Electronic price tag positioning feedback early warning method and system

Abstract

The invention relates to the field of electronic price tag management, in particular to an electronic price tag positioning feedback early warning method and system. According to the method, multi-modal sensor data is acquired and transmitted to a data processing module, and real-time data analysis and environment perception are carried out; an image recognition and sensor data fusion technology is utilized to accurately calculate the position of the electronic price tag and generate positioning feedback information; performing anomaly detection according to the feedback information, judging whether display deviation exists or not, and generating an early warning signal; calculating an optimal adjustment strategy by using an intelligent decision algorithm, generating an adjustment command, and guiding a merchant to carry out adjustment operation; the adjustment strategy and real-time monitoring data are uploaded to a cloud platform, data synchronization and centralized management are carried out, and cross-platform remote monitoring and optimization are supported. Through the technical scheme of the invention, the position of the electronic price tag can be monitored and accurately adjusted in real time, the accuracy of the display content is ensured, the management efficiency of the electronic price tag and the customer experience are improved, the manual intervention is reduced, and the commercial tenant operation is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic price tag management, and particularly to an electronic price tag positioning feedback warning method and system. Background Art

[0002] With the development of intelligent retail, electronic price tags have become widely used commodity information display tools in retail environments such as shopping malls and supermarkets. Electronic price tags can update product prices, promotional information and other content in real time, improving the efficiency and accuracy of information display. However, in a complex retail environment, the accurate display of electronic price tags faces many challenges. Electronic price tags may shift in position due to factors such as changes in shelves, ambient light, and viewing angle changes, resulting in inaccurate display content or inconsistency with the actual product, which has a negative impact on the customer shopping experience and merchant management.

[0003] Currently, existing electronic price tag management systems usually rely on manual inspections or simple positioning technologies, and cannot detect and correct the position and display content of electronic price tags in real time and accurately. In some cases, merchants can only make manual adjustments after discovering display errors, which not only wastes human resources, but may also lead to incorrect display of product information for a long time, affecting sales and customer satisfaction. Therefore, how to achieve automatic positioning, real-time feedback and intelligent adjustment of electronic price tags has become an important technical problem in retail management.

[0004] To address this challenge, some electronic price tag positioning methods based on image recognition or sensor technology have been proposed in the prior art, but these methods have problems such as insufficient accuracy and response delay in a dynamic and complex environment. How to accurately locate electronic price tags in real time and give early warnings based on multi-modal data (such as image data and sensor data) in a complex retail environment is a major problem in the current technology.

[0005] Based on this background, the present invention proposes an innovative electronic price tag positioning feedback warning method and system, which solves the problems of real-time positioning, display accuracy and automatic adjustment of electronic price tags by combining image recognition, sensor data fusion and intelligent decision-making algorithms. Summary of the Invention

[0006] The present invention provides an electronic price tag positioning feedback warning method and system to solve the problem of how to locate the position of an electronic price tag in real time based on multi-modal data in a complex retail environment, give feedback warnings, ensure accurate display of the electronic price tag and timely adjustment, and avoid display errors and position deviations.

[0007] To solve the above technical problems, the present invention provides an electronic price tag positioning feedback warning method, including: Obtain multi-modal sensor data and transmit the data to the data processing module for preliminary data analysis and provide real-time environmental perception; Utilize image recognition and sensor data fusion technology to accurately calculate the position of the electronic price tag and generate positioning feedback information; Conduct anomaly detection based on the positioning feedback information, determine whether there is a display deviation of the electronic price tag, and generate a warning signal through a preset threshold; Use an intelligent decision-making algorithm to calculate the optimal adjustment strategy according to the warning signal and feedback information, generate an adjustment command, and guide the merchant to execute the adjustment operation; Upload the adjustment strategy and real-time monitoring data to the cloud platform for data synchronization and centralized management, supporting cross-platform remote monitoring and optimization.

[0008] Further, the step of obtaining multi-modal sensor data includes: Collect image data of the location where the electronic price tag is located through a camera; Obtain data such as the position information of the electronic price tag, environmental temperature and humidity, and light intensity through sensor devices; Synchronously transmit the image data and sensor data to the data processing module for subsequent processing.

[0009] Further, the step of calculating the position of the electronic price tag by using image recognition and sensor data fusion technology specifically includes: Analyze the image data through an image recognition algorithm to identify the preliminary position and posture of the electronic price tag; Optimize based on the sensor data to further correct the actual position of the electronic price tag and obtain the final positioning result.

[0010] Further, the step of calculating the positioning result based on image recognition and sensor data fusion technology includes: Perform weighted fusion on the preliminary position coordinates of the electronic price tag obtained by image recognition and the position information in the sensor data to obtain the corrected accurate position.

[0011] Further, the step of conducting anomaly detection based on the positioning feedback information includes: Compare the positioning feedback information with the preset standard position, and calculate the deviation value between the actual position and the standard position of the electronic price tag; Judge whether the deviation value exceeds the preset threshold. If it exceeds the threshold, trigger a warning signal.

[0012] Further, the step of judging whether the deviation value exceeds the preset threshold further includes: If the deviation value exceeds the threshold, generate a warning signal and transmit the signal to the decision-making module for further calculation of the adjustment strategy.

[0013] Further, the steps of calculating the optimal adjustment strategy using the intelligent decision-making algorithm include: Based on the warning signal and feedback information, combined with the actual position and target position of the electronic price tag, calculate the optimal adjustment path and adjustment amount; Generate an adjustment command to guide the merchant to adjust the electronic price tag.

[0014] Further, the steps of uploading the adjustment strategy and real-time monitoring data to the cloud platform include: Upload the adjustment strategy and the real-time status data of the electronic price tag to the cloud computing platform for data storage and processing; Through the cloud platform, synchronously manage the electronic price tags of multiple stores to achieve cross-platform remote monitoring and optimization.

[0015] Further, the steps of real-time synchronizing the electronic price tag data of multiple stores through the cloud platform include: Upload the electronic price tag data of each store to the cloud platform for unified storage and synchronization to ensure that the status of the electronic price tags of each store is consistent and support remote adjustment and management.

[0016] Further, an electronic price tag positioning feedback warning system, the system includes: A data acquisition module, used to obtain real-time data related to the electronic price tag from multiple data sources, including collecting image data and environmental data through cameras and sensor devices installed in the store environment; A data processing module, used to perform preliminary processing on the collected data, including operations such as data cleaning, denoising, missing value filling, and format standardization; A positioning calculation and feedback module, used to use image recognition algorithms and sensor data fusion technology to perform real-time positioning calculation of the electronic price tag and generate positioning feedback information; An anomaly detection and warning module, used to compare the positioning feedback information with a preset standard position, detect the deviation between the actual position and the standard position of the electronic price tag, and generate a warning signal when the deviation exceeds a preset threshold; A decision-making and adjustment strategy module, used to calculate the adjustment strategy of the electronic price tag using an intelligent decision-making algorithm based on the warning signal and feedback information, and generate an adjustment command to guide the merchant or an automatic device to adjust the position of the electronic price tag; A cloud platform and data management module, used to upload the adjustment strategy and real-time monitoring data to the cloud platform for cross-platform data synchronization and centralized management, and support remote monitoring and optimization; User Interaction and Visualization Module, which is used to provide an intuitive user interface, display the positioning feedback, warning information and adjustment suggestions of the system, and support interactive operations; System Monitoring and Adaptive Optimization Module, which is used to continuously monitor the running state of the system and automatically optimize the system parameters according to the feedback information.

[0017] The key innovations of the present invention include: (1) Multi-modal data fusion: By combining the fusion technology of image recognition and sensor data, precise positioning of electronic price tags is achieved, solving the problem of insufficient accuracy of single-sensor technology.

[0018] (2) Real-time positioning and feedback warning: By combining image recognition algorithms and sensor data, the position of the electronic price tag can be calculated in real time and feedback information can be generated. By comparing the standard position with the actual position, the system can automatically trigger the warning mechanism to ensure the accuracy of the display content of the electronic price tag.

[0019] (3) Intelligent decision-making and automatic adjustment strategy: Using intelligent decision-making algorithms, the optimal adjustment strategy is calculated based on real-time positioning and feedback information, and adjustment commands are automatically generated to guide merchants or devices to make precise adjustments.

[0020] The following are its main beneficial effects: The electronic price tag positioning feedback warning method provided by the present invention, by combining multi-modal sensor data and image recognition technology, accurately calculates the real-time position of the electronic price tag and conducts feedback and warning, greatly improving the intelligent level of electronic price tag management. Compared with traditional manual inspection or simple positioning technology, the present invention avoids the delay and errors of manual intervention through automatic positioning and anomaly detection, and can timely detect and automatically generate adjustment commands when the electronic price tag deviates. Especially through the centralized management and remote monitoring functions of the cloud platform, the electronic price tags of multiple stores can be synchronized and optimized in real time, significantly improving the operation efficiency and reducing the operation cost. Compared with traditional methods, the present invention effectively reduces the display errors caused by the position deviation of electronic price tags, optimizes the customer experience, and improves the operation benefits of merchants. Brief Description of the Drawings

[0021] Figure 1 It is a schematic flowchart of an electronic price tag positioning feedback warning method provided by an embodiment of the present application; Figure 2 It is a structural block diagram of an electronic price tag positioning feedback warning system provided by an embodiment of the present application. Detailed Embodiments

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification, claims and drawings of this application are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification, claims or drawings of this application are used to distinguish different objects and not to describe a specific order.

[0023] Reference to "embodiments" herein means that the specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0024] Embodiment 1: Refer to Figure 1 , which is a schematic flowchart of an electronic price tag positioning feedback and warning method provided by an embodiment of the present invention. This process can at least include steps S100 - S500: S100. Obtain multi-modal sensor data and transmit it to the data processing module for preliminary data analysis to provide real-time environmental perception.

[0025] S200. Use image recognition and sensor data fusion technology to accurately calculate the position of the electronic price tag and generate positioning feedback information.

[0026] S300. Perform anomaly detection based on the positioning feedback information, determine whether there is a display deviation, and generate a warning signal through a preset threshold.

[0027] S400. Use an intelligent decision-making algorithm to calculate the optimal adjustment strategy based on the warning signal and feedback information, generate an adjustment command, and guide the merchant to perform adjustment operations.

[0028] S500. Upload the adjustment strategy and real-time monitoring data to the cloud platform for data synchronization and centralized management to support cross-platform remote monitoring and optimization.

[0029] Step S100 at least includes steps S110 - S130: S110. Collect real-time images through a camera installed in the store environment, obtain image information of the location where the electronic price tag is located, and transmit the image data to the data processing module for analysis.

[0030] In a store environment, cameras regularly collect real-time image data containing the location of electronic price tags according to preset positions and angles. Specifically, cameras installed at positions such as on product shelves and in display areas capture area images containing electronic price tags. The image data includes information such as the display content, position, and attitude of the electronic price tags, and the captured image data can be further analyzed through image recognition algorithms. During this process, the image data is transmitted from the camera system to the data processing module.

[0031] The image data is transmitted to the data processing module via a network. After receiving the image data, the data processing module performs preliminary image preprocessing, such as denoising and enhancing contrast, to ensure that the image quality is suitable for subsequent positioning calculations. The preprocessed image data will be used as the input data for subsequent positioning calculations.

[0032] Data processing: By using image processing techniques such as color, texture, and edge recognition on the image, the position features of the electronic price tags in the image are extracted to obtain the spatial positions of the electronic price tags in the image. This step will obtain position coordinate parameters (for example, x i , y i ) for use in positioning calculations in subsequent steps. After the transmission and processing of the image data are completed, the results will be passed to the next step (S120) to continue with multi-modal data fusion and processing.

[0033] S120. Obtain data such as the location information of the electronic price tag, environmental temperature, humidity, and light intensity through RFID and Bluetooth sensor devices, and transmit the sensor data to the data processing module for further processing.

[0034] Obtain sensor data: Through RFID and Bluetooth sensor devices, obtain data such as the location information of the electronic price tag, environmental temperature, humidity, and light intensity in real time. Specifically, through RFID sensors installed in the store environment, obtain the precise location information of the electronic price tag, such as position coordinates (x rfid , y rfid ). At the same time, Bluetooth sensors provide the specific location information of the electronic price tag in the store (x b t, y b t). These sensor data can effectively supplement the location information that may be missing in the camera data. Especially in complex environments, the positioning accuracy can be improved through multi-modal data fusion.

[0035] Obtain environmental data: Through sensor devices (such as temperature and humidity sensors, light intensity sensors), obtain environmental data related to the electronic price tag (such as temperature T, humidity H, light intensity L). These environmental data have a certain impact on subsequent positioning accuracy adjustment and the functional stability of the electronic price tag.

[0036] Data transmission: The RFID, Bluetooth sensors, and environmental data are transmitted to the data processing module in real time. In the data processing module, the sensor data will be formatted, cleaned, and time-synchronized with the aforementioned image data to ensure that all data can work together during subsequent positioning calculations to ensure positioning accuracy.

[0037] S130: Transmit the image data and sensor data obtained through S110 and S120 to the data processing module for preliminary data cleaning and merging, preparing for subsequent positioning calculations and feedback processing.

[0038] In the S110 module, the image data collected by the camera and the sensor data (RFID, Bluetooth, and environmental data) obtained by the S120 module will be transmitted to the data processing module. Specifically, the data processing module first preprocesses the data from different sources, removes noise and redundant information, and unifies the formats. Operations such as formatting of image data and calibration of sensor data are all to ensure the accuracy of subsequent data fusion.

[0039] Furthermore, the data processing module performs time synchronization processing. By aligning the timestamps of each acquisition device (such as the image acquisition timestamp and the sensor data timestamp), it ensures the consistency of the timeliness of the image data and the sensor data, avoiding positioning deviations caused by time errors.

[0040] After removing outliers through data cleaning, the image data and the sensor data are fused. Specifically, the position information in the sensor data is used to correct the positioning in the image data, and the environmental information (such as temperature, humidity, light intensity, etc.) is used to compensate the image data to improve the positioning accuracy. Finally, the data after cleaning and fusion forms a comprehensive multi-modal dataset, providing sufficient input for subsequent positioning calculations and feedback processing.

[0041] After the above steps, the data processing module will output a set of cleaned and fused positioning data (such as x combined , y combined ) as the input to the S200 module. These data will be used for subsequent positioning calculations (S210, S220) and anomaly detection to ensure that the position of the electronic price tag is accurately calculated and monitored.

[0042] Connection note: The image data obtained in the S110 step and the sensor data obtained in the S120 step will be merged through S130. The image data provides the approximate position of the electronic price tag in S110, while the sensor data (such as RFID, Bluetooth, etc.) provides more accurate positioning information. The combination of the two ensures the complementarity and accuracy of the data.

[0043] The fused data output in step S130 (such as x combined , y combined ) will be the input for the image recognition algorithm and sensor data fusion technology in S200, and will be further used to accurately calculate the position of the electronic price tag.

[0044] The data fusion processing in this part is based on the image data, sensor data and their timestamp synchronization results obtained in the previous steps, ensuring that the subsequent positioning calculation (S200) is not affected by data conflicts and errors.

[0045] Step S200 at least includes steps S210 - S230: S210. Analyze the image data transmitted by the S100 module through the image recognition algorithm, identify the specific position and posture of the electronic price tag, and obtain the accurate position coordinates of the electronic price tag in the store environment.

[0046] Based on the image data transmitted by the S100 module, first preprocess the image, including denoising, enhancing contrast, filtering, etc., to ensure that the quality of the image is suitable for positioning calculation. Specifically, use an edge detection algorithm (such as Canny edge detection) to extract the edge features of the electronic price tag in the image, and compare them with a known template through feature point matching technology to identify the boundary of the electronic price tag.

[0047] After extracting the edge features of the electronic price tag, calculate the posture of the electronic price tag relative to the camera view through feature matching and perspective transformation algorithms. Specifically, use the PnP (Perspective-n-Point) algorithm, combined with the camera internal parameters and external parameters, to calculate the three-dimensional position coordinates (x img , y img , z img ) of the electronic price tag, that is, the position of the electronic price tag in the store environment. This position coordinate is calculated based on the image data and is used for subsequent precise positioning by fusing sensor data.

[0048] After obtaining the three-dimensional coordinates of the electronic price tag, generate positioning feedback information (such as (x img , y img , z img ). These information will be transmitted to the S220 module, and will be further fused with sensor data to correct the possible errors in the image recognition process to improve the positioning accuracy.

[0049] S220. Based on the sensor data transmitted by the S120 module, use the positioning algorithm to further optimize the positioning information of the electronic price tag and correct the positioning deviation caused by environmental interference or errors.

[0050] The sensor data obtained from the S120 module includes RFID positioning data, Bluetooth positioning data, and environmental data (such as temperature and humidity, light intensity, etc.). These sensor data provide position correction information for the electronic price tag. Specifically, based on the RFID positioning algorithm, the rough position coordinates of the electronic price tag can be corrected by distance measurement to obtain the precise position (x rfid ,y rfid ), and the Bluetooth positioning algorithm further improves the positioning accuracy through the triangulation method to obtain more precise position coordinates (x b t,y b t).

[0051] After obtaining the image position (x img ,y img ,z img ) and the sensor position (x rfid ,y rfid ), the weighted average fusion technology is used to fuse these data. Specifically, by setting the weight coefficients (such as w img and w rfid ), the image positioning data and the sensor data are corrected by weighted average: (x fused ,y fused ,z fused )=w img ×(x img ,y img ,z img )+w rfid ×(x rfid ,y rfid ), where w img and w rfid are the weight coefficients, representing the relative reliability of the image data and the sensor data respectively, and x fused ,y fused ,z fused are the position coordinates of the electronic price tag after the final fusion.

[0052] After the fusion of the sensor data and the image data, the final corrected position of the electronic price tag (x fused ,y fused ) is obtained, and this position coordinate will be used as the input of the S230 module to further generate real-time positioning feedback information.

[0053] S230. According to the image recognition and sensor data fusion results of S210 and S220, generate real-time positioning feedback information for the electronic price tag, and transmit this information to the warning module for further processing.

[0054] Based on the results of S210 and S220, the positioning coordinates (x fused , y fused ) after fusing image recognition and sensor data are used as the real-time position feedback information of the electronic price tag. This feedback information includes the current position coordinates, attitude information, and possible error range of the electronic price tag. Specifically, in combination with the real-time monitored environmental data (such as temperature, humidity, light, etc.), the error range is calculated and marked to generate positioning feedback data with error tolerance.

[0055] Format the generated positioning feedback information to ensure that it meets the data format requirements received by the warning module. Specifically, pack and encode the feedback information (such as (x fused , y fused , z fused ), error range, etc.) into a specific format and transmit it to the warning module through the data transmission protocol. This data will be used as the basis for subsequent judgment of whether there is a display deviation.

[0056] Through the data transmission system, transmit the positioning feedback information to the warning module of the S300 module. This module will perform further anomaly detection and warning generation based on the real-time position of the electronic price tag and the deviation threshold to ensure the position and display accuracy of the electronic price tag.

[0057] Connection description: The preliminary position (x img , y img , z img ) of the electronic price tag calculated by image recognition in the S210 module is optimized and corrected through sensor data in the S220 module to obtain the final position (x fused , y fused ) of the electronic price tag and transmit it to the S230 module.

[0058] In the S230 module, the final positioning feedback information (including the position, attitude, and error range of the electronic price tag) will be passed as input to the S300 module for subsequent warning signal generation.

[0059] Step S300 at least includes steps S310 - S330: S310. Based on the positioning feedback information generated by the S200 module, compare it with the preset standard position to detect the deviation between the actual position and the standard position of the electronic price tag.

[0060] In this implementation process, the standard position refers to the predetermined or target position of the electronic price tag in the store environment. This standard position can be determined by factors such as store layout, store location, shelves, etc., and is set through data such as environmental information and installation information of the electronic price tag in the S100 module. Specifically, the standard position is a set of coordinates (x 0 , y 0, z 0 ), indicating the target position of the electronic price tag in the store.

[0061] In the S200 module, after image recognition and sensor data fusion, the actual position coordinates (x fused , y fused , z fused ) of the electronic price tag are obtained, which is the real-time positioning information of the electronic price tag in the store. Specifically, using the Euclidean distance formula, calculate the deviation between the standard position (x 0 , y 0 , z 0 ) and the actual position (x fused , y fused , z fused ): , where D represents the Euclidean distance deviation between the actual position and the standard position of the electronic price tag. This deviation value D will be used as the basis for subsequent judgment of whether there is a display deviation.

[0062] The deviation D obtained through the above calculation will be used as the input information for detecting the display deviation of the electronic price tag and transmitted to the S320 module for deviation range judgment. If D is less than the predetermined threshold, it means that the display position is within the tolerance range; otherwise, enter the abnormal detection process.

[0063] S320, by setting a deviation threshold, judges whether the display position of the electronic price tag exceeds the allowable range. If the deviation exceeds the threshold, trigger the warning mechanism.

[0064] In the S320 module, a predetermined deviation threshold T is set to determine whether the display position of the electronic price tag is within the allowable range. This threshold T is an adjustable parameter in actual applications and is usually set according to the store environment and the size of the electronic price tag. Specifically, T can be set to a certain value, such as 10 cm, 20 cm, etc., or adjusted dynamically according to environmental conditions.

[0065] Compare the deviation D calculated according to S310 with the set deviation threshold T. If D > T, it means that the position of the electronic price tag exceeds the allowable range and the warning mechanism needs to be triggered. At this time, there is a deviation in the display of the electronic price tag, which may affect the shopping experience of consumers and needs to be adjusted.

[0066] If the deviation D exceeds the set threshold T, generate a deviation alarm and transmit this information as an input to the S330 module to further generate a warning signal.

[0067] S330. If it is detected that the display position of the electronic price tag deviates and exceeds the threshold, a warning signal is generated and transmitted to the decision-making module for subsequent adjustment strategy formulation.

[0068] After the S320 module determines that the position deviation of the electronic price tag exceeds the threshold T, the system will automatically trigger a warning mechanism to generate a warning signal. The warning signal usually includes the position deviation information of the electronic price tag, the deviation value D, a reminder of exceeding the threshold, etc. Specifically, the warning signal can adopt a standard format, such as: Alert Signal={D,T,Status=Out of Range}, where D represents the deviation value, T is the threshold, and the Status field is the warning status (such as "out of range").

[0069] The generated warning signal will be transmitted to the decision-making module of the S400 module. The decision-making module will formulate an appropriate adjustment strategy based on the position deviation information, deviation value, etc. contained in the warning signal. This signal provides necessary information support for subsequent adjustment operations.

[0070] The warning signal generated by the S330 module not only alerts the system administrator or merchant that the electronic price tag has a position deviation but also provides a basis for subsequent adjustment operations. The decision-making module will formulate an adjustment plan based on this information to guide the merchant to take appropriate measures to restore the normal display of the electronic price tag.

[0071] Connection description: The actual position deviation D calculated in S310 will be compared with the deviation threshold T in the S320 module to determine whether it exceeds the allowable range.

[0072] If the deviation exceeds the threshold, a warning signal is generated in S320 and transmitted to the S330 module for decision support. The S330 module then generates the final warning signal and transmits it to the subsequent decision-making module to provide a basis for the adjustment strategy.

[0073] Step S400 at least includes steps S410 - S430: S410. Receive the generated warning signal from the S300 module and analyze it based on the feedback information to determine whether the electronic price tag needs to be adjusted.

[0074] Warning signal reception and analysis: The warning signal received by the system from the S300 module contains the following information: Deviation value D: The Euclidean distance between the electronic price tag and the standard position, , Threshold T: The tolerance range of the display position.

[0075] Status flag S status: Such as "out of range" or "normal".

[0076] According to the deviation value D in the received warning signal, the system compares this value with the deviation threshold T. Specifically, if the following condition is met: D > T, it indicates that the display position of the electronic price tag deviates from the standard position and adjustment operations are required. Otherwise, the display position is normal, no adjustment is needed, and the operation of this module ends.

[0077] Adjustment type identification: If it is determined that adjustment operations are required, the system further identifies the type of adjustment to be performed based on the deviation value D and the direction data of the electronic price tag, including horizontal movement, vertical movement, or angular rotation adjustment. This information will be used as the input for generating the adjustment strategy in the next module (S420).

[0078] S420. Based on the received warning signal and feedback information, use an intelligent decision-making algorithm to calculate the optimal adjustment strategy for the electronic price tag.

[0079] According to the deviation data in the warning signal, the system selects an applicable adjustment decision model based on historical adjustment records and environmental information. This model can include a multi-objective optimization model or a weighted least squares model.

[0080] The system calculates the optimal adjustment path of the electronic price tag based on the optimal path algorithm (such as the A algorithm or Dijkstra algorithm), combined with environmental data and shelf position data. The adjustment strategy calculation formula is as follows: Δx = x 0 - x fused , Δy = y 0 - y fused , Δθ = θ 0 - θ fused , where, Δx and Δy represent the horizontal and vertical position adjustment amounts of the electronic price tag; Δθ represents the angular rotation adjustment amount, calculating the difference between the rotation angle of the electronic price tag in the current display and the standard direction.

[0081] The system further considers environmental information (such as temperature and humidity, light intensity, etc.) to correct the above adjustment amounts. The specific formula is as follows: Δx adj = w env ×Δx, Δy adj = w env ×Δy, where, w env is the environmental correction coefficient, indicating the impact of environmental data on the adjustment strategy. The corrected adjustment amounts Δx adj, Δy adj will be used as the input data for the final adjustment command.

[0082] S430. Generate an adjustment command for the electronic price tag according to the calculated adjustment strategy to guide the merchant to perform the adjustment operation of the electronic price tag to restore normal display.

[0083] According to the adjustment strategy calculated in the S420 module, the system converts it into a standardized adjustment command format, as shown in the following example: Adjust_Cmd={Δx adj ,Δy adj ,Δθ,Timestamp,Priority}, where, Δx adj and Δy adj represent the horizontal and vertical adjustment amounts; Δθ represents the rotation adjustment angle; Timestamp represents the timestamp when the command is generated; Priority represents the priority of the adjustment command, and the higher the value, the higher the priority for processing.

[0084] Send the standardized adjustment command to the execution terminal or the merchant management terminal through the wireless communication protocol. If the store uses an automatic adjustment device (such as a smart robotic arm or an automatic shelf management system), the adjustment command will directly drive the device to complete the positioning adjustment operation of the electronic price tag.

[0085] After the adjustment operation is completed, the system will automatically perform a confirmation detection to ensure that the position and display content of the electronic price tag are consistent with the standard position. The confirmation signal will be sent to the cloud platform for recording and analysis to support the optimization of future adjustment strategies.

[0086] Connection description: In S410, the system determines whether the electronic price tag needs to be adjusted according to the warning signal generated by S300.

[0087] If adjustment is required, enter S420, and the system calculates the optimal adjustment strategy based on the optimal path algorithm and the multi-objective optimization model.

[0088] In S430, the system generates a standardized adjustment command according to the adjustment strategy and sends it to the execution terminal to guide the merchant to perform the adjustment operation.

[0089] Step S500 includes at least steps S510 - S530: S510. Upload the adjustment strategy generated by the S400 module and the real-time monitoring data of the electronic price tag to the cloud computing platform.

[0090] In S400, the system generates an adjustment strategy for the electronic price tag through the intelligent decision-making algorithm, including the horizontal adjustment amount Δx adj , the vertical adjustment amount Δy adj and the rotation adjustment angle Δθ, etc.

[0091] These adjustment strategies will be uploaded to the cloud computing platform through an encryption protocol, and the specific operations are as follows: Package the adjustment strategies of each store with metadata such as the corresponding store ID, device ID, timestamp, and priority to form an adjustment data packet.

[0092] The uploaded data packet contains Δx adj , Δy adj , Δθ, Timestamp, Priority, and ensure the security and integrity of the data transmission process through an encryption algorithm.

[0093] At the same time, the real-time monitoring data of the electronic price tags (including the current display position, status information, environmental monitoring data, etc.) of the electronic price tags will be synchronously uploaded to the cloud platform. This data usually includes the following content: The current coordinates (x current , y current , z current ) of the electronic price tag, and the current display status S current (such as whether the display is correct).

[0094] Environmental data, such as sensor data of temperature, humidity, light intensity, etc.: T current , H current , I current (temperature, humidity, light intensity), During the data upload process, the data is preliminarily processed by the edge computing node to reduce the burden on the cloud platform.

[0095] S520. Through the cloud platform, the electronic price tag data of multiple stores is synchronously updated in real time to provide remote monitoring functions for stores in different regions.

[0096] After the cloud platform receives the electronic price tag data uploaded by different stores, it will perform real-time synchronization of the data through asynchronous synchronization technology (such as a push mechanism based on a message queue). Specifically: The cloud platform integrates the electronic price tag positions, status information, and environmental data of different stores to ensure that the display status of each store is updated in real time.

[0097] Based on data structuring technology (such as JSON or Protobuf format), the electronic price tag data from each store is sorted and stored, and synchronously updated to the cloud database to ensure the real-time and consistency of the data.

[0098] The cloud platform pushes the processed store data to the merchant management terminal, and the merchant can perform remote monitoring through a unified management interface. The electronic price tag information (such as display content, location information) and environmental data (temperature, humidity, light intensity, etc.) of each store can be presented in real time on the management terminal interface.

[0099] Administrators can conduct real-time monitoring of stores in different regions, check whether there are deviations in electronic price tags, and take adjustment measures in a timely manner.

[0100] In addition, based on real-time data, administrators can directly view the adjustment records and real-time status of each store through the cloud platform, supporting remote scheduling and adjustment.

[0101] Based on the real-time data uploaded by stores, the cloud platform can provide a real-time notification function. If there are deviations or abnormal status in the electronic price tags of a certain store, the cloud platform can immediately send a notification reminder to the management personnel to help them make timely responses.

[0102] S530. Based on the centralized management and optimization functions provided by the cloud computing platform, it provides real-time electronic price tag adjustment suggestions for the store operation team and supports cross-platform data processing and analysis.

[0103] The cloud platform has a centralized management function, which can aggregate real-time data from different stores and provide a comprehensive analysis report for the store operation team through data analysis algorithms. Specifically, through real-time monitoring and data analysis, the cloud platform judges the following content: The display accuracy and display status of the electronic price tags in each store; The influence of environmental data (such as light intensity, temperature and humidity, etc.) in each store on the performance of electronic price tags; The rules and time periods of deviation occurrence to help the operation team identify potential adjustment needs.

[0104] Based on the analysis results, the cloud platform can automatically generate real-time adjustment suggestions. For example, if the deviation value of the electronic price tag of a certain store exceeds the preset tolerance range, the system will provide specific adjustment suggestions according to the adjustment strategy model, including: Adjust the position of the electronic price tag (Δx adj , Δy adj ); Adjust the display angle (Δθ); Provide corresponding adjustment suggestions according to environmental factors.

[0105] These suggestions will be displayed to the operation team through the user interface of the cloud platform for easy decision-making and execution.

[0106] The cloud platform also supports cross-platform data processing and analysis. The operation team can access cloud data through multiple platforms such as the PC side and the mobile side. The platform will conduct in-depth analysis based on big data analysis technologies (such as data mining, prediction models) to provide future adjustment trend predictions and help the operation team make preventive adjustment plans.

[0107] The cloud platform can combine historical data with real-time data to predict which stores' electronic price tags may have display deviations and remind the operation team in advance to avoid potential problems.

[0108] The cloud platform can also continuously optimize the adjustment strategy of electronic price tags based on the data feedback from each store. Through iterative cycles, the platform can adjust the strategy parameters according to the actual effects and gradually improve the accuracy and effectiveness of the adjustment strategy.

[0109] Connection description: In S510, the adjustment strategy and real-time monitoring data are uploaded to the cloud computing platform for subsequent cross-platform synchronization and centralized management.

[0110] Module S520 uses the cloud platform to achieve the real-time data synchronization function of multiple stores, enabling stores to conduct remote monitoring across regions.

[0111] Finally, in module S530, the cloud platform provides functions of centralized management, data analysis, and real-time adjustment suggestions to ensure that stores can respond in a timely manner and optimize the display and position of electronic price tags.

[0112] The key innovation points of the present invention include: (1) Multi-modal data fusion: By combining the fusion technology of image recognition and sensor data, precise positioning of electronic price tags is achieved, solving the problem of insufficient accuracy of single sensor technology.

[0113] (2) Real-time positioning and feedback warning: Combining image recognition algorithms and sensor data, the position of the electronic price tag can be calculated in real time and feedback information can be generated. By comparing the standard position with the actual position, the system can automatically trigger the warning mechanism to ensure the accuracy of the display content of the electronic price tag.

[0114] (3) Intelligent decision-making and automatic adjustment strategy: Using intelligent decision-making algorithms, the optimal adjustment strategy is calculated based on real-time positioning and feedback information, and adjustment commands are automatically generated to guide merchants or devices to make precise adjustments.

[0115] The following are its main beneficial effects: The electronic price tag positioning feedback and warning method provided by the present invention combines multi-modal sensor data and image recognition technology to accurately calculate the real-time position of the electronic price tag and perform feedback and warning, greatly improving the intelligent level of electronic price tag management. Compared with traditional manual inspections or simple positioning technologies, the present invention avoids the delays and errors of manual intervention through automated positioning and anomaly detection, and can detect in a timely manner when the electronic price tag deviates and automatically generate adjustment commands. In particular, through the centralized management and remote monitoring functions of the cloud platform, the electronic price tags of multiple stores can be synchronized and optimized in real time, significantly improving the operation efficiency and reducing the operation cost. Compared with traditional methods, the present invention effectively reduces the display errors caused by the position deviation of the electronic price tag, optimizes the customer experience, and improves the operation benefits of merchants.

[0116] Embodiment 2: Figure 2 The structural block diagram of an electronic price tag positioning feedback and warning system according to an embodiment of the present invention is shown. As Figure 2 shown, the system may include: A data acquisition module 10, which is responsible for obtaining real-time data related to the electronic price tag from multiple data sources. Specifically, the data acquisition module collects image data and environmental data through cameras and sensor devices (such as RFID and Bluetooth sensors) installed in the store environment.

[0117] Image data acquisition: The image information of the electronic price tag is captured in real time through a camera to obtain the position information and attitude of the electronic price tag.

[0118] Sensor data acquisition: Environmental data such as the position information, temperature and humidity, and light intensity of the electronic price tag are obtained through RFID and Bluetooth sensor devices.

[0119] The collected data will be transmitted to the data processing module to ensure the comprehensiveness and effectiveness of the data.

[0120] A data processing module 20, which performs preliminary processing on the collected data, mainly including operations such as data cleaning, denoising, missing value filling, and format standardization to ensure the consistency and accuracy of the data.

[0121] Image data preprocessing: The image data is denoised and enhanced to ensure that the image quality is suitable for subsequent positioning calculations.

[0122] Sensor data calibration: The sensor data is calibrated and corrected to reduce the influence of environmental interference on the positioning accuracy.

[0123] The processed data will be stored in an efficient database for use by subsequent positioning calculation and feedback warning modules.

[0124] The positioning calculation and feedback module 30 uses image recognition algorithms and sensor data fusion technology to perform real-time positioning calculations on the electronic price tags and generate positioning feedback information.

[0125] Image positioning: Analyze the image data transmitted by the S100 module through image recognition technology to identify the specific position and orientation of the electronic price tag.

[0126] Sensor positioning: Based on the data transmitted by RFID, Bluetooth sensors, etc., further optimize the positioning information of the electronic price tag and correct the deviation caused by environmental interference or errors.

[0127] The generated real-time positioning feedback information will be transmitted to the warning module for further anomaly detection.

[0128] The anomaly detection and warning module 40 compares the positioning feedback information generated by the S200 module with the preset standard position to detect the deviation between the actual position and the standard position of the electronic price tag.

[0129] Deviation detection: Calculate the deviation between the actual position and the standard position of the electronic price tag. If the deviation exceeds the preset threshold, trigger the warning mechanism.

[0130] Warning signal generation: If a display deviation exceeding the threshold is detected, the system generates a warning signal and transmits the signal to the decision-making module for further adjustment strategy formulation.

[0131] The decision-making and adjustment strategy module 50 calculates the adjustment strategy for the electronic price tag using intelligent decision-making algorithms based on the warning signal received from the warning module and generates an adjustment command.

[0132] Adjustment strategy calculation: Calculate the best adjustment path and method for the electronic price tag based on the actual deviation, environmental data, and historical adjustment records.

[0133] Command generation: Generate specific adjustment commands according to the calculated adjustment strategy to guide merchants or automatic devices to adjust the position of the electronic price tag.

[0134] The cloud platform and data management module 60 uploads the generated adjustment strategy and real-time monitoring data to the cloud through the cloud computing platform and performs cross-platform data synchronization and centralized management.

[0135] Data synchronization and management: The electronic price tag data of each store is synchronized in real time through the cloud platform to ensure data consistency and update speed among different stores.

[0136] Remote monitoring and optimization: Store operation personnel can remotely monitor the status of the electronic price tag through the cloud platform and perform adjustment and maintenance of the electronic price tag based on the real-time data and optimization suggestions provided by the platform.

[0137] User Interaction and Visualization Module 70, which provides an intuitive user interface to display the positioning feedback, warning information, and adjustment suggestions of the system.

[0138] Data Visualization: Display the real-time positioning, status, and adjustment results of electronic price tags through visual charts, maps, etc.

[0139] Interactive Operations: Users can interact with the system through touchscreens, mice, or other input devices to quickly view and adjust the status of electronic price tags.

[0140] System Monitoring and Adaptive Optimization Module 80, which continuously monitors the running status of the system and automatically optimizes system parameters according to feedback information to ensure the efficient and stable operation of the system.

[0141] Running Status Monitoring: Real-time monitor the running status of each module of the system to ensure the efficient and stable data transmission and calculation process.

[0142] Adaptive Optimization: Through technologies such as machine learning, continuously optimize adjustment strategies and system configurations to improve the adaptability and accuracy of the system.

[0143] The electronic price tag positioning feedback and warning method and system provided by the embodiments of the present invention effectively improve the intelligent level of electronic price tag management through technical means such as multi-modal data collection, real-time positioning, intelligent decision-making, and cloud platform management. Specific beneficial effects include: 1. High-precision real-time positioning: Through image recognition and sensor data fusion technologies, high-precision real-time positioning of the positions of electronic price tags is achieved to ensure that electronic price tags accurately display product information.

[0144] 2. Intelligent warning mechanism: The system can detect deviations of electronic price tags in real time and automatically trigger the warning mechanism according to preset thresholds to timely discover and correct problems, avoiding economic losses caused by display errors.

[0145] 3. Automatic adjustment strategy: Using intelligent decision-making algorithms, the system can automatically calculate and generate adjustment strategies for electronic price tags, reducing manual intervention and improving adjustment efficiency.

[0146] 4. Centralized management and remote monitoring: Through the cloud computing platform, the system can centrally manage and real-time monitor electronic price tags in multiple stores, provide real-time adjustment suggestions for the operation team, and ensure the stable operation of electronic price tags.

[0147] 5. Adaptive optimization ability: The system has the ability of adaptive learning and optimization, and can continuously optimize adjustment strategies and system parameters according to real-time data to adapt to different store environments and improve overall performance.

[0148] Obviously, the embodiments described above are only a part of the embodiments of this application, rather than all of them. The preferred embodiments of this application are shown in the accompanying drawings, but they do not limit the patent scope of this application. This application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of this application more thorough and comprehensive. Although this application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing specific embodiments, or perform equivalent replacements on some of the technical features. Any equivalent structure that makes use of the content of this application's specification and the accompanying drawings, directly or indirectly applied in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. An electronic price label positioning feedback warning method, characterized in that: The method comprises: Acquire multimodal sensor data and transmit said data to a data processing module for preliminary data analysis and providing real-time environmental perception; Using image recognition and sensor data fusion technology, the position of the electronic price tag is accurately calculated and positioning feedback information is generated; Perform anomaly detection based on the positioning feedback information, determine whether the electronic price tag has display deviation, and generate an early warning signal through a preset threshold; Utilize intelligent decision-making algorithms to calculate the optimal adjustment strategy based on the warning signals and feedback information, generate adjustment commands, and guide merchants to perform adjustment operations; The adjustment strategy and real-time monitoring data are uploaded to the cloud platform for data synchronization and centralized management, supporting cross-platform remote monitoring and optimization.

2. The electronic price label positioning feedback warning method according to claim 1, characterized in that: The step of acquiring multimodal sensor data comprises: Collect image data of the location of the electronic price tag through a camera; Obtain the location information, ambient temperature and humidity, and light intensity data of the electronic price tag through sensor devices; The image data and sensor data are synchronously transmitted to a data processing module for subsequent processing.

3. The electronic price label positioning feedback warning method according to claim 1, characterized in that: The step of calculating the position of the electronic price tag using image recognition and sensor data fusion technology specifically includes: Analyze image data through image recognition algorithms to identify the initial position and posture of the electronic price tag; Optimization is performed based on sensor data to further correct the actual position of the electronic price tag to obtain the final positioning result.

4. The electronic price label positioning feedback warning method according to claim 3, characterized in that: The step of calculating the positioning result based on the image recognition and sensor data fusion technology includes: The preliminary position coordinates of the electronic price tag calculated by image recognition are weightedly fused with the position information in the sensor data to obtain the corrected precise position.

5. The electronic price label positioning feedback warning method according to claim 1, characterized in that: The step of performing anomaly detection according to positioning feedback information comprises: Compare the positioning feedback information with the preset standard position, and calculate the deviation value between the actual position of the electronic price tag and the standard position; Determine whether the deviation value exceeds the preset threshold, and if so, trigger an early warning signal.

6. The electronic price label positioning feedback warning method according to claim 5, characterized in that: The step of determining whether the deviation value exceeds a preset threshold value also includes: If the deviation value exceeds the threshold, a warning signal is generated and transmitted to the decision module for further adjustment strategy calculation.

7. The electronic price label positioning feedback warning method according to claim 1, characterized in that: The step of calculating the optimal adjustment strategy using the intelligent decision-making algorithm includes: According to the warning signal and feedback information, combined with the actual position and target position of the electronic price tag, the optimal adjustment path and adjustment amount are calculated; Generate adjustment commands to guide merchants to adjust electronic price tags.

8. The electronic price label positioning feedback warning method according to claim 1, characterized in that: The step of uploading the adjustment strategy and real-time monitoring data to the cloud platform includes: Uploading the adjustment strategy and the real-time status data of the electronic price tag to the cloud computing platform for data storage and processing; The electronic price tag data of multiple stores are synchronized in real time through the cloud platform.

9. The electronic price label positioning feedback warning method according to claim 8, characterized in that: The step of synchronizing the electronic price tag data of multiple stores in real time through the cloud platform includes: Upload the electronic price tag data of each store to the cloud platform for unified storage and synchronization to ensure the consistency of the electronic price tags in each store and support remote adjustment and management.

10. An electronic price label positioning feedback warning system, characterized in that: The system comprises: A data acquisition module, used to obtain real-time data related to the electronic price label from multiple data sources, including collecting image data and environmental data through cameras and sensor devices installed in the store environment; A data processing module is used to perform preliminary processing on the collected data, including data cleaning, denoising, missing value filling and format standardization operations; Positioning calculation and feedback module, used to use image recognition algorithm and sensor data fusion technology to perform real-time positioning calculation of electronic price tags and generate positioning feedback information; An abnormality detection and warning module, used to compare the positioning feedback information with the preset standard position, detect the deviation between the actual position of the electronic price tag and the standard position, and generate a warning signal when the deviation exceeds a preset threshold; A decision-making and adjustment strategy module, which is used to calculate the adjustment strategy of the electronic price tag using an intelligent decision-making algorithm according to the warning signal and feedback information, and generate an adjustment command to guide the merchant or automatic equipment to adjust the position of the electronic price tag; The cloud platform and data management module is used to upload the adjustment strategy and real-time monitoring data to the cloud platform, perform cross-platform data synchronization and centralized management, and support remote monitoring and optimization; User interaction and visualization module, which is used to provide an intuitive user interface, display the system's positioning feedback, warning information and adjustment suggestions, and support interactive operations; The system monitoring and adaptive optimization module is used to continuously monitor the operating status of the system and automatically optimize system parameters based on feedback information.

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