AI intelligent checking method, device and equipment and storage medium

Abstract

The invention relates to an AI intelligent checking method and device, equipment and a storage medium. The method comprises the following steps: judging whether checking asset data conforms to checking regulations or not; if yes, performing format conversion on the inventory asset data to obtain formal standing book information; performing information checking on the formal standing book information to obtain a checking result; judging whether the checking device has a network or not, if not, storing the checking result in a local checking machine in the checking device, and detecting and recovering the network of the checking device; uploading a local inventory result of the inventory machine to a preset server, and generating an inventory report; and if there is a network, uploading the checking result to a preset server, and generating a checking report, thereby solving the technical problems that the traditional checking method is difficult to reflect the change of the assets in time, so that the problem of inconsistent account and reality frequently occurs, and the effectiveness and accuracy of asset management are affected.

Description

Technical Field

[0001] The present invention relates to the field of information inventory technology, and in particular to an AI intelligent inventory method, device, equipment and storage medium. Background Art

[0002] With the development of information technology, the management of fixed assets has become increasingly complex in all kinds of organizations. The traditional manual inventory method is not only time-consuming and labor-intensive, but also prone to errors, especially in large enterprises or institutions, where assets are of various types and widely distributed, which makes it a difficult task to accurately track and record the location and status of each asset. In addition, due to the lack of real-time performance, traditional inventory methods are difficult to reflect asset changes in a timely manner, resulting in frequent discrepancies between accounts and actual assets, affecting the effectiveness and accuracy of asset management. Therefore, how to use modern technology to improve inventory efficiency, ensure data accuracy, and realize dynamic updates of asset information has become a problem that needs to be solved urgently.

[0003] A key issue in the research background is that the existing inventory methods are not adaptable enough to large-scale fixed assets. At present, most entities still rely on regular manual inspections, which is inefficient and cannot meet the rapidly changing market needs. At the same time, manual operations are affected by subjective factors, which can easily lead to omissions or erroneous records, thereby reducing the reliability of inventory results. In addition, even if some companies have introduced technologies such as electronic tags to assist inventory, these technologies often require special equipment support in specific environments, which increases implementation costs and technical barriers. Therefore, it is particularly urgent to develop an intelligent and more automated inventory method that can both improve work efficiency and reduce operating costs.

[0004] In response to the above challenges, the "AI Smart Inventory" method came into being. This method uses advanced AI algorithms and mobile Internet technology to achieve efficient and accurate inventory of fixed assets. Through the preset inventory equipment combined with the built-in AI algorithm, it can automatically identify and process physical asset information, convert it into structured ledger data in real time, and verify it according to national standards. More importantly, the design of this solution takes into account the network stability issues in actual application scenarios. It can save the inventory results in an offline state and automatically upload them to the server after the network is restored, ensuring the security and integrity of data transmission. In short, "AI Smart Inventory" provides a new solution that effectively solves many problems existing in the traditional inventory process. Summary of the invention

[0005] The main purpose of the present invention is to provide an AI intelligent inventory method, device, equipment and storage medium, which solves the technical problem that traditional inventory methods are difficult to reflect asset changes in a timely manner, resulting in frequent discrepancies between accounts and actual assets, affecting the effectiveness and accuracy of asset management.

[0006] To achieve the above object, the present invention provides an AI intelligent inventory method, comprising the following steps: Conducting a real-time physical inventory of the target fixed assets through a preset inventory counting device to obtain inventory counted asset data, and judging whether the inventory counted asset data complies with inventory count regulations through a preset judgment mechanism; wherein the inventory count regulations include the use of asset information and national standard information; If it is in compliance, the asset inventory data is formatted and formal ledger information is obtained; The formal ledger information is counted by the AI ​​algorithm in the inventory APP downloaded by the inventory device to obtain the inventory result; wherein the inventory result includes normal inventory information and surplus inventory information; Determine whether the inventory counting device has a network. If not, save the inventory counting result locally in the inventory counting device, and detect and restore the network of the inventory counting device; upload the inventory counting result locally in the inventory counting machine to a preset server by using the restored inventory counting device to generate an inventory counting report; If there is a network, the inventory results are uploaded to a preset server to generate an inventory report.

[0007] Furthermore, the real-time physical inventory of the target fixed assets is performed by using a preset inventory counting device to obtain the inventory counted asset data, including: Scanning the label of the target fixed asset using a scanner provided on the inventory counting device to obtain asset identification information; The asset identification information is parsed to obtain asset basic data; wherein the asset basic data includes asset name, specification model and purchase date; Taking an image of the target fixed asset by an image acquisition module provided on the inventory counting device to obtain asset image data; Performing status recognition on the asset image data to obtain asset status information; Through the data verification mechanism, the asset basic data and the asset status information are verified to obtain the asset verification result; Determine whether there is any information inconsistency in the asset verification result. If so, record the inconsistent asset status information on the target fixed asset through the exception handling module on the inventory counting device, and replace the label on the target fixed asset accordingly based on the inconsistent asset status information; If it does not exist, the asset verification results are sorted out based on an information aggregation algorithm to obtain the asset inventory data; wherein the asset inventory data includes an asset list and a status report.

[0008] Furthermore, the inventory counting device is provided with a ledger format converter and an information integrator to convert the format of the inventory counted asset data to obtain formal ledger information, including: Eliminate redundancy from the inventory asset data through a data cleaning engine to obtain standardized data; Regularizing the format of the standardized data to obtain a standardized data structure; Performing semantic annotation on the normalized data structure based on a semantic parser to obtain semantic annotation data; wherein the semantic annotation data includes asset category labels, attribute associations, and usage scenarios; The semantically annotated data is restructured using the ledger format converter to obtain a fixed asset ledger; wherein the fixed asset ledger includes usage records and changes; The fixed asset ledger is summarized and processed based on the information integrator to obtain the formal ledger information; wherein the formal ledger information includes an asset list and usage status.

[0009] Furthermore, the inventory result includes normal inventory information and surplus inventory information. The formal ledger information is inventoryed by the AI ​​algorithm in the preset inventory APP to obtain the inventory result, including: The asset chain information is obtained by registering the formal ledger information through the preset blockchain technology; Conducting information inventory based on the asset chain information and historical target fixed assets to obtain preliminary inventory results; Perform difference analysis on the asset status verification results through the AI ​​algorithm in the preset inventory APP to obtain the difference analysis results; If the difference analysis result shows that the historical target fixed assets are consistent with the formal ledger information, the preliminary inventory result is normal inventory information; If the result of the difference analysis is that there is a difference between the historical target fixed assets and the formal ledger information, the preliminary inventory result will be surplus information.

[0010] Further, it is determined whether the inventory counting device has a network. If not, the inventory counting result is stored locally in the inventory counting device, and the network of the inventory counting device is detected and restored; the inventory counting result in the local inventory counting machine is uploaded to a preset server by using the restored inventory counting device to generate an inventory counting report, including: Determine whether the inventory counting device has a network. If there is no network and the inventory counting result is normal inventory counting information, then use the AI ​​algorithm in the inventory counting APP to record information of the target fixed asset based on the normal inventory counting information to obtain normal inventory counting record information; The normal inventory record information is stored in the SQLite database in the inventory device to obtain the normal inventory record information after storage; The network status in the inventory device is automatically monitored and detected in real time by the inventory device to obtain the network status; If the network status shows that the network is fully restored, the stored post-inventory normal record information is uploaded to the asset inventory system in the target PC through the inventory APP; Extracting the data fields of the stored post-inventory normal record information through the asset inventory system, and checking whether the data fields are correct. If correct, clicking a save button in the inventory device to add a timestamp to the stored post-inventory normal record information to obtain an inventory report; If the inventory counting device has no network, and the inventory counting result is surplus information, the surplus information is uploaded to the asset inventory counting system in the target PC in real time; Through the asset inventory system, the data fields of the stored post-inventory normal record information are extracted, and the data fields are checked to see if they are correct. If they are correct, the save button in the inventory device is clicked to add a timestamp to the stored post-inventory normal record information to obtain an inventory report.

[0011] Further, the storing the normal inventory record information in the SQLite database in the inventory device to obtain the stored normal inventory record information includes: Performing data format analysis on the normal inventory record information to obtain data structure information; Selecting a compression algorithm preset in the database based on the data structure information; Compressing the normal inventory record information based on a preset compression algorithm to obtain compressed normal inventory record information; The compressed normal record information is divided into blocks by a clustering algorithm to obtain block record data; The block record data is partitioned and stored through the SQLite database to obtain normal record information after storage.

[0012] Furthermore, if there is a network, the inventory result is uploaded to a preset server to generate an inventory report, including: If the inventory counting device has a network, and the inventory counting result is normal inventory counting information, then the normal inventory counting information is automatically generated into physical information by the asset inventory counting system to obtain detailed information of the inventory counting target fixed assets; Performing information verification on the target fixed asset detailed information based on a preset verification mechanism to verify whether the data fields in the fixed asset detailed information are correct; If correct, the detailed information of the target fixed asset is saved through the asset inventory system to obtain the detailed information of the saved target fixed asset; Modify the field of the inventory result in the formal ledger information corresponding to the detailed information of the saved target fixed asset to obtain the formal ledger information with the inventory result of "normal"; Upload the official account information with the inventory result of "normal" to a preset server to generate an inventory report; If the inventory counting device has a network, and the inventory counting result is surplus information, the surplus information is subjected to data verification and information verification through the asset inventory counting system to verify whether the data fields in the fixed asset detailed information are correct; If correct, the inventory surplus information is uploaded to a preset server to generate an inventory report.

[0013] The present invention also provides an AI intelligent inventory device, comprising: The first inventory module is used to perform a real-time physical inventory of the target fixed assets through a preset inventory device to obtain inventory asset data, and to determine whether the inventory asset data complies with the inventory regulations through a preset judgment mechanism; wherein the inventory regulations include the use of asset information and national standard information; A conversion module is used to convert the format of the inventory asset data to obtain formal ledger information if it meets the requirements; The second inventory module is used to perform an information inventory on the formal ledger information through an AI algorithm in the inventory APP downloaded by the inventory device to obtain an inventory result; wherein the inventory result includes normal inventory information and surplus inventory information; The detection module is used to determine whether the inventory counting device has a network. If there is no network, the inventory counting result is saved locally in the inventory counting machine in the inventory counting device, and the network of the inventory counting device is detected and restored; the inventory counting result in the local inventory counting machine is uploaded to a preset server by using the restored inventory counting device to generate an inventory counting report; The generation module is used to upload the inventory result to a preset server to generate an inventory report if there is a network.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0016] The AI ​​intelligent inventory method provided by the present invention comprises the following steps: performing a real-time physical inventory of target fixed assets through a preset inventory device to obtain inventory asset data, and judging whether the inventory asset data complies with the inventory regulations through a preset judgment mechanism; wherein the inventory regulations include the use of asset information and national standard information; if compliant, the inventory asset data is formatted to obtain formal ledger information; performing an information inventory on the formal ledger information through an AI algorithm in an inventory APP downloaded by the inventory device to obtain an inventory result; wherein the inventory result includes normal inventory information and surplus inventory information; judging whether the inventory device has a network, if not, saving the inventory result locally in the inventory machine in the inventory device, and detecting and restoring the network of the inventory device; uploading the inventory result locally in the inventory machine to a preset server using the restored inventory device to generate an inventory report; if there is a network, uploading the inventory result to a preset server to generate an inventory report. The above-mentioned technical means have solved the problem that the traditional inventory method is difficult to reflect the changes of assets in a timely manner, resulting in frequent discrepancies between accounts and actual assets, which affects the effectiveness and accuracy of asset management. It has realized real-time physical inventory through preset inventory equipment, and combined with AI algorithms to automatically process the obtained asset data. This method greatly reduces the need for manual intervention, thereby improving the speed and accuracy of inventory. At the same time, the use of built-in judgment mechanisms to ensure that the inventory asset data meets the specified standards has the beneficial effect of helping to reduce the occurrence of human errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the steps of the AI ​​intelligent inventory method in one embodiment of the present invention; Figure 2 This is a structural block diagram of an AI intelligent inventory device in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of an AI intelligent inventory method in one embodiment of the present invention; An embodiment of the present invention provides an AI intelligent inventory method, comprising the following steps: Step S1, conduct a real-time physical inventory of the target fixed assets through a preset inventory device to obtain inventory asset data, and use a preset judgment mechanism to determine whether the inventory asset data complies with inventory regulations; wherein the inventory regulations include the use of asset information and national standard information.

[0021] Specifically, when implementing the steps described above, first, it is necessary to conduct a real-time physical inventory of the target fixed assets through the preset inventory equipment. Here, the "preset inventory equipment" refers to a hardware device specially designed for asset inventory. It can be a mobile terminal equipped with sensors such as a barcode scanner, RFID reader or camera, such as a tablet or a dedicated handheld device. These devices can identify and record the existence and characteristics of physical assets, thereby obtaining detailed inventory asset data. Next, in order to ensure that the collected information is accurate and consistent with the enterprise's asset use information and national standard information, a preset judgment mechanism is integrated into the system. This judgment mechanism is a built-in software logic or algorithm that evaluates the obtained inventory asset data based on pre-set standards and rules. For example, if a fixed asset should be accompanied by a specific safety mark or label in accordance with national standards, then the judgment mechanism will check whether the corresponding inventory data contains this information. Similarly, for asset use information, that is, the specific regulations defined within the enterprise on how to properly use, maintain and manage assets, the judgment mechanism will also verify whether the actual inventory data meets these requirements. For example, in a large manufacturing plant application scenario, suppose a batch of machines and equipment are included in the inventory as fixed assets. When the staff uses the preset inventory equipment to scan these machines one by one, the unique identification (which may be a QR code or an RFID tag) on ​​each machine will be read, and the generated inventory asset data includes but is not limited to information such as equipment number, model, location, and status. Subsequently, this information will be analyzed through a preset judgment mechanism to determine whether they comply with the established inventory regulations. For example, according to relevant national standards, certain types of machines must undergo regular safety inspections and be affixed with the latest inspection pass labels; and from the perspective of the company's own asset information, these machines may also be required to be located in a designated work area and maintained in good operating condition. Once any discrepancies are found, the system will immediately mark them for follow-up processing. In this process, the preset judgment mechanism plays a vital role. It not only ensures the efficiency and accuracy of the inventory work, but also promotes the standardization and standardization of asset management. In this way, whether it is for production equipment in the manufacturing industry or fixed assets in other industries, more scientific and reasonable management and supervision can be achieved.

[0022] Step S2: If it meets the requirements, the asset inventory data is formatted and formal ledger information is obtained.

[0023] Specifically, in the steps mentioned above, if the preset judgment mechanism confirms that the inventory asset data complies with the inventory regulations, a key conversion process will be carried out next, that is, the format conversion of the inventory asset data to obtain the formal ledger information. This process is an important link to ensure that the inventory results can be effectively used and managed. Specifically, format conversion involves reorganizing and standardizing the original data collected from the on-site physical inventory according to established standards and structures to ensure that the data can be seamlessly integrated into the enterprise's asset management information system. For example, in the application scenario of a large manufacturing plant, when the staff completes the physical inventory of a batch of machines and equipment, the preset inventory equipment they use has recorded the relevant information of each machine, such as equipment number, model, location and status. However, these original inventory asset data may not be directly applicable to the enterprise's internal management system, because different systems often have their own data formats and input requirements. Therefore, in order to make these data part of the formal ledger information, they need to be format converted. This conversion process is usually automatically performed by the software algorithm built into the inventory APP, which will adjust the inventory asset data to a format compatible with the enterprise's existing ledger system according to pre-set rules. This includes, but is not limited to, mapping data fields to the correct table columns, unifying the representation of dates and times, and ensuring that all necessary metadata are included, such as asset classification codes or department affiliation information. Furthermore, format conversion is not only to adapt to specific technical requirements, but also to improve the quality and consistency of data. In this process, any inconsistent or missing information will be marked for subsequent manual review or supplementation. In addition, for some complex assets, additional processing steps may be required, such as merging multiple related records into a complete asset entry, or vice versa, splitting a comprehensive record into multiple independent components. Such processing ensures that the final generated formal ledger information not only accurately reflects the actual situation of the physical assets, but also facilitates subsequent query, analysis and report generation. In short, through this format conversion process, the real-time inventory asset data can be effectively converted into formal ledger information that is valuable to the enterprise, thereby supporting more efficient and accurate asset management practices.

[0024] Step S3, performing an inventory of the formal ledger information through the AI ​​algorithm in the inventory APP downloaded by the inventory device to obtain an inventory result; wherein the inventory result includes normal inventory information and surplus inventory information.

[0025] Specifically, in the steps mentioned above, the process of taking inventory of the formal ledger information through the AI ​​algorithm in the inventory APP downloaded by the inventory device is a key link in achieving efficient and accurate asset management. This process not only relies on advanced technical means, but also combines the application of intelligent algorithms to ensure that detailed and accurate inventory results are obtained, including normal inventory information and surplus inventory information. Specifically, in the application scenario of a large manufacturing plant, after the staff completes the physical inventory of fixed assets and converts the collected raw data into formal ledger information, the next step is to use the inventory APP installed on the preset inventory device for further information processing. This inventory APP is embedded with specially designed AI algorithms that can automatically analyze and compare formal ledger information with records in the company's internal database to evaluate the actual status of assets. For example, the AI ​​algorithm can identify whether the assets that should exist according to the plan actually appear in the inventory results, and whether their status is as expected, thereby generating the so-called normal inventory information. At the same time, for those additional assets that accidentally appear in the inventory results, that is, assets that are not in the original ledger records, the AI ​​algorithm will also mark them out to form part of the surplus information. For example, let’s say a manufacturing plant regularly counts the machines and equipment on its production line. After the physical inventory is completed and formatted into formal ledger information, the staff launches the inventory app on the inventory device, which then uses its built-in AI algorithm to process the formal ledger information. During this process, the AI ​​algorithm checks whether the latest inventory record of each machine and equipment matches the previously stored data. If everything is normal, then the information will be classified as normal inventory information; if there are new machines and equipment that have not appeared in the previous records, then the newly added equipment information will be identified as excess inventory information. The AI ​​algorithm can also further analyze the excess information to try to find possible reasons, such as newly purchased equipment that has not yet been entered into the system, or duplicate records caused by misoperation. In addition, the AI ​​algorithm can not only simply compare numbers and entries, but also predict potential problems based on historical data and trends. For example, it can predict the possible loss or replacement needs of certain types of equipment based on the inventory situation in the past few years. This forward-looking analysis helps companies prepare in advance and optimize asset management strategies. In general, using the AI ​​algorithm in the inventory APP downloaded by the inventory device to conduct information inventory of formal ledger information not only improves the efficiency and accuracy of the inventory work, but also provides enterprises with deeper data insights and supports more scientific and reasonable asset management decisions.

[0026] Step S4, determining whether the inventory counting device has a network. If not, the inventory counting results are saved locally in the inventory counting machine of the inventory counting device, and the network of the inventory counting device is detected and restored; the restored inventory counting device is used to upload the inventory counting results locally in the inventory counting machine to a preset server to generate an inventory report.

[0027] Specifically, in the steps described above, determining whether the inventory device has a network connection is a crucial link. This process ensures that the continuity of the inventory work and the security of the data can be guaranteed even in poor network conditions. Specifically, when the inventory device completes the information inventory of the formal ledger information and obtains the inventory result containing the normal inventory information and the surplus inventory information, the system will automatically check whether the inventory device currently has a valid network connection. If the inventory device is in a networkless state, in order not to interrupt the entire inventory process, the system will immediately save the inventory result in the local storage space of the inventory machine in the inventory device. Taking a large manufacturing plant as an example, suppose that during the physical inventory of machinery and equipment, the inventory personnel find that the wireless network signal in the area is unstable or completely missing. At this time, according to the preset logic, the inventory APP will not stop working or lose the collected data due to network problems. On the contrary, it will respond quickly and save all the generated inventory results safely to the local storage of the inventory device. This design not only protects the integrity of the data, but also allows the inventory personnel to continue with subsequent work without being affected by the network conditions. Next, the system will continue to monitor and try to restore the network connection of the inventory device. This usually involves a series of automated detection and troubleshooting operations, such as reconnecting to the nearest wireless access point, switching to an alternative network connection (such as mobile data), or prompting the user to take necessary manual intervention measures to solve the problem. Once the network connection is successfully restored, the inventory device can immediately upload the inventory results previously saved locally to the preset server. During this process, the system will also verify the integrity and accuracy of the data transmission to ensure that no information is missed or damaged. Finally, when all inventory results are successfully uploaded to the server, the system will automatically generate a detailed inventory report. This report not only summarizes the status of all inventory assets, but also includes records of any abnormal situations, such as inventory surplus information. In this way, even in a complex industrial environment, enterprises can obtain the latest asset information in a timely manner, provide accurate data support for management, and thus optimize asset management strategies. In short, through the above mechanism, the solution effectively solves the risk of data loss caused by network instability, while ensuring the efficiency and reliability of inventory work, making enterprises more handy in asset management.

[0028] Step S5: if there is a network, the inventory result is uploaded to a preset server to generate an inventory report.

[0029] Specifically, in the steps mentioned above, if the inventory device has a network connection, the inventory result is uploaded to the preset server to generate an inventory report. This process is a key link to ensure that the inventory data can be integrated into the enterprise asset management system in a timely and accurate manner. Specifically, when the inventory device completes the inventory of the formal ledger information and obtains the inventory result containing the normal inventory information and the surplus inventory information, the system will first confirm whether the inventory device has a valid network connection. If there is indeed an available network connection, the next step is to safely and reliably transmit these inventory results to the preset server. Taking a large manufacturing plant as an example, after the physical inventory is completed, the inventory device used by the staff has collected and processed the data of all relevant assets to form the final inventory result. At this time, assuming that the inventory device is in an environment with a stable network connection, the inventory APP will automatically start the data upload process. In order to ensure the security and integrity of data transmission, an encrypted communication protocol, such as HTTPS or SSL / TLS, is usually used between the inventory device and the preset server to prevent sensitive information from being intercepted or tampered with during transmission. At the same time, data compression and format optimization may be performed before uploading to improve transmission efficiency and reduce bandwidth usage. Once the inventory results are successfully uploaded to the preset server, the server-side application will immediately start processing the received data. This processing process includes but is not limited to verifying the integrity and consistency of the data, checking for duplicate records, and integrating the new inventory information into the existing asset database. At this stage, the server may also run a series of quality control algorithms, such as cross-checking inventory records from different time periods to detect any potential anomalies. In this way, it can be ensured that the uploaded inventory results not only accurately reflect the actual status of the current assets, but also are consistent with historical data. Finally, when all inventory results have been strictly verified and integrated, the server will automatically generate a detailed inventory report. This report not only summarizes the status of all inventory assets, but also includes records of any abnormal situations, such as inventory surplus information. For management, this inventory report provides valuable data support to help them make more scientific and reasonable asset management decisions. For example, in the application scenario of a manufacturing plant, management can use the latest inventory report to evaluate whether the equipment configuration on the production line is reasonable, whether there are idle or excess assets that need to be reallocated, or whether it is necessary to purchase new equipment to meet production needs. In short, through the above mechanism, the solution not only realizes the efficient uploading of inventory results and report generation, but also brings higher transparency and accuracy to the company's asset management.

[0030] In a specific embodiment, the real-time physical inventory of the target fixed assets is performed by a preset inventory counting device to obtain the inventory counted asset data, including: Scanning the label of the target fixed asset using a scanner provided on the inventory counting device to obtain asset identification information; The asset identification information is parsed to obtain asset basic data; wherein the asset basic data includes asset name, specification model and purchase date; Taking an image of the target fixed asset by an image acquisition module provided on the inventory counting device to obtain asset image data; Performing status recognition on the asset image data to obtain asset status information; Through the data verification mechanism, the asset basic data and the asset status information are verified to obtain the asset verification result; Determine whether there is any information inconsistency in the asset verification result. If so, record the inconsistent asset status information on the target fixed asset through the exception handling module on the inventory counting device, and replace the label on the target fixed asset accordingly based on the inconsistent asset status information; If it does not exist, the asset verification results are sorted out based on an information aggregation algorithm to obtain the asset inventory data; wherein the asset inventory data includes an asset list and a status report.

[0031] Specifically, in the steps mentioned above, the process of real-time physical inventory of the target fixed assets through the preset inventory equipment is the key link to achieve efficient and accurate asset management. This process not only relies on advanced hardware facilities, but also combines the application of intelligent algorithms to ensure that detailed and reliable inventory asset data is obtained. Specifically, the entire inventory process begins with scanning the labels of the target fixed assets using the scanner set on the inventory equipment to obtain asset identification information. The "label" here can be a barcode, QR code or RFID tag, which usually contains the basic identification characteristics of the asset. Taking a large manufacturing plant as an example, suppose that the staff is doing a physical inventory of a batch of machines and equipment. First, they use the inventory equipment equipped with a scanning function to scan the labels on these machines one by one. Each label stores specific information, such as equipment number, serial number, etc. When the scanner reads these labels, it can quickly and accurately obtain the corresponding asset identification information. Next, the system will parse and process these asset identification information to extract the asset basic data. The asset basic data includes but is not limited to the asset name, specification model and purchase date, which is crucial for subsequent data verification and management. After obtaining the basic data of the asset, in order to further verify the status of the asset, the inventory counting device will use its built-in image acquisition module to take an image of the target fixed asset. This step is to capture the current physical status of the asset, such as whether it is damaged, whether it is in a normal working position, etc. The asset image data obtained by shooting will be fed into the AI ​​algorithm for status recognition to generate asset status information. In this process, the AI ​​algorithm may apply computer vision technology to automatically analyze the image content and determine whether the asset has abnormal conditions, such as wear, rust or other forms of damage. With the collection of the basic asset data and asset status information completed, the next step is to verify the information between the two through the data verification mechanism to obtain the asset verification result. This verification process is to ensure that the collected data is accurate and matches the internal records of the enterprise. For example, in the context of a manufacturing plant, if the label of a machine shows that it was purchased three years ago, but the image recognition result shows that the machine looks very new, then such inconsistency will be marked. If there is information inconsistency in the asset verification result, it is necessary to record the inconsistent asset status information on the target fixed asset through the exception handling module on the inventory counting device. At the same time, based on these inconsistent information, staff may need to replace the labels on the target fixed assets to ensure that all records are up to date and accurate. However, if no information inconsistencies are found after verification, the system will sort out the asset verification results based on the information aggregation algorithm, and finally obtain the inventory asset data including the asset list and status report.The asset list mentioned here lists in detail all the fixed assets that have been counted and their related information, while the status report provides a specific description of the current status of each asset. This detailed inventory asset data not only provides important decision-making basis for management, but also makes the company's asset management more transparent and efficient. For example, in a manufacturing plant, managers can use the latest inventory asset data to evaluate whether the equipment configuration on the production line is reasonable, whether there are idle or surplus assets that need to be reallocated, or whether it is necessary to purchase new equipment to meet production needs. In addition, by regularly updating and maintaining this data, companies can also better track the life cycle of assets, plan maintenance plans in advance, reduce unexpected downtime, and improve overall operational efficiency. In short, through the above mechanism, the solution realizes an integrated process from physical inventory to data collation, which brings significant advantages to the company's asset management.

[0032] In a specific embodiment, the inventory counting device is provided with a ledger format converter and an information integrator, which converts the format of the inventory counted asset data to obtain formal ledger information, including: Eliminate redundancy from the inventory asset data through a data cleaning engine to obtain standardized data; Regularizing the format of the standardized data to obtain a standardized data structure; Performing semantic annotation on the normalized data structure based on a semantic parser to obtain semantic annotation data; wherein the semantic annotation data includes asset category labels, attribute associations, and usage scenarios; The semantically annotated data is restructured using the ledger format converter to obtain a fixed asset ledger; wherein the fixed asset ledger includes usage records and changes; The fixed asset ledger is summarized and processed based on the information integrator to obtain the formal ledger information; wherein the formal ledger information includes an asset list and usage status.

[0033] Specifically, in the steps described above, the inventory device has a ledger format converter and an information integrator, which converts the format of the inventory asset data through a series of complex processing processes, and finally obtains the formal ledger information. This process not only ensures the accuracy and consistency of the data, but also improves the readability and practicality of the data, providing a solid foundation for the asset management of the enterprise. Specifically, in the application scenario of a large manufacturing plant, after the staff completes the physical inventory of fixed assets and collects the inventory asset data including the asset list and status report, it is necessary to convert the format. First, the inventory asset data is redundantly eliminated through the data cleaning engine, which is a crucial preprocessing step. The data cleaning engine automatically identifies and removes duplicate or unnecessary data items. For example, if multiple machines and equipment have the same serial number or some asset records appear multiple times, these redundant information will be effectively cleaned up to obtain standardized data. This standardized data is the basis for all subsequent processing, which ensures the purity and accuracy of the data set. Then, in order to make these standardized data more widely used and understood, the system will format them to obtain a standardized data structure. This step involves adjusting the way the data is organized to conform to specific standards or protocols. For example, the date format, numerical representation method, etc. are unified to ensure that data from different sources can be seamlessly connected. For a manufacturing plant, this means that all machine equipment records will be in a consistent format, which is convenient for subsequent analysis and management. The normalized data structure not only improves the quality of the data, but also lays a good foundation for subsequent semantic parsing. Subsequently, the normalized data structure is semantically annotated based on the semantic parser to obtain semantically annotated data. Semantic annotation here refers to adding additional metadata to the data, such as asset category tags, attribute associations, and usage scenarios. For example, for a CNC machine tool, the semantic parser may assign it a category label of "production equipment" and point out its key attributes (such as accuracy level, working range) and main application scenarios (such as for processing specific types of parts). In this way, not only can the function and purpose of each asset be understood more intuitively, but also rich background information can be provided for advanced data analysis. Further, the semantically annotated data is restructured using the ledger format converter to obtain a fixed asset ledger. The role of the ledger format converter is to rearrange and combine data elements to form a logically clear and easy-to-query fixed asset ledger. In this process, each asset entry will contain detailed usage records and changes, such as the time when a piece of equipment was transferred from one workshop to another, or the specific content of the most recent maintenance. This detailed ledger record provides the company with a comprehensive historical view and helps track the entire life cycle of the asset.Finally, the fixed asset ledger is summarized and processed based on the information integrator to obtain the formal ledger information. The task of the information integrator is to conduct a comprehensive analysis of the data scattered in each ledger entry and generate a complete formal ledger information, which includes an asset list and usage status. For a manufacturing plant, this formal ledger information is not only the core document of enterprise asset management, but also an important basis for management to make decisions. For example, management can evaluate whether the equipment configuration on the production line is reasonable, whether there are idle or surplus assets that need to be reallocated, or whether it is necessary to purchase new equipment to meet production needs based on the latest formal ledger information. For example, in a manufacturing plant, managers can quickly find detailed information about any piece of equipment through formal ledger information, including its location, status, historical maintenance records, etc. In addition, by regularly updating and maintaining this information, enterprises can better track the life cycle of assets, plan maintenance plans in advance, reduce unexpected downtime, and improve overall operational efficiency. In short, through the above mechanism, the solution realizes a series of efficient conversions from original inventory asset data to formal ledger information, which not only enhances the value of data, but also promotes the scientific and refined asset management.

[0034] In a specific embodiment, the inventory result includes normal inventory information and surplus inventory information. The formal ledger information is inventoryed by the AI ​​algorithm in the preset inventory APP to obtain the inventory result, including: The asset chain information is obtained by registering the formal ledger information through the preset blockchain technology; Conducting information inventory based on the asset chain information and historical target fixed assets to obtain preliminary inventory results; Perform difference analysis on the asset status verification results through the AI ​​algorithm in the preset inventory APP to obtain the difference analysis results; If the difference analysis result shows that the historical target fixed assets are consistent with the formal ledger information, the preliminary inventory result is normal inventory information; If the result of the difference analysis is that there is a difference between the historical target fixed assets and the formal ledger information, the preliminary inventory result will be surplus information.

[0035] Specifically, in the steps described above, the process of inventorying the formal ledger information through the AI ​​algorithm in the preset inventory APP combines blockchain technology and smart contracts to ensure detailed and reliable inventory results. This process not only improves the security and transparency of the data, but also enhances the accuracy and efficiency of the inventory work. Specifically, the entire process starts with the asset registration of the formal ledger information through the preset blockchain technology, and then generates asset chain information. This step lays a solid foundation for subsequent information inventory and verification. Taking a large manufacturing plant as an example, assuming that the staff has completed the physical inventory of fixed assets and collected the formal ledger information including the asset list and status report, the next step is to process this information in detail. First, the system will use the preset blockchain technology to register the formal ledger information and obtain the asset chain information. The "blockchain technology" here refers to a distributed ledger technology that can record the status changes of all assets and ensure that these records cannot be tampered with. For example, in a manufacturing plant, the history of each machine and equipment from purchase to each location change and maintenance will be recorded in detail on the blockchain to form the so-called asset chain information. This asset chain information not only contains the basic attributes of the asset, such as name, model, purchase date, etc., but also includes all status change records, thus providing a complete view of the asset life cycle. Based on the asset chain information and the historical target fixed assets, an information inventory is conducted to obtain a preliminary inventory result. This step involves comparing the asset records in the current formal ledger information with the historical records on the blockchain to determine the actual status of each asset. For example, in a manufacturing plant, staff may find that the location of some equipment has changed, or new equipment has been added to the production line. By comparing the asset chain information, it is possible to accurately identify which assets are in place as planned (i.e., normal inventory information) and which are unexpectedly present or missing (i.e., inventory surplus or inventory shortage information). This blockchain-based inventory method greatly improves the consistency and accuracy of the data and avoids omissions or errors that may occur in traditional manual inventory. In order to further ensure the authenticity and reliability of the inventory results, the system will perform a difference analysis on the asset status verification results through the AI ​​algorithm in the preset inventory APP to obtain the difference analysis results. The "difference analysis" here refers to the use of AI algorithms to automatically detect inconsistencies between the formal ledger information and the historical target fixed assets. For example, in a manufacturing plant, if a piece of equipment is shown to be located in a certain workshop in the formal ledger information, but appears in another workshop in the blockchain record, then this difference will be marked. In this way, the system can not only identify actual differences, but also provide a clear direction for subsequent processing. If the difference analysis result is that the historical target fixed assets are consistent with the formal ledger information, the preliminary inventory result is normal inventory information.This means that the status of all assets is consistent with the historical records and no anomalies have been found. For a manufacturing plant, this indicates that all machines and equipment are in the expected location and in good condition. On the other hand, if the difference analysis result is that there is a difference between the historical target fixed assets and the formal ledger information, the preliminary inventory result is surplus information. This situation usually involves unexpected assets, which may require management to know and take corresponding measures as soon as possible. For example, in a manufacturing plant, if new equipment that has not been recorded before is found, the system will quickly mark this information as surplus information so that managers can update the asset list in time to avoid waste of resources or duplicate purchases. For example, in the application scenario of a manufacturing plant, suppose that during a regular inventory, staff discovered several newly installed CNC machine tools. Through the above process, the system will first register the relevant information of these new devices on the blockchain, then compare it with the existing ledger, and finally confirm it as surplus information. Subsequently, the system will verify the status of these new devices and perform difference analysis through AI algorithms to confirm that these devices are indeed not in the original historical records. Finally, based on the results of the difference analysis, the system will mark these new devices as surplus information and notify relevant personnel for further processing. In short, through the above mechanism, the solution realizes efficient, secure and reliable information inventory of formal ledger information. This method not only solves the problems existing in traditional inventory work, such as poor data consistency and many manual errors, but also provides enterprises with a new asset management tool, promoting the scientific and refined asset management. By combining blockchain technology and AI algorithms, the system not only ensures the authenticity and integrity of the data, but also improves the efficiency and accuracy of inventory work, making the company's asset management more transparent and efficient.

[0036] In a specific embodiment, it is determined whether the inventory counting device has a network. If not, the inventory counting result is saved locally in the inventory counting machine in the inventory counting device, and the network of the inventory counting device is detected and restored; the inventory counting result in the local inventory counting machine is uploaded to a preset server by using the restored inventory counting device to generate an inventory counting report, including: Determine whether the inventory counting device has a network. If there is no network and the inventory counting result is normal inventory counting information, then use the AI ​​algorithm in the inventory counting APP to record information of the target fixed asset based on the normal inventory counting information to obtain normal inventory counting record information; The normal inventory record information is stored in the SQLite database in the inventory device to obtain the normal inventory record information after storage; The network status in the inventory device is automatically monitored and detected in real time by the inventory device to obtain the network status; If the network status shows that the network is fully restored, the stored post-inventory normal record information is uploaded to the asset inventory system in the target PC through the inventory APP; Extracting the data fields of the stored post-inventory normal record information through the asset inventory system, and checking whether the data fields are correct. If correct, clicking a save button in the inventory device to add a timestamp to the stored post-inventory normal record information to obtain an inventory report; If the inventory counting device has no network, and the inventory counting result is surplus information, the surplus information is uploaded to the asset inventory counting system in the target PC in real time; Through the asset inventory system, the data fields of the stored post-inventory normal record information are extracted, and the data fields are checked to see if they are correct. If they are correct, the save button in the inventory device is clicked to add a timestamp to the stored post-inventory normal record information to obtain an inventory report.

[0037] Specifically, in the steps described above, determining whether the inventory device has a network connection is a key link to ensure the smooth progress of the inventory work. This process not only involves the evaluation of the current network status, but also includes how to properly handle the inventory results when the network is unavailable, and finally upload these results to the preset server to generate an inventory report. Specifically, the entire process starts with determining whether the inventory device has a network. If there is no network, a series of measures will be taken to ensure the continuity of the inventory work and the security of the data. Taking a large manufacturing plant as an example, assume that the staff is using a mobile device equipped with an inventory APP to conduct a physical inventory of a batch of machinery and equipment. After the information inventory is completed and the results containing normal inventory information and surplus information are obtained, the system will first automatically check whether the inventory device has an available network connection. If the network is found to be unavailable, the system will not interrupt the inventory process, but will immediately start the backup plan, that is, through the AI ​​algorithm in the inventory APP, the target fixed assets are recorded based on the normal inventory information to obtain the normal inventory record information. In this case, even if there is no network connection, the inventory data can continue to be recorded and saved, ensuring the continuity of the work. Next, in order to prevent data loss or damage, the system will store the normal inventory record information in the SQLite database in the inventory device to obtain the normal inventory record information after storage. SQLite is a lightweight relational database management system, which is particularly suitable for embedded applications. It can efficiently manage and query data in a local environment. In the application scenario of a manufacturing plant, this means that all normal inventory record information can be safely stored inside the inventory device until the network is restored. This step is crucial to ensure data integrity, especially in a working environment with unstable network conditions. At the same time, the inventory device will automatically monitor and detect the network status inside it in real time to obtain the network status. This continuous monitoring mechanism can capture changes in network conditions in a timely manner. Once the network is fully restored, the system will respond immediately and upload the normal inventory record information after storage to the asset inventory system in the target PC through the inventory APP. The target PC refers to the computer terminal used for asset management within the enterprise, and the asset inventory system is an application specially designed to process and analyze inventory data. In this way, even in the case of a short network interruption, it can ensure that all inventory data can eventually be accurately transmitted to the central management system of the enterprise. Furthermore, through the asset inventory system, the system will extract the data fields of the stored post-inventory normal record information and detect whether the data fields are correct. For example, in a manufacturing plant, managers can view detailed information of each machine equipment, such as model, purchase date, current location, etc., through the asset inventory system.If all data fields are correct, the user only needs to click the Save button in the inventory device to add a timestamp to the stored normal inventory record information and obtain a formal inventory report. The addition of a timestamp not only marks the specific time of data upload, but also enhances the traceability and reliability of the data. However, if the inventory device has no network and the inventory result is excess information, a different approach is required. In this case, the system will immediately upload the excess information to the asset inventory system in the target PC in real time. This is because excess information usually involves unexpected assets, which may require management to know and take corresponding measures as soon as possible. For example, in a manufacturing plant, if new equipment that has not been recorded before is found, the system will quickly send this information to the asset inventory system so that managers can update the asset list in time to avoid waste of resources or repeated purchases. Finally, whether it is for normal inventory information or excess information, the system will extract the corresponding data fields through the asset inventory system and detect whether these data fields are correct. If the confirmation is correct, the user also needs to click the Save button in the inventory device to add a timestamp to the stored normal inventory record information to obtain a formal inventory report. In this process, the addition of a timestamp provides a clear time reference for each asset, which is helpful for subsequent audits and management decisions. In short, through the above mechanism, this solution not only solves the risk of data loss caused by network instability, but also ensures the efficiency and reliability of inventory work. Whether the network is normal or abnormal, the inventory results can be accurately recorded, securely stored and uploaded in a timely manner, providing strong support for enterprises and promoting the scientific and refined management of assets.

[0038] In a specific embodiment, the storing the normal inventory record information in a SQLite database in the inventory counting device to obtain the stored normal inventory record information includes: Performing data format analysis on the normal inventory record information to obtain data structure information; Selecting a compression algorithm preset in the database based on the data structure information; Compressing the normal inventory record information based on a preset compression algorithm to obtain compressed normal inventory record information; The compressed normal record information is divided into blocks by a clustering algorithm to obtain block record data; The block record data is partitioned and stored through the SQLite database to obtain normal record information after storage.

[0039] Specifically, in the steps described above, the process of storing the normal inventory record information in the SQLite database in the inventory device not only involves a simple data saving operation, but also a systematic process including complex steps such as data format analysis, compression processing and partition storage. This process is designed to ensure the security, integrity and efficient access of data, thereby providing a solid foundation for subsequent data upload and management. Specifically, in the application scenario of a large manufacturing plant, when the staff uses the inventory device to complete the inventory of fixed assets and obtains the normal inventory record information, the system will first perform data format analysis on this information to obtain data structure information. The "data format analysis" here refers to determining its internal data type, field length, arrangement order and other characteristics by parsing the content and organization of the normal inventory record information. For example, in a manufacturing plant, the inventory record of each machine equipment may include multiple fields such as equipment number, model, purchase date, location coordinates, etc. By analyzing these fields, the specific attributes of each asset and its representation in the record can be accurately understood. This detailed structural information is crucial for subsequent data processing. It not only helps to select a suitable storage solution, but also provides a prerequisite for the effective use of data. Based on the obtained data structure information, the next step is to select the compression algorithm preset in the database. This is because directly storing the original normal inventory record information in the SQLite database may take up a large amount of space, especially in the case of large-scale fixed asset inventory. Therefore, in order to optimize storage efficiency and reduce resource consumption, the system will select the most suitable compression algorithm according to the characteristics of the data structure. For example, if there is a large amount of repeated or redundant information in the records of a certain type of asset, a compression algorithm that can effectively remove these redundancies can be selected; and for records containing a large amount of numerical data, a compression method specifically for this type of data can be selected. In this way, the data volume can be significantly reduced while maintaining the integrity and readability of the data. Once a suitable compression algorithm is selected, the system will compress the normal inventory record information to obtain the compressed normal inventory record information. This compression process is not just a simple reduction in file size, but more importantly, it can achieve efficient storage without affecting data quality. For example, in a manufacturing plant, assuming that the inventory records of a batch of machinery and equipment are compressed, the data that originally occupied a large amount of memory now only needs a small space to be fully stored. This not only increases the storage capacity of the SQLite database, but also speeds up the reading and writing speed of data, making subsequent operations smoother. In order to further improve data management and access efficiency, the system will also divide the compressed normal record information into blocks through a clustering algorithm to obtain block record data. Clustering algorithm is a data analysis technology that can classify similar data items into one category to form independent data blocks.This method is particularly suitable for data sets with specific patterns or associations. In the example of a manufacturing plant, assume that all machines and equipment in the same workshop are divided into a data block, while equipment in different workshops form their own blocks. Through such block processing, the information in each data block can be made more centralized and orderly, which is convenient for rapid positioning and retrieval. Finally, the block record data is partitioned and stored through the SQLite database to obtain the normal record information of the inventory after storage. As a lightweight relational database management system, SQLite supports a variety of storage strategies, including partition storage. In this case, the system will allocate the block record data to different database partitions according to pre-set rules. For example, different partitions can be created according to timestamps or geographic locations, which can not only improve query efficiency, but also simplify backup and recovery operations. For manufacturing plants, this means that managers can easily find and manage the inventory records of related assets according to specific conditions (such as time periods or workshops), which greatly improves the convenience and accuracy of asset management. In summary, through the above mechanism, the scheme realizes a series of efficient conversions from the original normal record information of inventory to the normal record information of inventory after storage. This process not only ensures the security and integrity of the data, but also greatly improves the storage efficiency and access speed of the data, providing strong support for enterprises and promoting the scientific and refined asset management.

[0040] In a specific embodiment, if there is a network, the inventory result is uploaded to a preset server to generate an inventory report, including: If the inventory counting device has a network, and the inventory counting result is normal inventory counting information, then the normal inventory counting information is automatically generated into physical information by the asset inventory counting system to obtain detailed information of the inventory counting target fixed assets; Performing information verification on the target fixed asset detailed information based on a preset verification mechanism to verify whether the data fields in the fixed asset detailed information are correct; If correct, the detailed information of the target fixed asset is saved through the asset inventory system to obtain the detailed information of the saved target fixed asset; Modify the field of the inventory result in the formal ledger information corresponding to the detailed information of the saved target fixed asset to obtain the formal ledger information with the inventory result of "normal"; Upload the official account information with the inventory result of "normal" to a preset server to generate an inventory report; If the inventory counting device has a network, and the inventory counting result is surplus information, the surplus information is subjected to data verification and information verification through the asset inventory counting system to verify whether the data fields in the fixed asset detailed information are correct; If correct, the inventory surplus information is uploaded to a preset server to generate an inventory report.

[0041] Specifically, in the steps described above, if there is a network, the inventory results are uploaded to the preset server. The process of generating an inventory report is a key link to ensure the smooth completion of the inventory work and timely update the enterprise asset management system. This process not only relies on an effective network connection, but also combines automated information processing and verification mechanisms to ensure the accuracy and consistency of the data. Specifically, the entire process starts with determining whether the inventory device has a network, and then takes corresponding processing measures according to the different types of inventory results (i.e., normal inventory information or surplus inventory information). First, in the application scenario of a large manufacturing plant, it is assumed that the staff uses a mobile device equipped with an inventory APP to complete the information inventory of a batch of machines and equipment, and obtains results containing normal inventory information and surplus inventory information. If the inventory device confirms that there is an available network connection, and the inventory result is normal inventory information, the system will automatically generate physical information for the normal inventory information through the asset inventory system to obtain detailed information of the inventory target fixed assets. The "physical information" mentioned here refers to a specific description corresponding to the actual existing assets, including but not limited to the equipment name, model, purchase date, location coordinates, etc. For example, in a manufacturing plant, when the inventory results show that a certain CNC machine tool is in normal use, the asset inventory system will automatically generate detailed information about the machine tool, such as the workshop it is currently in, the time of the last maintenance, etc., thereby forming a complete fixed asset record. Next, in order to ensure the accuracy of these automatically generated fixed asset details, the system will perform information verification on the target fixed asset details based on a preset verification mechanism. The verification mechanism here involves a series of verification rules to check whether each data field in the fixed asset details is correct. For example, the system may check whether the equipment number conforms to a specific format, whether the purchase date is reasonable, whether the location coordinates are within the legal range, etc. Through this strict verification process, data entry errors or inconsistencies can be effectively avoided, and the basic data quality of subsequent operations can be guaranteed. Once all data fields are confirmed to be correct after verification, the system will save the target fixed asset details through the asset inventory system to obtain the saved target fixed asset details. This step means that all normal inventory information has been formally recorded and become part of the enterprise asset management system. For manufacturing plants, this means that managers can now view the latest status of each machine and equipment through the central system, so as to better plan production arrangements and maintenance plans. Subsequently, in order to reflect the latest inventory results, the system will modify the field of the inventory results in the formal ledger information corresponding to the detailed information of the saved target fixed assets, and obtain the formal ledger information with the inventory result of "normal". This field modification is to clearly identify which assets have been counted and are in good condition, which is convenient for subsequent management and auditing.For example, in a manufacturing plant, the updated formal ledger information will show that the latest inventory result of a certain CNC machine tool is "normal", which is not only convenient for query, but also enhances the transparency and reliability of the data. Finally, the system will upload the formal ledger information with the inventory result of "normal" to the preset server to generate an inventory report. This upload process ensures that all the latest inventory data can be integrated into the central management system of the enterprise in a timely manner, so that the management can obtain the most accurate asset status at any time. At the same time, the generated inventory report provides an important decision-making basis for the management, helping them to evaluate whether the equipment configuration on the production line is reasonable, whether there are idle or surplus assets that need to be reallocated, or whether it is necessary to purchase new equipment to meet production needs. On the other hand, if the inventory equipment has a network and the inventory result is surplus information, the system will perform data verification on the surplus information through the asset inventory system to verify whether the data fields in the fixed asset detailed information are correct. For surplus information, that is, assets that appear unexpectedly in the inventory results, strict verification is particularly important, because they may be newly purchased equipment that has not been entered into the system in time, or assets that cannot be found in the original ledger due to other reasons. For example, in a manufacturing plant, if a batch of new equipment that has not been recorded before is found, the system will strictly verify the detailed information of these equipment to ensure that each data is accurate. If it is confirmed to be correct after verification, the system will directly upload the surplus information to the preset server to generate an inventory report. This instant upload method ensures that the management can quickly understand the situation of the newly added assets, update the asset management system in a timely manner, and take necessary management measures, such as registering new equipment, arranging installation and commissioning, etc. In short, through the above mechanism, the solution not only solves the problem of efficient uploading of inventory results under stable network conditions, but also ensures the accuracy and consistency of data through automated information processing and strict verification mechanisms. Whether processing normal inventory information or surplus information, it can achieve safe storage and timely update of data, providing strong support for enterprises and promoting scientific and refined asset management.

[0042] The above describes the AI ​​intelligent inventory method in the embodiment of the present invention. The following describes the AI ​​intelligent inventory system in the embodiment of the present invention. Figure 2 , an embodiment of the AI ​​intelligent inventory system in the embodiment of the present invention includes: The first inventory module 21 is used to perform a real-time physical inventory of the target fixed assets through a preset inventory device to obtain inventory asset data, and to determine whether the inventory asset data complies with the inventory regulations through a preset judgment mechanism; wherein the inventory regulations include the use of asset information and national standard information; The conversion module 22 is used to convert the format of the inventory asset data to obtain formal ledger information if it meets the requirements; The second inventory module 23 is used to perform an information inventory on the formal ledger information through the AI ​​algorithm in the inventory APP downloaded by the inventory device to obtain an inventory result; wherein the inventory result includes normal inventory information and surplus inventory information; The detection module 24 is used to determine whether the inventory counting device has a network. If there is no network, the inventory counting result is saved locally in the inventory counting device, and the network of the inventory counting device is detected and restored; the inventory counting result in the local inventory counting machine is uploaded to a preset server by using the restored inventory counting device to generate an inventory counting report; The generating module 25 is used to upload the inventory result to a preset server to generate an inventory report if there is a network.

[0043] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0044] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0045] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0046] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0047] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0048] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0049] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An AI intelligent inventory method, characterized in that: The following steps are involved: Conducting a real-time physical inventory of the target fixed assets through a preset inventory counting device to obtain inventory counted asset data, and judging whether the inventory counted asset data complies with inventory count regulations through a preset judgment mechanism; wherein the inventory count regulations include the use of asset information and national standard information; If it is in compliance, the asset inventory data is formatted and formal ledger information is obtained; The formal ledger information is counted by using an AI algorithm in the inventory APP downloaded by the inventory device to obtain an inventory result; Determine whether the inventory counting device has a network. If not, save the inventory counting result locally in the inventory counting device, and detect and restore the network of the inventory counting device; upload the inventory counting result locally in the inventory counting machine to a preset server by using the restored inventory counting device to generate an inventory counting report; If there is a network, the inventory results are uploaded to a preset server to generate an inventory report.

2. The AI ​​intelligent inventory method according to claim 1, characterized in that: The real-time physical inventory of the target fixed assets is performed by the preset inventory counting equipment to obtain the inventory counted asset data, including: Scanning the label of the target fixed asset using a scanner provided on the inventory counting device to obtain asset identification information; The asset identification information is parsed to obtain asset basic data; wherein the asset basic data includes asset name, specification model and purchase date; Taking an image of the target fixed asset by an image acquisition module provided on the inventory counting device to obtain asset image data; Performing status recognition on the asset image data to obtain asset status information; Through the data verification mechanism, the asset basic data and the asset status information are verified to obtain the asset verification result; Determine whether there is any information inconsistency in the asset verification result. If so, record the inconsistent asset status information on the target fixed asset through the exception handling module on the inventory counting device, and replace the label on the target fixed asset accordingly based on the inconsistent asset status information; If it does not exist, the asset verification results are sorted out based on an information aggregation algorithm to obtain the asset inventory data; wherein the asset inventory data includes an asset list and a status report.

3. The AI ​​intelligent inventory method according to claim 1, characterized in that: The inventory-taking device is provided with a ledger format converter and an information integrator, which converts the format of the inventory-taking asset data to obtain formal ledger information, including: Eliminate redundancy from the inventory asset data through a data cleaning engine to obtain standardized data; Regularizing the format of the standardized data to obtain a standardized data structure; Performing semantic annotation on the normalized data structure based on a semantic parser to obtain semantic annotation data; wherein the semantic annotation data includes asset category labels, attribute associations, and usage scenarios; The semantically annotated data is restructured using the ledger format converter to obtain a fixed asset ledger; wherein the fixed asset ledger includes usage records and changes; The fixed asset ledger is summarized and processed based on the information integrator to obtain the formal ledger information; wherein the formal ledger information includes an asset list and usage status.

4. The AI ​​intelligent inventory method according to claim 1, characterized in that: The inventory result includes normal inventory information and surplus inventory information. The formal ledger information is inventoryed by the AI ​​algorithm in the preset inventory APP to obtain the inventory result, including: The asset chain information is obtained by registering the formal ledger information through the preset blockchain technology; Conducting information inventory based on the asset chain information and historical target fixed assets to obtain preliminary inventory results; Perform difference analysis on the asset status verification results through the AI ​​algorithm in the preset inventory APP to obtain the difference analysis results; If the difference analysis result shows that the historical target fixed assets are consistent with the formal ledger information, the preliminary inventory result is normal inventory information; If the result of the difference analysis is that there is a difference between the historical target fixed assets and the formal ledger information, the preliminary inventory result will be surplus information.

5. The AI ​​intelligent inventory method according to claim 1, characterized in that: Determine whether the inventory counting device has a network. If not, save the inventory counting result locally in the inventory counting machine in the inventory counting device, and detect and restore the network of the inventory counting device; The restored inventory counting device is used to upload the inventory counting results in the local inventory counting machine to a preset server to generate an inventory counting report, including: Determine whether the inventory counting device has a network. If there is no network and the inventory counting result is normal inventory counting information, then use the AI ​​algorithm in the inventory counting APP to record information of the target fixed asset based on the normal inventory counting information to obtain normal inventory counting record information; The normal inventory record information is stored in the SQLite database in the inventory device to obtain the normal inventory record information after storage; The network status in the inventory device is automatically monitored and detected in real time by the inventory device to obtain the network status; If the network status shows that the network is fully restored, the stored post-inventory normal record information is uploaded to the asset inventory system in the target PC through the inventory APP; Extracting the data fields of the stored post-inventory normal record information through the asset inventory system, and checking whether the data fields are correct. If correct, clicking a save button in the inventory device to add a timestamp to the stored post-inventory normal record information to obtain an inventory report; If the inventory counting device has no network, and the inventory counting result is surplus information, the surplus information is uploaded to the asset inventory counting system in the target PC in real time; Through the asset inventory system, the data fields of the stored post-inventory normal record information are extracted, and the data fields are checked to see if they are correct. If they are correct, the save button in the inventory device is clicked to add a timestamp to the stored post-inventory normal record information to obtain an inventory report.

6. The AI ​​intelligent inventory method according to claim 5, characterized in that: The storing the normal inventory record information in the SQLite database in the inventory counting device to obtain the stored normal inventory record information includes: Performing data format analysis on the normal inventory record information to obtain data structure information; Selecting a compression algorithm preset in the database based on the data structure information; Compressing the normal inventory record information based on a preset compression algorithm to obtain compressed normal inventory record information; The compressed normal record information is divided into blocks by a clustering algorithm to obtain block record data; The block record data is partitioned and stored through the SQLite database to obtain normal record information after storage.

7. The AI ​​intelligent inventory method according to claim 5, characterized in that: If there is a network, the inventory result is uploaded to a preset server to generate an inventory report, including: If the inventory counting device has a network, and the inventory counting result is normal inventory counting information, then the normal inventory counting information is automatically generated into physical information by the asset inventory counting system to obtain detailed information of the inventory counting target fixed assets; Performing information verification on the target fixed asset detailed information based on a preset verification mechanism to verify whether the data fields in the fixed asset detailed information are correct; If correct, the detailed information of the target fixed asset is saved through the asset inventory system to obtain the detailed information of the saved target fixed asset; Modify the field of the inventory result in the formal ledger information corresponding to the detailed information of the saved target fixed asset to obtain the formal ledger information with the inventory result of "normal"; Upload the official account information with the inventory result of "normal" to the preset server to generate an inventory report; If the inventory counting device has a network, and the inventory counting result is surplus information, the surplus information is subjected to data verification and information verification through the asset inventory counting system to verify whether the data fields in the fixed asset detailed information are correct; If correct, the inventory surplus information is uploaded to a preset server to generate an inventory report.

8. An AI intelligent inventory device, characterized in that: include: The first inventory module is used to perform a real-time physical inventory of the target fixed assets through a preset inventory device to obtain inventory asset data, and to determine whether the inventory asset data complies with the inventory regulations through a preset judgment mechanism; wherein the inventory regulations include the use of asset information and national standard information; A conversion module is used to convert the format of the inventory asset data to obtain formal ledger information if it meets the requirements; The second inventory module is used to perform an information inventory on the formal ledger information through an AI algorithm in the inventory APP downloaded by the inventory device to obtain an inventory result; wherein the inventory result includes normal inventory information and surplus inventory information; The detection module is used to determine whether the inventory counting device has a network. If there is no network, the inventory counting result is saved locally in the inventory counting machine in the inventory counting device, and the network of the inventory counting device is detected and restored; the inventory counting result in the local inventory counting machine is uploaded to a preset server by using the restored inventory counting device to generate an inventory counting report; The generation module is used to upload the inventory result to a preset server to generate an inventory report if there is a network.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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