CN113807772A - Fixed asset management system based on cloud platform - Google Patents

Fixed asset management system based on cloud platform Download PDF

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Publication number
CN113807772A
CN113807772A CN202110943776.7A CN202110943776A CN113807772A CN 113807772 A CN113807772 A CN 113807772A CN 202110943776 A CN202110943776 A CN 202110943776A CN 113807772 A CN113807772 A CN 113807772A
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asset
fixed
information
cloud platform
fixed asset
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葛明
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Guangzhou Fengyijie Electronic Technology Co ltd
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Guangzhou Fengyijie Electronic Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
    • G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/30—Administration of product recycling or disposal
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation

Abstract

The invention provides a fixed asset management system based on a cloud platform, which comprises a warehousing module, a cloud platform module, an asset management module and a warehousing-out module; the warehousing module is used for acquiring the asset information of the newly purchased fixed asset; the cloud platform module is used for storing asset information; the asset management module comprises an asset counting unit and an asset management unit; the asset checking unit is used for updating the asset information based on the appearance image of the fixed asset; the asset management unit is used for managing the assets of the fixed assets based on the attribute information of the fixed assets; and the ex-warehouse module is used for updating the asset information of the scrapped fixed assets. The method and the device determine the damage degree of the fixed asset by acquiring the appearance image of the fixed asset, and then update the asset information of the fixed asset, so that the consistency of the judgment standard of large-scale enterprises on the damage degree of the fixed asset is favorably realized, and the enterprises can accurately grasp the damage degree of the fixed asset.

Description

Fixed asset management system based on cloud platform
Technical Field
The invention relates to the field of management, in particular to a fixed asset management system based on a cloud platform.
Background
The damage degree of the fixed assets generally needs to be filled in when the fixed assets are checked, and in the prior art, the damage degree is generally determined by the subjectivity of staff responsible for checking the fixed assets. If the fixed assets are relatively small in size, such as in some small companies, then subjective identification of the extent of damage to all fixed assets by the same person is not problematic and the identification criteria are consistent. However, if the fixed assets are large in scale, when a plurality of people are required to take charge of counting, the damage degree is difficult to be determined to be consistent with the standard due to the influence of individual subjective factors. This can make it difficult for a business to accurately ascertain the level of damage to a fixed asset.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a fixed asset management system based on a cloud platform, which includes an warehousing module, a cloud platform module, an asset management module and a warehousing module;
the warehousing module is used for acquiring the asset information of the newly purchased fixed asset and sending the asset information to the cloud platform module;
the cloud platform module is used for storing the asset information;
the asset management module comprises an asset counting unit and an asset management unit;
the asset counting unit is used for updating the asset information based on the appearance image of the fixed asset;
the asset management unit is used for managing the assets of the fixed assets based on the attribute information of the fixed assets;
and the ex-warehouse module is used for updating the asset information of the scrapped fixed assets.
Preferably, the warehousing module comprises an RFID reading unit and a communication unit;
the RFID reading unit is used for communicating with an RFID label stuck on a newly purchased fixed asset to acquire asset information of the fixed asset;
the communication unit is used for transmitting the asset information to the cloud platform module;
the RFID tag is used to store asset information of a newly purchased fixed asset.
Preferably, the asset information includes:
a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, and a damage rating of the fixed asset.
Preferably, the asset inventory unit comprises a shooting subunit, an image identification subunit and an information updating subunit;
the shooting subunit is used for acquiring an appearance image of the fixed asset and transmitting the appearance image to the image identification subunit;
the image identification subunit is used for carrying out image identification processing on the appearance image to obtain a damage degree rating of the fixed asset;
the information updating subunit is used for updating the asset information of the fixed asset stored in the cloud platform module according to the damage degree rating obtained by the image identifying subunit.
Preferably, the attribute information of the fixed asset includes:
one or more of a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, a damage rating of the fixed asset.
Preferably, the asset management unit comprises a query subunit, a delete subunit and a modify subunit;
the query subunit is used for querying the asset information in the cloud platform module based on the asset information of the attribute information of the fixed asset;
the deleting submodule is used for deleting the asset information in the cloud platform module;
the modification subunit is used for modifying the asset information in the cloud platform module.
The invention realizes the comprehensive management of the whole life cycle from purchase to abandonment of the fixed assets. The damage degree of the fixed asset is determined by obtaining the appearance image of the fixed asset, and then the asset information of the fixed asset is updated, so that the consistency of the judgment standard of large-scale enterprises on the damage degree of the fixed asset is favorably realized, and the enterprises can accurately grasp the damage degree of the fixed asset.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a fixed asset management system based on a cloud platform according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, the present invention provides a fixed asset management system based on a cloud platform, which includes a warehousing module, a cloud platform module, an asset management module and a warehousing module;
the warehousing module is used for acquiring the asset information of the newly purchased fixed asset and sending the asset information to the cloud platform module;
the cloud platform module is used for storing the asset information;
the asset management module comprises an asset counting unit and an asset management unit;
the asset counting unit is used for updating the asset information based on the appearance image of the fixed asset;
the asset management unit is used for managing the assets of the fixed assets based on the attribute information of the fixed assets;
and the ex-warehouse module is used for updating the asset information of the scrapped fixed assets.
The invention realizes the comprehensive management of the whole life cycle from purchase to abandonment of the fixed assets. The damage degree of the fixed asset is determined by obtaining the appearance image of the fixed asset, and then the asset information of the fixed asset is updated, so that the consistency of the judgment standard of large-scale enterprises on the damage degree of the fixed asset is favorably realized, and the enterprises can accurately grasp the damage degree of the fixed asset.
The asset information is stored through the cloud platform module, and the comprehensive management of large-scale enterprises on the asset information is facilitated. For example, all subsidiaries located in different places are provided with modules such as a warehousing module and the like, and all asset information of an enterprise is unified to a cloud platform module for comprehensive management.
Preferably, the warehousing module comprises an RFID reading unit and a communication unit;
the RFID reading unit is used for communicating with an RFID label stuck on a newly purchased fixed asset to acquire asset information of the fixed asset;
the communication unit is used for transmitting the asset information to the cloud platform module;
the RFID tag is used to store asset information of a newly purchased fixed asset.
Specifically, each newly purchased fixed asset is provided with one RFID tag, which is beneficial to improving the efficiency of subsequent asset counting, related information of the asset can be known only by being close to the tag, instead of managing the asset by using a paper tag as in the conventional method, when the paper tag is counted, a person in charge of counting needs to look at the paper tag, and then the asset information of the fixed asset is updated according to the attribute information on the tag, which obviously is not high in efficiency.
Preferably, the asset information includes:
a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, and a damage rating of the fixed asset.
Specifically, the damage rating of the fixed asset may be set according to actual needs, and may include, for example, a rating of severe damage, general damage, no damage, and the like. The damage level of the newly purchased fixed asset is rated as no damage. The more the rating is set, the more beneficial it is to accurately reflect the damage level of the asset.
Preferably, the asset inventory unit comprises a shooting subunit, an image identification subunit and an information updating subunit;
the shooting subunit is used for acquiring an appearance image of the fixed asset and transmitting the appearance image to the image identification subunit;
the image identification subunit is used for carrying out image identification processing on the appearance image to obtain a damage degree rating of the fixed asset;
the information updating subunit is used for updating the asset information of the fixed asset stored in the cloud platform module according to the damage degree rating obtained by the image identifying subunit.
Specifically, the updating the asset information of the fixed asset includes:
and judging whether the newly acquired damage degree rating is consistent with the damage degree rating stored in the cloud platform module, and if not, updating the damage degree rating stored in the cloud platform module by using the newly acquired damage degree rating.
In addition to updating the damage degree, information such as a use department, a number, and the like may be updated.
Preferably, the acquiring an appearance image of the fixed asset and transmitting the appearance image to the image identifying subunit includes:
acquiring an appearance image of a fixed asset;
and judging whether the appearance image meets a preset judgment condition, if so, transmitting the appearance image to the image identification subunit, and if not, re-acquiring the appearance image of the fixed asset.
Preferably, the determining whether the appearance image satisfies a preset determination condition includes:
dividing the appearance image into N sub-images with the same area;
respectively calculating the illumination uniformity index of each sub-image by the following method:
calculating the uniformity index of the corresponding L component image of the sub-image in the Lab color space by using the following formula:
Figure BDA0003215854690000041
in the formula, unis represents a set of all pixel points in the subimage, numofurnis represents the total number of pixel points contained in unis, L (a) represents the pixel value of a pixel point a in the L-component image, and spf represents the uniformity index of the L-component image corresponding to the subimage in the Lab color space;
the determination index of the appearance image is calculated by:
Figure BDA0003215854690000042
in the formula, judidx represents a judgment index of an appearance image, ub represents a set of all sub-images, spf (b) represents a uniformity index of the sub-image b, numofot represents the number of foreground pixel points in an L component image corresponding to the appearance image in a Lab color space, numofall represents the total number of pixel points included in the appearance image, α and β represent weight parameters, and α + β is 1;
if judidx is smaller than a preset judgment threshold, the appearance image meets the preset judgment condition, and if judidx is larger than or equal to the preset judgment threshold, the appearance image does not meet the preset judgment condition.
According to the embodiment of the invention, when the appearance image of the fixed asset is acquired, whether the appearance image meets the judgment condition is judged, and then the appearance image meeting the judgment condition is transmitted to the image identification subunit for processing, so that the quality of the appearance image entering the image identification subunit is improved, and the misjudgment of the damage degree of the fixed asset caused by the low-quality image is avoided. Specifically, in the setting of the judgment index, the difference between the pixel points and the proportion of the foreground pixel points are started, the smaller the difference of the pixel values between the pixel points is, the larger the proportion of the foreground pixel points is, the smaller the value of the judgment index is, so that the image with uniform illumination distribution and large proportion of the foreground pixel points can be selected as the appearance image of the fixed asset.
Preferably, the image recognition processing on the appearance image to obtain the damage degree rating of the fixed asset includes:
converting the appearance image into a grayscale image;
carrying out light ray adjustment processing on the gray level image to obtain a first processed image;
filtering the first processed image to obtain a second processed image;
calculating the similarity between the second processing image and a preset standard appearance image of the fixed asset;
a damage rating for the fixed asset is determined based on the similarity.
Specifically, the light ray adjustment is carried out to effectively and uniformly adjust the distribution of the light rays in the image, so that the influence of nonuniform light ray distribution on the accuracy of the subsequent calculation process is avoided. And the influence of the noise point on the subsequent calculation can be avoided by carrying out image filtering. The shooting angle and the height of the appearance image obtained by the shooting subunit are the same as the shooting angle and the shooting height of the standard appearance image of the preset fixed asset. For example, photographs were taken of the front of the fixed asset at a height of 1.5 m. Of course, this is only an example, and the height may be adjusted according to the size of the fixed asset in the directions of the back, the top view, and the like.
Specifically, determining a damage rating for a fixed asset based on similarity includes: a
The greater the similarity is, the smaller the damage degree of the fixed asset is, and corresponding damage degree ratings are set for the similarities in different sections, for example, when the similarity is greater than 98%, the corresponding damage degree rating is no damage, and the similarity is less than 80%, the corresponding damage degree rating is severe damage, and when the pixel point is greater than or equal to 80% and less than or equal to 98%, the pixel point is general damage. Here, it is only an example, and the damage rating may be set to more levels in an actual application.
Preferably, the converting the appearance image into a grayscale image includes:
establishing a gray level conversion model:
Figure BDA0003215854690000061
wherein m (u) represents a gray level conversion model, taru represents a set of pixel points in a gray level image, tar (u) represents a pixel value of the pixel point u in the gray level image, img (u) represents a pixel value of the pixel point u in the image F, and w (u) represents a pixel value of the pixel point u in the image F1And w2Denotes a scale parameter, w1And w2The sum of (1) and (n) is 1, neu represents a set of pixel points in a window with the size of Q multiplied by Q and taking u as a center, tar (v) represents the pixel value of a pixel point v in an image F, s represents a preset adjusting coefficient, and phi (u) and phi (v) respectively represent the pixel values of the pixel point u and the pixel point v in a phi component image; the image F is an image corresponding to the brightness component of the appearance image in the Lab color space;
taking the value of tar (u) when m (u) takes the minimum value as the pixel value of the pixel point u in the gray image.
The gray level conversion mode can minimize the difference between the pixel points in the gray level image and the difference between the pixel points in the original appearance image, thereby achieving the purpose of accurately retaining the edge information in the appearance image. The accuracy of subsequent similarity calculation is improved.
Preferably, the performing light adjustment processing on the grayscale image to obtain a first processed image includes:
the light adjustment process is performed using the following formula:
ag(x,y)＝c(x,y)×gma
wherein ag (x, y) represents the result of light ray adjustment processing on the pixel point with the coordinate (x, y) in the gray level image; c (x, y) represents a calculation coefficient of a pixel point of coordinates (x, y) in the gray image, gma represents a maximum value of pixel values of the pixel point in the gray image,
if g (x, y) is greater than T, then c (x, y) is calculated using the following formula:
Figure BDA0003215854690000062
if g (x, y) is less than or equal to T, c (x, y) is calculated using the following formula:
Figure BDA0003215854690000071
h represents a preset control coefficient, g (x, y) represents a pixel value of a pixel point with coordinates (x, y) in the grayscale image, gmi represents a minimum value of the pixel point in the grayscale image, and T represents a threshold value obtained by calculating the grayscale image by using an otsu algorithm.
According to the embodiment of the invention, different processing formulas are selected for different types of pixel points through T to calculate the calculation coefficient, so that the pertinence of the calculation coefficient is improved, the accuracy of the obtained light ray adjustment result is improved, the gray level distribution in the first processed image is more uniform, and the influence of the problem of illumination distribution on the subsequent similarity calculation result is further avoided.
Preferably, the filtering the first processed image to obtain a second processed image includes:
performing wavelet image decomposition on the first processed image to obtain a high-frequency image and a low-frequency image;
for high frequency images, the following processing is used:
if hg(s) < tb, the high frequency image is processed by the following formula:
Figure BDA0003215854690000072
if tb is less than or equal to hg(s) and less than or equal to ta, the high-frequency image is processed by the following formula:
Figure BDA0003215854690000073
if ta < hg(s), the high frequency image is processed by the following formula:
bhg(s)＝|hg(s)|
wherein hg and bhg respectively represent the high-frequency image before processing and the high-frequency image after processing, hg(s) and bhg(s) respectively represent the pixel values of the pixel points in hg and bhg, ta and tb represent preset judgment parameters, qs (hg (s)) represents a value-taking function,
Figure BDA0003215854690000074
thre is a preset comparison threshold, nois (hg (s)) represents the standard deviation of noise estimation for hg,
for low-frequency images, the following processing is adopted:
Figure BDA0003215854690000081
wherein sg and bsg represent a low-frequency image before processing and a low-frequency image after processing, neis represents a set of pixels in the neighborhood of c × c of a pixel s, sc represents a distance between pixels q and s, sq represents a result of noise estimation on sg, yz represents a variance of pixel values of pixels in neis, sg(s) and sg (q) represent pixel values of pixels s and q, respectively, bz(s) represents a tuning function,
Figure BDA0003215854690000082
sgma and sgmi respectively represent the maximum value and the minimum value of the pixel values of the pixels in neis, and sgav represents the average value of the pixel values of the pixels in neis;
bhg and bsg are reconstructed to obtain a second processed image.
In the above embodiment of the present invention, when filtering the first processed image, the first processed image is divided into the high frequency image and the low frequency image, then the high frequency image and the low frequency image are respectively filtered in different manners, and the filtering structures of the two images are reconstructed to obtain the second processed image. The arrangement mode is beneficial to filtering noise, and simultaneously, more edge detail information is reserved in the second processed image, and more detail information is reserved for subsequent similarity calculation.
When the high-frequency image is processed, different processing functions are adaptively selected for the high-frequency images with different types through the two judgment parameters for processing, so that the pertinence of the functions is improved, and the accuracy of the filtering result is improved.
When the low-frequency image is processed, besides calculation based on the difference between the distance and the pixel value, the noise estimation result is also considered, and an adjusting and optimizing function is also set, wherein the adjusting and optimizing function is obtained by comparing the pixel values s and the average value of the pixel values in neis, so that the difference degree between the edges of the low-frequency wavelet image obtained after filtering and the original low-frequency wavelet image can be reduced, the loss of edge information is reduced, and the information content contained in the obtained second processed image is increased. The accuracy of judging the damage degree of the fixed assets is improved.
Preferably, the attribute information of the fixed asset includes:
one or more of a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, a damage rating of the fixed asset.
Preferably, the asset management unit comprises a query subunit, a delete subunit and a modify subunit;
the query subunit is used for querying the asset information in the cloud platform module based on the asset information of the attribute information of the fixed asset;
the deleting submodule is used for deleting the asset information in the cloud platform module;
the modification subunit is used for modifying the asset information in the cloud platform module.
For example, the asset information of the fixed asset may be queried, deleted, or modified in the cloud platform module according to the number of the fixed asset.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (6)

1. A fixed asset management system based on a cloud platform is characterized by comprising a warehousing module, a cloud platform module, an asset management module and a warehousing-out module;
the warehousing module is used for acquiring the asset information of the newly purchased fixed asset and sending the asset information to the cloud platform module;
the cloud platform module is used for storing the asset information;
the asset management module comprises an asset counting unit and an asset management unit;
the asset counting unit is used for updating the asset information based on the appearance image of the fixed asset;
the asset management unit is used for managing the assets of the fixed assets based on the attribute information of the fixed assets;
and the ex-warehouse module is used for updating the asset information of the scrapped fixed assets.
2. The cloud platform-based fixed asset management system of claim 1, wherein the warehousing module comprises an RFID reading unit and a communication unit;
the RFID reading unit is used for communicating with an RFID label stuck on a newly purchased fixed asset to acquire asset information of the fixed asset;
the communication unit is used for transmitting the asset information to the cloud platform module;
the RFID tag is used to store asset information of a newly purchased fixed asset.
3. The cloud platform-based fixed asset management system of claim 1, wherein the asset information comprises:
a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, and a damage rating of the fixed asset.
4. The fixed asset management system based on the cloud platform as claimed in claim 3, wherein the asset inventory unit comprises a shooting subunit, an image identification subunit and an information updating subunit;
the shooting subunit is used for acquiring an appearance image of the fixed asset and transmitting the appearance image to the image identification subunit;
the image identification subunit is used for carrying out image identification processing on the appearance image to obtain a damage degree rating of the fixed asset;
the information updating subunit is used for updating the asset information of the fixed asset stored in the cloud platform module according to the damage degree rating obtained by the image identifying subunit.
5. The cloud platform-based fixed asset management system according to claim 3, wherein the attribute information of the fixed asset includes:
one or more of a name of the fixed asset, a purchase date of the fixed asset, a usage department of the fixed asset, a number of the fixed asset, a size of the fixed asset, a damage rating of the fixed asset.
6. The fixed asset management system based on the cloud platform as claimed in claim 3, wherein the asset management unit comprises a query subunit, a delete subunit and a modify subunit;
the query subunit is used for querying the asset information in the cloud platform module based on the asset information of the attribute information of the fixed asset;
the deleting submodule is used for deleting the asset information in the cloud platform module;
the modification subunit is used for modifying the asset information in the cloud platform module.
CN202110943776.7A 2021-08-17 2021-08-17 Fixed asset management system based on cloud platform Withdrawn CN113807772A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114611930A (en) * 2022-03-11 2022-06-10 佛山职业技术学院 Intelligent fixed asset management method and system based on cloud platform
CN117592908A (en) * 2024-01-19 2024-02-23 智慧(东营)大数据有限公司 Enterprise fixed asset management system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114611930A (en) * 2022-03-11 2022-06-10 佛山职业技术学院 Intelligent fixed asset management method and system based on cloud platform
CN117592908A (en) * 2024-01-19 2024-02-23 智慧(东营)大数据有限公司 Enterprise fixed asset management system

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Application publication date: 20211217