Digital management system for public property warehouse

Abstract

The invention relates to the technical field of public material warehouse management, and provides a public material warehouse digital management system, which comprises an internet of things and a management module, and is characterized in that an architecture model of the internet of things comprises a sensing layer, a network layer and an application layer, and the internet of things adopts a Kafka message queue technology to carry out real-time data acquisition; the Internet of Things performs batch data processing by using a Hadoop big data technology; the management module comprises a data acquisition module, an asset state monitoring module, a data processing module, a storage module, a user interface module and a scrap management module, auxiliary asset management, auxiliary house management and office material management are realized, and an RFID tag and a handheld data acquisition terminal are used; real-time updating and query of asset information are realized by using an Internet of Things platform, and asset checking is performed regularly to ensure account-real consistency.

Description

Technical Field

[0001] The invention belongs to the technical field of warehouse management, and in particular relates to a digital management system for public warehouses. Background Art

[0002] Public warehouse management usually refers to the management of warehouses or storage areas in an office environment. The public warehouse management mainly includes auxiliary asset management, auxiliary room management and office material management. The existing warehouse management system has the following problems in the process of managing auxiliary assets, office materials and office rooms:

[0003] 1. The accounts of auxiliary assets are inconsistent with the actual situation, and their usage status and maintenance cannot be tracked efficiently;

[0004] 2. Auxiliary room management lacks visualization means, and it is impossible to accurately grasp the use of office space;

[0005] 3. The efficiency of office supplies management is low, and it is difficult to realize intelligent management such as online collection and inventory management. Summary of the invention

[0006] (I) Purpose of the invention

[0007] In order to overcome the above shortcomings, the purpose of the present invention is to provide a public property warehouse digital management system to solve the above technical problems.

[0008] (II) Technical solution

[0009] To achieve the above objectives, the technical solutions provided by this application are as follows:

[0010] A digital management system for a public property warehouse includes an Internet of Things and a management module. The architecture model of the Internet of Things includes a perception layer, a network layer, and an application layer. The Internet of Things uses Kafka message queue technology for real-time data collection, and uses Hadoop big data technology for batch data processing. The management module includes a data collection module, an asset status monitoring module, a data processing module, a storage module, a user interface module, and a scrap management module, wherein:

[0011] The data collection module is used to collect initial data of assets, including asset name, quantity, purchase date, and user department;

[0012] Asset status monitoring module, which is used to monitor the usage status, location and maintenance of assets in real time and obtain real-time data through IoT technology;

[0013] Data processing module, which processes and analyzes the collected data to predict the asset's service life and maintenance needs;

[0014] The storage module is used to store all asset data and processing results, ensuring that the data can be saved and retained even after the system is shut down or fails, and implementing data encryption and security measures to protect the data from unauthorized access or tampering;

[0015] The user interface module provides a user operation interface to facilitate users to query, adjust and manage asset information;

[0016] The scrapping management module is used to manage the scrapping process of assets, automatically generate scrapping plans and handle scrapping procedures.

[0017] Preferably, the user of the data acquisition module inputs or scans asset data through the interface submodule. The asset data includes the asset name, quantity, purchase date, and using department. The data entry submodule receives the data input by the user and provides preliminary data verification. It obtains asset information by automatically scanning the barcode or RFID tag of the asset and compares it with the data entered by the user. The compared data is reviewed in detail to ensure the accuracy of the data. The reviewed data is stored in the database to establish an asset file.

[0018] Preferably, the asset status monitoring module installs or attaches IoT sensors and tags on office supplies, auxiliary assets and auxiliary rooms, configures asset information in the asset status monitoring module, sets monitoring parameters and thresholds, and uses the asset status monitoring module to view the asset's usage status, location and environmental conditions in real time. When the asset status is abnormal, the system automatically issues an early warning to remind management personnel, and arranges regular or on-demand maintenance work based on the predictive maintenance analysis results, and optimizes the allocation and use of office supplies and auxiliary rooms based on monitoring data.

[0019] Preferably, the monitoring of office supplies includes monitoring the receipt, return and inventory status of office supplies using RFID or barcode technology.

[0020] Preferably, the data processing module includes analyzing the frequency of use, consumption rate and replenishment cycle of office supplies, predicting future material needs, analyzing the performance data of auxiliary assets such as printers and copiers to identify potential failures and performance degradation; using the usage data of auxiliary rooms to analyze usage efficiency and demand patterns and optimize space allocation, the steps include:

[0021] S1 receives data from the data acquisition module and the asset status monitoring module, and cleans the data to remove errors and inconsistent data;

[0022] S2 extracts useful features from the data, which include usage frequency, failure rate, or other features related to the public warehouse;

[0023] S3 suggested prediction model;

[0024] S4 analyzes data through predictive models and predicts the performance and life of assets;

[0025] S5 evaluates the accuracy and reliability of the analysis results and generates reports for management.

[0026] Preferably, the ARIMA model of the prediction model includes:

[0027] Yt=c+φ1Yt-1+…+φpYt-p+θ1∈t-1+…+θq∈t-q+∈t

[0028] Where: Yt is the observed value at time point t, c is a constant term representing the baseline level of the model, φ1,…,φp are autoregressive coefficients, representing the relationship between the current value and the values ​​at the previous p time points; θ1,…,θq are moving average coefficients, representing the relationship between the current error term and the error term at the previous q time points; ∈t is the error term or random disturbance at time point t, usually assumed to be white noise; p is the order of the autoregressive term; q is the order of the moving average term.

[0029] Preferably, all data and processing results related to office supplies, auxiliary assets and auxiliary rooms in the storage module are stored in a central database, and the data is backed up regularly. When a failure occurs, the cluster or mirror server is driven to transfer data, and strict access control is implemented on the data. The user's identity is verified through multi-factor authentication, and different data access rights are allocated according to the user's role and responsibilities. Firewalls and intrusion detection systems are set up to protect data from attacks.

[0030] Preferably, the user interface module includes dividing the user interface into multiple functional modules, including material query, asset management, and room scheduling, and displaying data in real time to show the current status and usage of office materials, auxiliary assets, and auxiliary rooms, realizing advanced query functions, allowing users to search for asset information according to different conditions, including material name, location, and status, providing asset adding, editing, deleting, and allocating functions, enabling users to manage office materials and auxiliary assets, and for auxiliary rooms, providing reservation, allocation, and usage tracking functions to optimize the allocation and use of room resources.

[0031] Preferably, the scrapping management module sets scrapping conditions according to the service life, performance standards and safety standards of office supplies, auxiliary assets and auxiliary rooms, regularly evaluates assets to determine whether they meet the scrapping conditions, and allows users to submit scrapping applications through the user interface. The scrapping applications include necessary scrapping reasons and related information. The system automatically generates a scrapping plan based on preset scrapping standards and asset usage, implements the scrapping approval process, including department approval, asset management department review and final approval, and handles scrapping procedures, including asset write-off, financial processing and updating of related documents.

[0032] Beneficial effects:

[0033] 1. Auxiliary asset management, using RFID tags and handheld data collection terminals: identify and manage each auxiliary asset, use the Internet of Things platform to achieve real-time update and query of asset information, conduct regular asset inventory, and ensure that the accounts are consistent with the actual situation.

[0034] 2. Auxiliary room management: through the effective organization, allocation, maintenance and optimization of office space, the layout of auxiliary rooms can be rationally planned to ensure maximum space utilization and meet functional requirements. At the same time, office space can be fairly and reasonably allocated to achieve visual management.

[0035] 3. Office supplies management, optimize the existing office supplies management system: add background management functions, realize online procurement, online collection and inventory management of office supplies and office consumables, provide out-of-stock reservation, arrival reminder and item return functions, use system data for business analysis, and support budget expenditure, material consumption and procurement decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the structure of the present invention;

[0037] Reference numerals:

[0038] 1. Internet of Things; 2. Perception layer; 3. Network layer; 4. Application layer; 5. Data acquisition module; 6. Asset status monitoring module; 7. Data processing module; 8. Storage module; 9. Interface module; 10; Scrap management module; 11. Management module. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following is a detailed description of the present invention in conjunction with the specific implementation methods and with reference to the attached drawings. Figure 1 , the present invention is further described in detail. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concept of the present invention.

[0040] A digital management system for a public property warehouse realizes comprehensive digital management of public property warehouse assets by integrating advanced Internet of Things 1 and management module 11. In the Internet of Things architecture model, the perception layer 2 is responsible for real-time monitoring and data collection, the network layer 3 is responsible for data transmission, and the application layer 4 processes and analyzes data to provide decision support. The system uses Kafka message queue technology to achieve high-throughput real-time data collection and uses Hadoop big data processing technology for efficient batch data processing to ensure the efficiency and accuracy of data processing.

[0041] The management module 11 includes a data acquisition module 5 , an asset status monitoring module 6 , a data processing module 7 , a storage module 8 , a user interface module 9 and a scrapping management module 10 .

[0042] The data acquisition module is used to collect the initial data of assets, including asset name, quantity, purchase date, and user department. The user of the data acquisition module enters or scans asset data through the interface submodule. The asset data includes asset name, quantity, purchase date, and user department. The data entry submodule receives the data entered by the user and provides preliminary data verification. It obtains asset information by automatically scanning the barcode or RFID tag of the asset and compares it with the data entered by the user. The compared data is reviewed in detail to ensure the accuracy of the data. The reviewed data is stored in the database to establish an asset file.

[0043] The asset status monitoring module is used to monitor the use status, location and maintenance of assets in real time, and obtain real-time data through the Internet of Things technology. The asset status monitoring module installs or attaches Internet of Things sensors and tags on office supplies, auxiliary assets and auxiliary rooms, configures asset information in the asset status monitoring module, sets monitoring parameters and thresholds, and uses the asset status monitoring module to view the use status, location and environmental conditions of assets in real time. When the asset status is abnormal, the system automatically issues an early warning to remind management personnel, and arranges regular or on-demand maintenance work based on the results of predictive maintenance analysis, and optimizes the allocation and use of office supplies and auxiliary rooms based on monitoring data. The monitoring of office supplies includes the use of RFID or barcode technology to monitor the collection, return and inventory status of office supplies.

[0044] The data processing module processes and analyzes the collected data to predict the asset's service life and maintenance needs. The data processing module includes analyzing the frequency of use, consumption rate and replenishment cycle of office supplies, predicting future material needs, and analyzing the performance data of auxiliary assets such as printers and copiers to identify potential failures and performance degradation. The auxiliary room usage data is used to analyze usage efficiency and demand patterns and optimize space allocation. The steps include:

[0045] S1 receives data from the data acquisition module and the asset status monitoring module, and cleans the data to remove errors and inconsistent data;

[0046] S2 extracts useful features from the data, which include usage frequency, failure rate, or other features related to the public warehouse;

[0047] S3 suggested prediction model;

[0048] S4 analyzes data through predictive models and predicts the performance and life of assets;

[0049] S5 evaluates the accuracy and reliability of the analysis results and generates reports for management.

[0050] The ARIMA model of the forecasting model includes:

[0051] Yt=c+φ1Yt-1+…+φpYt-p+θ1vt-1+…+θq∈t-q+∈t

[0052] Where: Yt is the observed value at time point t, c is a constant term representing the baseline level of the model, φ1,…,φp are autoregressive coefficients, representing the relationship between the current value and the values ​​at the previous p time points; θ1,…,θq are moving average coefficients, representing the relationship between the current error term and the error term at the previous q time points; ∈t is the error term or random disturbance at time point t, usually assumed to be white noise; p is the order of the autoregressive term; q is the order of the moving average term.

[0053] The storage module is used to store all asset data and processing results, ensuring that the data can be saved and retained even after the system is shut down or a failure occurs, and implementing data encryption and security measures to protect the data from unauthorized access or tampering; all data and processing results related to office supplies, auxiliary assets and auxiliary rooms in the storage module are stored in a central database, and the data is backed up regularly. When a failure occurs, the cluster or mirror server is driven to transfer data, and strict access control is implemented on the data. The user's identity is verified through multi-factor authentication, and different data access rights are allocated according to the user's role and responsibilities. Firewalls and intrusion detection systems are set up to protect data from attacks.

[0054] The user interface module provides a user operation interface to facilitate users to query, adjust and manage asset information; the user interface module includes dividing the user interface into multiple functional modules, including material query, asset management, and room scheduling, and displays data in real time, showing the current status and usage of office materials, auxiliary assets and auxiliary rooms, realizing advanced query functions, allowing users to search for asset information according to different conditions, including material name, location and status, providing asset addition, editing, deletion and allocation functions, enabling users to manage office materials and auxiliary assets, and for auxiliary rooms, providing reservation, allocation and usage tracking functions to optimize the allocation and use of room resources.

[0055] The scrapping management module is used to manage the scrapping process of assets, automatically generate scrapping plans and handle scrapping procedures. The scrapping management module sets scrapping conditions according to the service life, performance standards and safety standards of office materials, auxiliary assets and auxiliary rooms, regularly evaluates assets to determine whether they meet the scrapping conditions, and allows users to submit scrapping applications through the user interface. The scrapping application includes necessary scrapping reasons and related information. The system automatically generates a scrapping plan based on the preset scrapping standards and asset usage, implements the scrapping approval process, including department approval, asset management department review and final approval, and handles scrapping procedures, including asset write-off, financial processing and updating of related documents.

[0056] The Internet of Things includes a space management model and an inventory management model.

[0057] The space management model includes three-dimensional model construction and space optimization algorithm, and the three-dimensional model construction uses surveying and mapping data to construct a three-dimensional model of the office room;

[0058] The inventory management model includes:

[0059] ABC analysis method, classify and manage inventory materials and optimize inventory levels;

[0060] Safety stock model, determine the safety stock level to prevent out-of-stock.

[0061] The demand forecasting algorithm of the Internet of Things includes:

[0062] Time series analysis, using ARIMA model for demand forecasting;

[0063] Machine learning algorithms use random forest algorithm and support vector machine algorithm.

[0064] Data mining algorithms extract valuable information from large amounts of data generated by devices to help with prediction and decision making;

[0065] Association rules, discovering the association relationship in the use of office supplies;

[0066] Cluster analysis to identify usage patterns and trends of office supplies.

[0067] The present invention realizes the "digital management" of auxiliary assets: the Internet of Things technology is adopted, and RFID tags and handheld data collection terminals are used to identify and manage auxiliary assets, thereby realizing their tracking and maintenance throughout their life cycle.

[0068] The present invention realizes the reasonable planning of the layout of auxiliary rooms through the effective organization, allocation, maintenance and optimization of office space, ensures the maximum utilization of space and meets functional requirements, and can reasonably allocate office space fairly and realize visual management.

[0069] The present invention realizes the "digital" management of office supplies: optimizes the office supplies management system, adds background management functions, realizes functions such as online collection of office supplies, inventory management, out-of-stock reservations, arrival reminders, etc., and provides business analysis support.

[0070] The present invention is designed for efficient management of office supplies, auxiliary rooms and auxiliary assets. The system integrates Internet of Things technology and advanced management modules to improve the efficiency, accuracy and security of asset management through automation and intelligent means. The key components of the system include data acquisition, asset status monitoring, data processing, storage, user interface and scrap management modules, which together form a comprehensive and integrated asset management platform.

[0071] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0072] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital management system for public property warehouses, characterized in that: It includes an Internet of Things and a management module. The architecture model of the Internet of Things includes a perception layer, a network layer and an application layer. The Internet of Things uses Kafka message queue technology for real-time data collection, and uses Hadoop big data technology for batch data processing; the management module includes a data collection module, an asset status monitoring module, a data processing module, a storage module, a user interface module and a scrap management module, wherein: The data collection module is used to collect the initial data of assets, including asset name, quantity, purchase date, and user department; Asset status monitoring module, which is used to monitor the usage status, location and maintenance of assets in real time and obtain real-time data through IoT technology; Data processing module, which processes and analyzes the collected data to predict the asset's service life and maintenance needs; The storage module is used to store all asset data and processing results, ensuring that the data can be saved and retained even after the system is shut down or fails, and implementing data encryption and security measures to protect the data from unauthorized access or tampering; The user interface module provides a user operation interface to facilitate users to query, adjust and manage asset information; The scrapping management module is used to manage the scrapping process of assets, automatically generate scrapping plans and handle scrapping procedures.

2. A public property warehouse digital management system according to claim 1, characterized in that: The user of the data acquisition module inputs or scans asset data through the interface submodule. The asset data includes the asset name, quantity, purchase date, and using department. The data entry submodule receives the data entered by the user and provides preliminary data verification. It obtains asset information by automatically scanning the barcode or RFID tag of the asset and compares it with the data entered by the user. The compared data is reviewed in detail to ensure the accuracy of the data. The reviewed data is stored in the database to establish an asset file.

3. A digital management system for public property warehouses according to claim 1, characterized in that: The asset status monitoring module installs or attaches IoT sensors and tags on office supplies, auxiliary assets and auxiliary rooms, configures asset information in the asset status monitoring module, sets monitoring parameters and thresholds, and uses the asset status monitoring module to view the asset's usage status, location and environmental conditions in real time. When the asset status is abnormal, the system automatically issues an early warning to remind managers, and arranges regular or on-demand maintenance work based on the predictive maintenance analysis results, and optimizes the allocation and use of office supplies and auxiliary rooms based on monitoring data.

4. A public property warehouse digital management system according to claim 3, characterized in that: The monitoring of office supplies includes the use of RFID or barcode technology to monitor the receipt, return and inventory status of office supplies.

5. The public property warehouse digital management system according to claim 1 is characterized in that: The data processing module includes analyzing the frequency of use, consumption rate and replenishment cycle of office supplies, predicting future material needs, and analyzing the performance data of auxiliary assets such as printers and copiers to identify potential failures and performance degradation; Use the usage data of auxiliary rooms to analyze usage efficiency and demand patterns and optimize space allocation. The steps include: S1 receives data from the data acquisition module and the asset status monitoring module, and cleans the data to remove errors and inconsistent data; S2 extracts useful features from the data, which include usage frequency, failure rate, or other features related to the public warehouse; S3 suggested prediction model; S4 analyzes data through predictive models and predicts the performance and life of assets; S5 evaluates the accuracy and reliability of the analysis results and generates reports for management.

6. A digital management system for public property warehouses according to claim 5, characterized in that: The ARIMA model of the forecasting model includes: Yt=c+φ1Yt-1+…+φpYt-p+θ1∈t-1+…+θq∈t-q+∈t Where: Yt is the observed value at time point t, c is a constant term representing the baseline level of the model, φ1,…,φp are autoregressive coefficients, representing the relationship between the current value and the values ​​at the previous p time points; θ1,…,θq are moving average coefficients, representing the relationship between the current error term and the error term at the previous q time points; ∈t is the error term or random disturbance at time point t, usually assumed to be white noise; p is the order of the autoregressive term; q is the order of the moving average term.

7. A public property warehouse digital management system according to claim 1, characterized in that: All data and processing results related to office supplies, auxiliary assets and auxiliary rooms in the storage module are stored in the central database, and the data is backed up regularly. When a failure occurs, the cluster or mirror server will be transferred, and strict access control is implemented on the data. The user's identity is verified through multi-factor authentication, and different data access rights are allocated according to the user's role and responsibilities. Firewalls and intrusion detection systems are set up to protect data from attacks.

8. The public property warehouse digital management system according to claim 1 is characterized in that: The user interface module includes dividing the user interface into multiple functional modules, including material query, asset management, and room scheduling, and displaying data in real time, showing the current status and usage of office materials, auxiliary assets, and auxiliary rooms, realizing advanced query functions, allowing users to search for asset information according to different conditions, including material name, location, and status, providing asset adding, editing, deleting, and allocating functions, enabling users to manage office materials and auxiliary assets, and for auxiliary rooms, providing reservation, allocation, and usage tracking functions to optimize the allocation and use of room resources.

9. A public property warehouse digital management system according to claim 1, characterized in that: The scrapping management module sets scrapping conditions according to the service life, performance standards and safety standards of office supplies, auxiliary assets and auxiliary rooms, regularly evaluates assets to determine whether they meet the scrapping conditions, and allows users to submit scrapping applications through the user interface. The scrapping application includes necessary scrapping reasons and related information. The system automatically generates a scrapping plan based on preset scrapping standards and asset usage, implements the scrapping approval process, including department approval, asset management department review and final approval, and handles scrapping procedures, including asset write-off, financial processing and updating of related documents.

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