Intelligent electronic price tag management system

Abstract

The invention relates to the technical field of internet management platforms, and discloses an intelligent electronic price tag management system which comprises a mobile terminal application, a WEB terminal, a server background, a Wi F i base station, an acquisition program, a PC terminal database, electronic price tag equipment, an SaaS system and a CDN server. The mobile terminal application comprises an i OS APP, an Android APP and a WeChat applet; the WEB end is used for background management, configuration operation and instruction control; the server background is based on a cloud computing architecture and is responsible for data processing, storage and multi-tenant data isolation management; the Wi F i base station is used for wireless communication connection, and the electronic price tag equipment is connected with other components of the system; the collection program automatically collects commodity data from a store ERP system through the Internet of Things technology; the PC end database is used for storing pictures, videos, template background pictures and multimedia contents of commodities; and the electronic price tag equipment receives and displays the graphic and text information through a wireless network. The method has the advantages of being efficient, flexible and easy to manage, and supporting dynamic price adjustment and multimedia content display.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet management platforms, and more specifically to an intelligent electronic price tag management system. Background Art

[0002] With the continuous development of the retail industry and the diversification of market demands, the traditional price tag management method has become increasingly unsuitable for the rapidly changing environment. The traditional method usually relies on manual updating of price tags, which is not only time-consuming but also error-prone. Especially when dealing with a large number of products and frequent price adjustments, the error rate is relatively high, resulting in a poor customer experience and even affecting sales and brand image. As consumers' requirements for the shopping experience become higher and higher, retailers need to be able to update product information in a timely and accurate manner, and display clear and dynamic price, promotion and other information, so as to enhance customers' purchase decisions and satisfaction. Although the existing electronic price tag systems in the market can improve management efficiency to a certain extent, most of them lack sufficient flexibility and integration, and cannot effectively meet the rapidly changing market demands. For example, existing systems often cannot reflect dynamic information such as price changes and promotion activities in real time, resulting in lagging price updates and unable to meet retailers' requirements for high efficiency, accuracy and flexibility. In addition, these solutions usually have deficiencies in multi-channel management, system integration, data synchronization, etc., and cannot achieve unified management across platforms and real-time data updates, further increasing the complexity of operations. Therefore, it is necessary to design an intelligent electronic price tag management system that is efficient, flexible and easy to manage. Summary of the Invention

[0003] (1) Technical Problems to be Solved

[0004] In view of the deficiencies of the prior art, the present invention provides an intelligent electronic price tag management system, which has the advantages of high efficiency, flexibility and easy management, supports dynamic price adjustment and multimedia content display, and solves the problems in the above background art.

[0005] (2) Technical Solutions

[0006] To achieve the above-mentioned purpose of high efficiency, flexibility and easy management, and supporting dynamic price adjustment and multimedia content display, the present invention provides the following technical solutions: An intelligent electronic price tag management system includes a mobile application, a WEB end, a server background, a WiFi base station, a collection program, a PC-side database, an electronic price tag device, a SaaS system and a CDN server;

[0007] The mobile application includes iOS APP, Android APP and WeChat mini-program, which serves as the main interface for users to initiate instructions and supports data interaction with other components of the system;

[0008] The WEB terminal is used for background management, configuration operations, and instruction control. It supports providing independent management services for multiple users through the SaaS model. The WEB terminal is connected to the SaaS system, responsible for management and instruction transmission, and passes operation instructions to the electronic price tag device. The WEB terminal can also obtain real-time data from the server background and perform visual display;

[0009] The server background is based on a cloud computing architecture, responsible for data processing, storage, and multi-tenant data isolation management. After the server background processes and stores data, it synchronizes the data to the WEB terminal, mobile application, and WiFi base station as needed;

[0010] The WiFi base station is used for wireless communication connection, connecting the electronic price tag device to other components of the system, supporting real-time data transmission. The data transmitted from the server background and the WEB terminal to the electronic price tag device arrives and is displayed in real time;

[0011] The collection program automatically collects product data from the store ERP system through Internet of Things technology, obtains product information and price data in real time, automatically collects product data from the store ERP system through Internet of Things technology, obtains product information and price data in real time, and the collected data will be transmitted to the database for storage and processing;

[0012] The PC terminal database is used to store pictures, videos, template background pictures, and multimedia content of products, and synchronize data with the server background. Through synchronization operations, the data is transmitted to the server background for processing and storage. The multimedia content is also managed here and provided to the electronic price tag device for display;

[0013] The electronic price tag device receives and displays graphic and text information through wireless network, supports dynamic display of images and multimedia content. The electronic price tag device receives data from the WiFi base station and displays updated product information, prices, and promotional activities through the display screen;

[0014] The multi-tenant management service is provided through the SaaS model, allowing multiple users to independently manage product data, display templates, and device configurations;

[0015] The CDN server is used to accelerate the distribution of image and video content.

[0016] Preferably, the management system further includes:

[0017] Users initiate placement instructions through the mobile application or the WEB terminal. The instructions include display requirements for product information, prices, and graphic and text content;

[0018] The system obtains product data from the store ERP system through the collection program and processes it in the server background to generate graphic and text information and multimedia content;

[0019] The generated images and multimedia content are transmitted in real time to the corresponding electronic price tag devices through a WiFi base station and are displayed after being decoded by the devices.

[0020] Preferably, the system further includes obtaining product data from the store ERP system through a collection program:

[0021] Using machine learning algorithms to automatically generate product graphic and text information, with image generation using TensorFlow or PyTorch, and using OpenCV for image optimization and processing. The generated graphic and text information needs to match the product data. The matching degree between the image and the text is quantified through multimodal learning. The image and the text are mapped to a common feature space through a deep neural network, and the matching effect is quantified by calculating their similarity. The formula is:

[0022] Similarity(I,T)=cos(f image ,f text )

[0023] In the formula, f image is the feature vector of the image, and f text is the feature vector of the text, and their matching degree is calculated using cosine similarity.

[0024] Preferably, the management system adopts the SaaS model, supports multi-tenant management, allows different users to independently manage their own product data, electronic price tag devices, and display templates, automatically docks with the store ERP system through Internet of Things technology, and synchronizes product data in real time, including price changes and inventory information. It provides multiple price display modes, including retail price, member price, and special price, and supports setting the time range for special price products. The system includes a template editing function that allows users to customize product information, graphic and text content, and layout templates according to product attributes, promotional information, and display requirements. Through the combination of Internet of Things technology and the SaaS model, product data is automatically collected, dynamic price changes are made, and multimedia content is matched.

[0025] Preferably, the mobile application interacts with the WEB side, the server background, and the collection program through the Internet, and supports real-time updates and dynamic configuration.

[0026] Preferably, the electronic price tag device receives graphic and text information and multimedia data through a WiFi base station and displays them on the electronic price tag screen in real time.

[0027] Preferably, the PC-side database is used to store product pictures, videos, multimedia content, and template background pictures, and supports real-time data synchronization with the server background.

[0028] (III) Beneficial effects

[0029] Compared with the prior art, the present invention provides an intelligent electronic price tag management system, which has the following beneficial effects:

[0030] The present invention combines Internet of Things technology and SaaS mode to achieve automated data collection, price change and multimedia content matching; an efficient information transmission mechanism ensures the timeliness and accuracy of price information, improving operation efficiency and service quality.

[0031] 1. Real-time price updates ensure that customers can always see the latest prices and promotional information, reducing dissatisfaction caused by price inconsistencies. The multimedia display function can also enhance the attractiveness of products and increase the desire to purchase.

[0032] 2. Traditional paper label replacement is time-consuming and laborious, while intelligent electronic price tags can be remotely updated with one key, greatly improving work efficiency and reducing labor costs.

[0033] 3. By using the data analysis function, merchants can flexibly adjust pricing strategies based on sales data and implement precision marketing, thus gaining an advantage in the highly competitive market.

[0034] 4. Reducing paper usage helps protect the environment. In addition, modern electronic price tags usually adopt low-power designs, having less impact on energy consumption.

[0035] 5. Combined with mobile applications, consumers can obtain more product information by scanning the QR code on the electronic price tag, participate in interactive activities, and increase brand loyalty.

[0036] 6. The data collected can help merchants better understand consumer behavior and make more informed business decisions, such as which products should be promoted and when to adjust prices. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic structural diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] The present invention provides a technical solution: an intelligent electronic price tag management system, including a mobile application, a WEB terminal, a server background, a WiFi base station, a collection program, a PC terminal database, an electronic price tag device, a SaaS system, and a CDN server;

[0040] The mobile applications include iOS APP, Android APP and WeChat Mini Programs. As the main interface for users to initiate instructions, they support data interaction with other components of the system.

[0041] The WEB side is used for background management, configuration operations and instruction control. It supports providing independent management services for multiple users through the SaaS model. The WEB side is connected to the SaaS system, responsible for management and instruction transmission, and passes operation instructions to the electronic price tag devices. The WEB side can also obtain real-time data from the server background and perform visual display.

[0042] The server background is based on the cloud computing architecture, responsible for data processing, storage and multi-tenant data isolation management. After the server background processes and stores the data, it synchronizes the data to the WEB side, mobile applications and WiFi base stations as needed.

[0043] The WiFi base station is used for wireless communication connection, connecting the electronic price tag devices with other components of the system, supporting real-time data transmission. The data transmitted from the server background and the WEB side to the electronic price tag devices arrives and is displayed in real time. In some scenarios, it can also be used as a relay server or a server deployed in the internal network.

[0044] The collection program automatically collects commodity data from the store ERP system through Internet of Things technology, obtains commodity information and price data in real time, automatically collects commodity data from the store ERP system through Internet of Things technology, obtains commodity information and price data in real time, and the collected data will be transmitted to the database for storage and processing.

[0045] The PC-side database is used to store pictures, videos, template background pictures and multimedia content of commodities, and synchronize data with the server background. Through synchronization operations, the data is transmitted to the server background for processing and storage. The multimedia content is also managed here and provided to the electronic price tag devices for display.

[0046] The electronic price tag devices receive and display graphic and text information through wireless networks, supporting dynamic display of images and multimedia content. The electronic price tag devices receive data from the WiFi base station and display updated commodity information, prices, and promotional activities through the display screen.

[0047] Provide multi-tenant management services through the SaaS model, allowing multiple users to independently manage commodity data, display templates, and device configurations.

[0048] The CDN server is used to accelerate the distribution of image and video content.

[0049] The management system further includes that the user issues a placement instruction through the mobile application or the WEB side, and the instruction includes the display requirements of product information, price, and graphic and text content; the system obtains product data from the store ERP system through a collection program, processes it in the server background, and generates graphic and text information and multimedia content; the generated images and multimedia content are transmitted to the corresponding electronic price tag devices in real time through the WiFi base station, and the devices display after decoding. The WiFi base station not only has a transmission function but also is a distributed processor, realizing decentralized processing and significantly reducing the server bandwidth load.

[0050] The system obtaining product data from the store ERP system through a collection program further includes:

[0051] Automatically generating product graphic and text information using machine learning algorithms. Image generation uses TensorFlow or PyTorch, and OpenCV is used for image optimization and processing. The generated graphic and text information needs to match the product data. The matching degree between the image and the text is quantified through multimodal learning. The image and the text are mapped to a common feature space through a deep neural network, and their similarity is calculated to quantify the matching effect. The formula is:

[0052] Similarity(I,T)=cos(f image ,f text )

[0053] In the formula, f image is the feature vector of the image, and f text is the feature vector of the text, and their matching degree is calculated using cosine similarity.

[0054] Quantification indicators:

[0055] Accuracy: Calculate the matching accuracy of the image and the text to measure whether the generated graphic and text information conforms to the product attributes.

[0056] Recall rate: Evaluate the product types that the graphic and text matching system can cover to ensure that reasonable graphic and text information can be generated for different categories of products.

[0057] Specifically, the management system adopts the SaaS model, supports multi-tenant management, allows different users to independently manage their own product data, electronic price tag devices, and display templates, automatically docks with the store ERP system through Internet of Things technology, and synchronizes product data in real time, including price changes and inventory information. It provides multiple price display modes, including retail price, member price, and special price, and supports setting the time range for special price products. The system includes a template editing function that allows users to customize product information, graphic content, and layout templates according to product attributes, promotional information, and display requirements. Through the combination of Internet of Things technology and the SaaS model, it automatically collects product data, dynamically changes prices, and matches multimedia content. Moreover, for chain supermarkets, this management system also supports the chain headquarters to view the online status of price tag devices in branches, release content, and manage product materials, advertising materials, etc. shared with branches, as well as manage the price tag placement in branches.

[0058] In this implementation plan, based on the SaaS model and Internet of Things technology, the intelligent electronic price tag management system further integrates a number of advanced technical means, improving the intelligence and automation level of the system. The system integrates big data analysis and machine learning technologies, which can optimize dynamic pricing and promotional strategies according to real-time data and historical sales situations, helping retailers make more accurate price adjustments and inventory management. Through real-time data analysis, the system can predict changes in product demand and automatically adjust prices and promotional strategies to adapt to fluctuations in market demand. The system adopts edge computing technology, enabling data processing to be carried out locally, thus reducing latency, improving real-time performance and efficiency, especially suitable for large-scale store environments, and can quickly respond to price changes and product information updates. At the same time, the system supports integration with other devices in the store, such as RFID tags, intelligent sensors, etc., further enhancing the ability to collect and synchronize product data, ensuring the accuracy and consistency of product information. The intelligent algorithm embedded in the system can automatically adjust the display template and content according to different product attributes, promotional rules, seasonal changes, etc. Through multimedia processing technology, the system can match high-definition images, videos, or animations for each product to better display product features and promotional information, enhancing the shopping experience of consumers. The system has powerful permission control and security management functions to ensure that each tenant can independently manage their own data, preventing data leakage and operational errors. Through cloud storage and backup technology, the system can ensure the high availability and reliability of data, and at the same time support unified management and real-time updates across regions and stores, ensuring that all stores can synchronize and display the latest product information in a timely manner. Through the combination of the SaaS model, Internet of Things, edge computing, big data analysis, and intelligent algorithms, the system provides an efficient, flexible, and intelligent product information management and display solution.

[0059] Specifically, the mobile application conducts data interaction with the WEB side, the server background, and the collection program through the Internet, supports real-time updates and dynamic configuration, uses RESTful API, GraphQL, and WebSocket technologies to support real-time data interaction between the mobile side and the WEB side, combines real-time data stream technology, supports the update requests initiated by the mobile side to be synchronized to the background in a timely manner, and feeds back to the terminal through the WebSocket push protocol. The OAuth 2.0 protocol is used for user identity authentication and authorization, and stateless authentication and encrypted communication are achieved in combination with JWT.

[0060] In this implementation, the mobile application conducts data interaction with the WEB side, the server background, and the acquisition program via the Internet, achieving a high degree of real-time performance and dynamic configuration capabilities. In addition to RESTful API, GraphQL, and WebSocket technologies, the system also combines multiple technical means to ensure the efficiency, security, and reliability of data transmission. The real-time data stream technology enables the system to transmit a large amount of real-time data in an efficient manner, which is particularly suitable for frequently changing information such as price updates and inventory synchronization. By integrating streaming processing frameworks (such as Apache Kafka, Apache Flink, etc.), the system can process and analyze data streams from multiple stores and devices, make quick responses, and synchronize them to the mobile side. To ensure the efficiency and low latency of data transmission, the system adopts message queue technologies (such as RabbitMQ, Kafka, etc.) to asynchronously process update requests and data pushes through message queues, ensuring the reliability of data transmission and the high concurrency performance of the system. In terms of data security, the system uses the OAuth 2.0 protocol for user authentication and authorization, combined with JWT (JSON Web Tokens) to achieve stateless authentication, ensuring that the identity of the user can be verified efficiently and securely for each request. The use of JWT makes the communication between the mobile side and the background more concise and fast, while supporting encrypted communication to protect sensitive data from being leaked. In addition, the TLS / SSL protocol is used for encrypted data transmission between the mobile side and the WEB side, further enhancing data security and preventing man-in-the-middle attacks and data tampering. The system also uses API gateway technologies (such as Kong, Nginx, etc.) for request routing, load balancing, and security protection, improving the performance and security of API calls. The API gateway not only supports the unified management of requests but also can perform traffic control, speed limiting, and prevent malicious requests to ensure the stable operation of the system. To achieve a high degree of scalability, the system adopts a microservices architecture in its design, enabling each service module to be independently extended and deployed. Through containerization technologies (such as Docker) and container orchestration tools (such as Kubernetes), the system can ensure efficient resource management and automated operation and maintenance during large-scale deployment. The system combines real-time data stream technology, message queues, OAuth 2.0, JWT, TLS / SSL, API gateways, microservices architecture, and containerization technology, making the data interaction between the mobile side and the WEB side more efficient, secure, and reliable, ensuring large-scale real-time data synchronization and the scalability of the system.

[0061] Specifically, the electronic price tag device receives graphic and text information and multimedia data through a WiFi base station and displays it on the electronic price tag screen in real time. It uses the MQTT protocol for low-power and low-latency data transmission. The electronic price tag device is embedded with a hardware decoding module that supports the decoding of JPEG and PNG image formats and also supports video playback and dynamic display of multimedia files. Based on LoRa or Zigbee low-power wireless communication technology, it combines with the IoT management platform for remote management and status monitoring of the device.

[0062] In this implementation, the intelligent power management technology is a key component of the system. To ensure the long-term operation of the electronic price tag device, especially in relatively remote or unmanned environments, the device is built with a dynamic power consumption regulation system that intelligently adjusts power consumption according to the display content and device activities. In the non-display or low-activity state, the device can enter the low-power mode to extend the battery life. The device supports edge computing technology. By processing some data at the electronic price tag device end, it can reduce data transmission latency and load. In this way, the processing of graphic content and multimedia data can be completed at the device end, and only necessary data or instructions will be uploaded to the cloud or management platform, thus improving the response speed and reducing the bandwidth requirement. To ensure efficient communication between the device and the management platform, the system also uses data compression and transmission optimization algorithms, such as image compression technologies (e.g., WebP or HEIF) and streaming media protocols (such as HLS or DASH) to optimize the transmission speed of image and video content. The compressed data occupies less bandwidth during transmission, ensuring efficient and stable data transmission even in low-bandwidth environments. The adaptive display technology enables the electronic price tag device to automatically adjust the screen brightness and contrast according to different environmental lighting conditions, thereby improving visibility and reducing energy consumption. In strong light, the device will automatically increase the display brightness, while in a dark environment, it will reduce the brightness to adapt to different working scenarios. To further enhance the intelligence and manageability of the device, the system integrates AI algorithms for automatic fault detection and early warning of the device. By continuously monitoring the device status, sensor data, and network connection status, the AI module can automatically identify device failures or communication problems and issue early warnings in advance, reducing manual intervention and fault handling time. In terms of device management and remote monitoring, combined with the Internet of Things management platform, the device supports real-time OTA (Over-the-Air) remote updates. By remotely pushing firmware updates, it simplifies the device maintenance and upgrade process. In addition, the device can also transmit status information in real time, such as battery power, screen health, network connection status, etc., to help managers manage and schedule devices more efficiently. The multi-protocol support of the system (such as WiFi, LoRa, Zigbee) ensures that the device can work stably in different communication environments and supports a hybrid network architecture. That is, when some devices perform high-bandwidth data transmission through WiFi, other devices can perform long-distance, low-power communication through LoRa or Zigbee, maximizing the network coverage and flexibility. The electronic price tag device adopts technical means such as intelligent power management, edge computing, data compression, streaming media optimization, adaptive display, AI fault detection, OTA remote updates, and multi-protocol support, which not only improve the performance, stability, and display effect of the device, but also optimize the device management and maintenance process, providing retailers with an efficient, intelligent, and easy-to-manage solution.

[0063] Specifically, the PC-side database is used to store product pictures, videos, multimedia content, and template background images, supports real-time data synchronization with the server background, uses a distributed storage system for large-capacity storage of product pictures and videos, combines object storage services for data backup and efficient reading, synchronizes the PC-side database with the cloud database in real time through the ETL process, uses the Kafka stream processing framework, combines big data analysis frameworks, analyzes and tags the multimedia content of products, and supports subsequent data mining and intelligent recommendation.

[0064] In this implementation plan, the system adopts a distributed file system (such as Ceph, HDFS, or GlusterFS) to handle the storage of large-capacity commodity pictures, videos, and other multimedia files. This technology can distribute data across multiple nodes to achieve high availability, scalability, and fault tolerance, ensuring the stability of large-scale data storage. Object storage services (such as Amazon S3, Alibaba Cloud OSS, Google Cloud Storage) are used to handle large amounts of unstructured data and can achieve efficient reading and backup. The scalability and low-cost characteristics of object storage are suitable for storing and managing massive multimedia content and support on-demand expansion. The system uses the ETL process to synchronize the PC-side database with the cloud database in real time. The ETL process ensures the accurate transfer of commodity data and multimedia content, and performs cleaning and format standardization during the data conversion process to avoid data redundancy and consistency issues. During the data synchronization process, incremental data synchronization and change data capture technologies are combined to only synchronize the changed data, reducing the transmission load and improving real-time performance. The Kafka stream processing framework, as a message queue system, processes high-throughput data streams and supports the real-time transmission of commodity multimedia content and its associated data. The efficient data transmission ability of Kafka ensures the rapid flow of data between the PC side and the cloud, supporting large-scale real-time processing. In cooperation with a stream processing engine (such as Apache Flink, Apache Storm, etc.), Kafka can process commodity data streams in real time, including real-time updates of pictures, videos, and other media content, tag generation, etc. Big data analysis frameworks (such as Apache Spark, Hadoop, etc.) perform in-depth analysis and processing on the commodity multimedia content. Through machine learning algorithms and natural language processing technologies, the system can automatically perform image recognition, video content analysis, semantic understanding, etc. on the multimedia content to generate accurate tags and metadata, improving the accuracy of commodity information. The intelligent recommendation engine provides personalized recommendations based on user behavior data, commodity tags, association rules, etc. Combining big data analysis and machine learning algorithms, the recommendation system can be continuously optimized and automatically adjust the recommendation strategy according to the user's interests and needs, improving the user experience and sales conversion rate. To ensure data security and high availability, the system adopts a multi-region data backup and disaster recovery mechanism. Even if a storage node fails, the data can be restored through other backup nodes to ensure the continuous availability of the system. Combining an automated backup strategy, the system can regularly back up commodity multimedia data and database content and quickly perform recovery operations in case of data loss or damage to ensure data integrity. To facilitate operation and management personnel to monitor data flow, storage capacity, and the update status of multimedia content, the system integrates data visualization tools (such as Grafana, Kibana, etc.) to provide a real-time monitoring dashboard.Through these visualization tools, operators can quickly understand the system performance, storage usage, and synchronization status of multimedia content, ensuring the stable operation of the system. Combined with anomaly detection algorithms, the system can automatically detect and alert potential storage or data synchronization problems, and take timely measures to avoid data loss or delays.

[0065] To ensure the efficient interaction and independence between different system modules, the system adopts a microservices architecture. Each functional module (such as product management, recommendation engine, multimedia content processing) runs as an independent service and communicates through RESTful APIs, ensuring the flexibility and scalability of the system. Combined with API gateway technologies (such as Kong, Nginx, etc.), load balancing, traffic control, and permission management can be achieved, improving the reliability and security of the system.

[0066] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise", or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or device.

[0067] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Intelligent electronic price tag management system, characterized by: Including mobile applications, WEB terminals, server backends, WiFi base stations, collection programs, PC databases, electronic price tag equipment, SaaS systems and CDN servers; The mobile applications include iOS APP, Android APP and WeChat applet, which serve as the main interface for users to initiate commands and support data interaction with other components of the system; The WEB end is used for background management, configuration operation and command control, and supports providing independent management services for multiple users through the SaaS model. The WEB end is connected to the SaaS system, responsible for management and command transmission, and transmits operation instructions to the electronic price tag device. The WEB end can also obtain real-time data from the server background and display it visually; The server backend is based on a cloud computing architecture and is responsible for data processing, storage and multi-tenant data isolation management. After the server backend processes and stores the data, it synchronizes the data to the WEB terminal, mobile terminal application and WiFi base station as needed; The WiFi base station is used for wireless communication connection, connecting the electronic price tag device with other components of the system, supporting real-time data transmission, and the data transmitted from the server backend and WEB end to the electronic price tag device by the WiFi base station arrives and is displayed in real time; The collection program automatically collects commodity data from the store ERP system through the Internet of Things technology, obtains commodity information and price data in real time, and automatically collects commodity data from the store ERP system through the Internet of Things technology, obtains commodity information and price data in real time, and the collected data will be transmitted to the database for storage and processing; The PC database is used to store pictures, videos, template background images and multimedia content of the goods, and synchronize data with the server background. Through synchronization operations, the data is transmitted to the server background for processing and storage. The multimedia content is also managed here and provided to the electronic price tag device for display; The electronic price tag device receives and displays graphic information through a wireless network, supports dynamic display of images and multimedia content, and receives data from a WiFi base station and displays updated product information, prices, and promotions through a display screen; The multi-tenant management service is provided through the SaaS model, allowing multiple users to independently manage product data, display templates, and device configurations; The CDN server is used to accelerate the distribution of image and video content.

2. The intelligent electronic price tag management system according to claim 1, characterized in that: The management system further comprises: The user initiates a delivery instruction through a mobile application or a web terminal, and the instruction includes the display requirements of product information, price, and graphic content; The system obtains product data from the store ERP system through a collection program and processes it in the server background to generate graphic information and multimedia content; The generated images and multimedia contents are transmitted to the corresponding electronic price tag devices in real time via WiFi base stations, and the devices decode and display them.

3. The intelligent electronic price tag management system according to claim 1, characterized in that: The system further comprises: obtaining commodity data from the store ERP system through a collection program; Use machine learning algorithms to automatically generate product image and text information. TensorFlow or PyTorch is used for image generation, and OpenCV is used for image optimization and processing. The generated image and text information needs to match the product data. Multimodal learning is used to quantify the matching degree between image and text. The image and text are mapped to a common feature space through a deep neural network, and the matching effect is quantified by calculating their similarity. The formula is: Similarity(I,T)=cos(f image ,f text ) In the formula, f image is the feature vector of the image, f text is the feature vector of the text, and their matching degree is calculated using cosine similarity.

4. The intelligent electronic price tag management system according to claim 2, characterized in that: The management system adopts the SaaS model, supports multi-tenant management, allows different users to independently manage their own product data, electronic price tag devices and display templates, and automatically connects with the store ERP system through the Internet of Things technology to synchronize product data in real time, including price changes and inventory information. It provides a variety of price display modes, including retail prices, member prices, special prices, and supports time range settings for special products. The system includes a template editing function that allows users to customize product information, graphic content and layout templates based on product attributes, promotional information and display requirements. Through the combination of Internet of Things technology and the SaaS model, product data is automatically collected, prices are dynamically changed and multimedia content is matched.

5. The intelligent electronic price tag management system according to claim 1, characterized in that: The mobile application interacts with the WEB side, server background, and collection program through the Internet, supports real-time updates and dynamic configuration, uses RESTful API, GraphQL, and WebSocket technologies to support real-time data interaction between the mobile and WEB sides, and combines real-time data streaming technology to support timely synchronization of update requests initiated by the mobile side to the background, and feedback to the terminal through the WebSocket push protocol. It uses the OAuth 2.0 protocol for user authentication and authorization, and combines JWT to achieve stateless authentication and encrypted communication.

6. The intelligent electronic price tag management system according to claim 1, characterized in that: The electronic price tag device receives graphic information and multimedia data through a WiFi base station and displays it on the electronic price tag screen in real time. The MQTT protocol is used for low-power, low-latency data transmission. The electronic price tag device has an embedded hardware decoding module that supports decoding of JPEG and PNG image formats, and supports video playback and dynamic display of multimedia files. It is based on LoRa or Zigbee low-power wireless communication technology and combined with the IoT management platform for remote management and status monitoring of the device.

7. The intelligent electronic price tag management system according to claim 1, characterized in that: The PC-side database is used to store product images, videos, multimedia content and template background images, supports real-time data synchronization with the server background, uses a distributed storage system to store large-capacity product images and videos, and combines object storage services for data backup and efficient reading. The PC-side database and the cloud database are synchronized in real time through the ETL process, and the Kafka stream processing framework is used in combination with the big data analysis framework to analyze and label the multimedia content of the product, supporting subsequent data mining and intelligent recommendations.

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