Method, system and server for locating products in supermarket

Abstract

The present application discloses a method, system and server for locating products in a supermarket. The method comprises: electronic shelf labels transmitting signals for measuring angles of arrival and signals for locating neighbor shelf labels, receiving locating neighbor signals of other shelf labels, and determining neighbor information; base stations measuring angles of arrival of shelf label signals; a cloud positioning server determining preliminary positions of the shelf labels on the basis of the angles; determining a neighbor relationship of all the shelf labels on the basis of the neighbor information; on the basis of the neighbor relationship, screening a plurality of preliminary locating positions of each electronic shelf label to obtain an optimized locating position of each electronic shelf label; a map server predicting a preliminary product display position aggregation result of each electronic shelf label on the basis of the optimized position, and mapping the preliminary product display position aggregation result onto a supermarket map image; and optimizing each preliminary aggregation result in the image on the basis of the following factors to obtain a result representing a locating result of each product bound to the corresponding shelf label: the neighbor relationship, an actual distance, the category of a display position, and the ratio of the area of the display position to the number of shelf labels having been aggregated.

Description

Methods, systems, and servers for locating products within supermarkets

[0001] Related applications

[0002] This application claims priority to Chinese Patent Application No. 202411648836.2, filed on November 18, 2024, and incorporates the disclosure of the aforementioned patent application as part of this application. Technical Field

[0003] This application relates to the field of product positioning technology, and in particular to a method, system and server for locating products in a supermarket. Background Technology

[0004] This section is intended to provide background or context for the embodiments of this application set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0005] Currently, electronic shelf labels are commonly used to replace traditional paper labels. Besides displaying ordinary information, electronic shelf labels can be used for many applications, such as rapid order picking, out-of-stock management, quick inventory checks, and human-computer interaction with users. Since each electronic shelf label is uniquely linked to a specific product, locating the electronic shelf label is equivalent to locating the product. This makes them highly valuable for applications such as rapid order picking, product retrieval, replenishment, and pre-setting product display locations (e.g., endcaps, etc.).

[0006] Currently, there is a method for locating products using the neighbor relationships of price tags. However, in specific situations, such as product displays, where the positions of products and their corresponding electronic price tags may change frequently, this neighbor-based location method, which relies on static or semi-static neighbor relationships, faces challenges. The existing methods for locating products using the neighbor relationships of price tags have the following problems:

[0007] 1. Frequent Location Changes: In a product display scenario, the product's placement may be frequently adjusted based on promotional needs, causing corresponding changes in the electronic price tag's position. Since neighbor relationships are identified and located based on predefined rules and known anchor point location information, frequent location changes will disrupt this dependency. That is, anchor point positions may move frequently, making it difficult for the system to quickly and accurately update the price tag's position.

[0008] 2. Price Tag Quantity Limitation: If the price tag density in the display area is low and the price tag distribution is sparse, the establishment of neighbor relationships between price tags will not be stable enough, which limits the reliability of the positioning algorithm. A sparse price tag distribution means a small number of neighbor data points, which may lead to inaccurate or erroneous positioning results.

[0009] 3. Limitations of automatic updates: When the price tag location changes, existing neighbor-based positioning systems may not be able to update the neighbor relationship database in real time. This delay affects the timeliness of positioning information and fails to reflect the current actual location promptly and effectively.

[0010] 4. Limitations of Anchor Points: This solution requires anchor price tags. Anchor-based electronic price tag positioning methods face several challenges, including the required number and distribution of anchor points, the accuracy of anchor point locations, system scalability, and maintenance costs. Uneven distribution or insufficient number of anchor points directly affects positioning accuracy; inaccurately positioned anchor points lead to error accumulation; and system expansion and anchor point maintenance can result in higher costs and complexity.

[0011] In summary, existing methods for locating products using the neighbor relationships of price tags have positioning errors, resulting in low positioning accuracy. Summary of the Invention

[0012] This application provides a method for locating goods in a supermarket to improve the accuracy of goods location. The method is applied to a system including: multiple electronic shelf labels, multiple electronic shelf label base stations, a cloud-based positioning server, and a map server. The method includes:

[0013] Each electronic price tag transmits a signal for measuring the angle of arrival at a preset time interval; it sends a signal for locating neighboring price tags within a preset time window, receives signals from other price tags for locating neighboring price tags, determines the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags, and sends it to the electronic price tag base station.

[0014] Each electronic price tag base station determines the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server.

[0015] The cloud-based positioning server determines multiple preliminary positioning positions for each electronic price tag based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, as the angle of arrival positioning result; it determines the neighbor relationships of all electronic price tags based on the neighbor information of each electronic price tag, as the neighbor positioning result; it filters the multiple preliminary positioning positions of each electronic price tag based on the neighbor relationships to obtain the optimized positioning position of each electronic price tag; and it sends the optimized positioning position of each electronic price tag and the neighbor relationships to the map server.

[0016] The map server predicts the preliminary product display location aggregation result for each electronic shelf label based on its optimized location. This preliminary aggregation result is then mapped onto the supermarket map image. Based on one or any combination of the following factors, the preliminary aggregation result is further optimized in the supermarket map image to obtain the optimized product display location aggregation result for each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0017] This application also provides a method for locating goods in a supermarket to improve the accuracy of goods location. This method is applied to a cloud-based location server and includes:

[0018] The system acquires the angle of arrival (AHA) of the electronic price tag signal and neighboring price tag information. The AHA of the electronic price tag signal is transmitted by the electronic price tag base station. The electronic price tag base station determines the AHA of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the AHA of each electronic price tag signal and neighboring price tag information to a cloud positioning server. Each electronic price tag is used to: transmit a signal for measuring the angle of arrival at a preset time interval; transmit a signal for locating neighboring price tags within a preset time window; receive signals from other price tags for locating neighboring price tags; determine the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags; and send it to the electronic price tag base station.

[0019] Based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, multiple preliminary positioning positions of each electronic price tag are determined as the angle of arrival positioning results;

[0020] The neighbor relationships of all electronic price tags are determined based on the neighbor price tag information of each electronic price tag, which serves as the neighbor location result;

[0021] Based on the neighbor relationships, multiple preliminary positioning positions of each electronic price tag are filtered to obtain the optimal positioning position of each electronic price tag.

[0022] The optimized location and neighbor relationships of each electronic shelf label are sent to a map server. The map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto the supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0023] This application also provides a method for locating goods in a supermarket to improve the accuracy of goods location. This method is applied to a map server and includes:

[0024] The system obtains optimized positioning locations and neighbor relationships from a cloud-based positioning server. The cloud-based positioning server is used to: determine multiple preliminary positioning locations for each electronic price tag as angle-of-arrival positioning results based on the angle of arrival of the electronic price tag signal, and the location and altitude of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as neighbor positioning results based on the neighbor information of each electronic price tag; and filter the multiple preliminary positioning locations of each electronic price tag according to the neighbor relationships to obtain the optimized positioning location for each electronic price tag. The angle of arrival and neighbor information of each electronic price tag signal are sent by the electronic price tag base station. The electronic price tag base station is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit signals for measuring the angle of arrival at preset time intervals; send signals for locating neighbor price tags within a preset time window; receive signals from other price tags for locating neighbor price tags; determine the neighbor information of each electronic price tag based on the signals for locating neighbor price tags; and send it to the electronic price tag base station.

[0025] Based on the optimized positioning of each electronic shelf label, the preliminary product display position aggregation results are predicted to indicate that each electronic shelf label belongs to the preset product display position range.

[0026] The initial product display location data is mapped onto the supermarket map image;

[0027] Based on one or any combination of the following factors, the preliminary product display location aggregation results for each electronic shelf label are optimized in the supermarket map image to obtain the optimized product display location aggregation results for each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the product category bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation results represent the location results of the products bound to the electronic shelf labels.

[0028] This application also provides a system for locating goods in supermarkets to improve the accuracy of goods location. The system includes: multiple electronic shelf labels, multiple electronic shelf label base stations, a cloud-based positioning server, and a map server, wherein:

[0029] Each electronic price tag is used to transmit a signal for measuring the angle of arrival at a preset time interval; send a signal for locating neighboring price tags in a preset time window; receive signals from other price tags for locating neighboring price tags; determine the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags; and send it to the electronic price tag base station.

[0030] Each electronic price tag base station is used to determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server.

[0031] A cloud-based positioning server is used to determine multiple preliminary positioning positions for each electronic price tag as angle-of-arrival positioning results based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as neighbor positioning results based on the neighbor information of each electronic price tag; filter the multiple preliminary positioning positions of each electronic price tag according to the neighbor relationships to obtain the optimized positioning position of each electronic price tag; and send the optimized positioning position of each electronic price tag and the neighbor relationships to the map server.

[0032] A map server is used to predict the preliminary product display location aggregation result of each electronic shelf label within a preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto a supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image according to one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0033] This application embodiment also provides a cloud-based positioning server for locating goods in supermarkets, in order to improve the accuracy of goods positioning. The cloud-based positioning server includes:

[0034] The first acquisition unit is used to acquire the arrival angle of the electronic price tag signal and neighboring price tag information; the arrival angle of the electronic price tag signal is sent by the electronic price tag base station; the electronic price tag base station is used to determine the arrival angle of each electronic price tag signal based on the signal used to measure the arrival angle, and send the arrival angle of each electronic price tag signal and neighboring price tag information to the cloud positioning server; each electronic price tag is used to: transmit a signal used to measure the arrival angle at a preset time interval; transmit a signal used to locate neighboring price tags in a preset time window, receive signals from other price tags to locate neighboring price tags, determine the neighboring price tag information of each electronic price tag based on the signals to locate neighboring price tags, and send it to the electronic price tag base station;

[0035] The arrival angle positioning unit is used to determine multiple preliminary positioning positions of each electronic price tag as arrival angle positioning results based on the arrival angle of the electronic price tag signal, as well as the position and height of the electronic price tag base station.

[0036] The neighbor positioning unit is used to determine the neighbor relationships of all electronic price tags based on the neighbor price tag information of each electronic price tag, and use this as the neighbor positioning result.

[0037] An optimization unit is used to filter multiple preliminary positioning positions of each electronic price tag according to the neighbor relationship to obtain an optimized positioning position for each electronic price tag.

[0038] A sending unit is used to send the optimized location and neighbor relationships of each electronic shelf label to a map server. The map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto a supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0039] This application embodiment also provides a map server for locating goods in supermarkets, in order to improve the accuracy of goods location. The map server includes:

[0040] The second acquisition unit is used to acquire the optimized positioning location and neighbor relationships sent by a cloud positioning server. The cloud positioning server is used to: determine multiple preliminary positioning locations for each electronic price tag as angle-of-arrival positioning results based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as neighbor positioning results based on the neighbor price tag information of each electronic price tag; and filter the multiple preliminary positioning locations of each electronic price tag according to the neighbor relationships to obtain the optimized positioning location of each electronic price tag. The angle of arrival of each electronic price tag signal and the neighbor price tag information are sent by the electronic price tag base station. The electronic price tag base station is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit the signal used to measure the angle of arrival at a preset time interval; send the signal used to locate neighbor price tags in a preset time window; receive the signal used by other price tags to locate neighbor price tags; determine the neighbor price tag information of each electronic price tag based on the signal used to locate neighbor price tags and send it to the electronic price tag base station.

[0041] The preliminary collection unit is used to predict the preliminary product display position collection result of each electronic price tag within the preset product display position range based on the optimized positioning position of each electronic price tag;

[0042] The mapping unit is used to map the preliminary product display location aggregation results onto the supermarket map image;

[0043] The optimization positioning unit is used to optimize the preliminary product display location aggregation results of each electronic shelf label in the supermarket map image based on one or any combination of the following factors, to obtain the optimized product display location aggregation result for each electronic shelf label: the neighbor relationship, the actual distance between the optimized positioning position of each electronic shelf label and the preset product display position, the matching degree between the category of the preset product display position and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display position to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the positioning result of the product bound to the electronic shelf label.

[0044] This application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for locating goods in a supermarket.

[0045] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for locating goods in a supermarket.

[0046] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for locating goods in a supermarket.

[0047] In this embodiment, the scheme for locating goods in a supermarket involves: each electronic shelf label transmitting a signal for measuring the angle of arrival at preset time intervals; transmitting signals for locating neighboring shelf labels within a preset time window, receiving signals from other shelf labels for locating neighboring shelf labels, determining the neighboring shelf label information of each electronic shelf label based on the signals for locating neighboring shelf labels, and sending this information to the electronic shelf label base station; each electronic shelf label base station determining the angle of arrival of each electronic shelf label signal based on the signals for measuring the angle of arrival, and sending the angle of arrival of each electronic shelf label signal and the neighboring shelf label information to a cloud positioning server; the cloud positioning server determining multiple preliminary positioning positions of each electronic shelf label as the angle of arrival positioning result based on the angle of arrival of the electronic shelf label signal, as well as the position and altitude of the electronic shelf label base station; determining the neighbor relationships of all electronic shelf labels as the neighbor positioning result based on the neighboring shelf label information of each electronic shelf label; and filtering the multiple preliminary positioning positions of each electronic shelf label based on the neighbor relationships to obtain the optimized positioning of each electronic shelf label. The process involves: 1) Sending the optimized location and neighbor relationships of each electronic shelf tag to the map server; 2) Based on the optimized location of each electronic shelf tag, the map server predicts the preliminary product display location aggregation result within the preset product display location range for each electronic shelf tag; 3) Mapping the preliminary product display location aggregation result onto the supermarket map image; 4) Optimizing the preliminary product display location aggregation result of each electronic shelf tag in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result for each electronic shelf tag: neighbor relationships, the actual distance between the optimized location of each electronic shelf tag and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf tag, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf tags; 5) The optimized product display location aggregation result represents the positioning result of the product bound to the electronic shelf tag. This scheme can improve the positioning accuracy of the electronic shelf tag, thereby improving the positioning accuracy of the product within the display area. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0049] Figure 1 is a flowchart illustrating the method for locating goods in a supermarket applied to the system in an embodiment of this application;

[0050] Figure 2 is a schematic diagram of the system for locating goods in a supermarket according to an embodiment of this application;

[0051] Figure 3 is a network diagram showing the connection relationships between all price tags in an embodiment of this application;

[0052] Figure 4 is a schematic diagram of the single base station method in the embodiments of this application;

[0053] Figure 5 is a schematic diagram of the multi-base station method in the embodiments of this application;

[0054] Figure 6 is a schematic diagram illustrating the principle of locating goods in a supermarket in an embodiment of this application;

[0055] Figure 7 is a flowchart illustrating the method for locating goods in a supermarket using a cloud-based positioning server, as described in this application.

[0056] Figure 8 is a flowchart illustrating the method for locating goods in a supermarket using a map server in an embodiment of this application.

[0057] Figure 9 is a schematic diagram of the structure of the cloud positioning server for locating goods in a supermarket in an embodiment of this application;

[0058] Figure 10 is a schematic diagram of the structure of the map server for locating goods in a supermarket in an embodiment of this application;

[0059] Figure 11 is a schematic diagram of a computer device structure according to an embodiment of this application. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and their descriptions are used to explain this application, but are not intended to limit this application.

[0061] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0062] Figure 1 is a flowchart illustrating the method for locating goods in a supermarket applied to the system in this application embodiment. The method is applied to the system. Figure 2 is a structural diagram of the system for locating goods in a supermarket in this application embodiment. As shown in Figure 2, the system includes: multiple electronic shelf labels, multiple electronic shelf label base stations, a cloud positioning server, and a map server. As shown in Figure 1, the method includes the following steps:

[0063] Step 101: Each electronic price tag transmits a signal for measuring the angle of arrival at a preset time interval; sends a signal for locating neighboring price tags within a preset time window, receives signals from other price tags for locating neighboring price tags, determines the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags, and sends it to the electronic price tag base station.

[0064] Step 102: Each electronic price tag base station determines the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server.

[0065] Step 103: The cloud positioning server determines multiple preliminary positioning positions for each electronic price tag based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, as the angle of arrival positioning result; it determines the neighbor relationship of all electronic price tags based on the neighbor price tag information of each electronic price tag, as the neighbor positioning result; it filters the multiple preliminary positioning positions of each electronic price tag based on the neighbor relationship to obtain the optimized positioning position of each electronic price tag; and it sends the optimized positioning position and neighbor relationship of each electronic price tag to the map server.

[0066] Step 104: Based on the optimized location of each electronic shelf label, the map server predicts the preliminary product display location aggregation result within the preset product display location range for each electronic shelf label; the preliminary product display location aggregation result is mapped onto the supermarket map image; based on one or any combination of the following factors, the preliminary product display location aggregation result for each electronic shelf label is optimized in the supermarket map image to obtain the optimized product display location aggregation result for each electronic shelf label: neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0067] The method for locating goods in a supermarket system, as described in this application embodiment, operates as follows: Each electronic shelf label transmits a signal for measuring the angle of arrival at preset time intervals; within a preset time window, it sends a signal for locating neighboring shelf labels, receives signals from other shelf labels for locating neighboring shelf labels, determines the neighboring shelf label information for each electronic shelf label based on the signals for locating neighboring shelf labels, and sends this information to the electronic shelf label base station; each electronic shelf label base station determines the angle of arrival of each electronic shelf label signal based on the signal for measuring the angle of arrival, and sends the angle of arrival of each electronic shelf label signal and the neighboring shelf label information to a cloud positioning server; the cloud positioning server determines multiple preliminary positioning positions for each electronic shelf label as the angle of arrival positioning result based on the angle of arrival of the electronic shelf label signal, as well as the position and height of the electronic shelf label base station; it determines the neighbor relationships of all electronic shelf labels as the neighbor positioning result based on the neighboring shelf label information of each electronic shelf label; and it filters the multiple preliminary positioning positions of each electronic shelf label based on the neighbor relationships to obtain the position of each electronic shelf label. The method involves optimizing the location of each electronic shelf label; sending the optimized location and neighbor relationships of each electronic shelf label to a map server; the map server predicting the preliminary product display location aggregation result within the preset product display location range based on the optimized location of each electronic shelf label; mapping the preliminary product display location aggregation result onto the supermarket map image; and optimizing the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result for each electronic shelf label: neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the product category of the preset product display location and the product category bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label. This method can improve the positioning accuracy of the electronic shelf label, thereby improving the positioning accuracy of the product within the display area. The following is a detailed description of this application.

[0068] This application primarily designs a novel positioning scheme for locating goods within a supermarket. This scheme integrates neighbor positioning and AOA (Angle of Arrival) positioning to automatically and accurately locate electronic shelf labels within different display areas of the supermarket, such as display stands and endcaps (collectively referred to as preset product display locations in this application). This new electronic shelf label positioning scheme achieves a more accurate and dynamically adaptable positioning system by integrating AOA and neighbor positioning technologies. First, AOA technology is used to accurately measure the pitch and azimuth angles of the electronic shelf labels to determine their positions. Next, neighbor positioning technology is used to collect and analyze the neighbor relationships between shelf labels. Finally, combining the data from these two technologies, each shelf label is precisely assigned to the corresponding preset product display location with the highest probability, such as a display stand or endcap, thereby optimizing product management and display efficiency in the retail environment. This scheme not only improves positioning accuracy but also flexibly responds to frequent changes in product locations in a commercial environment. The method is described in detail below with reference to Figures 2 to 6.

[0069] In specific implementation, the preset product display position in the embodiments of this application can be a display stand or endcap, etc. For ease of description, the embodiments and accompanying drawings of this application will be described with the preset product display position being a display stand as an example.

[0070] To better illustrate the method for locating goods in supermarkets provided in the embodiments of this application, the system architecture involved in the implementation of this application will first be described in detail.

[0071] Figure 2 shows the architecture diagram of the system for locating goods in a supermarket in this embodiment of the application. The system includes:

[0072] 1. Electronic shelf labels or LCD (Liquid Crystal Display) screens: The electronic shelf labels or LCD screens located at the bottom of the diagram represent different product location tags in a supermarket environment. These labels emit AOA signals that can be measured by a base station at predetermined time intervals. In addition, according to unified instructions from the cloud positioning server, signals are sent during predetermined time windows, and signals from other labels are continuously received when no signals are being sent to detect neighbors, and then the neighbor information is reported.

[0073] In this embodiment, ESL (Electronic Shelf Label) refers to an electronic shelf label or electronic price tag. An electronic shelf label (ESL) is an electronic display device used in retail stores, typically installed on shelves, to display product prices, promotional information, inventory status, etc.

[0074] In this embodiment of the application, the LCD screen or LCD ESL (multiple electronic shelf labels 01) is an electronic shelf label using liquid crystal display technology, used in a retail environment, which can remotely update and display product prices and information, thereby improving the efficiency and accuracy of label management.

[0075] 2. Electronic Shelf Label Base Station 02 (Access Point, AP): Includes a wireless communication module and an AOA receiving antenna array module. The base station is capable of receiving electronic shelf label signals and measuring the signal angle (AOA). The base station sends the collected data back to the communication control center.

[0076] In this embodiment, AP: base station. It is used to manage and control wireless devices, such as ESL, to ensure that electronic shelf labels can receive and send information. Specifically, the base station may include the following modules:

[0077] a. Wireless Communication Module: In practical implementation, this wireless communication module can receive wireless signals from electronic price tags and send response or command signals (such as a command to detect neighboring price tag information) to the price tags when needed. The wireless communication module is also responsible for preliminary processing of the received signal data, such as signal decoding and data extraction. For example, the signal data may be modulated using QAM (Quadrature Amplitude Modulation) or FSK (Frequency-Shift Keying) modulation schemes. The wireless communication module will demodulate these modulations to prepare for subsequent AOA calculations.

[0078] b. AOA Receiver Antenna Array Module: In practice, this AOA receiver antenna array module consists of multiple antennas arranged in a linear antenna array. Each antenna can independently receive signals from the same signal source. By comparing the time or phase differences of the same signals received from different antennas, the module can calculate the angle of arrival (Angle of Arrival). This information is crucial for determining the location of the signal source (e.g., an electronic price tag).

[0079] 3. Communication Control Center 03: As the communication hub between the cloud positioning server and the base station, it is responsible for transmitting the server's instructions to the base station and transmitting data back from the base station to the server.

[0080] As can be seen from the above, in one embodiment, as shown in Figure 2, the system further includes: a communication control center 03; the method for locating goods in a supermarket further includes:

[0081] The communication control center forwards the arrival angle of each electronic price tag signal and neighboring price tag information from the electronic price tag base station to the cloud positioning server; or forwards the signal sending instructions from the cloud positioning server to each electronic price tag through the electronic price tag base station.

[0082] In practice, the communication control center can forward the arrival angle of each electronic price tag signal and neighboring price tag information from the electronic price tag base station to the cloud positioning server; or the signal sending instructions from the cloud positioning server (operation instructions for processing electronic price tags, such as instructions to start neighbor positioning or AOA positioning) can be forwarded to each electronic price tag through the electronic price tag base station. This achieves unified forwarding and processing of data or information from all electronic price tag base stations to the cloud positioning server or forwarding instructions from the cloud positioning server to each electronic price tag, thereby improving the efficiency of data or instruction processing.

[0083] 4. Cloud Positioning Server 04: This module is responsible for AOA (Angle of Arrival, the angle of arrival of a wireless signal when it reaches the receiving device) positioning signal calculation and the entire neighbor positioning service. Neighbor positioning is a positioning method based on the neighbor relationship between devices. For example, if the location of some ESLs is known (often called anchor tags), the anchor tags can be used to help locate surrounding unmarked ESLs. The cloud positioning server is responsible for coordinating and processing neighbor positioning commands and data. It issues commands to the tags to start sending signals and receives data returned by the base station (the base station receives signals sent by the tags according to commands) for further processing and analysis, such as determining whether the quality of the returned data meets the angle (AOA) calculation requirements. It is also responsible for processing the signals received from the base station and calculating the corresponding pitch angle, azimuth angle, and RSSI (Received Signal Strength Indication) data, and then using this data to calculate the position of the tags.

[0084] 5. Map Server 05: The map server stores and provides internal map information for the supermarket, including shelf layout, preset product display locations, and price tag aggregation results. The map server maps electronic price tags to specific locations within the supermarket, allowing system users to see the precise location of each price tag on the supermarket's digital map.

[0085] In specific implementation, as shown in the system architecture in Figure 2, this application embodiment includes two servers: a map server and a cloud positioning server. The optimized system architecture design has a clear division of labor and reasonable functional design, which further ensures the positioning efficiency of goods. The map server is also responsible for store map management (such as creating new maps and revising maps), while the cloud positioning server is responsible for price tags and base station configuration.

[0086] The system for locating goods within a supermarket, as provided in this embodiment, ultimately fuses neighbor location results with AOA location results (AOA location is a technique that uses the angle of arrival of a received signal to determine the location of a signal source). The cloud-based positioning server initiates a full-field probe, sending messages (probe instructions) to all base stations via the communication control center. Subsequently, the base stations broadcast notifications to all price tags to begin probing neighbor information through random sending and continuous receiving within a predetermined time window. After obtaining the neighbor list, the price tag sends this list back to the cloud-based positioning server via the base station. The cloud-based positioning server uses this information to construct a network diagram displaying the connections between all price tags, enabling the system to visually represent the neighbor relationships between price tags. Neighbor relationship refers to the relationship between devices (such as ESLs) considered adjacent based on certain criteria (such as signal strength). In the positioning system, this relationship is used to identify whether the locations of ESLs are adjacent. As shown in Figure 3, which is a network diagram displaying the connections between all price tags in this embodiment, Figure 3 shows price tags that are neighbors of ESL2 and ESL1.

[0087] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: a cloud-based positioning server constructing a network diagram that displays the connection relationships between all electronic price tags.

[0088] In practice, the cloud positioning server constructs a network diagram that displays the connection relationships between all price tags based on neighbor price tag information (such as the arrival angle and time of the wireless signal emitted by the price tag, as well as the signal strength, etc.), so that the system can intuitively display the neighbor relationships between price tags, as shown in Figure 3. Figure 3 is a network diagram that displays the connection relationships between all price tags in this embodiment of the application. Figure 3 shows the electronic price tag that has a neighbor relationship with ESL2 and the electronic price tag that has a neighbor relationship with ESL1.

[0089] The mechanism of neighbor-to-neighbor positioning is shown in Figure 3. AOA positioning requires the installation of a base station device with a signal angle measuring function on the ceiling of the area in the supermarket where the product needs to be located. This device can measure the angle of the wireless signal transmitted from the electronic shelf label, thereby locating the electronic shelf label based on the measured angle. AOA systems typically use an array receiver equipped with multiple antennas. By comparing the phase difference of the same signal received by different antennas, the system can calculate the angle of arrival (AOA). The signals received by different antennas have a slight time difference due to their different distances from the source; this time difference is converted into a phase difference and used to calculate the AOA. AOA positioning works by measuring the angle of arrival of the wireless signal from the transmitting source (e.g., the electronic shelf label) to the receiver (base station). These angles include azimuth and elevation angles. After calculating the AOA, a single-base station or multi-base station positioning method can be used. The single-base station method is shown in Figure 4, which is a schematic diagram of the single-base station method in this embodiment. The base station location and height, as well as the shelf label height, can be measured in advance and input into the system as known configuration information. The location and height of the electronic price tag base station, as well as the price tag height, can be determined and stored during the installation of the electronic price tag base station / price tag. After the location of the electronic price tag base station / price tag changes, its corresponding location and height also change accordingly, ensuring that the location and height of each electronic price tag base station and the price tag height are consistent with the actual location and height of the electronic price tag base station and the price tag height. After obtaining the azimuth and elevation angles, the horizontal distance between the base station and the price tag can be calculated using the height difference and the elevation angle. This calculation is based on trigonometry, using the height difference divided by the tangent of the vertical angle to obtain the distance. After obtaining the horizontal distance, the specific location of the price tag can be determined by combining the azimuth angle and the base station location. The multi-base station method is shown in Figure 5 (the figure shows two base stations as an example). Figure 5 is a schematic diagram of the multi-base station method in this application embodiment. The base station location and height can be measured in advance and input into the system as known configuration information. After obtaining the azimuth and elevation angles of multiple base stations, the location of the target can be determined by finding the corresponding straight line intersection point through geometric calculations, as shown in Figures 4 and 5 for the AOA positioning mechanism.

[0090] As can be seen from the above, in one embodiment, determining multiple preliminary positioning positions of each electronic price tag as the angle of arrival positioning result based on the arrival angle of the electronic price tag signal and the position and height of the electronic price tag base station may include: determining the preliminary positioning position of each electronic price tag as the angle of arrival positioning result by using a single base station or multiple base station positioning method based on the arrival angle of the electronic price tag signal and the position and height of the electronic price tag base station.

[0091] In practice, the cloud-based positioning server can use single-base station or multi-base station positioning methods to determine the preliminary positioning position of each electronic price tag based on the arrival angle of the electronic price tag signal, the position and height of the electronic price tag base station, and the height of the electronic price tag. This improves the accuracy of determining the preliminary positioning position, thereby improving the accuracy of subsequent electronic price tag positioning and ultimately improving the positioning accuracy of the goods bound to the electronic price tag.

[0092] Neighbor positioning and AOA positioning can both locate electronic shelf labels independently. However, because some electronic shelf labels may have a direct line of wireless signal propagation path to the base station location, or not, the AOA angle measurement results are uncertain, leading to significant errors in AOA positioning, such as greater than 2 meters, and even more than 5 meters in complex environments. To accurately locate all display areas within a supermarket, such as displays or endcaps, using only AOA positioning results would require deploying a sufficient number of base station devices. This is not only too costly but also cannot adapt to changes in shelf, display, and endcap positions over long-term use. Meanwhile, neighbor positioning systems primarily rely on reference labels (anchor points) at known locations to assist in locating labels at unknown locations, forming a location network map. The location of each label is determined by analyzing the distances and adjacency relationships between these labels. However, this anchor-based method has limitations; for example, due to varying label distribution density, there may be situations where no definite neighbor relationships exist within a certain distance. Meanwhile, in environments requiring frequent location changes, anchor price tags may be moved frequently, which limits the accuracy and stability of neighbor positioning. Therefore, this application embodiment combines the aforementioned neighbor positioning method and AOA positioning method to obtain a more automated and accurate positioning result. That is, in this application embodiment, an advanced electronic price tag positioning system optimized for supermarket environments is designed. Multiple angle arrival (AOA) base stations are deployed inside the supermarket, distributed in different areas to ensure coverage of the entire mall and provide accurate angle measurement data. Figure 6 is a schematic diagram of the principle of locating goods in a supermarket in this application embodiment. As shown in Figure 6, the implementation steps of this application embodiment are as follows:

[0093] 1. Preparatory steps before the "electronic price tag signal" in Figure 6: Base station deployment and configuration: Install multiple electronic price tag base stations in different areas of the supermarket to ensure effective angle measurement of electronic price tags in each area. Specifically, first, select appropriate base station installation locations based on the characteristics of different areas within the supermarket and the required coverage space. Building upon traditional vertical base station installation to ensure vertical signal coverage, consider tilting the base stations to extend the signal coverage laterally. Base station configuration includes frequency selection, signal transmission interval, and power adjustment to adapt to various environmental conditions. Base station density must ensure coverage of the area requiring positioning; base station coverage is height-dependent, with higher base stations providing greater coverage. After base station deployment, the base station location and height need to be measured and recorded. The base station location and height, along with the price tag height information, need to be configured into the positioning system. The base station needs to be placed horizontally to ensure accurate measurement of the AOA angle. Simultaneously, a horizontal detection device is installed inside the base station. This device detects the base station attitude and reports it to compensate for attitude errors and improve AOA angle measurement accuracy.

[0094] As can be seen from the above, in one embodiment, the electronic price tag base station is equipped with a horizontal detection device to detect the attitude of the electronic price tag base station and report the attitude of the electronic price tag base station to the cloud positioning server; the method for locating goods in the supermarket also includes: the cloud positioning server compensating for the error caused by the attitude of the electronic price tag base station to improve the accuracy of the arrival angle positioning result.

[0095] In practice, the base station needs to be placed horizontally to ensure the accuracy of the measured AOA angle. Simultaneously, the base station is equipped with a horizontal detection device, which detects and reports the base station's attitude to compensate for errors caused by the attitude and improve the accuracy of AOA angle measurement.

[0096] Regarding base station deployment and configuration, this application provides a preferred solution for tilting base stations to expand coverage area: In optimizing the base station deployment strategy of the electronic price tag positioning system, tilting base stations to expand coverage area is an effective method. This configuration can help improve the signal coverage range of base stations, especially in large spaces such as shopping malls, thereby enhancing the accuracy and stability of positioning. The specific steps for tilting base stations to expand coverage area are as follows: First, select a suitable base station installation location based on the characteristics of different areas within the shopping mall and the size of the space to be covered. Building upon the traditional vertical installation of base stations to ensure vertical signal coverage, consider tilting the base stations to horizontally expand the signal coverage range. Angle selection: Determine the tilt angle of the base station. The ideal tilt angle should be adjusted according to the spatial height and architecture of the shopping mall to maximize coverage area while avoiding excessively large or small signal overlap areas. This may require a series of site tests to determine the optimal angle. It is also necessary to ensure that tilting does not cause the signal to be directly blocked by the ground or obstacles. Through this tilting base station method, the coverage area of ​​each base station can be effectively expanded, improving the overall performance and reliability of the electronic price tag positioning system, thus better adapting to the complex environment of large spaces like shopping malls.

[0097] 2. The steps to prepare before the “electronic price tag signal” in Figure 6 are as follows: The cloud positioning server pre-configures the electronic price tag to send wireless signals. The configuration information includes frequency point, signal transmission interval period, signal transmission power, etc.

[0098] 3. As shown in Figure 6, “Electronic Price Tag Signal,” “AOA Positioning Signal,” and “AOA Angle Measurement”: Signal Transmission and Angle Measurement: Each electronic price tag periodically transmits a wireless signal (“Electronic Price Tag Signal” in Figure 6) according to preset parameters. The first batch of electronic price tag signals is the AOA positioning signal. The base station measures the AOA positioning signal, that is, the electronic price tag base station captures these AOA positioning signals and measures their transmission angle, which is the “AOA Angle Measurement” step in Figure 6. Then, these data (measured angle signals) are sent to the cloud positioning server.

[0099] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: the cloud positioning server pre-configuring the frequency of the electronic price tag signal transmission, the preset time interval, the power and interval period of the transmission signal, and the location and height of the electronic price tag base station.

[0100] In practice, the cloud-based positioning server configures the electronic price tags to send wireless signals, including setting the frequency, signal transmission interval, and power. Each electronic price tag can periodically send wireless signals according to preset parameters. Additionally, after deploying base stations, their location and altitude need to be measured and recorded. The base station location and altitude, along with the price tag height information, need to be configured into the positioning system by the cloud-based positioning server.

[0101] 4. As shown in Figure 6, “Base Station Filtering”: Based on the information reported by the electronic price tag and the measured angle, the cloud positioning server scores and filters different base stations, eliminating base stations with poor results. For example, if the information and measured angle include pitch angle and RSSI, multiple thresholds can be set. For example, if the pitch angle is greater than or equal to the first threshold (e.g., 60° is assigned 0 points, and less than 60° is assigned 1 point), and the RSSI is greater than or equal to the second threshold (e.g., 80° is assigned 0 points, and less than 80° is assigned 1 point), different base stations are scored and filtered according to the final score, eliminating base stations with poor results (e.g., scores below the third threshold).

[0102] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: the cloud positioning server filters different electronic price tag base stations based on the information reported by the electronic price tag and the angle of arrival, and removes electronic price tag base stations whose positioning results are lower than a preset value.

[0103] In practice, the cloud positioning server scores and filters different base stations based on the information reported by the electronic price tag and the measured angle. It eliminates base stations with poor results, uses the arrival angle provided by the filtered base stations for arrival angle positioning, and uses the neighbor price tag information provided by the filtered base stations for neighbor positioning. This improves the positioning accuracy of the electronic price tag, thereby improving the positioning accuracy of the goods bound to the electronic price tag.

[0104] 5. As shown in Figure 6, "Multi-base station or single-base station positioning" and "Positioning result": The cloud positioning server calculates the approximate (preliminary) physical location of the electronic shelf label based on the angle measurement values ​​(AOA angle measurement data) reported by the base stations and the "base station location height and price tag height" in Figure 6, thus performing AOA positioning and obtaining the "Positioning result" as shown in Figure 6. AOA positioning can be performed using a single base station or multiple base stations. Single-base station positioning requires the price tag height to be known, while multi-base station positioning does not. The map server infers the pre-defined product display position of the electronic shelf label within a predetermined display area based on its physical location, such as a display shelf or endcap, as shown in Figure 6, "Preliminary display shelf aggregation." Preliminary display shelf aggregation: Based on the physical location calculated by the cloud positioning server, the electronic shelf label is aggregated into a specific display shelf according to certain rules. A predetermined display area is a pre-planned area for displaying specific products or promotional activities. A display shelf is a location in a shopping mall or supermarket used for promotions or special displays of certain products. Display shelf aggregation: This is an operational process that refers to classifying the electronic shelf label into a specific display shelf location.

[0105] As can be seen from the above, in one embodiment, when using single base station positioning, the cloud positioning server also considers the height of the electronic price tag and determines multiple preliminary positioning positions of each electronic price tag as the arrival angle positioning result.

[0106] 6. The cloud positioning server configures the electronic price tag communication system to send wireless signals that can be measured for angle measurement. The configuration information includes frequency points, signal transmission intervals, and signal power. This step can be a pre-prepared and configured step.

[0107] 7. Neighbor Location Initiation: The cloud-based location server initiates neighbor location through the electronic price tag communication system. (There is no fixed order between the initiation of neighbor location ("Neighbor Location Signal" in Figure 6) and the transmission of the AOA signal ("AOA Location Signal" in Figure 6). For example, neighbor location measurements can be performed daily or every few days, but the AOA location signal can be continuously transmitted throughout the day according to a fixed cycle.)

[0108] 8. The electronic shelf labels periodically send wireless signals (as shown in Figure 6, "Electronic Shelf Label Signals," which can also be "Neighbor Location Signals" as shown in Figure 6) according to the configured parameters, and detect neighboring electronic shelf labels. After the detection time window ends, each label sends the detected neighbor information (as shown in Figure 6, "Neighbor Information") to the base station. The base station then transmits the neighbor information of each electronic shelf label to the cloud positioning server. The cloud positioning server calculates the neighbor relationships between the electronic shelf labels based on the reported results, as shown in Figure 6, "Determining Neighbor Relationships."

[0109] 9. Filtering Location Results Using Neighbor Information: By using neighbor information and neighboring price tags' location results, multiple AOA location results are filtered. This involves using neighbor relationships to assist in filtering AOA location results, removing those with significant positioning errors. Due to the actual location and environment of the price tags and base stations, multiple locations may appear for a single price tag (ESL1) using AOA positioning. When the distance difference between multiple location results is less than a threshold (configurable, e.g., 5 meters), the average is taken as the final AOA location result. If the distance difference between location results is greater than the threshold, neighbor information can be used to assist the AOA positioning process. If a price tag (ESL1) has multiple AOA location results and the distance difference is greater than the threshold, neighbor information can be used to determine the adjacent price tag (ESL2). If the adjacent price tag (ESL2) has only one AOA location result, or multiple location results with similar positions, the location results of the adjacent price tag (ESL2) can be compared with those of the price tag (ESL1). Location results from ESL1 that are farthest from the ESL2 location result are removed, thus obtaining the final AOA location result. Additionally, if there are 3 location results, and the distance between 2 of them is greater than the threshold, and the distance between 2 of them is less than the threshold, then the same procedure applies: compare the current electronic price tag's three location results with the location results of neighboring price tags, and remove the results whose distance from the neighboring price tag's location result is greater than a preset distance threshold.

[0110] As can be seen from the above, in one embodiment, filtering multiple preliminary positioning positions of each electronic price tag based on neighbor relationships to obtain an optimized positioning position for each electronic price tag may include:

[0111] When the distance between any two preliminary locations to be screened for the current electronic price tag is greater than a preset distance threshold, the adjacent electronic price tags of the current electronic price tag are determined based on the neighbor relationship.

[0112] If there is only one arrival angle positioning result for adjacent electronic price tags, or multiple arrival angle positioning results with similar positions, the positioning results of adjacent electronic price tags are compared with each preliminary positioning position to be screened for the current electronic price tag. Positioning results that are more than a preset distance away from the positioning results of adjacent electronic price tags are eliminated from all preliminary positioning positions to be screened for the current electronic price tag, thus obtaining the optimized positioning position for each electronic price tag.

[0113] As can be seen from the above, in one embodiment, filtering multiple preliminary positioning positions of each electronic price tag based on neighbor relationships to obtain an optimized positioning position for each electronic price tag further includes:

[0114] When the distance between any two initial positioning positions is less than a preset distance threshold, the average coordinates of all initial positioning positions are taken as the optimized positioning position for each electronic price tag.

[0115] In practice, the above-described optimized positioning method for each electronic price tag can further improve the positioning accuracy of the electronic price tag, thereby further improving the positioning accuracy of goods in supermarkets.

[0116] 10. The map server combines the neighbor positioning results with the results of the preset product display positions (e.g., display stands or endcaps) based on angle measurements, and further locates the electronic price tags in the predetermined display area according to a comprehensive processing method. The map server not only optimizes the positioning accuracy based on the neighbor positioning results and angle measurement results, but also accurately locates the electronic price tags in the predetermined display area through a comprehensive processing method. This comprehensive processing method combines the neighbor positioning results and AOA positioning results, using the following factors (parameters) to further accurately locate each electronic price tag to the preset product display position (e.g., display stand or endcap) in the predetermined display area. The details of this comprehensive processing method (as shown in "Display Stand Aggregation and Comprehensive Scoring" in Figure 6) are as follows:

[0117] a) Actual distance between the initial (or optimized) location of the electronic shelf label and the preset product display location (e.g., display stand or endcap) (as shown in "Distance Information between Sheet Label and Display Stand" in Figure 6): Evaluate the actual distance between the electronic shelf label's location coordinates (initial / optimized location) and the preset product display location (e.g., display stand or endcap). The closer the electronic shelf label is to the preset product display location (e.g., display stand or endcap), the higher the score, indicating a closer relationship between the shelf label and its corresponding preset product display location (e.g., display stand or endcap).

[0118] b) Preset the category relationship between the product display location (e.g., endcap or display shelf) and price tag (as shown in "Endcap Category Information" in Figure 6), i.e., category matching degree: Analyze whether the product category of the endcap matches the product category indicated on the price tag. A perfect match receives a higher score, i.e., analyze and score the degree of category matching between the endcap products and the price tag products; the higher the similarity, the higher the endcap score. (This can be configured through the system and selected as needed).

[0119] c) Preset product display location (e.g., endcap or countertop) area and the number of price tags already positioned at the preset product display location (as shown in Figure 6, "Endcap area and number of price tags already collected"): Because the number of price tags on the endcap will fluctuate within a range, it is necessary to consider the ratio of the actual area of ​​the endcap to the number of price tags already positioned, so as to avoid situations where there are no price tags or too many price tags on the endcap. That is, consider the ratio of the area of ​​the endcap to the number of price tags already positioned. The lower the ratio of the number of price tags to the area, the higher the score.

[0120] d) Neighbor Relationship (as shown in Figure 6, "Neighbor Relationship"): Scoring is based on the closeness of the relationship between the price tag and its neighboring price tags. The closer the neighbor relationship, the closer the price tags are, and the more likely they are to be in the same preset product display location (e.g., endcap or display shelf). In other words, the scoring is based on the neighbor relationship between price tags. The more price tags with the same neighbor relationship in the preset product display location (e.g., endcap or display shelf), the higher the score for the preset product display location (e.g., endcap or display shelf).

[0121] 10. Combining the above parameters (factor AD, i.e., the connection relationship between all electronic price tags in the neighbor location results, actual distance, category information of the preset product display positions (e.g., display positions such as endcaps and countertops), and information on the area of ​​the display position and the number of collected price tags, i.e., the ratio of the display position area to the number of collected price tags), the preset product display positions near the location of each price tag are scored to determine the most suitable preset product display position (e.g., endcap or countertop). Simultaneously, based on the layout of different stores, the different factors of the above comprehensive processing method can be configured with different weights according to the actual situation. The weights are configured on the map server based on the accuracy of the preset product display position (e.g., endcap or countertop) collection results, thereby adapting to different store needs. That is, weight adjustment: based on the collection accuracy of the preset product display positions (e.g., endcap or countertops), the weights of each factor in the comprehensive processing method are adjusted and configured into the map positioning server to adapt to the actual situation of the store.

[0122] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: the map server adjusting the weight of each factor based on the verification results of the optimized product display location aggregation results for each electronic price tag, in order to adapt to the actual situation of different supermarkets.

[0123] In practice, the map server adjusts the weights of various factors based on the accuracy (verification results) of the preset product display location (such as the endcap or display shelf), and configures the weights into the map server to adapt to the actual situation of the store, with high flexibility and accuracy.

[0124] 11. Through the above steps, the instantaneous collection results of the preset product display positions (e.g., endcaps or display shelves) can be calculated. Since the system relies on wireless signals for positioning, the wireless signals are affected by the environment at different times, which may lead to inaccurate positioning results. Therefore, this application embodiment also designs a time window filtering algorithm to further improve accuracy, as shown in "Time Window Filtering" in Figure 6. The time window filtering algorithm collects and analyzes a series of results within a set time window, and then selects the result with the highest frequency of occurrence from these results (as shown in "Final Endcap Collection Result" in Figure 6) as the final output. This algorithm reduces the impact of instantaneous errors or occasional fluctuations by accumulating data over a period of time, that is, collecting and analyzing accumulated data within a set time window and selecting the result with the highest frequency of occurrence as the final output, thereby improving the accuracy and stability of decision-making.

[0125] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: the map server obtains the optimized product display location aggregation results (e.g., display stands or endcaps) for each electronic price tag at multiple times within a preset filtering time window, and selects the optimized product display location aggregation result with the highest frequency as the final product display location aggregation result.

[0126] In practical implementation, since the system relies on wireless signals for positioning, and these signals are affected by the environment at different times, the positioning results may be inaccurate. Therefore, this application embodiment also designs a time window filtering algorithm to further improve accuracy. The time window filtering algorithm collects and analyzes a series of results within a set time window, and then selects the result with the highest frequency from these results as the final preset product display location (e.g., display stand or endcap) aggregation result output. This algorithm reduces the impact of instantaneous errors or occasional fluctuations by accumulating data over a period of time, thereby improving the accuracy and stability of decision-making.

[0127] 12. Fusion and Adjustment: Neighbor positioning and AOA positioning results are recorded as a reference for subsequent comparisons. If the deviation between subsequent positioning results and the reference baseline increases, the weight of the corresponding positioning result is adjusted to optimize and adjust the final location determination. Specifically, different update cycles are typically set when implementing neighbor positioning and AOA positioning; the update cycle is configurable. To effectively fuse these two positioning results, an algorithmic strategy can be adopted. This strategy first records the neighbor positioning and AOA positioning results as a benchmark for subsequent comparisons. Based on this, the algorithm compares the deviation between the latest neighbor positioning and AOA positioning data and the previously recorded benchmark values. If the deviation of the new positioning result from the established benchmark is large, the weight of the corresponding positioning result in the final positioning decision will be reduced accordingly. In this way, the algorithm can dynamically adjust the fusion ratio of the two positioning results to achieve higher positioning accuracy and efficiency. This method not only considers the characteristics of both technologies but also flexibly responds to possible positioning errors, ensuring the overall performance of the positioning system.

[0128] As can be seen from the above, in one embodiment, the method for locating goods in a supermarket further includes: when the error between the optimized product display location aggregation result and the reference location result exceeds a preset deviation value, the map server adjusts the weights of the neighbor location result and the arrival angle location result to obtain a product display location aggregation result with an error between it and the reference location result that is lower than the preset deviation value.

[0129] In practice, neighbor location and AOA location results are recorded as a reference for subsequent comparisons. If the deviation between subsequent location results and the reference baseline value increases, the weight of the corresponding location results is adjusted to optimize and adjust the final location judgment, thereby improving the accuracy of subsequent electronic shelf label location and thus improving the location accuracy of the goods bound to the electronic shelf label.

[0130] In supermarket environments, the positions of price tags on pre-set product display locations (such as endcaps or display shelves) may change frequently. To address these changes, the system periodically (daily) initiates the above steps to ensure accurate repositioning of all price tags.

[0131] The method for locating goods in a supermarket provided in this application embodiment achieves the following:

[0132] 1. Location fusion combining neighbor positioning and angle measurement: This fusion positioning aims to combine the advantages of neighbor positioning and AOA positioning to improve the overall accuracy and reliability of the location. Specific implementation methods include:

[0133] a. AOA positioning operation: The cloud positioning server configures the electronic shelf label to send wireless signals, including setting the frequency, signal interval, and power. The base station receives these signals, measures the angle of arrival, and then sends this angle information back to the cloud positioning server to calculate the physical location of the electronic shelf label.

[0134] b. Base Station Strategy: Deploy base stations in suitable locations within the store. Each base station receives signals and angle information from the electronic price tags. These signals are used to score the base stations, filtering out those with poor performance. Based on the filtered base station results, select one or multiple base stations to locate the price tags.

[0135] c. Neighbor Location Operation: The cloud-based location server initiates neighbor location through the electronic price tag communication system. The electronic price tags periodically send wireless signals according to configuration parameters. The base station not only measures the angle of the signal but also records the signal arrival time and strength to help calculate the neighbor relationships between electronic price tags.

[0136] d. Data Fusion: Due to the different timeframes of neighbor positioning and AOA positioning, there is no strict temporal relationship between the two methods. Even without a strict temporal relationship, after obtaining the positioning result from AOA, it can be combined with the most recent neighbor positioning result and then processed to aggregate preset product display locations (e.g., display stands or endcaps), resulting in preset product display locations for each price tag. The map server combines the neighbor positioning results and AOA positioning results to further integrate this data to optimize positioning accuracy and determine which preset product display location (e.g., display stand or endcap) the electronic price tag should be placed in. Neighbor positioning and AOA positioning complement each other, and their combined use improves the accuracy of the final location estimation.

[0137] 2. Comprehensive Processing: The purpose of the comprehensive scoring method is to determine the most suitable preset product display position for each electronic shelf label based on multiple scoring factors. These scoring factors include:

[0138] a. Distance between the location and the preset product display location: The closer the actual distance between the electronic price tag's location coordinates and the predefined preset product display location, the higher the score. This indicates a closer relationship between the price tag and its corresponding preset product display location.

[0139] b. Relationship between product categories in preset display locations and those on price tags: Analyze whether the product categories in preset display locations match the product categories indicated on price tags. A perfect match receives a higher score, indicating consistency and relevance in product layout.

[0140] c. Preset product display area and number of price tags already positioned in the preset product display area: Consider the ratio of the actual area of ​​the preset product display area to the number of price tags already positioned, thus avoiding situations where there are no price tags or too many price tags in the preset product display area. A reasonable ratio scores higher and helps maintain the attractiveness and functionality of the display effect.

[0141] d. Neighbor Relationship: Scored based on the closeness of the relationship between the price tag and its neighboring price tags. The closer the neighbor relationship, the closer the price tags are, and the more likely they are to be in the same preset product display position.

[0142] 3. Time window filtering and weight adjustment: By analyzing results over a period of time, instantaneous errors are eliminated. Weight parameters can be dynamically adjusted based on changes in the internal layout of the supermarket.

[0143] a. Time window filtering: Based on the results over a period of time, eliminate instantaneous errors and select the results with the highest frequency of occurrence.

[0144] b. Overall score weight adjustment: Adjust the weight of each component based on the actual preset product display position aggregation results.

[0145] c. Weight adjustment of neighbor location and AOA location fusion: The weight ratio of the two is dynamically adjusted based on the consistency and stability of the location results.

[0146] This application also provides a method for locating goods in a supermarket using a cloud-based positioning server, as described in the following embodiments. Since the principle behind this method is similar to that of the method for locating goods in a supermarket using a system, the implementation of this method for locating goods in a supermarket using a cloud-based positioning server can refer to the implementation of the method for locating goods in a supermarket using a system; repeated details will not be elaborated further.

[0147] Figure 7 is a flowchart illustrating the method for locating goods in a supermarket using a cloud-based positioning server, as shown in Figure 7. The method includes the following steps:

[0148] Step 201: Obtain the angle of arrival of the electronic price tag signal and neighboring price tag information; the angle of arrival of the electronic price tag signal is sent by the electronic price tag base station; the electronic price tag base station is used to determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and send the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server; each electronic price tag is used to: transmit a signal used to measure the angle of arrival at a preset time interval; send a signal used to locate neighboring price tags in a preset time window, receive signals from other price tags to locate neighboring price tags, determine the neighboring price tag information of each electronic price tag based on the signals to locate neighboring price tags, and send it to the electronic price tag base station;

[0149] Step 202: Based on the arrival angle of the electronic price tag signal, as well as the location and height of the electronic price tag base station, determine multiple preliminary positioning positions for each electronic price tag as the arrival angle positioning result;

[0150] Step 203: Determine the neighbor relationships of all electronic price tags based on the neighbor price tag information of each electronic price tag as the neighbor location result;

[0151] Step 204: Filter the multiple preliminary positioning positions of each electronic price tag based on neighbor relationships to obtain the optimized positioning position of each electronic price tag;

[0152] Step 205: Send the optimized location and neighbor relationships of each electronic shelf label to the map server; the map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto the supermarket map image; optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0153] In one embodiment, the method described above for locating goods in a supermarket using a cloud-based location server may further include: constructing a network diagram that displays the connections between all electronic price tags.

[0154] In one embodiment, the method for locating goods in a supermarket using a cloud-based positioning server may further include: filtering different electronic price tag base stations based on the information reported by the electronic price tag and the angle of arrival, and eliminating electronic price tag base stations whose positioning results are lower than a preset value.

[0155] In one embodiment, determining multiple preliminary positioning positions of each electronic price tag as the angle of arrival positioning result based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station includes: determining the preliminary positioning position of each electronic price tag as the angle of arrival positioning result by means of a single base station or multiple base station positioning method based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station.

[0156] In one embodiment, the method for locating goods in a supermarket using a cloud-based positioning server may further include: pre-configuring the frequency of the electronic shelf label's signal transmission, the preset time interval, the power and interval period of the transmitted signal, and pre-configuring the location and altitude of the electronic shelf label base station.

[0157] In one embodiment, the electronic price tag base station is equipped with a horizontal detection device to detect the attitude of the electronic price tag base station and report the attitude of the electronic price tag base station to the cloud positioning server; the method for locating goods in the supermarket also includes: compensating for the error caused by the attitude of the electronic price tag base station to improve the accuracy of the arrival angle positioning result.

[0158] In one embodiment, multiple preliminary location positions of each electronic price tag are filtered based on neighbor relationships to obtain an optimized location position for each electronic price tag, including:

[0159] When the distance between any two preliminary locations to be screened for the current electronic price tag is greater than a preset distance threshold, the adjacent electronic price tags of the current electronic price tag are determined based on the neighbor relationship.

[0160] If there is only one arrival angle positioning result for adjacent electronic price tags, or multiple arrival angle positioning results with similar positions, the positioning results of adjacent electronic price tags are compared with each preliminary positioning position to be screened for the current electronic price tag. Positioning results that are more than a preset distance away from the positioning results of adjacent electronic price tags are eliminated from all preliminary positioning positions to be screened for the current electronic price tag, thus obtaining the optimized positioning position for each electronic price tag.

[0161] In one embodiment, filtering multiple preliminary location positions of each electronic price tag based on neighbor relationships to obtain an optimized location position for each electronic price tag further includes:

[0162] When the distance between any two initial positioning positions is less than a preset distance threshold, the average coordinates of all initial positioning positions are taken as the optimized positioning position for each electronic price tag.

[0163] In one embodiment, when using single-base station positioning, the cloud positioning server also considers the height of the electronic price tag and determines multiple preliminary positioning positions for each electronic price tag as the arrival angle positioning result.

[0164] This application also provides a method for locating goods in a supermarket using a map server, as described in the following embodiments. Since the principle behind this method is similar to that of the method for locating goods in a supermarket using a system, the implementation of this method for locating goods in a supermarket using a map server can be found in the implementation of the method for locating goods in a supermarket using a system; repeated details will not be elaborated further.

[0165] Figure 8 is a flowchart illustrating the method for locating goods in a supermarket using a map server in an embodiment of this application. As shown in Figure 8, the method includes the following steps:

[0166] Step 301: Obtain the optimized location and neighbor relationships sent by a cloud positioning server; the cloud positioning server is used to: determine multiple preliminary location positions for each electronic price tag as the angle of arrival positioning result based on the angle of arrival of the electronic price tag signal, and the position and height of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as the neighbor positioning result based on the neighbor price tag information of each electronic price tag; filter the multiple preliminary location positions of each electronic price tag according to the neighbor relationships to obtain the optimized location position of each electronic price tag; the angle of arrival of each electronic price tag signal and the neighbor price tag information are sent by the electronic price tag base station, the electronic price tag base station is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit the signal used to measure the angle of arrival at a preset time interval; send the signal used to locate neighbor price tags in a preset time window, receive the signal used by other price tags to locate neighbor price tags, determine the neighbor price tag information of each electronic price tag based on the signal used to locate neighbor price tags and send it to the electronic price tag base station;

[0167] Step 302: Based on the optimized positioning of each electronic shelf label, predict the preliminary product display position aggregation results for each electronic shelf label within the preset product display position range;

[0168] Step 303: Map the preliminary product display location aggregation results onto the supermarket map image;

[0169] Step 304: Based on one or any combination of the following factors, optimize the preliminary product display location aggregation results for each electronic shelf label in the supermarket map image to obtain the optimized product display location aggregation results for each electronic shelf label: neighbor relationship, actual distance between the optimized location of each electronic shelf label and the preset product display location, matching degree between the category of the preset product display location and the product category bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation results represent the location results of the products bound to the electronic shelf labels.

[0170] In one embodiment, the method for locating goods in a supermarket applied to a map server may further include: obtaining optimized product display location aggregation results for each electronic price tag at multiple times within a preset filtering time window, and selecting the optimized product display location aggregation result with the highest frequency as the final product display location aggregation result.

[0171] In one embodiment, the method for locating goods within a supermarket applied to a map server may further include: adjusting the weights of various factors based on the verification results of the optimized product display location aggregation results for each electronic price tag, in order to adapt to the actual situation of different supermarkets.

[0172] In one embodiment, the method for locating goods in a supermarket applied to a map server may further include: when the error between the optimized product display location aggregation result and the reference location result exceeds a preset deviation value, adjusting the weights of the neighbor location result and the arrival angle location result to obtain a product display location aggregation result with an error lower than the preset deviation value compared to the reference location result.

[0173] This application also provides a system for locating goods in a supermarket, as described in the following embodiments. Since the principle behind this system's problem-solving is similar to the method for locating goods in a supermarket applied to a system, the implementation of this system can refer to the implementation of the method for locating goods in a supermarket applied to a system; repeated details will not be elaborated further.

[0174] Figure 2 is a schematic diagram of the system for locating goods in a supermarket according to an embodiment of this application. As shown in Figure 2, the system includes: multiple electronic price tags 01, multiple electronic price tag base stations 02, a cloud positioning server 04, and a map server 05, wherein:

[0175] Each electronic price tag 01 is used to transmit a signal for measuring the angle of arrival at a preset time interval; send a signal for locating neighboring price tags in a preset time window; receive signals from other price tags for locating neighboring price tags; determine the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags; and send it to the electronic price tag base station.

[0176] Each electronic price tag base station 02 is used to determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and send the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server.

[0177] The cloud-based positioning server 04 is used to determine multiple preliminary positioning positions for each electronic price tag based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, as the angle of arrival positioning result; determine the neighbor relationship of all electronic price tags based on the neighbor price tag information of each electronic price tag as the neighbor positioning result; filter the multiple preliminary positioning positions of each electronic price tag based on the neighbor relationship to obtain the optimized positioning position of each electronic price tag; and send the optimized positioning position and neighbor relationship of each electronic price tag to the map server.

[0178] Map server 05 is used to predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto the supermarket map image; optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image according to one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0179] In one embodiment, as shown in Figure 2, the system further includes: a communication control center 03, used to forward the arrival angle of each electronic price tag signal sent by the electronic price tag base station and neighbor price tag information to the cloud positioning server; or to forward the signal sending instructions of the cloud positioning server to each electronic price tag through the electronic price tag base station.

[0180] In one embodiment, the cloud-based location server is also used to construct a network diagram that displays the connections between all electronic price tags.

[0181] In one embodiment, the cloud positioning server is also used to filter different electronic price tag base stations based on the information and arrival angle reported by the electronic price tag, and eliminate electronic price tag base stations whose positioning results are lower than a preset value.

[0182] In one embodiment, the cloud positioning server is specifically used to: determine the preliminary positioning position of each electronic price tag as the angle of arrival positioning result by means of a single base station or multiple base station positioning method, based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station.

[0183] In one embodiment, the map server is further configured to obtain optimized preset product display location aggregation results at multiple times within a preset filtering time window, and select the optimized preset product display location aggregation result with the highest frequency as the final preset product display location aggregation result.

[0184] In one embodiment, the map server is also used to adjust the weights of various factors based on the verification results of the optimized preset product display location aggregation results, so as to adapt to the actual situation of different supermarkets.

[0185] In one embodiment, the map server is further configured to adjust the weights of neighbor positioning results and arrival angle positioning results when the error between the optimized preset product display location aggregation result and the reference positioning result exceeds a preset deviation value, so as to obtain a preset product display location aggregation result with an error between it and the reference positioning result that is lower than the preset deviation value.

[0186] In one embodiment, the cloud positioning server is specifically used to: pre-configure the frequency of the electronic price tag's signal transmission, the preset time interval, the power and interval period of the transmitted signal, and pre-configure the location and altitude of the electronic price tag base station.

[0187] In one embodiment, the electronic price tag base station is equipped with a horizontal detection device to detect the attitude of the electronic price tag base station and report the attitude of the electronic price tag base station to the cloud positioning server; the method for locating goods in the supermarket also includes: compensating for the error caused by the attitude of the electronic price tag base station to improve the accuracy of the arrival angle positioning result.

[0188] In one embodiment, multiple preliminary location positions of each electronic price tag are filtered based on neighbor relationships to obtain an optimized location position for each electronic price tag, including:

[0189] When the distance between any two preliminary locations to be screened for the current electronic price tag is greater than a preset distance threshold, the adjacent electronic price tags of the current electronic price tag are determined based on the neighbor relationship.

[0190] If there is only one arrival angle positioning result for adjacent electronic price tags, or multiple arrival angle positioning results with similar positions, the positioning results of adjacent electronic price tags are compared with each preliminary positioning position to be screened for the current electronic price tag. Positioning results that are more than a preset distance away from the positioning results of adjacent electronic price tags are eliminated from all preliminary positioning positions to be screened for the current electronic price tag, thus obtaining the optimized positioning position for each electronic price tag.

[0191] In one embodiment, filtering multiple preliminary location positions of each electronic price tag based on neighbor relationships to obtain an optimized location position for each electronic price tag further includes:

[0192] When the distance between any two initial positioning positions is less than a preset distance threshold, the average coordinates of all initial positioning positions are taken as the optimized positioning position for each electronic price tag.

[0193] In one embodiment, when using single-base station positioning, the cloud positioning server also considers the height of the electronic price tag and determines multiple preliminary positioning positions for each electronic price tag as the arrival angle positioning result.

[0194] This application also provides a cloud-based positioning server for locating goods within a supermarket, as described in the following embodiments. Since the principle behind this cloud-based positioning server is similar to the method for locating goods within a supermarket applied to a system, the implementation of this cloud-based positioning server can refer to the implementation of the method for locating goods within a supermarket applied to a system; repeated details will not be elaborated further.

[0195] Figure 9 is a schematic diagram of the structure of the cloud positioning server for locating goods in a supermarket according to an embodiment of this application. As shown in Figure 9, the cloud positioning server includes:

[0196] The first acquisition unit 041 is used to acquire the optimized positioning location and neighbor relationships sent by a cloud positioning server. The cloud positioning server is used to: determine multiple preliminary positioning locations of each electronic price tag as the angle of arrival positioning result based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as the neighbor positioning result based on the neighbor price tag information of each electronic price tag; filter the multiple preliminary positioning locations of each electronic price tag according to the neighbor relationships to obtain the optimized positioning location of each electronic price tag; the angle of arrival of each electronic price tag signal and the neighbor price tag information are sent by the electronic price tag base station, which is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit the signal used to measure the angle of arrival at a preset time interval; send the signal used to locate neighbor price tags in a preset time window, receive the signal used by other price tags to locate neighbor price tags, determine the neighbor price tag information of each electronic price tag based on the signal used to locate neighbor price tags, and send it to the electronic price tag base station;

[0197] The arrival angle positioning unit 042 is used to determine multiple preliminary positioning positions of each electronic price tag as arrival angle positioning results based on the arrival angle of the electronic price tag signal and the position and height of the electronic price tag base station.

[0198] The neighbor positioning unit 043 is used to determine the neighbor relationship of all electronic price tags based on the neighbor price tag information of each electronic price tag as the neighbor positioning result;

[0199] The optimization unit 044 is used to filter multiple preliminary positioning positions of each electronic price tag based on neighbor relationships to obtain the optimized positioning position of each electronic price tag.

[0200] The sending unit 045 is used to send the optimized location and neighbor relationship of each electronic shelf label to the map server. The map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto the supermarket map image; optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image according to one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

[0201] In one embodiment, the neighbor location unit is also used to construct a network diagram showing the connection relationships between all electronic price tags.

[0202] In one embodiment, the cloud positioning server for locating goods in the supermarket may further include a base station filtering unit, used to: filter different electronic price tag base stations based on the information reported by the electronic price tag and the angle of arrival, and eliminate electronic price tag base stations whose positioning results are lower than a preset value.

[0203] In one embodiment, the aforementioned angle of arrival positioning unit is specifically used to: determine the preliminary positioning position of each electronic price tag as the angle of arrival positioning result by means of a single base station or multi-base station positioning method, based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station.

[0204] In one embodiment, the cloud positioning server for locating goods within a supermarket may further include a configuration unit for: pre-configuring the frequency of the electronic price tag's signal transmission, the preset time interval, the power and interval period of the transmitted signal, and pre-configuring the location and altitude of the electronic price tag base station.

[0205] In one embodiment, the electronic price tag base station is equipped with a horizontal detection device to detect the attitude of the electronic price tag base station and report the attitude of the electronic price tag base station to the cloud positioning server; the cloud positioning server for locating goods in the supermarket may also include a compensation unit to compensate for the error caused by the attitude of the electronic price tag base station in order to improve the accuracy of the arrival angle positioning result.

[0206] In one embodiment, multiple preliminary location positions of each electronic price tag are filtered based on neighbor relationships to obtain an optimized location position for each electronic price tag, including:

[0207] When the distance between any two preliminary locations to be screened for the current electronic price tag is greater than a preset distance threshold, the adjacent electronic price tags of the current electronic price tag are determined based on the neighbor relationship.

[0208] If there is only one arrival angle positioning result for adjacent electronic price tags, or multiple arrival angle positioning results with similar positions, the positioning results of adjacent electronic price tags are compared with each preliminary positioning position to be screened for the current electronic price tag. Positioning results that are more than a preset distance away from the positioning results of adjacent electronic price tags are eliminated from all preliminary positioning positions to be screened for the current electronic price tag, thus obtaining the optimized positioning position for each electronic price tag.

[0209] In one embodiment, filtering multiple preliminary location positions of each electronic price tag based on neighbor relationships to obtain an optimized location position for each electronic price tag further includes:

[0210] When the distance between any two initial positioning positions is less than a preset distance threshold, the average coordinates of all initial positioning positions are taken as the optimized positioning position for each electronic price tag.

[0211] In one embodiment, when using single-base station positioning, the cloud positioning server also considers the height of the electronic price tag and determines multiple preliminary positioning positions for each electronic price tag as the arrival angle positioning result.

[0212] This application also provides a map server for locating goods within a supermarket, as described in the following embodiments. Since the principle behind this map server's problem-solving is similar to the method for locating goods within a supermarket applied to the system, the implementation of this map server can refer to the implementation of the method for locating goods within a supermarket applied to the system; repeated details will not be elaborated further.

[0213] Figure 10 is a schematic diagram of the structure of the map server for locating goods in a supermarket according to an embodiment of this application. As shown in Figure 10, the map server includes:

[0214] The second acquisition unit 051 is used to acquire the optimized positioning location and neighbor relationships sent by a cloud positioning server. The cloud positioning server is used to: determine multiple preliminary positioning locations of each electronic price tag as the angle of arrival positioning result based on the angle of arrival of the electronic price tag signal and the position and height of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as the neighbor positioning result based on the neighbor price tag information of each electronic price tag; filter the multiple preliminary positioning locations of each electronic price tag according to the neighbor relationships to obtain the optimized positioning location of each electronic price tag; the angle of arrival of each electronic price tag signal and the neighbor price tag information are sent by the electronic price tag base station, which is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit the signal used to measure the angle of arrival at a preset time interval; send the signal used to locate neighbor price tags in a preset time window, receive the signal used by other price tags to locate neighbor price tags, determine the neighbor price tag information of each electronic price tag based on the signal used to locate neighbor price tags, and send it to the electronic price tag base station;

[0215] The preliminary collection unit 052 is used to predict the preliminary product display position collection result of each electronic price tag within the preset product display position range based on the optimized positioning position of each electronic price tag.

[0216] Mapping unit 053 is used to map the preliminary product display location collection results onto the supermarket map image;

[0217] The optimization positioning unit 054 is used to optimize the preliminary product display location aggregation results of each electronic shelf label in the supermarket map image based on one or any combination of the following factors, to obtain the optimized product display location aggregation results for each electronic shelf label: neighbor relationship, the actual distance between the optimized positioning location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the product category bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation results represent the positioning results of the products bound to the electronic shelf labels.

[0218] In one embodiment, the map server for locating goods within a supermarket may further include: a final positioning unit, configured to: obtain optimized product display location aggregation results for each electronic price tag at multiple times within a preset filtering time window, and select the optimized product display location aggregation result with the highest frequency as the final product display location aggregation result.

[0219] In one embodiment, the map server for locating goods within a supermarket may further include: a first weight adjustment unit, configured to: adjust the weights of various factors based on the verification results of the optimized product display location aggregation results for each electronic price tag, in order to adapt to the actual situation of different supermarkets.

[0220] In one embodiment, the map server for locating goods within a supermarket may further include: a second weight adjustment unit, configured to: adjust the weights of neighboring location results and arrival angle location results when the error between the optimized product display location aggregation result and the reference location result exceeds a preset deviation value, so as to obtain a product display location aggregation result with an error between it and the reference location result that is lower than the preset deviation value.

[0221] Based on the aforementioned application concept, as shown in Figure 11, this application also proposes a computer device 600, including a memory 610, a processor 620, and a computer program 630 stored in the memory 610 and executable on the processor 620. When the processor 620 executes the computer program 630, it implements the aforementioned method for locating goods in a supermarket.

[0222] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for locating goods in a supermarket.

[0223] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for locating goods in a supermarket.

[0224] In this embodiment, the scheme for locating goods in a supermarket involves: each electronic shelf label transmitting a signal for measuring the angle of arrival at preset time intervals; transmitting signals for locating neighboring shelf labels within a preset time window, receiving signals from other shelf labels for locating neighboring shelf labels, determining the neighboring shelf label information of each electronic shelf label based on the signals for locating neighboring shelf labels, and sending this information to the electronic shelf label base station; each electronic shelf label base station determining the angle of arrival of each electronic shelf label signal based on the signals for measuring the angle of arrival, and sending the angle of arrival of each electronic shelf label signal and the neighboring shelf label information to a cloud positioning server; the cloud positioning server determining multiple preliminary positioning positions of each electronic shelf label as the angle of arrival positioning result based on the angle of arrival of the electronic shelf label signal, as well as the position and altitude of the electronic shelf label base station; determining the neighbor relationships of all electronic shelf labels as the neighbor positioning result based on the neighboring shelf label information of each electronic shelf label; and filtering the multiple preliminary positioning positions of each electronic shelf label based on the neighbor relationships to obtain the optimized positioning of each electronic shelf label. The process involves: 1) Sending the optimized location and neighbor relationships of each electronic shelf tag to the map server; 2) Based on the optimized location of each electronic shelf tag, the map server predicts the preliminary product display location aggregation result within the preset product display location range for each electronic shelf tag; 3) Mapping the preliminary product display location aggregation result onto the supermarket map image; 4) Optimizing the preliminary product display location aggregation result of each electronic shelf tag in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result for each electronic shelf tag: neighbor relationships, the actual distance between the optimized location of each electronic shelf tag and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf tag, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf tags; 5) The optimized product display location aggregation result represents the positioning result of the product bound to the electronic shelf tag. This scheme can improve the positioning accuracy of the electronic shelf tag, thereby improving the positioning accuracy of the product within the display area.

[0225] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0226] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0227] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0228] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0229] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for locating goods in a supermarket, characterized in that, This method is applied to a system that includes: multiple electronic price tags, multiple electronic price tag base stations, a cloud positioning server, and a map server. The method includes: Each electronic price tag transmits a signal for measuring the angle of arrival at a preset time interval; it sends a signal for locating neighboring price tags within a preset time window, receives signals from other price tags for locating neighboring price tags, determines the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags, and sends it to the electronic price tag base station. Each electronic price tag base station determines the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server. The cloud-based positioning server determines multiple preliminary positioning positions for each electronic price tag based on the angle of arrival (AHA) of the signal, as well as the location and altitude of the electronic price tag base station. It then determines the neighbor relationships of all electronic price tags based on their neighbor information, serving as the neighbor positioning results. Based on these neighbor relationships, the server filters the multiple preliminary positioning positions for each electronic price tag to obtain an optimized positioning position. Finally, it sends the optimized positioning position of each electronic price tag and its neighbor relationships to the map server. The map server predicts the preliminary product display location aggregation result for each electronic shelf label based on its optimized location. This preliminary aggregation result is then mapped onto the supermarket map image. Based on one or any combination of the following factors, the preliminary aggregation result is further optimized in the supermarket map image to obtain the optimized product display location aggregation result for each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

2. The method of claim 1, wherein, The system further includes: a communication control center; the method for locating goods within the supermarket further includes: The communication control center forwards the arrival angle of each electronic price tag signal and neighboring price tag information from the electronic price tag base station to the cloud positioning server; or forwards the signal sending instructions from the cloud positioning server to each electronic price tag through the electronic price tag base station.

3. A method of locating a product within a store, the method comprising: This method is applied to a cloud-based positioning server, and includes: The system acquires the angle of arrival (AHA) of the electronic price tag signal and neighboring price tag information. The AHA of the electronic price tag signal is transmitted by the electronic price tag base station. The electronic price tag base station determines the AHA of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the AHA of each electronic price tag signal and neighboring price tag information to a cloud positioning server. Each electronic price tag is used to: transmit a signal for measuring the angle of arrival at a preset time interval; transmit a signal for locating neighboring price tags within a preset time window; receive signals from other price tags for locating neighboring price tags; determine the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags; and send it to the electronic price tag base station. Based on the angle of arrival of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, multiple preliminary positioning positions of each electronic price tag are determined as the angle of arrival positioning results; The neighbor relationships of all electronic price tags are determined based on the neighbor price tag information of each electronic price tag, which serves as the neighbor location result; Based on the neighbor relationships, multiple preliminary positioning positions for each electronic price tag are filtered to obtain an optimized positioning position for each electronic price tag; and The optimized location and neighbor relationships of each electronic shelf label are sent to a map server. The map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto the supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

4. The method of claim 3, wherein, Also includes: Construct a network diagram that shows the connections between all electronic price tags.

5. The method of claim 3, wherein, Also includes: Based on the information reported by the electronic price tags and the arrival angle, different electronic price tag base stations are screened, and electronic price tag base stations with positioning results lower than the preset value are eliminated.

6. The method of claim 3, wherein, Based on the arrival angle of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, multiple preliminary positioning positions of each electronic price tag are determined as the arrival angle positioning result. This includes: using a single base station or multiple base station positioning method, based on the arrival angle of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station, determining the preliminary positioning position of each electronic price tag as the arrival angle positioning result.

7. The method of claim 3, wherein, Also includes: The frequency of the electronic price tag's signal transmission is pre-configured, along with the preset time interval, the power and interval period of the transmitted signal, and the location and altitude of the electronic price tag base station.

8. The method of claim 3, wherein, The electronic price tag base station is equipped with a horizontal detection device to detect the attitude of the electronic price tag base station and report the attitude of the electronic price tag base station to the cloud positioning server; the method for locating goods in the supermarket also includes: compensating for the error caused by the attitude of the electronic price tag base station to improve the accuracy of the arrival angle positioning result.

9. The method of claim 3, wherein, Based on the neighbor relationships, multiple preliminary positioning positions for each electronic price tag are filtered to obtain an optimized positioning position for each electronic price tag, including: When the distance between any two preliminary locations to be screened for the current electronic shelf label is greater than a preset distance threshold, the adjacent electronic shelf labels of the current electronic shelf label are determined according to the neighbor relationship; and If there is only one arrival angle positioning result for an adjacent electronic price tag, or multiple arrival angle positioning results with similar positions, the positioning result of the adjacent electronic price tag is compared with each preliminary positioning position to be screened for the current electronic price tag. Positioning results that are more than a preset distance away from the positioning result of the adjacent electronic price tag are removed from all preliminary positioning positions to be screened for the current electronic price tag, so as to obtain the optimized positioning position of each electronic price tag.

10. The method of claim 9, wherein, Based on the neighbor relationships, multiple preliminary positioning positions for each electronic price tag are filtered to obtain an optimized positioning position for each electronic price tag, which also includes: When the distance between any two initial positioning positions is less than a preset distance threshold, the average coordinates of all initial positioning positions are taken as the optimized positioning position for each electronic price tag.

11. The method of claim 3, wherein, When using single-base station positioning, the cloud positioning server also considers the height of the electronic price tag and determines multiple preliminary positioning positions for each electronic price tag as the arrival angle positioning result.

12. A method for locating goods in a supermarket, characterized in that, This method is applied to a map server and includes: The system obtains optimized positioning locations and neighbor relationships from a cloud-based positioning server. The cloud-based positioning server is used to: determine multiple preliminary positioning locations for each electronic price tag as angle-of-arrival positioning results based on the angle of arrival of the electronic price tag signal, and the location and altitude of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as neighbor positioning results based on the neighbor information of each electronic price tag; and filter the multiple preliminary positioning locations of each electronic price tag according to the neighbor relationships to obtain the optimized positioning location for each electronic price tag. The angle of arrival and neighbor information of each electronic price tag signal are sent by the electronic price tag base station. The electronic price tag base station is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit signals for measuring the angle of arrival at preset time intervals; send signals for locating neighbor price tags within a preset time window; receive signals from other price tags for locating neighbor price tags; determine the neighbor information of each electronic price tag based on the signals for locating neighbor price tags; and send it to the electronic price tag base station. Based on the optimized positioning of each electronic shelf label, the preliminary product display position aggregation results are predicted to indicate that each electronic shelf label belongs to the preset product display position range. The preliminary product display location data was mapped onto the supermarket map image; and Based on one or any combination of the following factors, the preliminary product display location aggregation results for each electronic shelf label are optimized in the supermarket map image to obtain the optimized product display location aggregation results for each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the product category bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation results represent the location results of the products bound to the electronic shelf labels.

13. The method of claim 12, wherein, Also includes: Within a preset filtering time window, the optimized product display position aggregation results for each electronic price tag at multiple times are obtained, and the optimized product display position aggregation result with the highest frequency is selected as the final product display position aggregation result.

14. The method of claim 12, wherein, Also includes: Based on the verification results of the optimized product display position aggregation for each electronic price tag, the weights of each factor are adjusted to adapt to the actual situation of different supermarkets.

15. The method of claim 12, wherein, Also includes: When the error between the optimized product display location aggregation result and the reference location result exceeds a preset deviation value, the weights of the neighbor location result and the arrival angle location result are adjusted to obtain a product display location aggregation result with an error between it and the reference location result that is lower than the preset deviation value.

16. A system for locating merchandise within a store, the system comprising: The system includes: multiple electronic shelf labels, multiple electronic shelf label base stations, a cloud positioning server, and a map server, among which: Each electronic price tag is used to transmit a signal for measuring the angle of arrival at a preset time interval; send a signal for locating neighboring price tags in a preset time window; receive signals from other price tags for locating neighboring price tags; determine the neighboring price tag information of each electronic price tag based on the signals for locating neighboring price tags; and send it to the electronic price tag base station. Each electronic price tag base station is used to determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival, and sends the angle of arrival of each electronic price tag signal and neighboring price tag information to the cloud positioning server. A cloud-based positioning server is used to determine multiple preliminary positioning positions for each electronic price tag based on the angle of arrival (AHE) of the electronic price tag signal, as well as the location and altitude of the electronic price tag base station. It then determines the neighbor relationships of all electronic price tags based on their neighbor information, serving as the neighbor positioning results. Based on these neighbor relationships, it filters the multiple preliminary positioning positions for each electronic price tag to obtain an optimized positioning position. Finally, it sends the optimized positioning position of each electronic price tag and the neighbor relationships to a map server. A map server is used to predict the preliminary product display location aggregation result of each electronic shelf label within a preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto a supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image according to one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationship, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

17. A cloud positioning server for locating items within a store, the server comprising: include: The first acquisition unit is used to acquire the arrival angle of the electronic price tag signal and neighboring price tag information; The arrival angle of the electronic price tag signal is sent by the electronic price tag base station; the electronic price tag base station is used to determine the arrival angle of each electronic price tag signal based on the signal used to measure the arrival angle, and send the arrival angle of each electronic price tag signal and neighboring price tag information to the cloud positioning server; each electronic price tag is used to: transmit a signal used to measure the arrival angle at a preset time interval; send a signal used to locate neighboring price tags in a preset time window, receive signals from other price tags to locate neighboring price tags, determine the neighboring price tag information of each electronic price tag based on the signals to locate neighboring price tags, and send it to the electronic price tag base station; The arrival angle positioning unit is used to determine multiple preliminary positioning positions of each electronic price tag as arrival angle positioning results based on the arrival angle of the electronic price tag signal, as well as the position and height of the electronic price tag base station. The neighbor positioning unit is used to determine the neighbor relationships of all electronic price tags based on the neighbor price tag information of each electronic price tag, and use this as the neighbor positioning result. An optimization unit is used to filter multiple preliminary positioning positions of each electronic price tag according to the neighbor relationship to obtain an optimized positioning position for each electronic price tag. as well as A sending unit is used to send the optimized location and neighbor relationships of each electronic shelf label to a map server. The map server is used to: predict the preliminary product display location aggregation result of each electronic shelf label within the preset product display location range based on the optimized location of each electronic shelf label; map the preliminary product display location aggregation result onto a supermarket map image; and optimize the preliminary product display location aggregation result of each electronic shelf label in the supermarket map image based on one or any combination of the following factors to obtain the optimized product display location aggregation result of each electronic shelf label: the neighbor relationships, the actual distance between the optimized location of each electronic shelf label and the preset product display location, the matching degree between the category of the preset product display location and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display location to the number of aggregated electronic shelf labels. The optimized product display location aggregation result represents the location result of the product bound to the electronic shelf label.

18. A map server for locating items within a store, the map server comprising: include: The second acquisition unit is used to acquire the optimized location and neighbor relationships sent by a cloud-based positioning server; The cloud-based positioning server is used to: determine multiple preliminary positioning positions for each electronic price tag as angle-of-arrival positioning results based on the angle of arrival of the electronic price tag signal and the location and altitude of the electronic price tag base station; determine the neighbor relationships of all electronic price tags as neighbor positioning results based on the neighbor information of each electronic price tag; filter the multiple preliminary positioning positions of each electronic price tag according to the neighbor relationships to obtain the optimized positioning position of each electronic price tag; the angle of arrival of each electronic price tag signal and the neighbor information are sent by the electronic price tag base station, which is used to: determine the angle of arrival of each electronic price tag signal based on the signal used to measure the angle of arrival; each electronic price tag is used to: transmit the signal used to measure the angle of arrival at preset time intervals; send the signal used to locate neighbor price tags in a preset time window, receive the signal used by other price tags to locate neighbor price tags, determine the neighbor information of each electronic price tag based on the signal used to locate neighbor price tags, and send it to the electronic price tag base station; The preliminary collection unit is used to predict the preliminary product display position collection result of each electronic price tag within the preset product display position range based on the optimized positioning position of each electronic price tag; The mapping unit is used to map the preliminary product display location aggregation results onto the supermarket map image; as well as The optimization positioning unit is used to optimize the preliminary product display location aggregation results of each electronic shelf label in the supermarket map image based on one or any combination of the following factors, to obtain the optimized product display location aggregation result for each electronic shelf label: the neighbor relationship, the actual distance between the optimized positioning position of each electronic shelf label and the preset product display position, the matching degree between the category of the preset product display position and the category of the product bound to the electronic shelf label, and the ratio of the area of ​​the preset product display position to the number of aggregated electronic shelf labels; the optimized product display location aggregation result represents the positioning result of the product bound to the electronic shelf label.

19. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the method of any one of claims 1 to 15.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 15.

21. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 15.

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