the data processing thread opened specifically for the replenishment operation, release the buffer memory, and restore the system to normal operation to prepare for processing other tasks.

[0128] This embodiment provides a commodity replenishment counting method. This embodiment first automatically enters the replenishment mode based on the replenishment start operation. In the replenishment mode, the pulse signal and the weight signal are stored in the cache area in real time, avoiding data loss and ensuring data integrity, so as to accurately count the replenishment quantity later.

[0129] Based on Example 1, Example 6 of this application proposes a commodity replenishment counting method, referring to Figure 6 , after step S40, including: Step S170 : In response to the replenishment start operation, the type of the target product for replenishment is identified.

[0130] Identify the target product type at the start of replenishment to implement tailored data collection, processing, and analysis strategies based on the characteristics of each product type. Different product types vary in replenishment quantity statistics, weight monitoring, and other aspects. Clarifying product type improves the accuracy of replenishment data, avoids errors caused by using a unified processing method, and ensures refined inventory management.

[0131] It should be noted that the type of target product for replenishment refers to the classification of the product to be replenished in terms of shape, specifications, and packaging. It can be divided into regular product types and irregular product types. Regular products have a relatively regular shape, such as square cardboard packaging products; irregular products have an irregular shape, such as potato chips and products in odd-shaped packaging.

[0132] As an optional implementation, a barcode scanner is installed in the replenishment area, and replenishment staff scan the barcode of the target product when replenishing. The backend associates the product code with the product type information. When the product code is transmitted by the barcode scanner, the database is searched to obtain the corresponding target product type.

[0133] As another optional implementation, a camera is installed in the replenishment area to capture images of the target product in real time. The captured images are analyzed using an image recognition algorithm to extract features such as the product's shape, outline, and color. The images are then compared with a pre-stored product type feature library to identify the type of the target product.

[0134] Step S180: If the target commodity is an irregular commodity, characteristic parameters corresponding to the target commodity are obtained, and a pulse signal compensation value and a weight signal compensation value are calculated.

[0135] For irregularly shaped items, the pulse and weight signals collected by the roller counting and weight sensors during the replenishment process may exhibit significant errors due to their irregular shapes. By obtaining characteristic parameters corresponding to the target item type and calculating pulse and weight signal compensation values, the original signals are corrected to eliminate errors caused by the irregularity of the item and improve the accuracy of replenishment quantity counting and weight monitoring.

[0136] It should be noted that characteristic parameters are related to the type of irregular product and can reflect its characteristics, including the product's maximum length, minimum length, average width, height, density, surface roughness, etc. The pulse signal compensation value is used to correct the pulse signal collected by the roller counting sensor to eliminate pulse signal errors caused by the irregular shape of irregular products passing through the sensor. The weight signal compensation value is used to correct the weight signal collected by the weight sensor to eliminate the impact of the uneven weight distribution of irregular products on the sensor's measurement results.

[0137] Optionally, through experiments and data analysis, a compensation model can be established between the characteristic parameters of irregular products and the pulse signal compensation values ​​and weight signal compensation values. For the pulse signal compensation value, a nonlinear relationship between the pulse signal error and parameters such as the maximum length and surface roughness of the product can be obtained through extensive experiments. For the weight signal compensation value, a compensation value calculation model can be established based on factors such as product density and shape.

[0138] As an optional implementation, a pre-established database stores characteristic parameters for different types of irregular goods. Once the target product type is identified, the corresponding characteristic parameters are retrieved from the database. These characteristic parameters are then input into the established compensation model, which then outputs compensation values ​​for the pulse signal and the weight signal.

[0139] As another optional implementation method for obtaining characteristic parameters, for characteristic parameters that can be measured in real time during replenishment, corresponding measuring equipment is used to measure the replenished goods, a laser rangefinder is used to measure the maximum and minimum lengths of irregular goods, a densitometer is used to measure the density of goods, etc., and the measurement results are used as characteristic parameters.

[0140] Step S190 , compensating the pulse signal based on the pulse signal compensation value, and compensating the weight signal based on the weight signal compensation value.

[0141] By correcting sensor signal errors caused by the irregular characteristics of goods, subsequent operations such as inventory updates and replenishment quantity verification can be performed based on accurate data, improving the accuracy of calculated product quantities.

[0142] For example, the original pulse signal is multiplied by the calculated pulse signal compensation value to obtain a compensated pulse signal, and the number of compensated pulse signals is counted. The original weight signal is multiplied by the calculated weight signal compensation value to obtain a compensated weight signal, and the weight value corresponding to the weight signal is calculated.

[0143] Step S200: If the difference between the value after compensation and the value before compensation is greater than the compensation threshold, the vibration signal and pressure distribution of the shelf are analyzed.

[0144] If the difference is greater than the compensation threshold, it means that other factors may affect the accuracy of the sensor signal, such as abnormal shelf structure causing unstable placement of goods on the shelf, which in turn affects the sensor measurement results.

[0145] It should be noted that the compensation threshold is a pre-set numerical range used to determine whether the difference between the compensated and pre-compensated values ​​is within an acceptable range. The setting of the compensation threshold requires comprehensive consideration of factors such as the actual application scenario, sensor accuracy, and product characteristics. The vibration signal is the mechanical vibration signal generated by the shelf when it is subjected to external forces. It is collected by a vibration sensor. Abnormal shelf structure may cause changes in the frequency, amplitude, and other characteristics of the vibration signal. Pressure distribution is the distribution of pressure exerted on the shelf by the goods on the shelf on the shelf surface. It is measured by a pressure sensor array. Abnormal shelf structure may cause uneven pressure distribution or abnormal areas of concentrated pressure.

[0146] As an optional implementation, the absolute difference between the compensated pulse signal value and the pre-compensated pulse signal value, as well as the absolute difference between the compensated weight signal value and the pre-compensated weight signal value, is calculated. The relative difference between the post-compensated and pre-compensated values ​​is calculated, i.e., the absolute difference divided by the pre-compensated value. The calculated relative difference is compared with a preset compensation threshold. When the difference is greater than the compensation threshold, a vibration sensor is used to collect the shelf's vibration signal, and the vibration signal's characteristics are analyzed using signal processing techniques. A pressure distribution sensor is used to obtain a pressure distribution image on the shelf, and image processing and pattern recognition techniques are used to determine whether the pressure distribution is uniform.

[0147] Step S210: If an abnormal vibration signal or pressure distribution is detected, the shelf structure is determined to be abnormal, and manual review information is generated and displayed on the electronic price tag corresponding to the shelf.

[0148] It should be noted that shelf structure abnormality refers to damage, deformation, looseness, etc. of the shelf's supporting structure, connecting parts, shelves, etc., which affects the shelf's stability and carrying capacity, thereby affecting the sensor readings on the shelf.

[0149] As an optional implementation, an abnormality is determined when the amplitude of the vibration signal exceeds a set threshold, or when a significant pressure concentration area appears in the pressure distribution diagram and the pressure value exceeds the normal range. When an abnormal vibration signal or pressure distribution is detected, manual review information is generated based on the type of abnormality on the shelf. This information is transmitted to the corresponding electronic shelf tag, where it is displayed in real time to alert management personnel to take action.

[0150] Optionally, the generated manual review information can also be sent directly to the backend management terminal to remind management personnel to handle it.

[0151] This embodiment provides a method for counting and replenishing merchandise. It first identifies the type of replenishment target merchandise and distinguishes between regular and irregular merchandise, thus avoiding data processing errors caused by confusion between merchandise types. For irregular merchandise, characteristic parameters are obtained and pulse and weight signal compensation values ​​are calculated. The original signals are then corrected so that the pulse and weight signals more accurately reflect the actual quantity and weight of the merchandise, improving the accuracy of replenishment data. By analyzing the difference between the post-compensation and pre-compensation values, and if the difference exceeds a compensation threshold, further monitoring of the shelf's vibration signal and pressure distribution can detect structural anomalies in advance, preventing problems such as dropped or damaged merchandise caused by shelf failure.

[0152] For example, in order to help understand the implementation process of the commodity replenishment counting method obtained by combining this embodiment with the above-mentioned embodiment 6, please refer to Figure 7 , Figure 7 A brief flowchart of a product replenishment counting method is provided, specifically: When the user triggers a replenishment operation, the system enters replenishment mode for the target product. In this mode, the system first identifies the target product type. If the target product is a standard product, the system executes a standard algorithm, receiving pulse signals from the roller counting sensor in real time and storing them in a buffer. Simultaneously, the system uses a weight sensor to detect changes in the weight of the products on the shelf in real time, converting the weight signal into a digital signal and also storing it in the buffer.

[0153] If the target product is a special product of an irregular type, the system will obtain the characteristic parameters corresponding to the target product type, load the characteristic parameters, and then calculate the pulse signal compensation value and weight signal compensation value. Then, the pulse signal is compensated based on the calculated pulse signal compensation value, and the weight signal is compensated based on the weight signal compensation value.

[0154] After signal compensation is completed, the system will perform a difference detection to check the difference between the compensated value and the pre-compensation value. If the difference is less than the preset threshold, the compensated result will be directly output.

[0155] If the difference is greater than or equal to the preset compensation threshold, the system will initiate multi-dimensional verification and further perform vibration signal analysis and pressure distribution detection on the shelf.

[0156] Based on the vibration signal analysis and pressure distribution detection, it is further determined whether the shelf has structural abnormalities. If there are no structural abnormalities, the compensation coefficient is adjusted and the compensation result is recalculated.

[0157] If the shelf structure is determined to be abnormal, the manual review process is triggered, and manual review information is generated. The information is displayed on the electronic price tag corresponding to the shelf to remind the management staff to review.

[0158] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the product replenishment counting method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0159] The present application provides a product replenishment counting device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the product replenishment counting method of the above-mentioned embodiment 1.

[0160] Reference below Figure 8, which shows a schematic diagram of the structure of a product replenishment and counting device suitable for implementing embodiments of the present application. The product replenishment and counting device in embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, personal digital assistants (PDAs), tablet computers (PADs), and the like, as well as fixed terminals such as desktop computers. Figure 8 The commodity replenishment counting device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0161] like Figure 8 As shown, the product replenishment counting device may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the product replenishment counting device. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to I / O interface 1006: input device 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 1003 including, for example, a magnetic tape, hard disk, etc.; and communication device 1009. Communication device 1009 may allow the product replenishment counting device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a product replenishment counting device with various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0162] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0163] The product replenishment counting device provided in this application utilizes the product replenishment counting method described in the aforementioned embodiment, resolving the technical issue of incorrect replenishment quantity counting caused by sensor signal loss. Compared to the prior art, the product replenishment counting device provided in this application achieves the same beneficial effects as the product replenishment counting method described in the aforementioned embodiment. Other technical features of this product replenishment counting device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0164] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0165] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0166] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, wherein the computer-readable program instructions are used to execute the commodity replenishment counting method in the above embodiment.

[0167] The computer-readable storage medium provided herein may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including, but not limited to, wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0168] The computer-readable storage medium may be included in the commodity replenishment counting device; or may exist independently without being assembled into the commodity replenishment counting device.

[0169] The computer-readable storage medium carries one or more programs. When executed by the product replenishment counting device, the one or more programs enable the product replenishment counting device to write computer program code for performing the operations of the present application in one or more programming languages, or a combination thereof. The programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0170] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of 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 than that 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 and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0171] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0172] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned product replenishment counting method. This computer-readable storage medium can address the technical issue of replenishment quantity errors caused by sensor signal loss. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are similar to those of the product replenishment counting method provided in the aforementioned embodiments and are not further elaborated here.

[0173] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A commodity replenishment counting method, characterized in that: The commodity replenishment counting method includes: In response to the replenishment completion operation, a pulse signal fed back by the roller counting sensor and a weight signal fed back by the weight sensor during the replenishment process are acquired in the buffer area; Calculating replenishment length information of the target product according to the pulse signal, and determining quantity data of the first product according to the standard length information of the target product and the replenishment length information; determining replenishment weight information of the target product based on the weight signal, and determining quantity data of the second product based on the standard weight information of the target product; If the first product quantity data does not match the preset replenishment quantity, the first product quantity data is corrected based on the second product quantity data.

2. The commodity replenishment counting method according to claim 1, characterized in that: After the steps of determining the replenishment weight information of the target product based on the weight signal and determining the quantity data of the second product according to the standard weight information of the target product, the product replenishment counting method further includes: Get the preset replenishment quantity; If the first product quantity data and the second product quantity data do not match the preset replenishment quantity, a replenishment product type error message is generated; Render the replenishment product type error information to the corresponding electronic price tag.

3. The commodity replenishment counting method according to claim 1, characterized in that: The step of calculating the replenishment length information of the target product according to the pulse signal, and determining the quantity data of the first product according to the standard length information of the target product and the replenishment length information includes: Counting the pulse signal to obtain the number of pulses; Calculating the roller rotation distance based on the number of pulses and the unit pulse length corresponding to the pulse signal as replenishment length information of the target product; Based on a pre-established commodity information database, standard length information corresponding to the target commodity is obtained, and the first commodity quantity data is calculated according to a quotient of the replenishment length information and the standard length information.

4. The commodity replenishment counting method according to claim 3, characterized in that: The step of calculating the roller rotation distance based on the number of pulses and the unit pulse length corresponding to the pulse signal as the replenishment length information of the target product includes: Acquiring the operating status data of the roller counting sensor and calculating the dynamic correction coefficient of the roller rotation distance of the roller counting sensor; Based on the number of pulses, the unit pulse length, and the dynamic correction coefficient, the roller rotation distance is calculated to obtain the corresponding replenishment length information of the target product.

5. The commodity replenishment counting method according to claim 1, characterized in that: After the steps of determining the replenishment weight information of the target product based on the weight signal and determining the quantity data of the second product according to the standard weight information of the target product, the method further includes: Based on the pulse signal of the roller counting sensor, the standard deviation of the pulse interval time is calculated, the pulse stability coefficient is determined, and normalized to the counting dimension confidence; Based on the weight signal of the weight sensor, calculating the weight average absolute difference, determining the weight fluctuation rate, and normalizing it into a quality dimension confidence; Establishing a two-dimensional confidence evaluation system for commodity quantity data based on the counting dimension confidence and the quality dimension confidence; Based on the two-dimensional confidence evaluation system and in combination with the environmental factor correction coefficient, the weight coefficient of the first commodity quantity data corresponding to the counting dimension confidence and the weight coefficient of the second commodity quantity data corresponding to the quality dimension confidence are dynamically adjusted; The actual quantity of the replenished goods is calculated based on the weight coefficient of the first commodity quantity data and the weight coefficient of the second commodity quantity data.

6. The commodity replenishment counting method according to claim 1, characterized in that: After the step of correcting the first product quantity data based on the second product quantity data if the first product quantity data does not match the preset replenishment quantity, the method further includes: If there is a discrepancy between the corrected quantity data of the first product and the preset replenishment quantity, it is determined that the replenishment product is lost; Calculating the difference between the corrected quantity data of the first product and the preset replenishment quantity; Generate replenishment commodity missing information based on the difference, and render the replenishment commodity missing information on the corresponding electronic price tag.

7. The commodity replenishment counting method according to claim 1, characterized in that: Before the step of acquiring, in the buffer area, the pulse signal fed back by the roller counting sensor and the weight signal fed back by the weight sensor during the replenishment process in response to the replenishment completion operation, the method includes: In response to a user-triggered replenishment start operation, entering a replenishment mode for the target product; Based on the replenishment mode, the pulse signal output by the roller counting sensor is received in real time and stored in a buffer area; The weight sensor detects the weight change of the goods on the shelf in real time, and converts the weight signal into a digital signal and stores it in the buffer area. In response to the replenishment completion operation, the replenishment mode is exited, and the reception of the signals output by the roller counting sensor and the weight sensor is stopped.

8. The commodity replenishment counting method according to claim 1, wherein: Before the step of acquiring, in the buffer area, a pulse signal fed back by the roller counting sensor and a weight signal fed back by the weight sensor during the replenishment process in response to the replenishment completion operation, the commodity replenishment counting method further comprises: In response to a replenishment start operation, identifying a type of target commodity for replenishment; If the target commodity is an irregular commodity, obtaining characteristic parameters corresponding to the target commodity type and calculating a pulse signal compensation value and a weight signal compensation value; compensating the pulse signal based on the pulse signal compensation value, and compensating the weight signal based on the weight signal compensation value; If the difference between the value after compensation and the value before compensation is greater than the compensation threshold, the vibration signal and pressure distribution of the shelf are analyzed; If an abnormal vibration signal or pressure distribution is detected, the shelf structure is determined to be abnormal, and manual review information is generated and displayed on the electronic price tag corresponding to the shelf.

9. A commodity replenishment counting device, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the commodity replenishment counting method according to any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the commodity replenishment counting method according to any one of claims 1 to 8 are implemented.

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