Agricultural product wholesale market transaction management system and method

Abstract

The invention discloses an agricultural product wholesale market transaction management system and method, and the method comprises the steps: a commercial tenant and a user register real-name authentication on a platform, a seller uploads and updates the information of agricultural products, and a buyer selects a commodity and fills in an order; multiple payment channels are integrated, a settlement bill is automatically generated for fund settlement, sales and price data are collected, and the market trend is analyzed by using big data; the purchase trend is predicted according to the transaction record and the buyer preference, and replenishment suggestions are automatically generated; transaction data is encrypted by SSL and protected by multiple identity authentication, and transaction monitoring abnormity is recorded by the block chain; an APP and a Web end are provided, and personalized setting and 24 / 7AI customer service are supported; the performance of the system is evaluated in each quarter, functions are optimized according to feedback, and a modular framework is adopted for flexible expansion; according to the agricultural product wholesale market transaction management system and method, an AI technology is introduced, demand changes are automatically identified, inventory and supply chain scheduling are optimized, and pricing and customer prediction intelligent suggestions are provided.

Description

Technical Field

[0001] The present invention belongs to the field of trading management in agricultural product wholesale markets, and particularly relates to a trading management system and method for agricultural product wholesale markets. Background Art

[0002] The trading management system for agricultural product wholesale markets is an information management tool specifically designed for agricultural product wholesale markets, used to realize the intelligent, standardized, and automated management of market transactions. It helps managers, merchants, and customers operate more efficiently in aspects such as transactions, settlements, inventories, transportation, and quality supervision through technical means, records and manages various transaction information, including both buyers and sellers, types of goods, quantities, prices, etc., supports the unified management of online and offline transaction information; tracks all aspects of order creation, processing, shipping, receipt, etc., to ensure the efficiency and accuracy of order execution; supports multiple payment methods, provides settlement and account management functions, and simplifies the financial process of transactions; helps merchants manage product inventories, monitors inventory levels in real-time, and avoids inventory backlogs or shortages; provides information management for transportation and distribution to ensure the smooth logistics of agricultural products from the market to customers; automatically generates reports on transactions, sales, inventories, etc., to help managers make decisions and adjust market strategies; through the product information traceability system, ensures the traceability of the sources and quality of agricultural products, and enhances the credibility of the market.

[0003] However, existing systems may lack sufficient intelligent data analysis and decision support functions, and cannot effectively provide real-time market trend analysis, consumer behavior prediction, commodity price fluctuations, etc., resulting in insufficient decision support for management. Summary of the Invention

[0004] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a trading management system and method for agricultural product wholesale markets, introduce AI technology, automatically identify changes in market demand, optimize inventory management and supply chain scheduling, and even provide intelligent suggestions in aspects such as price pricing and customer prediction.

[0005] The technical solution adopted by the present invention to solve its technical problems is:

[0006] A trading management system for agricultural product wholesale markets, comprising:

[0007] A transaction management module, used to process transaction information, introduce smart contract technology, automate transaction execution and settlement, adopt an online and offline hybrid trading method, where merchants perform transaction operations through mobile or PC terminals, and integrate a payment platform, with multiple payment methods set;

[0008] Order and Inventory Management Module, which is used to handle the merchant's product management, order allocation, and inventory monitoring. It introduces Internet of Things technology and RFID devices to track products in real time, adopts automated inventory management, and sets up an intelligent system for optimization;

[0009] Data Analysis and Decision Support Module, which is used to generate real-time market data analysis and prediction, assist the decision-making level in optimizing market strategies, integrate big data analysis and machine learning technologies, conduct market trend prediction, price fluctuation analysis, and consumer behavior analysis, and display market dynamics to managers through visual reports and real-time monitoring;

[0010] Security and Permission Management Module, which is used to protect system data security, transaction security, and user privacy. It uses SSL encryption technology to encrypt transaction data and sets up a multi-level permission management system;

[0011] Supply Chain Management Module, which is used to improve the agricultural product supply chain management, integrate supply chain information, track the origin and flow of products in real time through Internet of Things technology and RFID, and the intelligent scheduling system automatically selects suppliers and transportation routes according to order requirements and generates a supply chain optimization report;

[0012] User Experience and Interface Optimization Module, which is used to enhance the user-friendliness of the system, design a simple and intuitive user interface, adopt personalized settings, and allow merchants to customize their own transaction processes according to their needs;

[0013] Intelligent Customer Service and Support Module, which is used to provide 24 / 7 customer support and assistance, answer questions encountered by users during the transaction process, and introduce AI customer service to provide instant responses to merchants and buyers.

[0014] A trading management method for an agricultural product wholesale market, including:

[0015] Merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update inventory status. Buyers browse the products on the platform, select the required products, and fill in order information;

[0016] Among them, the payment link integrates multiple payment channels, automatically generates settlement statements according to the agreed settlement cycle, conducts fund settlement with buyers and sellers, automatically collects product sales volume, price fluctuation transaction data through API interfaces, and uses big data analysis technology to identify and analyze market trends;

[0017] Track according to the buyer's purchase preferences and the historical transaction records of both buyers and sellers, analyze market demand and predict future procurement trends, and automatically generate replenishment suggestions based on inventory and sales data;

[0018] Transaction data is encrypted and protected using SSL encryption technology, and multiple identity authentications are implemented. The system records all transaction data through blockchain technology and detects abnormal transactions in real time through data monitoring and analysis;

[0019] It adopts an APP version and a Web terminal, which can be used by users on mobile phones, tablets and computers. Users can customize the system functions according to their personal needs, and provide 24 / 7 AI customer service to answer common questions for users through natural language processing technology;

[0020] Performance evaluation is carried out quarterly to detect the system's response speed, transaction processing ability, and data storage ability, and user research is conducted to collect the usage feedback and suggestions of buyers and sellers, and the system functions are optimized according to the requirements. Based on the modular architecture, it can be flexibly expanded.

[0021] Preferably, merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update the inventory situation. Buyers browse the products on the platform and select the required products. The method of filling in order information is as follows:

[0022] Users and merchants create accounts on the platform, enter name, contact phone number, and email information. Buyers or sellers select the account type, and the system provides different function modules according to the role;

[0023] Users or merchants submit identity verification materials for real-name authentication. The platform administrator reviews the relevant certificates and notifies the review results by text message or email;

[0024] After logging in to the platform, sellers enter the commodity management module and upload information such as the name of agricultural products, commodity description, unit, price, pictures, shelf life, and storage requirements, and regularly update the inventory situation. The platform automatically synchronizes the inventory data or the seller manually updates the inventory quantity;

[0025] Buyers browse agricultural products through the home page or category page of the platform. The system intelligently recommends relevant products based on historical data and preferences. Buyers select the products to purchase, enter the quantity, and add the products to the shopping cart;

[0026] After the buyer confirms the purchase, enter the settlement page and fill in the order information. The order information includes the delivery address, payment method, delivery method, and remarks.

[0027] Preferably, multiple payment channels are integrated in the payment link. According to the agreed settlement cycle, settlement statements are automatically generated and funds are settled with buyers and sellers. The method of automatically collecting product sales volume and price fluctuation transaction data through the API interface and using big data analysis technology to identify and analyze market trends is as follows:

[0028] The system integrates payment channels such as Alipay, WeChat Pay, bank cards, and credit cards, connects to major payment platforms through API interfaces, and adopts a callback mechanism for payment results. After the user completes the payment, the platform automatically confirms the payment status and performs corresponding processing;

[0029] The platform automatically conducts fund settlement according to the daily, weekly, and monthly settlement cycles agreed upon between merchants and buyers, and records relevant information for each transaction, including transaction time, amount, payment channel, and payment status;

[0030] Automatically conducts data interaction with the payment platform, order management system, and inventory management system through API interfaces, and collects data related to product sales volume, transaction price fluctuations, and inventory changes;

[0031] Adopts big data analysis technology to process, mine, and analyze the collected transaction data. The data analysis methods include data cleaning, data mining, and machine learning models to identify market trends and product sales dynamics;

[0032] Adopts time series analysis, regression analysis, clustering analysis machine learning models, and deep learning algorithms for market trend prediction. Based on the big data analysis platform, it quickly processes a large amount of transaction data for real-time data analysis and decision support.

[0033] Preferably, the method of tracking the buyer's purchase preferences and historical transaction records between the buyer and the seller, analyzing market demand, predicting future procurement trends, and automatically generating replenishment suggestions based on inventory and sales data is as follows:

[0034] Collects the buyer's browsing history, purchase records, search behavior, items added to the shopping cart, and favorited items data through the mobile terminal and sensor data, analyzes their purchase preferences and consumption habits, and identifies the buyer's long-term needs through data analysis;

[0035] Collects and integrates the seller's historical transaction data through the e-commerce platform background data, including order amount, sold products, transaction frequency, time period, and product price fluctuations, and classifies and aggregates the historical transaction data;

[0036] Based on the buyer's purchase preferences and historical transaction records, adopts data mining and machine learning technologies to analyze demand trends, and identifies periodic demands and trend changes through time series analysis and regression analysis methods;

[0037] Predicts future demand trends using time series models through the analysis of historical sales data;

[0038] Combines real-time inventory data with demand prediction results, calculates the expected sales volume and inventory gap, automatically calculates the expected out-of-stock products based on historical sales trends and current inventory, and generates replenishment suggestions based on the predicted demand.

[0039] Preferably, the transaction data is encrypted and protected using SSL encryption technology, and multi-factor authentication is implemented. The system records all transaction data through blockchain technology. The method for real-time detecting of abnormal transactions through data monitoring and analysis is as follows:

[0040] The SSL protocol is used to encrypt all transmitted transaction data. Through multi-factor authentication, the system ensures that only legitimate users can access and operate the transaction data;

[0041] Through blockchain technology, each transaction is recorded in the form of a block, and all blocks are connected to the previous block through hash values. The smart contract in the blockchain is used to automatically execute and verify transactions;

[0042] Through the real-time data monitoring and analysis system, detect abnormal behaviors such as excessive transaction amounts or frequent small transaction amounts in transactions. Use machine learning and data analysis models to detect deviations from the normal transaction pattern.

[0043] Preferably, an APP version and a Web version are adopted. Users can use it on mobile phones, tablets, and computers. Users can customize the system functions according to their personal needs, and a 24 / 7 AI customer service is provided. The method for answering common questions for users through natural language processing technology is as follows:

[0044] Adopt cross-platform development frameworks such as React Native, Flutter, or Electron to run the application on mobile phones, tablets, and computers at the same time. The Web version adopts a responsive design to ensure that the interface adapts to mobile phones, tablets, and computer devices;

[0045] Users can customize the interface layout, function modules, and notification methods according to their personal needs. By analyzing the user's historical behavior data, personalized function recommendations are provided to the user. Through machine learning algorithms, set options required by the user are recommended;

[0046] The AI customer service understands and processes user questions through natural language processing technology. The AI customer service is based on a chatbot model to handle common questions and simple customer requests;

[0047] The AI customer service continuously optimizes the answer quality through a machine learning model. As the user interacts, the answer method and the accuracy of the content are gradually adjusted. The AI customer service system gradually improves the answer quality by monitoring and analyzing the user's feedback, and uses sentiment analysis technology to analyze the emotional information in the user's text.

[0048] Preferably, perform performance evaluations quarterly, detect the response speed, transaction processing capabilities, and data storage capabilities of the system, conduct user research, collect usage feedback and suggestions from buyers and sellers, optimize system functions according to requirements, and the method of flexible expansion based on a modular architecture is as follows:

[0049] Use JMeter and LoadRunner performance testing tools to simulate user access, detect the response speed of the system under high concurrency, verify the processing capabilities of the system under a large number of transaction requests through stress testing and load testing, and conduct database performance testing to evaluate the data storage and retrieval capabilities of the system;

[0050] Deploy an application performance management tool for real-time monitoring, and identify potential bottlenecks and anomalies through a log analysis tool;

[0051] Through questionnaires, user interviews, and feedback collection channels, understand the usage requirements and satisfaction of buyers and sellers. By analyzing user behavior data such as page access frequency, click path, and function usage frequency in the system, identify the functions that users care about and system performance bottlenecks;

[0052] Adopt a modular architecture, make the system payment, transaction, inventory management, and user management function modules independent of each other, and optimize certain modules specifically according to quarterly performance evaluations and user feedback;

[0053] Based on a microservices architecture or containerization technology, when the system load increases, perform horizontal expansion by adding microservice instances or expanding containers.

[0054] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements an agricultural product wholesale market transaction management system and method as described in any one of the above.

[0055] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium with a computer program stored thereon. When the program is executed by a processor, it implements an agricultural product wholesale market transaction management system and method.

[0056] The beneficial effects of the present invention are:

[0057] SSL encryption technology ensures the security of transaction data and user information during transmission, avoids the leakage of sensitive data, strengthens the security protection of the platform, prevents unauthorized access and operations, records transaction data through distributed ledger technology, which is tamper-proof, ensures the transparency and credibility of transactions, and also helps prevent fraud; provides multiple payment channels, allowing users to choose the most convenient payment method according to their preferences, improving the convenience of transactions; automatically generates settlement statements and conducts fund settlements according to the agreed settlement cycle, simplifies the settlement process, reduces manual operation errors and management costs; collects transaction data such as sales volume and price fluctuations through API interfaces, and uses big data analysis technology to predict market trends, helping merchants make more informed decisions; analyzes market demand and predicts future procurement trends based on buyers' purchase preferences and transaction history, helping sellers formulate accurate procurement and sales strategies; automatically generates replenishment suggestions based on inventory and sales data, reduces out-of-stock and overstock situations, and improves operational efficiency; users can customize platform functions according to personal needs, enhancing user experience and satisfaction; the AI customer service using natural language processing technology answers common questions for users all day long, reduces the burden on manual customer service, and provides more efficient support; provides an APP version and a Web version, supports various devices such as mobile phones, tablets, and computers, allowing users to operate anytime and anywhere, increasing user convenience; based on a modular architecture, the platform can be flexibly expanded and upgraded according to business needs, continuously optimizing functions, improving the long-term sustainability and adaptability of the system; regularly conducts system performance evaluations, detects response speed, transaction processing capabilities, and data storage capabilities, ensures the platform runs smoothly in a high-concurrency and big-data environment, and provides a smooth user experience. Through data monitoring and analysis technology, abnormal transactions are detected in real time, effectively preventing potential risks and ensuring the healthy operation of the platform; identifying market trends and user needs through big data technology can help merchants flexibly adjust products and services, enhancing market adaptability; the platform adopts a modular architecture, can flexibly expand functions and services according to needs, adapts to business growth of different scales, and maintains a long-term competitive advantage; by integrating multiple technologies and functions, such as big data analysis, blockchain technology, AI customer service, etc., the platform can stand out in the market, enhance competitiveness, and attract more users and merchants to join the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic flow diagram of a trading management system for an agricultural products wholesale market of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0059] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not intended to limit the scope of the present invention. The present invention is described more specifically by way of example in the following paragraphs. The advantages and features of the present invention will be clearer according to the following description and the claims.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0061] Embodiment

[0062] An agricultural product wholesale market transaction management system includes:

[0063] A transaction management module for processing transaction information, introducing smart contract technology to automate transaction execution and settlement, adopting an online-offline hybrid transaction mode, allowing merchants to conduct transaction operations through mobile or PC terminals, integrating a payment platform, and setting up multiple payment methods;

[0064] An order and inventory management module for handling merchants' product management, order allocation, and inventory monitoring, introducing Internet of Things technology and RFID devices to track products in real time, adopting automated inventory management, and setting up an intelligent system for optimization;

[0065] A data analysis and decision support module for generating real-time market data analysis and prediction to assist the decision-making layer in optimizing market strategies, integrating big data analysis and machine learning technologies for market trend prediction, price volatility analysis, and consumer behavior analysis, and presenting market dynamics to managers through visual reports and real-time monitoring;

[0066] A security and permission management module for protecting system data security, transaction security, and user privacy, encrypting transaction data using SSL encryption technology, and establishing a multi-level permission management system;

[0067] A supply chain management module for improving agricultural product supply chain management, integrating supply chain information, tracking the origin and flow of products in real time through Internet of Things technology and RFID, and having an intelligent scheduling system automatically select suppliers and transportation routes according to order requirements and generate a supply chain optimization report;

[0068] A user experience and interface optimization module for enhancing the user-friendliness of the system, designing a simple and intuitive user interface, adopting personalized settings, and allowing merchants to customize their own transaction processes according to their needs;

[0069] An intelligent customer service and support module for providing 24 / 7 customer support and assistance, answering questions encountered by users during transactions, and introducing AI customer service to provide instant responses to merchants and buyers.

[0070] Automatically execute and settle transactions, reduce manual intervention, and improve efficiency and accuracy. Smart contracts ensure that the agreements between both parties are fulfilled, thereby reducing transaction disputes and risks. Support multiple transaction modes, enabling merchants and buyers to flexibly choose transaction methods, which can adapt to both the online e-commerce market and support traditional offline transactions, expanding market coverage. Achieve real-time tracking of products, improve supply chain transparency, and ensure the traceability of product sources and movements. Through Internet of Things devices and RFID technology, monitor inventory in real time, avoid overstocking or out-of-stock situations, and reduce inventory costs. The automated inventory management and order allocation functions can automatically adjust according to demand and inventory conditions, reducing manual operations and improving efficiency. Help merchants and management understand market dynamics in real time and make accurate decisions. Through big data analysis and machine learning technologies, provide market trend predictions, price volatility analysis, and consumer behavior analysis, and clearly display market changes through charts and reports to help decision-makers better understand complex data and quickly identify potential opportunities or risks. Protect sensitive data during transactions, avoid leakage or theft, and ensure transaction security. Through permission control, ensure that different roles (such as merchants, administrators, buyers, etc.) can only access and operate relevant data, improving the security and reliability of the system. Through technical means, track product sources, movements, and inventory status in real time, ensure supply chain transparency, reduce counterfeit and shoddy products, automatically select suppliers and transportation routes according to order requirements, improve the response speed and accuracy of the supply chain, and reduce delays and supply chain bottlenecks. Through careful design, simplify the user operation process and improve the usability of the system. Merchants can customize the transaction process according to their own needs and operation habits, enhancing the flexibility and adaptability of the system. AI customer service provides 24 / 7 support to help merchants and buyers solve common problems and improve the user experience. Through natural language processing (NLP) technology, AI customer service can quickly and accurately answer user questions, reducing the burden on human customer service.

[0071] A trading management method for agricultural product wholesale markets, including:

[0072] Merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update inventory situations. Buyers browse the products on the platform, select the required products, and fill in order information.

[0073] Among them, the payment link integrates multiple payment channels, automatically generates settlement statements according to the agreed settlement cycle, and conducts fund settlements with buyers and sellers. Automatically collects product sales volume, price volatility transaction data through API interfaces, and uses big data analysis technology to identify and analyze market trends.

[0074] Track according to the buyer's purchase preferences and the historical transaction records of both buyers and sellers, analyze market demand and predict future procurement trends, and automatically generate replenishment suggestions based on inventory and sales data.

[0075] Transaction data is encrypted and protected using SSL encryption technology, and multiple identity authentications are implemented. The system records all transaction data through blockchain technology and detects abnormal transactions in real time through data monitoring and analysis.

[0076] The APP version and the Web version are adopted, and users can use them on mobile phones, tablets and computers. Users can customize the system functions according to their personal needs, and 24 / 7 AI customer service is provided to answer common questions for users through natural language processing technology.

[0077] Performance evaluation is carried out quarterly to detect the response speed, transaction processing ability and data storage ability of the system, and user research is carried out to collect the usage feedback and suggestions of buyers and sellers. The system functions are optimized according to the requirements, and based on the modular architecture, it can be flexibly expanded.

[0078] Real-name authentication ensures the legality and authenticity of the identities of merchants and users on the platform, enhances the trust in the market, and reduces counterfeit and shoddy products and fraud; Sellers can update agricultural product information in a timely manner to ensure the accuracy of goods and the real-time nature of inventory, and avoid out-of-stock or expired goods; Multiple payment channels (such as credit cards, online payment, etc.) are integrated to provide a variety of payment options, improving the convenience and security of transactions and meeting the needs of different buyers; Transaction data (such as sales volume, price fluctuations, etc.) is collected through API interfaces, and big data analysis technology is used to identify market trends, consumer behavior and future procurement trends to help merchants formulate accurate market strategies; According to historical sales data, inventory status and market trends, the system automatically generates replenishment suggestions to help merchants maintain inventory balance and avoid out-of-stock or inventory backlog; SSL encryption technology is used to protect the security of transaction data and prevent data from being stolen or tampered with; Blockchain technology ensures the immutability and transparency of transaction data, making every transaction traceable, thereby enhancing the credibility of the platform and preventing fraud; The APP version and the Web version are provided, and users can access the platform on mobile phones, tablets and computers at any time and place, improving the convenience and flexibility of users; Round-the-clock customer support is provided, and the AI customer service can quickly respond and solve common problems, reducing waiting time and improving user satisfaction; System performance evaluation is carried out quarterly to ensure that the response speed, transaction processing ability, data storage, etc. of the platform can meet market requirements; Based on the modular architecture, the system can be flexibly expanded to adapt to merchants of different scales and needs, and can be functionally expanded according to market development and business needs.

[0079] Merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update the inventory situation. Buyers browse the products on the platform and select the products they need. The method of filling in the order information is as follows:

[0080] Users and merchants create accounts on the platform, enter their names, contact numbers, and email information, and buyers or sellers select account types. The system provides different functional modules based on the roles.

[0081] Users or merchants submit identity documents for real-name authentication, and the platform administrator reviews the relevant documents and notifies the review results via SMS or email;

[0082] After the seller logs in to the platform, he / she enters the commodity management module and uploads the name, description, unit, price, picture, shelf life, storage requirements of the agricultural product, and regularly updates the inventory status. The platform automatically synchronizes the inventory data or the seller manually updates the inventory.

[0083] Buyers browse agricultural products through the platform's homepage or category page. The system intelligently recommends related products based on historical data and preferences. Buyers select the products to be purchased, enter the quantity, and add the products to the shopping cart;

[0084] After the buyer confirms the purchase, he / she goes to the checkout page and fills in the order information, which includes the delivery address, payment method, delivery method, and remarks.

[0085] Through account registration, users and merchants can choose different functional modules according to their roles, which improves the system's pertinence and user experience. Buyers and sellers have different needs, and the system provides customized functions through role differentiation, which simplifies the operation process; real-name authentication increases the trust of the platform, ensures the authenticity of the identities of both parties on the platform, and avoids false transactions and fraud; sellers can upload and update agricultural product information in real time, including name, description, price, picture, etc., to ensure that the product information seen by buyers is accurate and up-to-date; the system makes intelligent product recommendations based on buyers' historical data and preferences, which improves the user's purchasing experience, saves buyers' time searching for products, and may lead to additional purchases; the shopping cart function allows buyers to select multiple products and manage them centrally, optimizes the shopping process, and avoids the trouble of adding products repeatedly; the order information generated by the system includes detailed transaction content, helping buyers and sellers to understand the transaction details more clearly and effectively avoid transaction disputes; it provides a variety of payment and delivery methods, allowing buyers to choose the most suitable payment channels and logistics services according to their needs, improving user experience; the system provides corresponding functional modules and operation permissions based on the account type of buyers or sellers, enhancing the flexibility and pertinence of the platform.

[0086] The payment process integrates multiple payment channels, automatically generates settlement orders according to the agreed settlement cycle, and settles funds with buyers and sellers. It automatically collects product sales volume and price fluctuation transaction data through the API interface, and uses big data analysis technology to identify and analyze market trends. The method is as follows:

[0087] The system integrates payment channels such as Alipay, WeChat Pay, bank cards, and credit cards, connects to major payment platforms through API interfaces, and adopts a callback mechanism for payment results. After the user completes the payment, the platform automatically confirms the payment status and conducts corresponding processing;

[0088] The platform automatically conducts fund settlement according to the daily, weekly, and monthly settlement cycles agreed upon between merchants and buyers, and records relevant information for each transaction, including transaction time, amount, payment channel, and payment status;

[0089] Automatically conducts data interaction with the payment platform, order management system, and inventory management system through API interfaces, and collects data related to product sales volume, transaction price fluctuations, and inventory changes;

[0090] Adopts big data analysis technology to process, mine, and analyze the collected transaction data. Data analysis methods include data cleaning, data mining, and machine learning models to identify market trends and product sales dynamics;

[0091] Adopts machine learning models and deep learning algorithms such as time series analysis, regression analysis, and clustering analysis for market trend prediction. Based on the big data analysis platform, it can quickly process a large amount of transaction data for real-time data analysis and decision support.

[0092] Integrating payment channels such as Alipay, WeChat Pay, bank cards, and credit cards can meet the payment habits of different buyers, enhance the user experience, and increase the transaction success rate; Flexible settlement cycle: According to the agreement between merchants and buyers, the system can automatically perform daily, weekly, or monthly settlements, reducing manual operations and ensuring that both parties settle funds on time; Through data interaction with the payment platform, order management system, and inventory management system, it can collect key data such as product sales volume, price fluctuations, and inventory changes in real time, providing accurate data support for decision-making analysis; Through big data analysis technology, valuable business insights can be extracted from historical transaction data to help the platform identify market trends and predict future demand changes; Through machine learning algorithms (such as time series analysis, regression analysis, clustering analysis, etc.), the platform can predict market trends, help merchants adjust inventory, optimize pricing, and formulate promotional strategies; The big data platform can quickly process and analyze a large amount of transaction data, reduce latency, and provide real-time support for decision-making.

[0093] The method of tracking the purchase preferences of buyers and the historical transaction records of both buyers and sellers, analyzing market demand and predicting future procurement trends, and automatically generating replenishment suggestions based on inventory and sales data is as follows:

[0094] Collects buyers' browsing history, purchase records, search behaviors, items added to the shopping cart, and favorited items data through mobile devices and sensor data, analyzes their purchase preferences and consumption habits, and identifies the long-term needs of buyers through data analysis;

[0095] Collect and integrate the historical transaction data of sellers through the back-end data of the e-commerce platform, including order amount, sold goods, transaction frequency, time period, and commodity price fluctuations, and classify and aggregate the historical transaction data;

[0096] Based on the purchase preferences and historical transaction records of buyers, use data mining and machine learning technologies to analyze demand trends, and identify periodic demands and trend changes through time series analysis and regression analysis methods;

[0097] Predict future demand trends using a time series model through the analysis of historical sales data;

[0098] Combine the real-time inventory data with the demand forecast results, calculate the estimated sales volume and inventory gap, automatically calculate the estimated out-of-stock commodities based on the historical sales trend and current inventory, and generate replenishment suggestions based on the predicted demand.

[0099] By tracking inventory and sales data in real time, the system can predict future demand, helping merchants avoid overstocking or out-of-stock problems. The replenishment suggestions are based on accurate forecast data to ensure that inventory matches demand, reducing the risk of inventory backlog and stockouts; by analyzing data such as buyers' browsing history, purchase records, and search behaviors, the long-term demands and consumption habits of buyers can be identified. Merchants can predict the demands of different buyers based on this data and then formulate personalized marketing strategies; through data mining and machine learning technologies (such as time series analysis, regression analysis, etc.), the system can identify periodic demand fluctuations and trend changes. Merchants can adjust procurement plans and inventory strategies based on these predictions to avoid out-of-stock or overstocking; automated replenishment suggestions can help merchants make replenishment decisions quickly, avoiding delays and errors in manual decisions and improving operational efficiency; through accurate forecasting and replenishment suggestions, merchants can stock up in advance when demand is high, avoiding inventory backlogs; while when demand is low, unnecessary inventory purchases can be reduced, improving the efficiency of capital use; by predicting and replenishing the inventory of hot-selling commodities in advance, merchants can avoid out-of-stock situations and ensure that customer demands are met in a timely manner, thereby improving customer satisfaction.

[0100] The transaction data is encrypted and protected using SSL encryption technology, and multiple identity authentications are implemented. The system records all transaction data through blockchain technology. The methods for real-time detecting abnormal transactions through data monitoring and analysis are as follows:

[0101] Use the SSL protocol to encrypt all transmitted transaction data. Through multiple identity authentications, the system ensures that only legitimate users can access and operate the transaction data;

[0102] Through blockchain technology, each transaction is recorded in the form of a block, and all blocks are connected to the previous block through a hash value. The smart contract in the blockchain is used to automatically execute and verify transactions;

[0103] Through a real-time data monitoring and analysis system, detect abnormal behaviors such as excessive transaction amounts or frequent small transaction amounts in transactions. Use machine learning and data analysis models to detect deviations from regular transaction patterns.

[0104] Use the SSL protocol to encrypt all transaction data to ensure the confidentiality and integrity of transaction data during transmission, and prevent data from being stolen or tampered with during transmission; through blockchain technology, all transaction data is stored in the form of blocks, and each transaction is connected to the previous block through a hash value. This makes the transaction record tamper-proof. Once a transaction is recorded on the blockchain, it cannot be modified or deleted. The transparency of transactions has been greatly improved; through the real-time data monitoring system, abnormal activities in transactions can be detected and identified in a timely manner. For example, the system can monitor abnormal behaviors such as large transactions or frequent small transactions, and trigger an alarm or block the transaction immediately when an abnormality is found, which can prevent illegal activities such as money laundering and fraud; the smart contract automatically executes transactions without manual intervention, reducing the time and labor costs of transaction processing. At the same time, it also eliminates human errors or omissions, improving the processing efficiency and accuracy of transactions; since all transactions are recorded on the blockchain, anyone can query the detailed records of historical transactions. This transparency enhances users' trust in the trading platform; blockchain technology can support high-concurrency transactions and large-scale transaction data storage, and the system can be expanded as the transaction volume grows to ensure the continuous and stable operation of the system.

[0105] Use the APP version and the Web side. Users can use it on mobile phones, tablets and computers. Users can customize the system functions according to their personal needs, and provide 24 / 7 AI customer service. The method of using natural language processing technology to answer common questions for users is as follows:

[0106] Use cross-platform development frameworks such as React Native, Flutter or Electron to run the application on mobile phones, tablets and computer terminals at the same time. The Web side adopts a responsive design to ensure that the interface adapts to mobile phones, tablets and computer devices;

[0107] Users can customize the interface layout, function modules, and notification methods according to their personal needs. By analyzing the user's historical behavior data, personalized function recommendations are provided to the user. Through machine learning algorithms, set options that meet the user's needs are recommended;

[0108] The AI customer service understands and processes user questions through natural language processing technology. Based on the chatbot model, the AI customer service handles common questions and simple customer requests.

[0109] The AI customer service continuously optimizes the answer quality through machine learning models. With user interaction, it gradually adjusts the answering style and content accuracy. The AI customer service system improves the answer quality step by step by monitoring and analyzing user feedback, and adopts sentiment analysis technology to analyze the emotional information in user texts.

[0110] Cross-platform development frameworks such as React Native, Flutter, and Electron are used. With these frameworks, applications can run on multiple platforms such as mobile phones, tablets, and computers simultaneously, providing a consistent user experience. Users can adjust the interface layout, select display function modules, set notification methods, etc. according to their own needs and preferences, so as to create a personalized user interface. The AI customer service system can provide services to users 24 / 7, eliminating the time limit of traditional human customer service and enabling users to obtain help and answers at any time. The AI customer service continuously optimizes the answering quality through machine learning. With user interaction, it can gradually adjust the answering style and content accuracy. This continuous optimization mechanism ensures that the AI customer service can adapt to the changing user needs and questions and provide higher and higher quality services. The AI customer service can identify the emotional information in user texts, such as anger, anxiety, joy, etc., through sentiment analysis technology. According to the change of user emotions, the AI customer service can adjust the tone and wording of the answer and provide more empathetic services. Due to the adoption of cross-platform development frameworks and responsive design, the system can flexibly adapt to different devices, operating systems, and screen sizes and provide a consistent experience for users. The personalized customization and AI customer service provided by the system can improve user satisfaction and stickiness, making users more dependent on the platform. As users gradually become familiar with the system, personalized settings and the improvement of AI customer service help increase customer loyalty. The system can more accurately understand user needs and preferences by collecting and analyzing user historical behavior data and provide data support for subsequent optimization.

[0111] Performance evaluations are conducted quarterly to detect the system's response speed, transaction processing ability, and data storage ability, and user research is carried out to collect the usage feedback and suggestions of buyers and sellers. The system functions are optimized according to the requirements. Based on the modular architecture, the flexible expansion method is as follows:

[0112] Use JMeter and LoadRunner performance testing tools to simulate user access situations, detect the system's response speed under high concurrency, verify the system's processing ability under a large number of transaction requests through stress testing and load testing, and conduct database performance testing to evaluate the system's data storage and retrieval ability.

[0113] Deploy application performance management tools for real-time monitoring and use log analysis tools to identify potential bottlenecks and anomalies;

[0114] Through questionnaires, user interviews and feedback collection channels, we understand the usage needs and satisfaction of buyers and sellers. By analyzing the user's page access frequency, click path, and function usage frequency behavior data in the system, we can identify the functions that users care about and the system performance bottlenecks.

[0115] Adopting a modular architecture, the payment, transaction, inventory management, and user management modules of the system are independent of each other, and certain modules are optimized in a targeted manner based on quarterly performance evaluations and user feedback;

[0116] Based on microservice architecture or containerization technology, when the system load increases, horizontal expansion is performed by adding microservice instances or expanding containers.

[0117] By using professional performance testing tools such as JMeter and LoadRunner, it is possible to simulate different numbers of user access and transaction requests, and identify the performance bottlenecks of the system under high concurrency and pressure conditions in advance; through questionnaires, user interviews and feedback collection channels, it is possible to directly collect usage experience, needs and suggestions from buyers and sellers, and timely grasp their concerns and pain points; the use of modular architecture makes the different functions of the system (such as payment, transaction, inventory management, user management, etc.) independent of each other, enhancing the flexibility and scalability of the system; through modular architecture, the independence of each functional module makes optimization and troubleshooting more accurate; through containerization technology and microservice architecture, the system can automatically expand according to real-time load conditions, reducing the need for manual intervention; the modular characteristics of microservice architecture make it possible to flexibly add new functional modules or integrate third-party services in the future, such as adding new payment methods, logistics tracking systems, etc.; through microservice architecture and containerization technology, the system can dynamically allocate computing resources according to actual needs; the independence of each functional module makes security management more efficient.

[0118] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, an agricultural product wholesale market transaction management system and method as described above is implemented.

[0119] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the agricultural products wholesale market transaction management system and method as described above are implemented.

[0120] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0122] The above embodiments of the present invention do not limit the protection scope of the present invention. The embodiments of the present invention are not limited thereto. All kinds of modifications, substitutions, or changes made to the above structure of the present invention according to the above content of the present invention, in accordance with the common general knowledge and customary means in the art, without departing from the above basic technical idea of the present invention, shall fall within the protection scope of the present invention.

Claims

1. A transaction management system for agricultural product wholesale market, characterized in that: Included are: The transaction management module is used to process transaction information, introduce smart contract technology, automate transaction execution and settlement, and adopt a hybrid online and offline transaction method. Merchants conduct transactions through mobile or PC terminals, and integrate payment platforms to set up multiple payment methods. The order and inventory management module is used to handle the merchant's product management, order allocation, inventory monitoring, introduce Internet of Things technology and RFID equipment, track products in real time, adopt automated inventory management, and set up intelligent systems for optimization; Data analysis and decision support module, used to generate real-time market data analysis and forecasts, assist decision-makers in optimizing market strategies, integrate big data analysis and machine learning technologies, conduct market trend forecasts, price fluctuation analysis, consumer behavior analysis, and present market dynamics to managers through visual reports and real-time monitoring; The security and authority management module is used to protect system data security, transaction security and user privacy. It uses SSL encryption technology to encrypt transaction data and establish a multi-level authority management system. Supply chain management module, used to improve agricultural product supply chain management, integrate supply chain information, track the source and flow of products in real time through Internet of Things technology and RFID, and the intelligent scheduling system automatically selects suppliers and transportation routes according to order requirements and generates supply chain optimization reports; User experience and interface optimization module, which is used to improve the user-friendliness of the system, design a simple and intuitive user interface, and adopt personalized settings so that merchants can customize their transaction processes according to their needs; The intelligent customer service and support module is used to provide 24 / 7 customer support and assistance, answer questions encountered by users during the transaction process, and introduce AI customer service to provide instant response to merchants and buyers.

2. A transaction management method for a wholesale market of agricultural products, characterized in that: Included are: Merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update inventory status. Buyers browse the products on the platform, select the required products, and fill in the order information. The payment process integrates multiple payment channels, automatically generates settlement orders according to the agreed settlement cycle, and settles funds with buyers and sellers. It automatically collects product sales volume and price fluctuation transaction data through the API interface, and uses big data analysis technology to identify and analyze market trends; Track buyers’ purchasing preferences and historical transaction records between buyers and sellers, analyze market demand and predict future purchasing trends, and automatically generate replenishment suggestions based on inventory and sales data; Transaction data is encrypted and protected using SSL encryption technology, and multiple identity authentication is implemented. The system records all transaction data through blockchain technology, and detects abnormal transactions in real time through data monitoring and analysis; It uses an APP version and a web version, and users can use it on mobile phones, tablets, and computers. Users can personalize system functions according to their personal needs, and provide 24 / 7 AI customer service to answer common questions for users through natural language processing technology; We conduct performance evaluations every quarter to test the system's response speed, transaction processing capabilities, and data storage capabilities. We also conduct user surveys to collect feedback and suggestions from buyers and sellers, optimize system functions based on demand, and flexibly expand based on a modular architecture.

3. The agricultural product wholesale market transaction management method according to claim 2, characterized in that: Merchants and users register on the platform and pass real-name authentication. Sellers upload agricultural product information to the platform and regularly update inventory status. Buyers browse the products on the platform and select the required products. The method for filling in order information is as follows: Users and merchants create accounts on the platform, enter their names, contact numbers, and email information, and buyers or sellers select account types. The system provides different functional modules based on the roles. Users or merchants submit identity documents for real-name authentication, and the platform administrator reviews the relevant documents and notifies the review results via SMS or email; After the seller logs in to the platform, he / she enters the commodity management module and uploads the name, description, unit, price, picture, shelf life, storage requirements of the agricultural product, and regularly updates the inventory status. The platform automatically synchronizes the inventory data or the seller manually updates the inventory. Buyers browse agricultural products through the platform's homepage or category page. The system intelligently recommends related products based on historical data and preferences. Buyers select the products to be purchased, enter the quantity, and add the products to the shopping cart; After the buyer confirms the purchase, he / she goes to the checkout page and fills in the order information, which includes the delivery address, payment method, delivery method, and remarks.

4. The agricultural product wholesale market transaction management method according to claim 3, characterized in that: The payment process integrates multiple payment channels, automatically generates settlement orders according to the agreed settlement cycle, and settles funds with buyers and sellers. It automatically collects product sales volume and price fluctuation transaction data through the API interface, and uses big data analysis technology to identify and analyze market trends. The method is as follows: The system integrates Alipay, WeChat, bank cards, and credit card payment channels, connects with major payment platforms through API interfaces, and adopts a payment result callback mechanism. After the user completes the payment, the platform automatically confirms the payment status and performs corresponding processing; The platform automatically settles funds according to the daily, weekly, and monthly settlement cycles agreed upon between merchants and buyers, and records relevant information for each transaction, including transaction time, amount, payment channel, and payment status; Automatically interact with payment platforms, order management systems, and inventory management systems through API interfaces to collect data on product sales, transaction price fluctuations, and inventory changes; Use big data analysis technology to process, mine and analyze the collected transaction data. Data analysis methods include data cleaning, data mining, and machine learning models to identify market trends and product sales dynamics; We use time series analysis, regression analysis, cluster analysis, machine learning models and deep learning algorithms to predict market trends. Based on the big data analysis platform, we can quickly process large amounts of transaction data and conduct real-time data analysis and decision support.

5. The agricultural product wholesale market transaction management method according to claim 4, characterized in that: Tracking buyers’ purchasing preferences and historical transaction records between buyers and sellers, analyzing market demand and predicting future purchasing trends, and automatically generating replenishment suggestions based on inventory and sales data are as follows: Collect buyers’ browsing history, purchase history, search behavior, shopping cart additions, and favorited product data through mobile terminals and sensor data, analyze their purchase preferences and consumption habits, and identify buyers’ long-term needs through data analysis; Collect and integrate sellers’ historical transaction data through the backend data of the e-commerce platform, including order amount, sales goods, transaction frequency, time period, and commodity price fluctuations, and classify and aggregate the historical transaction data; Based on buyers’ purchase preferences and historical transaction records, data mining and machine learning techniques are used to analyze demand trends, and time series analysis and regression analysis methods are used to identify cyclical demand and trend changes; By analyzing historical sales data, use time series models to predict future demand trends; Combine real-time inventory data with demand forecast results to calculate expected sales and inventory gaps. Based on historical sales trends and current inventory, the system automatically calculates expected out-of-stock items and generates replenishment suggestions based on predicted demand.

6. The agricultural product wholesale market transaction management method according to claim 5, characterized in that: The transaction data is encrypted and protected using SSL encryption technology, and multiple identity authentication is implemented. The system records all transaction data through blockchain technology. The method of real-time detection of abnormal transactions through data monitoring and analysis is as follows: The SSL protocol is used to encrypt all transmitted transaction data. Through multiple identity authentication, the system ensures that only legitimate users can access and operate transaction data; Through blockchain technology, each transaction is recorded in the form of blocks, and all blocks are connected to the previous block through hash values, and smart contracts in the blockchain are used to automatically execute and verify transactions; Through real-time data monitoring and analysis systems, abnormal behaviors such as excessive transaction amounts or frequent small transaction amounts are detected, and machine learning and data analysis models are used to detect deviations from regular transaction patterns.

7. The agricultural product wholesale market transaction management method according to claim 6, characterized in that: The system uses an APP version and a web version. Users can use it on their mobile phones, tablets, and computers. Users can personalize system functions according to their personal needs and provide 24 / 7 AI customer service. The method of answering common questions for users through natural language processing technology is as follows: Use cross-platform development frameworks such as React Native, Flutter or Electron to run the app on mobile phones, tablets and computers at the same time. The web side uses responsive design to ensure that the interface is adaptive on mobile phones, tablets and computers. Users customize the interface layout, function modules, and notification methods according to their personal needs. By analyzing the user's historical behavior data, personalized function recommendations are provided to users. Through machine learning algorithms, setting options that meet user needs are recommended; AI customer service uses natural language processing technology to understand and process user questions. Based on the chatbot model, AI customer service handles common questions and simple customer requests. AI customer service continuously optimizes the quality of answers through machine learning models, and gradually adjusts the accuracy of answer methods and content as users interact. The AI ​​customer service system gradually improves the quality of answers by monitoring and analyzing user feedback, and uses sentiment analysis technology to analyze emotional information in user texts.

8. The agricultural product wholesale market transaction management method according to claim 7, characterized in that: We conduct performance evaluation every quarter to test the system's response speed, transaction processing capabilities, and data storage capabilities. We also conduct user surveys to collect feedback and suggestions from buyers and sellers, optimize system functions based on demand, and use a modular architecture with flexible expansion methods such as: Use JMeter and LoadRunner performance testing tools to simulate user access and detect the system's response speed under high concurrency. Use stress testing and load testing to verify the system's processing capabilities under a large number of transaction requests. Perform database performance testing to evaluate the system's data storage and retrieval capabilities. Deploy application performance management tools for real-time monitoring and use log analysis tools to identify potential bottlenecks and anomalies; Through questionnaires, user interviews and feedback collection channels, we understand the usage needs and satisfaction of buyers and sellers. By analyzing the user's page access frequency, click path, and function usage frequency behavior data in the system, we can identify the functions that users care about and the system performance bottlenecks. Adopting a modular architecture, the payment, transaction, inventory management, and user management modules of the system are independent of each other, and certain modules are optimized in a targeted manner based on quarterly performance evaluations and user feedback; Based on microservice architecture or containerization technology, when the system load increases, horizontal expansion is performed by adding microservice instances or expanding containers.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, a transaction management method for a wholesale market of agricultural products as described in any one of claims 2 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements a transaction management method for a wholesale market of agricultural products as described in any one of claims 2-8.

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