CN115512481A - Server data processing method networked with vending machine - Google Patents
Server data processing method networked with vending machine Download PDFInfo
- Publication number
- CN115512481A CN115512481A CN202211157399.5A CN202211157399A CN115512481A CN 115512481 A CN115512481 A CN 115512481A CN 202211157399 A CN202211157399 A CN 202211157399A CN 115512481 A CN115512481 A CN 115512481A
- Authority
- CN
- China
- Prior art keywords
- data
- vending machine
- server
- determining
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F9/00—Details other than those peculiar to special kinds or types of apparatus
- G07F9/002—Vending machines being part of a centrally controlled network of vending machines
-
- 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
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
-
- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F11/00—Coin-freed apparatus for dispensing, or the like, discrete articles
- G07F11/004—Restocking arrangements therefor
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F9/00—Details other than those peculiar to special kinds or types of apparatus
- G07F9/001—Interfacing with vending machines using mobile or wearable devices
Landscapes
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Engineering & Computer Science (AREA)
- Finance (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Control Of Vending Devices And Auxiliary Devices For Vending Devices (AREA)
Abstract
The invention provides a server data processing method networked with an automatic vending machine, which comprises the following steps: acquiring a first network port of the vending machine and a second network port of the server, and networking the vending machine and the server based on the first network port and the second network port; acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result; and performing data processing on the operation data based on the server, and generating a data processing report based on a processing result. Through networking vending machine and server, realize carrying out accurate effectual collection to vending machine's operational data, simultaneously, through handling the operational data who gathers to the realization is effectively held the operation conditions of vending machine according to the processing result, has improved data processing's rate of accuracy and efficiency, has also ensured carrying out effectual management to vending machine.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a server data processing method networked with an automatic vending machine.
Background
At present, with the pursuit of people on living quality, more and more vending machines appear in the life of people, and beverage vending machines, boxed meal vending machines, medicine vending machines and the like are continuously on the rise;
however, with the mass emergence of vending machines, the vending machines are managed therewith, and the traditional vending machines are independent from the management terminal, that is, the management terminal cannot know the current sales condition and the operation condition of the vending machines in time, and needs to use manpower to periodically patrol, and meanwhile, the operation data and the like of the vending machines need to be analyzed manually, so that the data analysis efficiency and the accuracy rate are greatly reduced, and the management effect of the vending machines is greatly damaged;
accordingly, the present invention provides a server data processing method networked with vending machines.
Disclosure of Invention
The invention provides a server data processing method networked with a vending machine, which is used for accurately and effectively acquiring the operation data of the vending machine by networking the vending machine with the server, and meanwhile, effectively grasping the operation condition of the vending machine according to a processing result by processing the acquired operation data, thereby improving the accuracy and efficiency of data processing and ensuring the effective management of the vending machine.
The invention provides a server data processing method networked with an automatic vending machine, which comprises the following steps:
step 1: acquiring a first network port of the vending machine and a second network port of the server, and networking the vending machine and the server based on the first network port and the second network port;
step 2: acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result;
and step 3: and performing data processing on the operation data based on the server, and generating a data processing report based on a processing result.
Preferably, a method for processing data of a server networked with a vending machine, in step 1, acquiring a first network port of the vending machine and a second network port of the server, includes:
acquiring a terminal identification of the vending machine, matching the terminal identification with a preset identification library, and determining a target model of the vending machine based on a matching result;
determining a first network port type of the vending machine based on the target model, determining a first network port parameter of the vending machine based on the first network port type, and determining a first network port of the vending machine based on the first network port parameter;
acquiring a target message of a server, and determining a network port set in the server based on the target message;
determining idle network ports in a network port set, and determining port parameters of the idle network ports, wherein at least one idle network port is provided;
and matching the first network port parameter with the port parameter of the idle network port, and determining a second network port of the server from the idle network port based on the matching result.
Preferably, a server data processing method networked with a vending machine, in step 1, the vending machine and the server are networked based on a first network port and a second network port, and the method includes:
the method comprises the steps of obtaining a first network port of the vending machine and a second network port of a server, and controlling the vending machine to send a device networking request to the second network port of the server based on the first network port;
the server analyzes the received equipment networking request, determines the networking authority of the automatic vending machine, matches the networking authority with a preset authority data table, and judges whether the server allows the automatic vending machine to be networked or not;
if the operation is allowed, feeding back a networking secret key to the automatic vending machine, and finishing the networking operation of the automatic vending machine and the server based on the networking secret key;
otherwise, the device networking request sent by the vending machine is rejected.
Preferably, a server data processing method networked with a vending machine, which completes the networking operation of the vending machine and the server based on a networking key, includes:
the method comprises the steps of obtaining a networking result of the vending machine and a server, and determining a wireless transmission path between the vending machine and the server based on the networking result;
controlling the vending machine to send a test data packet to the server based on the wireless transmission path, and acquiring receiving information of the server on the test data packet in real time;
determining a transmission performance parameter of the wireless transmission path based on the received information, and comparing the transmission performance parameter with a preset threshold;
if the transmission performance parameter is larger than or equal to the preset threshold value, judging that the wireless transmission path between the automatic vending machine and the server is qualified, and finishing the verification of the networking result between the automatic vending machine and the server;
otherwise, judging that the wireless transmission path between the vending machine and the server is unqualified.
Preferably, a server data processing method networked with a vending machine, for determining that a wireless transmission path between the vending machine and the server is not qualified, includes:
acquiring a target requirement on a wireless transmission path, acquiring receiving information of a server on a test data packet, and determining transmission delay and transmission rate of the wireless transmission path based on the receiving information, wherein the target requirement corresponds to the transmission delay and the transmission rate;
determining a difference value between the target requirement and the transmission delay and the transmission rate;
acquiring a network node in a wireless transmission path, and determining a transmission configuration parameter of the network node for a test data packet;
and adjusting the configuration parameters of the network nodes based on the difference values, and re-determining the transmission performance parameters of the wireless transmission path after adjustment until the transmission performance parameters are greater than or equal to a preset threshold value.
Preferably, a server data processing method networked with a vending machine, in step 2, acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result, includes:
acquiring data uploading frequency, and determining a time interval for data acquisition of the vending machine based on the data uploading frequency;
acquiring operation data of the vending machine based on time intervals, and splitting the operation data to obtain M sub-operation data blocks;
determining the position information of each sub-operation data block in the operation data, and respectively setting data block identifiers for the M sub-operation data blocks based on the position information;
determining an uploading sequence of the M sub-operation data blocks based on the data block identification, and caching the M sub-operation data blocks in a preset cache queue based on the uploading sequence;
and determining a data transmission clock of a wireless transmission path between the vending machine and the server based on the data uploading frequency, and uploading the M sub-operation data blocks cached in the preset cache queue to the server according to an uploading sequence based on the data transmission clock.
Preferably, in step 3, the data processing method for the server networked with the vending machine, based on the server, performs data processing on the operation data, and includes:
obtaining classification categories of the operation data of the automatic vending machine, and obtaining a historical data set of each category based on the classification categories;
dividing each category of historical data set into a first data set and a second data set, and processing the first data set based on a preset iterative algorithm to obtain a classification dictionary corresponding to the operation data of the automatic vending machine;
processing the second data set based on the classification dictionary to obtain training feature vectors corresponding to each category, and cascading the training feature vectors to obtain a training matrix, wherein the training matrix comprises at least one training feature vector, and one training feature vector corresponds to one category;
acquiring operation data of the vending machine received by the server, normalizing the operation data, and extracting a feature vector of the operation data;
inputting the feature vector into a training matrix, determining a Hamming distance between the feature vector and the training feature vector based on the training matrix, and judging that the running data corresponding to the feature vector and the historical data set corresponding to the training feature vector are in the same category when the Hamming distance is smaller than a preset distance threshold;
finishing the classification of the operation data of the automatic vending machine based on the judgment result, and performing clustering processing on each type of operation data based on the classification result to determine an isolated sample in each type of operation data;
matching target data cleaning rules from a preset data cleaning rule base based on the data category of each type of operation data, and performing first cleaning on isolated samples in each type of operation data based on the target data cleaning rules to obtain initial cleaning data corresponding to each type of operation data;
determining an effective data length evaluation parameter of each type of operation data based on the data type of each type of operation data, processing each type of operation data based on the effective data length evaluation parameter, and determining an effective load field in each type of operation data;
determining the effective data length in each type of operation data based on the effective load field, and performing second cleaning on each type of operation data based on the effective data length to obtain target operation data;
determining a target labeling information set based on the data type of the target operation data, and labeling the target operation data through the target labeling set based on a preset data labeling rule, wherein the target labeling information set comprises at least one piece of target labeling information, and the target operation data of each type corresponds to one piece of target labeling information;
and finishing the classification operation of the operation data of the automatic vending machine based on the labeling result.
Preferably, a server data processing method networked with a vending machine, which completes classification of operation data of the vending machine based on a determination result, includes:
acquiring commodity information and corresponding sales data of commodities in the vending machine based on the classification result, and determining the types of the commodities stored in the vending machine based on the commodity information;
determining commodity names of different commodity types based on commodity information, extracting data characteristics of sales data, and classifying the sales data based on the data characteristics to obtain sub-sales data;
determining the corresponding relation between different commodity types and the sub-sales data based on the classification result, and constructing a commodity sales histogram based on the corresponding relation, wherein the abscissa of the commodity sales histogram is the commodity name, and the ordinate is the sub-sales data;
determining the sales volume situation of different commodity types stored in the vending machine in a target time period based on the commodity sales volume histogram, and determining target hot sales commodities in different commodity types based on the sales volume situation, wherein the target hot sales commodities are at least one;
acquiring historical sales data of the target hot-sold commodity in a historical prediction time period, and determining sales characteristic data of the target hot-sold commodity based on the historical sales data;
determining influence factors on the sales volume of the target hot-sold commodities based on the sales characteristic data, and determining an incidence relation between the characteristic samples and the result samples of the target hot-sold commodities in the historical prediction time period based on the influence factors;
constructing a sales forecasting model based on the incidence relation, and forecasting sales of the target hot-sold commodity after the target period based on the sales forecasting model to obtain a sales forecasting value;
building commodity category trees of different commodity types stored in the vending machine, and determining the association attributes between the target hot-sold commodity and other commodities based on the commodity category trees;
correcting the predicted value of the sales volume based on the correlation attributes to obtain a target predicted value of the sales volume, meanwhile, obtaining the current stock of the target hot sales commodity in the automatic vending machine, and performing difference operation on the target predicted value of the sales volume and the current stock to obtain the predicted replenishment volume;
and transmitting the predicted replenishment quantity to a management terminal for replenishment reminding.
Preferably, a server data processing method networked with a vending machine, which completes classification of operation data of the vending machine based on a determination result, further includes:
obtaining working data of the automatic vending machine based on the classification result, and determining the device type of the automatic vending machine and the service characteristics of each device based on the working data;
determining a performance evaluation index for the vending machine based on the device type and the service characteristics of each device, and constructing a performance evaluation system based on the performance evaluation index;
processing the working data of the vending machine based on a performance evaluation system, and determining abnormal data in the working data based on a processing result;
determining the data characteristics of the abnormal data, and determining the operation characteristics of the device corresponding to the abnormal data based on the data characteristics;
and determining a target hidden danger device based on the operation characteristics, and recording the working data of the target hidden danger device. Obtaining a recording result of the target hidden danger device;
and transmitting the recording result to a management terminal, and reminding the management terminal to maintain the target hidden danger device.
Preferably, in step 3, the data processing method of the server networked with the vending machine generates a data processing report based on the processing result, and includes:
acquiring a processing result of data processing performed on the running data by the server, and determining data processing items contained in the processing result, wherein the data processing items are at least one;
determining the project name of the data processing project and the project quantity of the data processing project, and constructing a data processing report template based on the project name and the project quantity;
and acquiring a target processing result corresponding to the data processing item, and recording the item name of the data processing item and the corresponding target processing result in a data processing report template to obtain a data processing report, wherein the item name of the data processing item corresponds to the target processing result one by one.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method for processing data of a server networked with a vending machine in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of step 1 of a method for processing data of a server networked with a vending machine according to an embodiment of the present invention;
fig. 3 is a flowchart of step 2 of a server data processing method networked with a vending machine according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the embodiment provides a server data processing method networked with a vending machine, as shown in fig. 1, including:
step 1: acquiring a first network port of the vending machine and a second network port of the server, and networking the vending machine and the server based on the first network port and the second network port;
and 2, step: acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result;
and step 3: and performing data processing on the operation data based on the server, and generating a data processing report based on a processing result.
In this embodiment, the first network port is used to characterize the connection interface of the vending machine to the server when networked, and is located on the vending machine.
In this embodiment, the second network port is a connection interface for characterizing the server and the vending machine when networking, and is located on the server.
In this embodiment, the operation data refers to the storage, sales and change data of goods inside the vending machine, the operation status data of the vending machine itself, and the like, including the failure data of the vending machine.
In this embodiment, the data processing of the operating data based on the server means that the operating data of the vending machine acquired in the server is classified, and the data characteristics of the operating data of different types are determined according to the classification result, so that the working condition of the vending machine is determined.
In this embodiment, the data processing report refers to a recording file obtained by recording a processing result of the operation data of the vending machine.
The beneficial effects of the above technical scheme are: through networking vending machine and server, realize carrying out accurate effectual collection to vending machine's operational data, simultaneously, through handling the operational data who gathers to the realization is effectively held the operation conditions of vending machine according to the processing result, has improved data processing's rate of accuracy and efficiency, has also ensured carrying out effectual management to vending machine.
Example 2:
on the basis of embodiment 1, this embodiment provides a server data processing method networked with a vending machine, as shown in fig. 2, in step 1, acquiring a first network port of the vending machine and a second network port of the server, including:
step 101: acquiring a terminal identifier of the vending machine, matching the terminal identifier with a preset identifier library, and determining a target model of the vending machine based on a matching result;
step 102: determining a first network port type of the vending machine based on the target model, determining a first network port parameter of the vending machine based on the first network port type, and determining a first network port of the vending machine based on the first network port parameter;
step 103: acquiring a target message of a server, and determining a network port set in the server based on the target message;
step 104: determining idle network ports in a network port set, and determining port parameters of the idle network ports, wherein at least one idle network port is provided;
step 105: and matching the first network port parameter with the port parameter of the idle network port, and determining a second network port of the server from the idle network port based on the matching result.
In this embodiment, the terminal identifier is a tag label used to tag different types and different vending machines, and one vending machine corresponds to one terminal identifier.
In this embodiment, the preset identifier library is set in advance and is used for storing the terminal identifiers corresponding to different vending machines.
In this embodiment, the target model refers to the device model of the current vending machine.
In this embodiment, the first network port type refers to a network port type of a vending machine.
In this embodiment, the first network port parameter refers to the transmission requirements of the vending machine's network port for data and networking requirements when networking with the server.
In this embodiment, the target packet refers to ethernet data in the server, so as to determine the port set of the server.
In this embodiment, the set of network ports refers to a set of all network ports existing in the server.
In this embodiment, the idle network port refers to port information that is not currently connected to the device terminal in the server.
The beneficial effects of the above technical scheme are: through the equipment type who confirms the vending machine, realize carrying out accurate analysis to the network port parameter of vending machine to the realization is confirmed the network port of vending machine accurately, secondly, through analyzing the message of server, realize confirming all network interface in the server, finally realize confirming the network port of being connected with vending machine among a plurality of network port, for realizing networking vending machine and server provides convenience, thereby improved the efficiency and the degree of accuracy of the operation data processing to vending machine.
Example 3:
on the basis of embodiment 1, this embodiment provides a server data processing method networked with a vending machine, in step 1, networking the vending machine and a server based on a first network port and a second network port, including:
acquiring a first network port of the vending machine and a second network port of the server, and controlling the vending machine to send an equipment networking request to the second network port of the server based on the first network port;
the server analyzes the received equipment networking request, determines the networking authority of the automatic vending machine, matches the networking authority with a preset authority data table, and judges whether the server allows the automatic vending machine to be networked or not;
if the operation is allowed, feeding back a networking secret key to the automatic vending machine, and finishing the networking operation of the automatic vending machine and the server based on the networking secret key;
otherwise, the device networking request sent by the vending machine is rejected.
In this embodiment, the device networking request is sent by the vending machine to the server for establishing networking operations with the server.
In this embodiment, networking rights refer to the condition that the vending machine meets networking requirements.
In this embodiment, the preset authority data table is set in advance and is used for storing networking authorities of different devices.
In this embodiment, the networking key refers to a parameter that needs to be verified when the vending machine and the server are networked, and the networking between the vending machine and the server can be completed through the key.
The beneficial effects of the above technical scheme are: through first network port and second network port, realize that the vending machine sends the equipment networking request to the server, and the server verifies the equipment networking request after receiving the equipment networking request, ensures that the vending machine possesses the authority of networking to ensure the security to vending machine operation data processing, also be convenient for in time receive the operation data of vending machine simultaneously, improved operation data processing efficiency.
Example 4:
on the basis of embodiment 3, this embodiment provides a server data processing method networked with a vending machine, and the networking operation between the vending machine and the server is completed based on a networking key, including:
the method comprises the steps of obtaining a networking result of the vending machine and a server, and determining a wireless transmission path between the vending machine and the server based on the networking result;
controlling the vending machine to send a test data packet to the server based on the wireless transmission path, and acquiring receiving information of the server on the test data packet in real time;
determining a transmission performance parameter of the wireless transmission path based on the received information, and comparing the transmission performance parameter with a preset threshold;
if the transmission performance parameter is larger than or equal to the preset threshold value, judging that the wireless transmission path between the automatic vending machine and the server is qualified, and finishing the verification of the networking result between the automatic vending machine and the server;
otherwise, judging that the wireless transmission path between the vending machine and the server is unqualified.
In this embodiment, the wireless transmission path refers to a data transmission link for data transmission between the vending machine and the server.
In this embodiment, the test data packet is set in advance, and is sent by the vending machine to the server, so as to verify whether a transmission link between the vending machine and the server is a path.
In this embodiment, the receiving information includes the receiving time of the test data packet by the server, the data amount of the received test data packet, the receiving delay of the data, and the like
In this embodiment, the transmission performance parameter is used to characterize the data transmission condition of the wireless transmission path, and a larger value indicates that the data transmission performance of the wireless transmission path is better.
In this embodiment, the preset threshold is set in advance, and is used to measure whether the performance of the wireless transmission path for transmitting data meets the expected requirement.
The beneficial effects of the above technical scheme are: test data package is sent to the server through the vending machine, realizes the reliability to the wireless transmission path between vending machine and the server to ensured that the server can effectually receive the operation data in the vending machine, thereby reached quick, accurate handle vending machine data.
Example 5:
on the basis of embodiment 4, the present embodiment provides a server data processing method networked with a vending machine, determining that a wireless transmission path between the vending machine and a server is not qualified, including:
acquiring a target requirement on a wireless transmission path, acquiring receiving information of a server on a test data packet, and determining transmission delay and transmission rate of the wireless transmission path based on the receiving information, wherein the target requirement corresponds to the transmission delay and the transmission rate;
determining a difference value between the target requirement and the transmission delay and the transmission rate;
acquiring a network node in a wireless transmission path, and determining a transmission configuration parameter of the network node for a test data packet;
and adjusting the configuration parameters of the network nodes based on the difference values, and re-determining the transmission performance parameters of the wireless transmission path after adjustment until the transmission performance parameters are greater than or equal to a preset threshold value.
In this embodiment, the target requirement is set in advance to characterize the theoretical transmission performance of the wireless transmission path on the data.
In this embodiment, the difference value refers to the transmission delay of the wireless transmission path and the difference between the transmission rate and the target requirement.
In this embodiment, the network node is a node in the wireless transmission path that processes transmission data, and different configurations result in different transmission performance of data in the wireless transmission path.
In this embodiment, the transmission configuration parameter refers to a transmission condition of the network node when transmitting data, specifically, a rate of processing the data, a bandwidth of transmission, and the like.
The beneficial effects of the above technical scheme are: through when judging that the transmission performance of the wireless transmission path is unqualified, the configuration parameters of the wireless transmission path are adjusted, the wireless transmission path between the vending machine and the server can be used for accurately and efficiently transmitting the operation data of the vending machine, and therefore the effect of the server on processing the vending operation data is guaranteed.
Example 6:
on the basis of embodiment 1, this embodiment provides a server data processing method networked with a vending machine, as shown in fig. 3, in step 2, acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result, including:
step 201: acquiring data uploading frequency, and determining a time interval for data acquisition of the vending machine based on the data uploading frequency;
step 202: acquiring operation data of the vending machine based on time intervals, and splitting the operation data to obtain M sub-operation data blocks;
step 203: determining the position information of each sub-operation data block in the operation data, and respectively setting data block identifiers for the M sub-operation data blocks based on the position information;
step 204: determining an uploading sequence of the M sub-operation data blocks based on the data block identification, and caching the M sub-operation data blocks in a preset cache queue based on the uploading sequence;
step 205: and determining a data transmission clock of a wireless transmission path between the vending machine and the server based on the data uploading frequency, and uploading the M sub-operation data blocks cached in the preset cache queue to the server according to an uploading sequence based on the data transmission clock.
In this embodiment, the data upload frequency refers to the frequency at which the vending machine transmits data to the server.
In this embodiment, the sub operation data block refers to a data fragment of operation data obtained by splitting operation data of the vending machine.
In this embodiment, the location information refers to a location condition of different sub-operation data blocks in the operation data before the operation data is split.
In this embodiment, the data block identifier is a tag used to tag different sub-data blocks, and the tag can quickly and accurately determine information such as the location of the corresponding sub-data block.
In this embodiment, the uploading sequence is determined according to the position condition of the sub-operation data block in the operation data, and may be a sequence determined according to the time acquisition sequence of the operation data.
In this embodiment, the preset buffer queue is a storage area that is set in advance and is used for temporarily storing and correspondingly processing data when the data is transmitted to the data receiving end.
In this embodiment, the data transmission clock is used to represent the time difference between two adjacent data when the wireless transmission path between the vending machine and the server transmits data.
The beneficial effects of the above technical scheme are: through confirming the frequency of uploading to vending machine operation data to the realization is effectively confirmed vending machine data acquisition's time interval, secondly, gather vending machine's operation data through the time interval, thereby and carry out the piecemeal realization with the operation data accurate efficient transmission to the server of vending machine with the operation data of gathering, ensured the server to vending machine operation data's receiving effect, improved the treatment effeciency and the treatment accuracy to vending machine operation data.
Example 7:
on the basis of embodiment 1, this embodiment provides a server data processing method networked with a vending machine, and in step 3, data processing is performed on operation data based on a server, including:
obtaining classification types of the operation data of the vending machine, and obtaining a historical data set of each type based on the classification types;
dividing each category of historical data set into a first data set and a second data set, and processing the first data set based on a preset iterative algorithm to obtain a classification dictionary corresponding to the operating data of the automatic vending machine;
processing the second data set based on the classification dictionary to obtain training feature vectors corresponding to each category, and cascading the training feature vectors to obtain a training matrix, wherein the training matrix comprises at least one training feature vector, and one training feature vector corresponds to one category;
acquiring operation data of the vending machine received by the server, normalizing the operation data, and extracting a feature vector of the operation data;
inputting the feature vector into a training matrix, determining a Hamming distance between the feature vector and the training feature vector based on the training matrix, and judging that the running data corresponding to the feature vector and the historical data set corresponding to the training feature vector are in the same category when the Hamming distance is smaller than a preset distance threshold;
finishing the classification of the operation data of the automatic vending machine based on the judgment result, and performing clustering processing on each type of operation data based on the classification result to determine an isolated sample in each type of operation data;
matching target data cleaning rules from a preset data cleaning rule base based on the data category of each type of operation data, and performing first cleaning on isolated samples in each type of operation data based on the target data cleaning rules to obtain initial cleaning data corresponding to each type of operation data;
determining an effective data length evaluation parameter of each type of operation data based on the data type of each type of operation data, processing each type of operation data based on the effective data length evaluation parameter, and determining an effective load field in each type of operation data;
determining the effective data length in each type of operation data based on the effective load field, and performing second cleaning on each type of operation data based on the effective data length to obtain target operation data;
determining a target labeling information set based on the data type of the target operation data, and labeling the target operation data through the target labeling set based on a preset data labeling rule, wherein the target labeling information set comprises at least one piece of target labeling information, and the target operation data of each type corresponds to one piece of target labeling information;
and finishing the classification operation of the operation data of the automatic vending machine based on the labeling result.
In this embodiment, the classification category is the number of categories for which it is known in advance that the collected operation data of the vending machine needs to be classified, and the category of data included in each category.
In this embodiment, the historical data set is obtained in advance, and is the operating data of the vending machine over a period of time, including different categories of data information.
In this embodiment, the first data set and the second data set refer to that historical data sets of the same category are divided into two blocks, so as to implement construction of a training matrix, where the first data set is used to determine a classification dictionary, and the second data set is used to determine corresponding feature vectors.
In this embodiment, the predetermined iterative algorithm is set in advance.
In this embodiment, the classification dictionary is used to record data characteristics of different types of data, including association relationships between data, data structure characteristics, and data value taking conditions.
In this embodiment, the training feature vector refers to a data feature corresponding to the second data set, and includes a data value and the like.
In this embodiment, the cascading refers to summarizing the training feature vectors corresponding to the data sets of different categories, so as to obtain the training matrix.
In this embodiment, the training matrix is a classification tool used to classify the vending machine operating data and is obtained through training.
In this embodiment, the normalization process refers to performing the same specification on the values of the operating data, so as to facilitate the accurate classification of the operating data.
In this embodiment, the feature vector refers to a value-taking condition corresponding to a data feature of the vending machine operating data, and is intended to be matched with a training feature vector in a training matrix, so as to achieve the purpose of classification.
In this embodiment, the hamming distance is used to characterize the distance between different data, and a closer distance indicates that the two are more similar and share the same type center.
In this embodiment, the preset distance threshold is set in advance to measure whether the classification criterion is satisfied.
In this embodiment, an isolated sample refers to data in the same category of data whose data values significantly deviate from the data mean.
In this embodiment, the preset data cleaning rule base is set in advance and is used for storing the data cleaning rules corresponding to different types of data.
In this embodiment, the target data cleansing rule refers to a cleansing rule suitable for cleansing data of a current data category, and is one or a combination of several preset data cleansing rule bases.
In this embodiment, the first cleaning refers to cleaning isolated samples in each type of operation data.
In this embodiment, the initial cleaning data refers to cleaning data obtained by cleaning isolated sample data in the operating data of each category.
In this embodiment, the valid data length evaluation parameter is used to measure an evaluation criterion or a reference criterion of valid data bytes in the running data, specifically, a correlation degree between core content of a field and the entire data, and the like.
In this embodiment, the payload field refers to a valid data field in each category of operation data.
In this embodiment, the valid data length refers to the number of key bytes in each category of operation data that can indicate the core content of the category of operation data.
In this embodiment, the second cleaning is to extract the effective data length in each type of operation data.
In this embodiment, the target operation data refers to final data obtained by performing isolated sample cleaning on each type of operation data and extracting the effective data length.
In this embodiment, the target annotation information set refers to a set of label data for performing category labeling on each category of run data.
In this embodiment, the preset data labeling rule is set in advance, and is used for performing data labeling on different types of operation data.
The beneficial effects of the above technical scheme are: through confirming the categorised classification to the vending machine operational data, and realize carrying out accurate effectual structure to the training matrix according to categorised classification, thereby the categorised rate of accuracy to the vending machine operational data has been ensured, secondly, through carrying out first washing and second washing to the operational data of each classification, ensure that the operational data that obtains is accurate effective, for the guarantee to facilitate to the treatment effect of vending operational data, finally, carry out different marks to the operational data of each classification, thereby be convenient for direct-view efficient distinguishes different operational data classifications, the treatment effect to the vending machine operational data has been ensured.
Example 8:
on the basis of embodiment 7, the present embodiment provides a server data processing method networked with a vending machine, which completes classification of operation data of the vending machine based on a determination result, and includes:
acquiring commodity information and corresponding sales data of commodities in the vending machine based on the classification result, and determining the types of the commodities stored in the vending machine based on the commodity information;
determining commodity names of different commodity types based on commodity information, extracting data characteristics of sales data, and classifying the sales data based on the data characteristics to obtain sub-sales data;
determining the corresponding relation between different commodity types and the sub-sales data based on the classification result, and constructing a commodity sales histogram based on the corresponding relation, wherein the abscissa of the commodity sales histogram is the commodity name, and the ordinate is the sub-sales data;
determining sales volume conditions of different commodity types stored in the vending machine in a target time period based on the commodity sales volume histogram, and determining target hot sales commodities in different commodity types based on the sales volume conditions, wherein the target hot sales commodities are at least one;
acquiring historical sales data of the target hot-sold commodity in a historical prediction time period, and determining sales characteristic data of the target hot-sold commodity based on the historical sales data;
determining influence factors on the sales amount of the target hot-sold commodities based on the sales characteristic data, and determining an incidence relation between the characteristic samples and the result samples of the target hot-sold commodities in the historical prediction time period based on the influence factors;
constructing a sales prediction model based on the association relationship, and predicting sales of the target hot-sold commodity after the target period based on the sales prediction model to obtain a sales prediction value;
building commodity category trees of different commodity types stored in the vending machine, and determining the correlation attributes between the target hot-sell commodities and other commodities based on the commodity category trees;
correcting the predicted value of the sales volume based on the correlation attributes to obtain a target predicted value of the sales volume, meanwhile, obtaining the current stock of the target hot sales commodity in the automatic vending machine, and performing difference operation on the target predicted value of the sales volume and the current stock to obtain the predicted replenishment volume;
and transmitting the predicted replenishment quantity to a management terminal for replenishment reminding.
In this embodiment, the commodity information refers to the type of commodity, the corresponding commodity name, and the like.
In this embodiment, the article name refers to the article name of the article stored in the vending machine.
In this embodiment, the data feature refers to a category feature and a corresponding specific value contained in the sales data.
In this embodiment, the sub-sales data refers to sales data included in each category after the sales data is classified.
In this embodiment, the histogram of commodity sales is used to characterize sales of commodities of different types in a certain period of time.
In this embodiment, the target time period is set in advance, and may be specifically one month or half year.
In this embodiment, the target hot sold commodity refers to a commodity category of which the sales amount reaches a preset threshold value in the target time period, and the preset threshold value is modifiable.
In this embodiment, the historical predicted time period is set in advance and is sales data of the vending machine before a certain time period.
In this embodiment, the sales characteristic data refers to the sales speed of the target hot-sold commodity at different time points and the sales volume at different time points in the historical prediction time period.
In this embodiment, the historical sales data refers to sales of the target hot sold goods by the vending machine over a historical predicted time period.
In this embodiment, the influencing factors include weather, customer browsing volume, and the like.
In this embodiment, the characteristic sample refers to the corresponding inventory amount of the target hot commodity at the beginning of the historical prediction time period.
In this embodiment, the result sample refers to the corresponding remaining inventory of the target hot commodity after the historical prediction time period ends.
In this embodiment, the target period is set in advance, specifically, one week, one month, two months, or the like.
In this embodiment, the sales volume prediction value refers to the number of hot commodities that are likely to be sold at the end of the target period.
In this embodiment, the commodity category tree is used to represent an association relationship between commodity attributes of different types of commodities in the vending machine, so as to facilitate determination of whether other commodities affect the sales volume of the target hot-sold commodity.
In this embodiment, the association attribute refers to whether or not other commodities are stored in accordance with the target hot-sell commodity type, and the like.
In this embodiment, the target sales forecast value refers to a final sales forecast result obtained by correcting the value of the sales forecast value.
In this embodiment, the predicted replenishment quantity refers to the quantity of replenishment required for the target hot-sell commodity.
The beneficial effects of the above technical scheme are: the sales data of the commodities in the vending machine are called according to the classification result, so that the sales heat of different commodity types in the vending machine is effectively analyzed, accurate locking of the target hot sold commodity is realized, secondly, the historical sales data of the target hot sold commodity are processed and analyzed, a sales prediction model is built, accurate prediction of the sales of the target hot sold commodity in a target period is achieved, the replenishment quantity is timely determined according to the prediction result, the practicability of data processing of the vending machine is improved, and meanwhile, accurate and effective analysis of the sales data in the operation data of the vending machine is guaranteed.
Example 9:
on the basis of embodiment 7, this embodiment provides a server data processing method networked with a vending machine, which completes classification of operation data of the vending machine based on a determination result, and further includes:
obtaining working data of the vending machine based on the classification result, and determining the device type of the vending machine and the service characteristics of each device based on the working data;
determining a performance evaluation index for the vending machine based on the device type and the service characteristics of each device, and constructing a performance evaluation system based on the performance evaluation index;
processing the working data of the vending machine based on a performance evaluation system, and determining abnormal data in the working data based on a processing result;
determining data characteristics of the abnormal data, and determining the operation characteristics of a device corresponding to the abnormal data based on the data characteristics;
and determining a target hidden danger device based on the operation characteristics, and recording the working data of the target hidden danger device. Obtaining a recording result of the target hidden danger device;
and transmitting the recording result to a management terminal, and reminding the management terminal to maintain the target hidden danger device.
In this embodiment, the operating data refers to the operating status data of the vending machine itself, including data during normal operation and data during abnormal operation.
In this embodiment, the service characteristics refer to the operation types and corresponding operation characteristics of different devices.
In this embodiment, the performance evaluation index is used to evaluate whether each device satisfies the requirements for normal performance.
In this embodiment, the abnormal data refers to a data segment with an abnormal value in the working data of the vending machine.
In this embodiment, the data characteristics refer to the data type of the abnormal data and the corresponding specific value.
In this embodiment, the operation characteristics refer to the operation characteristics of the device, the realized operation functions, and the like.
In this embodiment, the target hidden trouble device refers to a device having a potential trouble in the vending machine.
The beneficial effects of the above technical scheme are: through the working data of calling the vending machine according to the classification result, and analyzing and processing the working data, the fault hidden danger devices in the vending machine can be accurately and effectively analyzed according to the working data, so that the accuracy rate of the operation performance of the vending machine according to data evaluation is improved, and when a fault exists, a worker can be reminded of carrying out operation and maintenance in time.
Example 10:
on the basis of embodiment 1, this embodiment provides a data processing method for a server networked with a vending machine, in step 3, generating a data processing report based on a processing result, including:
acquiring a processing result of data processing performed on the running data by the server, and determining data processing items contained in the processing result, wherein the data processing items are at least one;
determining the project name of the data processing project and the project quantity of the data processing project, and constructing a data processing report template based on the project name and the project quantity;
and acquiring a target processing result corresponding to the data processing item, and recording the item name of the data processing item and the corresponding target processing result in a data processing report template to obtain a data processing report, wherein the item name of the data processing item corresponds to the target processing result one by one.
In this embodiment, the data processing item refers to a type of processing operation data of the vending machine, and specifically includes data classification, data cleaning, sales prediction, troubleshooting, and the like.
In this embodiment, the target processing result refers to a data processing result obtained after the server processes different data processing items.
The beneficial effects of the above technical scheme are: the data processing items of the automatic selling operation data are determined by the server, and the processing results of different data processing items are obtained at the same time, so that the data processing items and the corresponding processing results are accurately and effectively recorded, and the management terminal can conveniently check the processing results in real time.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A server data processing method networked with a vending machine, comprising:
step 1: acquiring a first network port of the vending machine and a second network port of the server, and networking the vending machine and the server based on the first network port and the second network port;
step 2: acquiring operation data of the vending machine, and uploading the operation data to a server based on a networking result;
and step 3: and performing data processing on the operation data based on the server, and generating a data processing report based on a processing result.
2. The method according to claim 1, wherein the step 1 of obtaining the first network port of the vending machine and the second network port of the server comprises:
acquiring a terminal identifier of the vending machine, matching the terminal identifier with a preset identifier library, and determining a target model of the vending machine based on a matching result;
determining a first network port type of the vending machine based on the target model, determining a first network port parameter of the vending machine based on the first network port type, and determining a first network port of the vending machine based on the first network port parameter;
acquiring a target message of a server, and determining a network port set in the server based on the target message;
determining idle network ports in a network port set, and determining port parameters of the idle network ports, wherein at least one idle network port is provided;
and matching the first network port parameter with the port parameter of the idle network port, and determining a second network port of the server from the idle network port based on the matching result.
3. The method for processing data of a server networked with a vending machine according to claim 1, wherein in step 1, the step of networking the vending machine with the server based on the first network port and the second network port comprises:
the method comprises the steps of obtaining a first network port of the vending machine and a second network port of a server, and controlling the vending machine to send a device networking request to the second network port of the server based on the first network port;
the server analyzes the received equipment networking request, determines the networking authority of the vending machine, matches the networking authority with a preset authority data table and judges whether the server allows the vending machine to be networked or not;
if the operation is allowed, feeding back a networking secret key to the automatic vending machine, and finishing the networking operation of the automatic vending machine and the server based on the networking secret key;
otherwise, the device networking request sent by the vending machine is rejected.
4. The data processing method of the server networked with the vending machine according to claim 3, wherein the networking operation of the vending machine and the server is completed based on the networking key, and comprises the following steps:
the method comprises the steps of obtaining a networking result of the vending machine and a server, and determining a wireless transmission path between the vending machine and the server based on the networking result;
controlling the vending machine to send a test data packet to a server based on a wireless transmission path, and acquiring receiving information of the server on the test data packet in real time;
determining a transmission performance parameter of the wireless transmission path based on the received information, and comparing the transmission performance parameter with a preset threshold;
if the transmission performance parameter is larger than or equal to the preset threshold value, judging that the wireless transmission path between the automatic vending machine and the server is qualified, and finishing the verification of the networking result between the automatic vending machine and the server;
otherwise, judging that the wireless transmission path between the vending machine and the server is unqualified.
5. The method of claim 4, wherein determining that the wireless transmission path between the vending machine and the server is unacceptable comprises:
acquiring a target requirement on a wireless transmission path, acquiring receiving information of a server to a test data packet, and determining transmission delay and transmission rate of the wireless transmission path based on the receiving information, wherein the target requirement corresponds to the transmission delay and the transmission rate;
determining the difference value between the target requirement and the transmission time delay and the transmission rate;
acquiring a network node in a wireless transmission path, and determining a transmission configuration parameter of the network node for a test data packet;
and adjusting the configuration parameters of the network nodes based on the difference values, and re-determining the transmission performance parameters of the wireless transmission path after adjustment until the transmission performance parameters are greater than or equal to a preset threshold value.
6. The data processing method of the server networked with the vending machine according to claim 1, wherein in the step 2, acquiring the operation data of the vending machine and uploading the operation data to the server based on the networking result comprises:
acquiring data uploading frequency, and determining a time interval for data acquisition of the vending machine based on the data uploading frequency;
acquiring operation data of the vending machine based on a time interval, and splitting the operation data to obtain M sub-operation data blocks;
determining the position information of each sub-operation data block in the operation data, and respectively setting data block identifiers for the M sub-operation data blocks based on the position information;
determining an uploading sequence of the M sub-operation data blocks based on the data block identification, and caching the M sub-operation data blocks in a preset cache queue based on the uploading sequence;
and determining a data transmission clock of a wireless transmission path between the vending machine and the server based on the data uploading frequency, and uploading the M sub-operation data blocks cached in the preset cache queue to the server according to the uploading sequence based on the data transmission clock.
7. The method as claimed in claim 1, wherein the step 3 of processing the operation data based on the server comprises:
obtaining classification categories of the operation data of the automatic vending machine, and obtaining a historical data set of each category based on the classification categories;
dividing each category of historical data set into a first data set and a second data set, and processing the first data set based on a preset iterative algorithm to obtain a classification dictionary corresponding to the operation data of the automatic vending machine;
processing the second data set based on the classification dictionary to obtain training feature vectors corresponding to each category, and cascading the training feature vectors to obtain a training matrix, wherein the training matrix comprises at least one training feature vector, and one training feature vector corresponds to one category;
acquiring operation data of the vending machine received by the server, normalizing the operation data, and extracting a feature vector of the operation data;
inputting the feature vectors into a training matrix, determining Hamming distances between the feature vectors and the training feature vectors based on the training matrix, and judging that the operation data corresponding to the feature vectors and the historical data sets corresponding to the training feature vectors are in the same category when the Hamming distances are smaller than a preset distance threshold;
finishing the classification of the operation data of the automatic vending machine based on the judgment result, and performing clustering processing on each type of operation data based on the classification result to determine an isolated sample in each type of operation data;
matching target data cleaning rules from a preset data cleaning rule base based on the data category of each type of operation data, and performing first cleaning on isolated samples in each type of operation data based on the target data cleaning rules to obtain initial cleaning data corresponding to each type of operation data;
determining an effective data length evaluation parameter of each type of operation data based on the data type of each type of operation data, processing each type of operation data based on the effective data length evaluation parameter, and determining an effective load field in each type of operation data;
determining the effective data length in each type of operation data based on the effective load field, and performing second cleaning on each type of operation data based on the effective data length to obtain target operation data;
determining a target labeling information set based on the data type of the target operation data, and labeling the target operation data through the target labeling set based on a preset data labeling rule, wherein the target labeling information set comprises at least one piece of target labeling information, and the target operation data of each type corresponds to one piece of target labeling information;
and finishing the classification operation of the operation data of the automatic vending machine based on the labeling result.
8. The method of claim 7, wherein the step of classifying the operating data of the vending machine based on the determined result comprises:
acquiring commodity information and corresponding sales data of commodities in the vending machine based on the classification result, and determining the types of the commodities stored in the vending machine based on the commodity information;
determining commodity names of different commodity types based on commodity information, extracting data characteristics of sales data, and classifying the sales data based on the data characteristics to obtain sub-sales data;
determining the corresponding relation between different commodity types and the sub-sales data based on the classification result, and constructing a commodity sales histogram based on the corresponding relation, wherein the abscissa of the commodity sales histogram is the commodity name, and the ordinate is the sub-sales data;
determining sales volume conditions of different commodity types stored in the vending machine in a target time period based on the commodity sales volume histogram, and determining target hot sales commodities in different commodity types based on the sales volume conditions, wherein the target hot sales commodities are at least one;
acquiring historical sales data of the target hot-selling goods in a historical prediction time period, and determining sales characteristic data of the target hot-selling goods based on the historical sales data;
determining influence factors on the sales volume of the target hot-sold commodities based on the sales characteristic data, and determining an incidence relation between the characteristic samples and the result samples of the target hot-sold commodities in the historical prediction time period based on the influence factors;
constructing a sales prediction model based on the association relationship, and predicting sales of the target hot-sold commodity after the target period based on the sales prediction model to obtain a sales prediction value;
building commodity category trees of different commodity types stored in the vending machine, and determining the correlation attributes between the target hot-sell commodities and other commodities based on the commodity category trees;
correcting the predicted value of the sales volume based on the correlation attributes to obtain a target predicted value of the sales volume, meanwhile, obtaining the current stock of the target hot sales commodity in the automatic vending machine, and performing difference operation on the target predicted value of the sales volume and the current stock to obtain the predicted replenishment volume;
and transmitting the predicted replenishment quantity to a management terminal for replenishment reminding.
9. The data processing method of a server networked with vending machines according to claim 7, wherein the sorting of the operation data of the vending machines is completed based on the determination result, further comprising:
obtaining working data of the vending machine based on the classification result, and determining the device type of the vending machine and the service characteristics of each device based on the working data;
determining performance evaluation indexes of the automatic vending machine based on the device types and the service characteristics of all devices, and constructing a performance evaluation system based on the performance evaluation indexes;
processing the working data of the vending machine based on a performance evaluation system, and determining abnormal data in the working data based on a processing result;
determining the data characteristics of the abnormal data, and determining the operation characteristics of the device corresponding to the abnormal data based on the data characteristics;
and determining a target hidden danger device based on the operation characteristics, and recording the working data of the target hidden danger device. Obtaining a recording result of the target hidden danger device;
and transmitting the recording result to a management terminal, and reminding the management terminal to maintain the target hidden danger device.
10. The data processing method of server networked with vending machine according to claim 1, wherein in step 3, generating a data processing report based on the processing result comprises:
acquiring a processing result of data processing of the running data by the server, and determining data processing items contained in the processing result, wherein the data processing items are at least one;
determining the project name of the data processing project and the project quantity of the data processing project, and constructing a data processing report template based on the project name and the project quantity;
and acquiring a target processing result corresponding to the data processing item, and recording the item name of the data processing item and the corresponding target processing result in a data processing report template to obtain a data processing report, wherein the item name of the data processing item corresponds to the target processing result one by one.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211157399.5A CN115512481B (en) | 2022-09-22 | 2022-09-22 | Server data processing method networked with vending machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211157399.5A CN115512481B (en) | 2022-09-22 | 2022-09-22 | Server data processing method networked with vending machine |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115512481A true CN115512481A (en) | 2022-12-23 |
| CN115512481B CN115512481B (en) | 2023-07-14 |
Family
ID=84506479
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211157399.5A Active CN115512481B (en) | 2022-09-22 | 2022-09-22 | Server data processing method networked with vending machine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115512481B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100138037A1 (en) * | 2008-10-22 | 2010-06-03 | Newzoom, Inc. | Vending Store Inventory Management and Reporting System |
| CN102118429A (en) * | 2010-12-23 | 2011-07-06 | 宾丽萍 | Automatic vending control method based on remote network management and control system thereof |
| CN102892029A (en) * | 2011-07-18 | 2013-01-23 | 深圳市龙视传媒有限公司 | Digital television testing method, system and terminal testing equipment |
| CN104202334A (en) * | 2014-09-16 | 2014-12-10 | 广州金山网络科技有限公司 | Network connection establishing method and device |
| CN113516528A (en) * | 2021-04-23 | 2021-10-19 | 广东便捷神科技股份有限公司 | Remote management and monitoring system for vending machine |
| CN114389981A (en) * | 2021-12-18 | 2022-04-22 | 苏州浪潮智能科技有限公司 | Detection method and device for edge server 5G module and storage medium |
| CN114821894A (en) * | 2022-06-06 | 2022-07-29 | 广东便捷神科技股份有限公司 | Intelligent beverage vending machine based on Internet of things and control method thereof |
-
2022
- 2022-09-22 CN CN202211157399.5A patent/CN115512481B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100138037A1 (en) * | 2008-10-22 | 2010-06-03 | Newzoom, Inc. | Vending Store Inventory Management and Reporting System |
| CN102118429A (en) * | 2010-12-23 | 2011-07-06 | 宾丽萍 | Automatic vending control method based on remote network management and control system thereof |
| CN102892029A (en) * | 2011-07-18 | 2013-01-23 | 深圳市龙视传媒有限公司 | Digital television testing method, system and terminal testing equipment |
| CN104202334A (en) * | 2014-09-16 | 2014-12-10 | 广州金山网络科技有限公司 | Network connection establishing method and device |
| CN113516528A (en) * | 2021-04-23 | 2021-10-19 | 广东便捷神科技股份有限公司 | Remote management and monitoring system for vending machine |
| CN114389981A (en) * | 2021-12-18 | 2022-04-22 | 苏州浪潮智能科技有限公司 | Detection method and device for edge server 5G module and storage medium |
| CN114821894A (en) * | 2022-06-06 | 2022-07-29 | 广东便捷神科技股份有限公司 | Intelligent beverage vending machine based on Internet of things and control method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115512481B (en) | 2023-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111639363B (en) | Data analysis method based on block chain and edge computing server | |
| CN102315974B (en) | Stratification characteristic analysis-based method and apparatus thereof for on-line identification for TCP, UDP flows | |
| WO2011130957A1 (en) | Method and apparatus for online distinguishing transmission control protocol traffic by using data flow head characteristics | |
| CN109861957A (en) | A kind of the user behavior fining classification method and system of the privately owned cryptographic protocol of mobile application | |
| CN113992563B (en) | Multilink multimode intelligent switching and packet sending method | |
| CN106559634A (en) | For the date storage method and device of traffic block port video monitoring | |
| CN113127563B (en) | Intelligent retail management method and system based on block chain | |
| CN116070249B (en) | Asset data intelligent monitoring management system and method | |
| CN115942262A (en) | Short message service system with data security mechanism and method thereof | |
| CN116319777A (en) | Intelligent gateway service processing method based on edge calculation | |
| CN108123834A (en) | Log analysis system based on big data platform | |
| CN113657747B (en) | Intelligent assessment system for enterprise safety production standardization level | |
| CN115512481A (en) | Server data processing method networked with vending machine | |
| CN114881177B (en) | Nutritional health data acquisition system based on Internet of things technology | |
| CN117240527A (en) | Network security risk prevention system and method | |
| CN105678456B (en) | Method and system for automatically evaluating running state of electric energy metering device | |
| WO2022262775A1 (en) | Information processing method and apparatus based on data exchange, and device and storage medium | |
| CN113393169B (en) | Financial industry transaction system performance index analysis method based on big data technology | |
| CN112860768B (en) | Electromagnetic spectrum available frequency recommendation method | |
| CN115150294A (en) | Data analysis method, equipment and medium for monitoring Internet of things equipment | |
| Syal et al. | Automatic detection of network traffic anomalies and changes | |
| CN110175635B (en) | OTT application program user classification method based on Bagging algorithm | |
| CN112396531A (en) | Management system integrating information, social contact and multi-platform aggregation service | |
| CN115953130B (en) | Intelligent analysis processing system for gateway declaration data | |
| Syal | Automatic network traffic anomaly detection and analysis using supervised machine learning techniques |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |