Digital data processing system and method based on cloud computing

Abstract

The invention relates to the technical field of data processing, in particular to a digital data processing system and method based on cloud computing, and the system comprises a product classification system, a data entry system, a data encryption system, a data backup and recovery system and a data integrity verification system. And a classification manager is automatically prompted to perform auditing and adjustment. The supermarket products are classified carefully, and a dynamic classification system is established, so that the product management is clearer and more orderly, workers can quickly position and manage various products, time waste and management errors caused by disordered classification are reduced, the daily management efficiency is improved, and the product quality is improved by monitoring the date of the product. The system can grasp the quality guarantee period state of the product in real time and automatically carry out price reduction processing or off-shelf processing according to a preset rule, which is beneficial for reducing inventory overstock and product expiration loss, improving the inventory turnover rate, optimizing the inventory structure and reducing the inventory cost.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and in particular relates to a digital data processing system and method based on cloud computing. Background Art

[0002] Cloud computing is a technology that provides computing resources and services on demand through the Internet. It has the characteristics of on-demand self-service, wide access, resource pooling, rapid elasticity and measurability. It is widely used in many fields such as enterprise IT, software services, big data processing, etc., helping users reduce costs and improve efficiency and flexibility.

[0003] With the rapid development of information technology and increasingly fierce market competition, supermarkets and other retail enterprises are facing huge operational challenges. Traditional data processing methods and systems have many shortcomings in product management, inventory control, sales analysis, etc., resulting in low management efficiency, serious inventory backlogs, low customer satisfaction and high operating costs.

[0004] In traditional supermarket management systems, product classification is usually extensive and lacks a dynamic adjustment mechanism. With market changes and the emergence of new products, the fixed classification system cannot adapt to new business needs in a timely manner, resulting in chaotic product management and affecting the accuracy of inventory management and sales analysis. In addition, manual classification and management methods are inefficient, prone to errors, and increase management costs.

[0005] In order to solve these problems and improve the competitiveness of enterprises, a more efficient, intelligent and secure digital data processing system and method is urgently needed. Summary of the invention

[0006] To achieve the above object, the present invention proposes a digital data processing method based on cloud computing, comprising the following steps:

[0007] Step 1: Product classification: classify the products in the supermarket and give each category a detailed classification label;

[0008] Step 2: Data entry: enter the data of the classified products, including their production date, shelf life and pricing;

[0009] Step 3: Data preservation: entering product data into cloud storage and local storage for preservation;

[0010] Step 4: Data monitoring and processing. Real-time processing of products is performed through product date monitoring, including the following solutions: no interference is performed on products within the shelf life, and prices of products approaching the expiration date are reduced. The price reduction range is pre-set, and barcode printers are equipped for independent printing. Labels of near-expiry products are replaced in a timely manner, and expired products are eliminated, that is, the products are removed from the shelves;

[0011] Step 5: Data analysis: After a period of operation, the sales data of each category of products will be saved, and their elimination rates will be compared to re-assign new product replenishment plans.

[0012] In one example, the product classification divides products into four categories: food, daily necessities, daily office and home appliances and digital products, and each category is subdivided. Food is divided into fresh food and processed food, and the corresponding categories are further subdivided.

[0013] In one example, intelligent recognition technology is introduced in the data entry to automatically identify product information, the entered data is encrypted, and the SSL / TLS encryption protocol is used to ensure the security of the data during transmission.

[0014] In one example, a digital data processing system based on cloud computing includes a product classification system, a data entry system, a data encryption system, a data backup and recovery system, and a data integrity verification system.

[0015] In one example, the product classification system establishes a dynamic classification system, automatically prompts classification management personnel to review and adjust, and implements a classification update mechanism, and designs and implements operations of adding, deleting, modifying and checking data nodes.

[0016] In one example, the data entry system includes image acquisition and barcode recognition functions, and performs image preprocessing, including image noise reduction, background separation, and image correction.

[0017] In one example, the data encryption system includes transmission encryption and storage encryption. The transmission encryption uses the SSL / TLS encryption protocol to ensure the security of data during transmission, and the storage encryption encrypts the data stored in the cloud and locally.

[0018] In one example, the data monitoring and early warning system monitors data access and operation behavior in real time, records user access time, access content, and operation type information, generates audit logs, defines abnormal behavior indicators, and sets reasonable thresholds. When actual behavior reaches or exceeds the threshold, the early warning mechanism is immediately triggered.

[0019] In one example, the data backup and recovery system formulates a detailed data backup plan, determines the backup cycle based on the importance and update frequency of the data, and the backup data should be stored in a secure off-site storage device.

[0020] In one example, the data backup and recovery system uses professional data destruction technology to ensure that deleted data cannot be recovered. For data stored in the physical media of the hard disk, multiple overwriting and demagnetization methods can be used for destruction. For data stored in the cloud, the cloud service provider should provide reliable data deletion services.

[0021] The digital data processing system and method based on cloud computing proposed by the present invention can bring the following beneficial effects:

[0022] 1. The present invention makes product management clearer and more orderly by classifying supermarket products in detail and establishing a dynamic classification system. Staff can quickly locate and manage various products, reduce time waste and management errors caused by classification confusion, and improve daily management efficiency.

[0023] 2. By monitoring the date of the product, the system of the present invention can grasp the shelf life status of the product in real time, and automatically reduce the price or remove the product from the shelf according to the preset rules, which helps to reduce inventory backlogs and product expiration losses, improve inventory turnover, optimize inventory structure, and reduce inventory costs.

[0024] 3. After a period of operation, the present invention saves and analyzes the sales data of each category of products, compares their elimination rates, and provides new product replenishment plans for supermarkets. It introduces big data analysis and artificial intelligence algorithms to conduct in-depth mining of consumers' purchasing behaviors and preferences, predict consumers' purchasing trends, and provide strong data support for supermarkets' precision marketing, procurement decisions, product pricing and promotion strategies, thereby further optimizing inventory management and operational efficiency.

[0025] 4. The present invention uses the system to timely reduce the price of products approaching their expiration date, and is equipped with a barcode printer to facilitate label replacement, ensuring that consumers can purchase fresh and safe products. At the same time, expired products are promptly removed from shelves, maintaining the supermarket's reputation and enhancing consumers' trust and satisfaction with the supermarket.

[0026] 5. The present invention can better understand consumers' needs and preferences through the analysis of consumer purchasing behavior, thereby providing more personalized product recommendations and services. For example, according to consumers' purchase history and preferences, relevant promotional activities and new product information can be pushed to them, thereby improving consumers' shopping experience and satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0028] Figure 1 A schematic flow chart of the method of the present invention;

[0029] Figure 2 Schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0030] In order to more clearly illustrate the overall concept of the present invention, a detailed description is given below in an exemplary manner in conjunction with the accompanying drawings.

[0031] In the description of the present invention, it is necessary to understand that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0032] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0033] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or a communication; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0034] In the present invention, unless otherwise clearly specified and limited, the first feature "on" or "under" the second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. In the description of this specification, the description of reference terms "one scheme", "some schemes", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the scheme or example are included in at least one scheme or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same scheme or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more schemes or examples in a suitable manner.

[0035] like Figure 1-2 As shown, the present invention proposes a digital data processing system and method based on cloud computing, and the data processing method includes the following steps:

[0036] Step 1: Product classification. Classify the products in the supermarket into four categories: food, daily necessities, daily office and home appliances and digital products. Each category is subdivided, such as food is divided into fresh food and processed food, and then further subdivided accordingly, such as processed food is divided into snacks, grains and oils, etc. At the same time, a dynamic classification system is established and a classification update mechanism is set up. When new products appear, the system automatically prompts classification management personnel to review and adjust them to adapt to market changes and the continuous emergence of new products.

[0037] The second step is data entry. The classified products are entered with data including their production date (the production date of fresh food is the purchase date), shelf life (the shelf life of fresh food is a self-set shelf life, generally 2-3 days) and pricing. In this process, intelligent recognition technologies such as image recognition and barcode scanning are introduced to automatically identify product information, reduce manual entry errors, and improve the efficiency and accuracy of data entry. At the same time, the entered data is encrypted, and encryption protocols such as SSL / TLS are used to ensure the security of data during transmission and prevent data from being stolen and tampered with.

[0038] The third step: data preservation, enter the product data into cloud storage and local storage for preservation. Use a distributed storage architecture to disperse and store data on multiple nodes to enhance the system's fault tolerance. At the same time, regularly conduct data backup and recovery drills to ensure data security and reliability, and quickly restore data even in unexpected situations. In addition, encrypt the data stored in the cloud and locally, use symmetric encryption algorithms (such as AES) or asymmetric encryption algorithms (such as RSA) to generate keys for the data, and only authorized personnel or systems with the correct keys can decrypt and view the data to prevent data leakage.

[0039] The fourth step: data monitoring and processing. Real-time processing of products is carried out through date monitoring of products, including the following solutions: no interference is made for products within the shelf life, and prices are reduced for products approaching the expiration date. The price reduction range is preset. For example, a 25% price reduction is carried out when the product is about to expire. A barcode printer is equipped for autonomous printing to facilitate timely replacement of labels for products approaching the expiration date. Expired products are eliminated, i.e. the products are removed from the shelves.

[0040] During this process, the system monitors data access and operation behaviors in real time, records user access time, access content, operation type and other information, generates audit logs for subsequent tracing and analysis, and defines abnormal behavior indicators, such as large-scale access to sensitive data in a short period of time, sudden and substantial increase in data transmission volume, etc. (for example, multiple autonomous price changes within the system, inconsistent prices charged with pricing, etc.), sets reasonable thresholds (the threshold is the number of times abnormal behavior indicators appear), and when actual behavior reaches or exceeds the threshold, immediately triggers the early warning mechanism, sends email notifications and SMS reminders to system administrators, and promptly discovers and handles data security issues.

[0041] Step 5: Data analysis. After a period of operation, the sales data of each category of products are saved and compared with their elimination rates. New product replenishment plans are re-assigned, and big data analysis and artificial intelligence algorithms are introduced to conduct in-depth mining of consumers' purchasing behaviors and preferences. For example, data such as consumers' purchase time, purchase frequency, and purchase combinations are analyzed to predict consumers' purchasing trends and provide a basis for the supermarket's precise marketing. At the same time, combined with market data, the price elasticity and seasonal fluctuations of products are analyzed to provide a reference for product pricing and promotion strategies. The data analysis function is further optimized, its depth and breadth are expanded, and the data processing system can better serve the operation and management of the supermarket.

[0042] The system required to complete the above data analysis method includes:

[0043] Product classification system:

[0044] Dynamic classification system: Establishing a dynamic classification system can automatically prompt classification managers to review and adjust to adapt to market changes and the continuous emergence of new products.

[0045] Classification update mechanism, design and implement the addition, deletion, modification and query operations of data nodes to ensure the timeliness and accuracy of the classification structure.

[0046] Data entry system: Image acquisition, capturing barcode images through digital cameras, scanners or dedicated image sensors (such as CCD image sensors or CMOS image sensors).

[0047] Image preprocessing includes image noise reduction, background separation, image correction, etc. The median filter method is used to remove noise, the standard deviation threshold tracking method is used for background separation, and the image correction is performed by combining the line difference operation with the Hough transform.

[0048] Barcode recognition: barcode recognition and processing can be realized through tools such as MATLAB to improve the efficiency and accuracy of data entry.

[0049] Automation tools, OCR technology, use OCR (optical character recognition) technology to automatically convert paper documents into electronic data, reducing the workload of manual input.

[0050] Reporting tools: Choose a comprehensive and easy-to-use reporting tool, such as FineReport, which supports simple drag-and-drop operations and can easily design complex reports to meet the company's diverse data entry needs.

[0051] Data standardization, unified data standards, and formulation of unified data standards ensure consistency in data formats across different departments and systems, reduce problems encountered during data entry and integration, and improve data accuracy and consistency.

[0052] Data encryption system: transmission encryption, using encryption protocols such as SSL / TLS to ensure the security of data during transmission and prevent data from being stolen and tampered with.

[0053] Storage encryption: Encrypt data stored in the cloud and locally, use symmetric encryption algorithms (such as AES) or asymmetric encryption algorithms (such as RSA) to generate keys for the data. Only authorized personnel or systems with the correct keys can decrypt and view the data.

[0054] Data monitoring and early warning system: real-time monitoring, the system monitors data access and operation behavior in real time, records user access time, access content, operation type and other information, and generates audit logs for subsequent tracing and analysis.

[0055] Abnormal behavior detection: define abnormal behavior indicators, such as a large amount of access to sensitive data in a short period of time, a sudden and significant increase in data transmission volume, etc., set reasonable thresholds, and immediately trigger the early warning mechanism when the actual behavior reaches or exceeds the threshold, and send email notifications, SMS reminders, etc. to the system administrator.

[0056] Data backup and recovery system: Perform regular backups and develop a detailed data backup plan. Determine the backup cycle based on the importance and update frequency of the data. The backup data should be stored in a secure off-site storage device.

[0057] Disaster recovery plan: Develop a comprehensive disaster recovery plan in advance, clarify the recovery process and responsible persons under different disaster scenarios. The plan should include RTO (recovery time objective) and RPO (recovery point objective) to ensure that business operations can be restored in the shortest time after data loss or system failure.

[0058] Backup data verification: Regularly verify backup data to ensure the integrity and availability of backup data. You can restore backup data to a test environment to check whether the data can be read and used correctly.

[0059] Data classification and grading management system: Data classification, detailed classification of data, in addition to classification by product category, can also be classified according to the sensitivity and importance of the data. For example, customer personal information can be classified as highly sensitive data, and the basic attributes of the product can be classified as ordinary data.

[0060] Access control policy: formulate strict access control policy according to data classification, and different levels of data correspond to different access rights. For example, highly sensitive data can only be accessed by senior managers of supermarkets and specific personnel with strict authorization.

[0061] Data integrity verification system: Regular verification. The system regularly performs integrity verification on data stored in the cloud and locally. It checks whether the data has been tampered with by calculating the hash value, checksum, etc. of the data.

[0062] Data operation records: when data is modified, deleted, etc., the system automatically records the data status and operator information before and after the operation to ensure data integrity and traceability.

[0063] Data deletion and destruction system: Data deletion policy, formulate a clear data deletion policy, stipulate the retention period of different types of data, and the system will automatically mark and delete data that exceeds the retention period.

[0064] Technical means should be used to adopt professional data destruction technology to ensure that deleted data cannot be recovered. For data stored in physical media such as hard disks, it can be destroyed by multiple overwriting, demagnetization and other methods; for data stored in the cloud, cloud service providers should provide reliable data deletion services.

[0065] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0066] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A digital data processing method based on cloud computing, characterized in that: The following steps are involved: Step 1: Product classification: classify the products in the supermarket and give each category a detailed classification label; Step 2: Data entry: enter the data of the classified products, including their production date, shelf life and pricing; Step 3: Data preservation: entering product data into cloud storage and local storage for preservation; Step 4: Data monitoring and processing. Real-time processing of products is performed through product date monitoring, including the following solutions: no interference is performed on products within the shelf life, and prices of products approaching the expiration date are reduced. The price reduction range is pre-set, and barcode printers are equipped for independent printing. Labels of near-expiry products are replaced in a timely manner, and expired products are eliminated, that is, the products are removed from the shelves; Step 5: Data analysis. After a period of operation, the sales data of each category of products are saved, and their elimination rates are compared to re-assign new product replenishment plans.

2. The digital data processing method based on cloud computing according to claim 1, characterized in that: The product classification divides products into four major categories: food, daily necessities, daily office and home appliances and digital products, and subdivides each major category. Food is divided into fresh food and processed food, and the corresponding ones are further subdivided.

3. The digital data processing method based on cloud computing according to claim 1, characterized in that: Intelligent recognition technology is introduced in the data entry to automatically identify product information, the entered data is encrypted, and the SSL / TLS encryption protocol is used to ensure the security of the data during transmission.

4. A system for executing the cloud computing-based digital data processing method according to claims 1 to 3, characterized in that: It includes product classification system, data entry system, data encryption system, data backup and recovery system and data integrity verification system.

5. The digital data processing system based on cloud computing according to claim 4, characterized in that: The product classification system establishes a dynamic classification system, automatically prompts classification management personnel to review and adjust, and implements a classification update mechanism, and designs and implements operations of adding, deleting, modifying and checking data nodes.

6. The digital data processing system based on cloud computing according to claim 4, characterized in that: The data entry system includes image acquisition and barcode recognition functions, and performs image preprocessing, including image noise reduction, background separation, and image correction.

7. The digital data processing system based on cloud computing according to claim 4, characterized in that: The data encryption system includes transmission encryption and storage encryption. Transmission encryption uses SSL / TLS encryption protocol to ensure the security of data during transmission, and storage encryption encrypts data stored in the cloud and locally.

8. The digital data processing system based on cloud computing according to claim 4, characterized in that: The data monitoring and early warning system monitors data access and operation behavior in real time, records user access time, access content, and operation type information, generates audit logs, defines abnormal behavior indicators, sets reasonable thresholds, and immediately triggers an early warning mechanism when actual behavior reaches or exceeds the threshold.

9. The digital data processing system based on cloud computing according to claim 4, characterized in that: The data backup and recovery system formulates a detailed data backup plan and determines the backup cycle based on the importance and update frequency of the data. The backup data should be stored in a secure off-site storage device.

10. The digital data processing system based on cloud computing according to claim 4, characterized in that: The data backup and recovery system uses professional data destruction technology to ensure that deleted data cannot be recovered. For data stored in the physical media of the hard disk, multiple overwriting and demagnetization methods can be used for destruction. For data stored in the cloud, the cloud service provider should provide reliable data deletion services.

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