CN110322197A - Commodity intelligence replenishing method, device, terminal and storage medium - Google Patents
Commodity intelligence replenishing method, device, terminal and storage medium Download PDFInfo
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- 238000007405 data analysis Methods 0.000 claims description 4
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- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
Abstract
The present invention relates to intelligent retail domains, the invention discloses a kind of commodity intelligence replenishing method, device, terminal and storage mediums, the commodity intelligence replenishing method is applied to terminal, if the commodity intelligence replenishing method includes: based on there are commodity vacant locations in default camera detection to default shelf, the absence information and the type of merchandise of the commodity vacant locations are then obtained, and determines the merchandise news of the type of merchandise from preset model；It is calculated according to the merchandise news and the absence information, to obtain information out of stock；If detecting, the information out of stock reaches trigger condition, generates the warning information that replenishes according to the information out of stock, and the warning information that replenishes is sent to the default server that replenishes.It is cumbersome tediously long that the present invention solves the commodity process that replenishes, the effect that replenishes precisely not in time, employee replenish inefficiency the technical issues of.
Description
Technical field
The present invention relates to intelligent retail technology field more particularly to a kind of commodity intelligence replenishing method, device, terminal and deposit
Storage media.
Background technique
In traditional retail shelf when Out of Stock occurs, employee is needed to replenish.Many product have been occupied on traditional shelf
The commodity of kind, and quantity is big, due to not knowing which type of merchandize lacked, will appear commodity when employee replenishes and replenishes not
Foot is excessive, and employee is caused to need that the task of replenishing could be completed several times back and forth.This causes employee to waste a large amount of valuable times
Again can not completion commodity in time, reduce the efficiency that replenishes, while also affecting the buying experience of client.Therefore, how to shorten benefit
Flow of goods journey improves the efficiency that replenishes, and is current technical problem urgently to be resolved.
Summary of the invention
The main purpose of the present invention is to provide a kind of commodity intelligence replenishing method, device, terminal and storage mediums, it is intended to
The solution process that replenishes is cumbersome tediously long, employee replenish inefficiency the technical issues of.
To achieve the above object, the embodiment of the present invention provides a kind of commodity intelligence replenishing method, and the commodity intelligently replenish
Method is applied to terminal, and the commodity intelligence replenishing method includes:
If obtaining commodity vacancy position based on there are commodity vacant locations in default camera detection to default shelf
The absence information and the type of merchandise set, and determine from preset model the merchandise news of the type of merchandise；
It is calculated according to the merchandise news and the absence information, to obtain information out of stock；
If detecting, the information out of stock reaches trigger condition, generates the warning information that replenishes according to the information out of stock,
And the warning information that replenishes is sent to the default server that replenishes.
Optionally, the information out of stock includes quantity, commodity vacancy rate, commodity amount and Out of Stock rate out of stock,
It is described to be calculated according to the merchandise news and the absence information, include: the step of information out of stock to obtain
The commodity single-item volume in the commodity vacancy volume and merchandise news in absence information is obtained, and according to the commodity
Vacancy volume and the commodity single-item volume calculate quantity out of stock；
According in merchandise news commodity total volume and the commodity vacancy volume, calculate commodity vacancy rate；
Commodity amount is calculated according to the commodity total volume and the commodity single-item volume；
Out of Stock rate is calculated according to the quantity out of stock and the commodity amount.
Optionally, it if described detect that the information out of stock reaches trigger condition, is generated and is mended according to the information out of stock
The step of goods warning information further include:
If the commodity vacancy volume is greater than the first trigger value, and/or,
The commodity amount less than the second trigger value, and/or,
The commodity vacancy rate is greater than third trigger value, and/or,
The Out of Stock rate is greater than the 4th trigger value, then generates the warning information that replenishes according to the information out of stock.
Optionally, it if described detect that the information out of stock reaches trigger condition, is generated and is mended according to the information out of stock
Goods warning information, and by the warning information that replenishes be sent to it is default replenish server the step of after further include:
If detecting the amendment data based on the warning information feedback that replenishes, the data correction category of the amendment data is obtained
Property；
Trigger condition corresponding with the data correction attribute is obtained, and is based on triggering item described in the amendment data modification
Part.
Optionally, it if described detect that the information out of stock reaches trigger condition, is generated and is mended according to the information out of stock
Goods warning information, and by the warning information that replenishes be sent to it is default replenish server the step of after further include:
Commodity are generated according to the absence information, merchandise news, information out of stock and the warning information that replenishes to replenish record, and general
The commodity replenish to record and save to the preset model；
The record that replenishes of all commodity in the preset model replenish data analysis every the first preset duration, with
Generate the trend analysis report that replenishes in different preset time sections.
Optionally, it if described detect that the information out of stock reaches trigger condition, is generated and is mended according to the information out of stock
Goods warning information, and by the warning information that replenishes be sent to it is default replenish server the step of after further include:
The frequency that replenishes is obtained from the trend analysis report that replenishes in the first preset time section every the second preset duration
Less than first threshold, and the quantity that replenishes is less than first type of merchandise of second threshold；
It generates commodity to be replaced according to the first merchandise news of first type of merchandise and the first commodity record that replenishes and builds
Discuss table.
Optionally, it if described detect that the information out of stock reaches trigger condition, is generated and is mended according to the information out of stock
Goods warning information, and by the warning information that replenishes be sent to it is default replenish server the step of after further include:
The frequency that replenishes is obtained from the trend analysis report that replenishes in the second preset time section every third preset duration
Greater than third threshold value, and the quantity that replenishes is greater than second type of merchandise of the 4th threshold value；
It generates commodity to be expanded according to the second merchandise news of second type of merchandise and the second commodity record that replenishes and builds
Discuss table.
The present invention also provides a kind of commodity intelligence goods compensator, the commodity intelligence goods compensator is applied to terminal, described
Commodity intelligence goods compensator includes:
First obtains module, if for being based in default camera detection to default shelf there are commodity vacant locations,
The absence information and the type of merchandise of the commodity vacant locations are obtained, and determines the commodity of the type of merchandise from preset model
Information；
Computing module, for being calculated according to the merchandise news and the absence information, to obtain information out of stock；
Sending module, if being generated for detecting that the information out of stock reaches trigger condition according to the information out of stock
Replenish warning information, and the warning information that replenishes is sent to the default server that replenishes.
Optionally, the information out of stock includes quantity, commodity vacancy rate, commodity amount and Out of Stock rate out of stock, described
Computing module includes:
First computing unit, for obtaining the commodity vacancy volume in absence information and the commodity single-item body in merchandise news
Product, and quantity out of stock is calculated according to the commodity vacancy volume and the commodity single-item volume；
Second computing unit, for according in merchandise news commodity total volume and the commodity vacancy volume, calculate quotient
Product vacancy rate；
Third computing unit, for calculating commodity amount according to the commodity total volume and the commodity single-item volume；
4th computing unit, for calculating Out of Stock rate according to the quantity out of stock and the commodity amount.
Optionally, the sending module further include:
Generation unit, if it is greater than the first trigger value for the commodity vacancy volume, and/or,
The commodity amount less than the second trigger value, and/or,
The commodity vacancy rate is greater than third trigger value, and/or,
The Out of Stock rate is greater than the 4th trigger value, then generates the warning information that replenishes according to the information out of stock.
Optionally, the commodity intelligence goods compensator further include:
Detection module, if obtaining the amendment number for detecting based on the amendment data for the warning information feedback that replenishes
According to data correction attribute；
Correction module for obtaining trigger condition corresponding with the data correction attribute, and is based on the amendment data
Modify the trigger condition.
Optionally, the commodity intelligence goods compensator further include:
Preserving module, for generating commodity according to the absence information, merchandise news, information out of stock and the warning information that replenishes
Replenish record, and the commodity are replenished to record and are saved to the preset model；
Analysis module, for being mended every the first preset duration to the record that replenishes of all commodity in the preset model
Goods data analysis, to generate the trend analysis report that replenishes in different preset time sections.
Optionally, the commodity intelligence goods compensator further include:
Second obtains module, for every the second preset duration from the trend analysis report that replenishes in the first preset time section
The frequency that replenishes is obtained in announcement less than first threshold, and the quantity that replenishes is less than first type of merchandise of second threshold；
First generation module replenishes record for the first merchandise news and the first commodity according to first type of merchandise
Generate commodity suggestion table to be replaced.
Optionally, the commodity intelligence goods compensator further include:
Third obtains module, for every third preset duration from the trend analysis report that replenishes in the second preset time section
The frequency that replenishes is obtained in announcement greater than third threshold value, and the quantity that replenishes is greater than second type of merchandise of the 4th threshold value；
Second generation module replenishes record for the second merchandise news and the second commodity according to second type of merchandise
Generate commodity suggestion table to be expanded.
In addition, to achieve the above object, the present invention also provides a kind of terminal, the terminal include: memory, processor and
The commodity that being stored in can run on the memory and on the processor intelligently replenish program, in which:
The commodity intelligently replenish when program is executed by the processor and realize commodity intelligence replenishing method as described above
The step of.
In addition, to achieve the above object, the present invention also provides computer storage mediums；
It is stored with commodity in the computer storage medium intelligently to replenish program, the commodity program that intelligently replenishes is processed
It realizes when device executes such as the step of above-mentioned commodity intelligence replenishing method.
In the present invention, if based on described in, there are commodity vacant locations, being obtained in default camera detection to default shelf
The absence information and the type of merchandise of commodity vacant locations, and determine from preset model the merchandise news of the type of merchandise；Root
It is calculated according to the merchandise news and the absence information, to obtain information out of stock；If detecting, the information out of stock reaches
Trigger condition then generates the warning information that replenishes according to the information out of stock, and the warning information that replenishes is sent to default benefit
Goods server.The application captures the state of shelf using camera, judges whether that product locations vacancy occurs, using detecting reality
When absence information variation and the merchandise news in database etc., Reasonable calculates the real-time status of vacancy, and is arranged corresponding
Data critical point, the early warning that replenishes is carried out when reaching critical point, thus the type of merchandise that replenishes required for obtaining, replenish quantity
Etc., and then optimize and replenish process, reduce unnecessary artificial enquiry, solves commodity and replenish that process is cumbersome tediously long, and replenish effect
Fruit precisely not in time, employee replenish inefficiency the technical issues of.
Detailed description of the invention
Fig. 1 is the device structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram of one embodiment of commodity intelligence replenishing method of the present invention；
Fig. 3 is the master-plan block diagram of commodity intelligence replenishing method of the present invention.
The object of the invention is realized, the embodiments will be further described with reference to the accompanying drawings for functional characteristics and advantage.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
As shown in Figure 1, Fig. 1 is the device structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
The terminal of that embodiment of the invention can be PC machine or server apparatus.
As shown in Figure 1, the terminal may include: processor 1001, such as CPU, network interface 1004, user interface
1003, memory 1005, communication bus 1002.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), input unit such as keyboard (Keyboard), optional user interface
1003 can also include standard wireline interface and wireless interface.Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as WI-FI interface).Memory 1005 can be high speed RAM memory, be also possible to stable memory
(non-volatile memory), such as magnetic disk storage.Memory 1005 optionally can also be independently of aforementioned processor
1001 storage device.
It will be understood by those skilled in the art that device structure shown in Fig. 1 does not constitute the restriction to equipment, can wrap
It includes than illustrating more or fewer components, perhaps combines certain components or different component layouts.
As shown in Figure 1, as may include that operating system, network are logical in a kind of memory 1005 of computer storage medium
Letter module, Subscriber Interface Module SIM and commodity intelligently replenish program.
In equipment shown in Fig. 1, network interface 1004 is mainly used for connection witness participant node, with witness participant
Node carries out data communication；User interface 1003 is mainly used for connecting client (user terminal), carries out data communication with client；
And processor 1001 can be used for calling the commodity stored in memory 1005 intelligently to replenish program, and execute following block chain quotient
Operation in each embodiment of product intelligence replenishing method.
Based on above-mentioned hardware configuration, block chain commodity intelligence replenishing method embodiment of the present invention is proposed.
The invention belongs to intelligent retail domain, the present invention provides a kind of commodity intelligence replenishing method, which intelligently replenishes
Method is mainly used in terminal, in one embodiment of commodity intelligence replenishing method, referring to Fig. 2, and the intelligent side of replenishing of the commodity
Method includes:
Step S10, if obtaining the quotient based on there are commodity vacant locations in default camera detection to default shelf
The absence information and the type of merchandise of product vacant locations, and determine from preset model the merchandise news of the type of merchandise；
Step S20 is calculated according to the merchandise news and the absence information, to obtain information out of stock；
Step S30, if detecting, the information out of stock reaches trigger condition, is replenished according to the information generation out of stock pre-
Alert information, and the warning information that replenishes is sent to the default server that replenishes.
Particular content is as follows:
Step S10, if obtaining the quotient based on there are commodity vacant locations in default camera detection to default shelf
The absence information and the type of merchandise of product vacant locations, and determine from preset model the merchandise news of the type of merchandise；
Default camera is provided on default shelf side in the present invention, the default camera is depth camera, real
When monitor condition of merchandise on default shelf, if by default camera detection to default shelf there are commodity vacant locations,
It then proves that the commodity in current commodity vacant locations are bought by client, needs further to obtain the vacancy of commodity vacant locations at this time
Information and the type of merchandise.Default camera can identify label in the commodity vacant locations, similar quotient by image recognition technology
The packaging and brand of product, thus the parameters such as length, width and height for identifying the type of merchandise of the vacant locations, while detecting the vacant locations,
To get commodity vacancy volume (i.e. the volumes of vacant locations).The preset model refers to the pre-set data of terminal
Model includes a large amount of merchandise news, including but not limited to: descriptive labelling information, commodity single-item volume, commodity vacancy body
N number of parameter is imported in " supervised learning model " and is instructed by product, N number of characteristic parameter such as the commodity total volume of commodity in shelf
Practice, obtains the preset model after training.It is understood that preset model is integrally disposed by default merchandise news
Commodity on shelf data model, and trained model has machine learning ability, can independently be judged data
And autonomous classification, while also can have data judgement and data recognition capability by artificial addition preset data.
Step S20 is calculated according to the merchandise news and the absence information, to obtain information out of stock；
Specifically, the information out of stock includes quantity, commodity vacancy rate, commodity amount and Out of Stock rate out of stock, described
Step S20 includes:
Step a1, obtain absence information in commodity vacancy volume and merchandise news in commodity single-item volume, and according to
The commodity vacancy volume and the commodity single-item volume calculate quantity out of stock；
Step a2, according in merchandise news commodity total volume and the commodity vacancy volume, calculate commodity vacancy rate；
Step a3 calculates commodity amount according to the commodity total volume and the commodity single-item volume；
Step a4 calculates Out of Stock rate according to the quantity out of stock and the commodity amount.
All merchandise newss record in preset model has the single-item length, width and height of each type of merchandise, therefore is determining commodity class
After type, the commodity single-item volume Vp1 of each commodity can be obtained.When detecting the commodity single-item body for having no such commodity in preset model
Vp1 when product can use after depth camera calculates the volume for obtaining the commodity single-item and be uploaded to preset model automatically.The following are
Pass through the data calculation process of merchandise news and absence information:
1, quantity Qp1=Vc1/Vp1 out of stock can be calculated according to commodity vacancy volume Vc1 and commodity single-item volume Vp1；
2, include commodity total volume Vs1 in merchandise news, refer to when the commodity of the type of merchandise occupy default shelf
The commodity vacancy rate Pc1=of the commodity can be calculated according to commodity total volume Vs1 and commodity vacancy volume Vc1 in total volume
Vc1/Vs1；
3, the commodity full goods on default shelf can be calculated according to commodity total volume Vs1 and commodity single-item volume Vp1
When commodity amount be Qf1=Vs1/Vp1；
4, Out of Stock rate Pp1=Qp1/Qf1 is obtained by quantity Qp1 out of stock and commodity amount Qf1.
It can get information out of stock: quantity, commodity vacancy rate and Out of Stock rate out of stock as a result,.
Step S30, if detecting, the information out of stock reaches trigger condition, is replenished according to the information generation out of stock pre-
Alert information, and the warning information that replenishes is sent to the default server that replenishes.
In the present embodiment, information out of stock is the important evidence that the personnel that replenish carry out that commodity replenish, and the present embodiment is provided with
Trigger condition, the process that replenishes could be executed by only having reached trigger condition, frequently replenished and replenished so as to avoid the personnel of replenishing
(effect that replenishes in the case where there was only 1 such as the quantity out of stock on default shelf is little) occurs for the little phenomenon of effect.
The trigger condition can be artificial preset judgment criteria, be also possible to independently sentencing for preset model continuous renewal
Disconnected system.After reaching trigger condition, terminal generates the warning information that replenishes according to information out of stock, which includes direct
It is sent to the default server that replenishes, the default server that replenishes is that rear end replenishes the operating platform of personnel, and the personnel of replenishing pass through
The platform can quickly know the type of merchandise required supplementation with, quantity and corresponding default shelf.
Specifically, the step S30 further include:
If the commodity vacancy volume Vc1 is greater than the first trigger value, and/or,
The commodity amount Qf1 less than the second trigger value, and/or,
The commodity vacancy rate Pc1 is greater than third trigger value, and/or,
The Out of Stock rate Pp1 is greater than the 4th trigger value, then generates the warning information that replenishes according to the information out of stock.
Data type of the case where the triggering trigger condition based on information out of stock, including commodity vacancy volume, commodity amount, quotient
Product vacancy rate and Out of Stock rate.It is understood that information out of stock can intuitively react the situation out of stock of commodity on default shelf.
Terminal is provided with the data critical point for triggering the process that replenishes: the first trigger value, the second trigger value, third trigger value and the 4th triggering
Value.In the present embodiment, any one of commodity vacancy volume, commodity amount, commodity vacancy rate and Out of Stock rate data reach
To trigger condition, that is, it can trigger the early warning process that replenishes.For example, commodity vacancy volume is greater than the first trigger value or commodity amount is small
It is greater than third trigger value in the second trigger value or commodity vacancy rate or Out of Stock rate is greater than the 4th trigger value.Above four kinds of feelings
As long as meeting one or more kinds of, i.e., the triggerable early warning process that replenishes in condition, and the early warning letter that replenishes is generated according to information out of stock
Breath.Information out of stock is labeled, and integrates information out of stock according to form, to generate the warning information that replenishes.
It is understood that device end can be according to the actual warning information that replenishes, to default mould after triggering early warning
Type is modified and updates, and the real data for the warning information that replenishes is more, and amendment and update are more, and machine learning and intelligence are sentenced
Disconnected process is more accurate, can carry out standardization correction to the subsequent process that replenishes.
It is the master-plan block diagram of commodity intelligence replenishing method of the present invention referring to Fig. 3, Fig. 3.It is understood that described
It can simultaneously include a variety of type of merchandises on default shelf, the default camera can be captured simultaneously on multiple default shelf
Commodity vacant locations, technical solution of the present invention are similarly applied to the above scene.
In the present invention, if based on described in, there are commodity vacant locations, being obtained in default camera detection to default shelf
The absence information and the type of merchandise of commodity vacant locations, and determine from preset model the merchandise news of the type of merchandise；Root
It is calculated according to the merchandise news and the absence information, to obtain information out of stock；If detecting, the information out of stock reaches
Trigger condition then generates the warning information that replenishes according to the information out of stock, and the warning information that replenishes is sent to default benefit
Goods server.The application captures the state of shelf using camera, judges whether that product locations vacancy occurs, using detecting reality
When absence information variation and the merchandise news in database etc., Reasonable calculates the real-time status of vacancy, and is arranged corresponding
Data critical point, the early warning that replenishes is carried out when reaching critical point, thus the type of merchandise that replenishes required for obtaining, replenish quantity
Etc., and then optimize and replenish process, reduce unnecessary artificial enquiry, solves commodity and replenish that process is cumbersome tediously long, and replenish effect
Fruit precisely not in time, employee replenish inefficiency the technical issues of.
Further, it is based on first embodiment, proposes the second embodiment of this forwarding method, in this embodiment, the step
After rapid S30 further include:
Step A obtains the data of the amendment data if detecting the amendment data based on the warning information feedback that replenishes
Correct attribute；
Since preset model is by the pre-set data model of terminal, and original information of goods information data is only preliminary
Data, not necessarily most accurately data.For example, getting the commodity list of A commodity according to the merchandise news of preset model
Product volume, quantity out of stock is 5 altogether after calculating.But the personnel of replenishing have mended and have found that the quantity out of stock of A commodity can be with after goods
It is 6, the reason is that the vacant locations of original A commodity are 5 by quantity out of stock is calculated, but what A commodity can be put by positive desuperposition
Mode vacates a position again.It so proceeds from the reality, quantity out of stock can be changed to 6.Assuming that it is not modified operation, then
The quantity out of stock that next terminal is got remains 5, is fed back then needing amendment process.That feeds back in amendment process repairs
Correction data can be the personnel that replenish and actively be modified, and is also possible to default camera and is analyzed by real-time capture and intelligence learning
To obtain amendment data.It is understood that the preset model for having machine learning function can be realized the update of data iteration
With data standard criterion, to form autonomous capability for correcting.Default camera is according to the autonomous capability for correcting to real-time acquisition
To commodity vacant locations carry out assessment judgement, to confirm the actual premise that replenishes, and then independently get trigger condition
Rationally modification range, and the warning information that replenishes is combined rationally to be fed back, i.e. amendment data are to be based on replenishing warning information and anti-
What feedback was got.Two ways is independently corrected by artificial active correction and preset model, terminal gets the amendment data of feedback,
Analysis obtains the data correction type of amendment data.
Step B obtains trigger condition corresponding with the data correction attribute, and based on described in the amendment data modification
Trigger condition.
The data correction type refers to wanting modified data object, in the present embodiment, is for the data of modification
The first trigger value in trigger condition, the second trigger value, third trigger value and the 4th trigger value.It is determined by data correction attribute
Trigger condition, the present embodiment can be based on the first trigger value in amendment data modification trigger condition, the second trigger value, third trigger values
Or the 4th any one of trigger value or appoint several numerical value.
By changing the trigger value in trigger condition, terminal can correct inaccurate model data, to standardize default mould
All commodity data information of type, so that the data of preset model are more partial to real data, to greatly promote default mould
The data accuracy and data reliability of type.
Further, it is based on first embodiment, proposes the 3rd embodiment of this forwarding method, in this embodiment, the step
After rapid S30 further include:
Step C generates commodity according to the absence information, merchandise news, information out of stock and the warning information that replenishes and replenishes note
Record, and the commodity are replenished to record and are saved to the preset model；
Step D carries out the data that replenish to the record that replenishes of all commodity in the preset model every the first preset duration
Analysis, to generate the trend analysis report that replenishes in different preset time sections.
After getting absence information, merchandise news, information out of stock and the warning information that replenishes, it was demonstrated that currently generated
One commodity replenishes record, and the terminal record that the commodity will be replenished is saved into preset model, using as data sample.
The present embodiment is arranged the first preset duration and then extracts all commodity in preset model every the first preset duration
Replenish record, and it includes benefit that replenish record reflection due to all commodity is to supplement every time the quantity of various commodity out of stock naturally
Fill the frequency, the data that replenish such as supplement interval and supplemental amount.Terminal analyzes the data that replenish by actual demand, generates different default
The commodity of time interval replenish trend analysis report.Such as the institute extracted in preset model every 15 days (i.e. the first preset duration)
There are commodity to replenish record, generates in one week respectively, in one day, the trend that replenishes in (i.e. different preset time sections) is divided in two weeks
Analysis report.These trend analysis reports that replenish can react the rule that replenishes in different time intervals, to be the benefit on backstage
Goods personnel provide the reference frame that replenishes of different time intervals, and then the personnel that help to replenish know the commodity classes of the commodity that replenish in advance
The information such as type, quantity carry out tune goods in advance, quickly prepare the commodity to be supplemented, to improve the efficiency that replenishes indirectly.
Further, it is based on first embodiment, proposes the fourth embodiment of this forwarding method, in this embodiment, the step
After rapid S30 further include:
Step E is obtained from the trend analysis report that replenishes in the first preset time section every the second preset duration and is mended
The goods frequency is less than first threshold, and the quantity that replenishes is less than first type of merchandise of second threshold；
Step F, being replenished according to the first merchandise news of first type of merchandise and the first commodity, it is to be replaced to record generation
Commodity suggest table.
In actual life, if certain commodity on shelf often do not have to replenish, illustrate that the commodity market is smaller, demand
It is small, then needing to carry out off-frame treatment to the commodity.In the present embodiment, firstly, it is necessary to determine that the frequency that replenishes is less, and the number that replenishes
Measure the less type of merchandise.Terminal is fixed from the trend analysis report that replenishes in the first preset time section every the second preset duration
Position goes out to replenish the frequency less than first threshold, and the quantity that replenishes is less than first type of merchandise of second threshold.Such as every other month
Detect to replenish the frequency less than 7 from the trend analysis report that replenishes in a season, and commodity of the quantity less than 50 that replenish.
After obtaining first type of merchandise, terminal can be directly obtained first type of merchandise the first merchandise news and
First commodity replenish record (directly acquiring from preset model).And it replenishes according to the first merchandise news and the first commodity and records life
Suggest table at commodity to be replaced.The commodity suggestion table to be replaced, which refers to, replaces the few commodity undercarriage of the bad sales volume of market manifestation
Analysis report, including the commodity in the first preset time section replenish situation and sales situation etc. and undercarriage takes
Generation analysis conclusion.Through this embodiment, part can be oriented and sells bad commodity, avoid commodity overstocking, conveniently replenish people
Maintenance of the member to default shelf improves the service efficiency of default shelf.
Further, after the step S30 further include:
Step G is obtained from the trend analysis report that replenishes in the second preset time section every third preset duration and is mended
The goods frequency is greater than third threshold value, and the quantity that replenishes is greater than second type of merchandise of the 4th threshold value；
Certain possible commodity are received by the market very much in actual life, but because the commodity amount of default shelf presence supplies
It should not ask, cause the personnel of replenishing that frequent progress is needed to replenish, reduce the efficiency that replenishes.Therefore a kind of improvement project can be provided, it is right
The commodity being received by the market are expanded, and the supply of the commodity is increased.
For example, every two weeks (i.e. third preset duration) from half monthly (i.e. the second preset time section), replenish trend analysis
It is detected in report, if detecting, the frequency that replenishes is greater than 10 (i.e. third threshold values), and the quantity that replenishes is greater than 50 (i.e. the 4th thresholds
Value) commodity be can happy peppery item, it is determined that can happy peppery item be second type of merchandise.
Step H is generated according to the second merchandise news of second type of merchandise and the second commodity record that replenishes wait expand
Commodity suggest table.
Terminal obtains corresponding second merchandise news according to second type of merchandise and (is 5 cubic centimetres of volume as laughable, numbers
112233；Peppery item be 1 cubic centimetre of volume, number 23333) and the second commodity replenish record (such as cola the half monthly record that replenishes
With the monthly record that replenishes of peppery item half), by above data, terminal produces commodity suggestion table to be expanded.The commodity to be expanded
It is recommended that table refers to that the commodity burning hot to the welcome sales volume in market increase the analysis report of supply.The analysis report can help
The sales volume situation of commodity is analyzed, to provide the analysis of commodity supply strategy.Through this embodiment, can determine quick-fried money commodity and
Corresponding market demand helps the goods supply analysis of commodity tune, provides the transformation of commodity supply strategy, and then reduce and replenish personnel's
Reorder frequency saves the quality time, improves the service efficiency of default shelf, improves the efficiency that replenishes for the personnel that replenish.
It is understood that first type of merchandise and second type of merchandise may include a variety of commodity, it is not limited to only
There is one kind.
In addition, the embodiment of the present invention also proposes a kind of commodity intelligence goods compensator, the commodity intelligence goods compensator application
In terminal, the commodity intelligence goods compensator includes:
First obtains module, if for being based in default camera detection to default shelf there are commodity vacant locations,
The absence information and the type of merchandise of the commodity vacant locations are obtained, and determines the commodity of the type of merchandise from preset model
Information；
Computing module, for being calculated according to the merchandise news and the absence information, to obtain information out of stock；
Sending module, if being generated for detecting that the information out of stock reaches trigger condition according to the information out of stock
Replenish warning information, and the warning information that replenishes is sent to the default server that replenishes.
Optionally, the information out of stock includes quantity, commodity vacancy rate, commodity amount and Out of Stock rate out of stock, described
Computing module includes:
First computing unit, for obtaining the commodity vacancy volume in absence information and the commodity single-item body in merchandise news
Product, and quantity out of stock is calculated according to the commodity vacancy volume and the commodity single-item volume；
Second computing unit, for according in merchandise news commodity total volume and the commodity vacancy volume, calculate quotient
Product vacancy rate；
Third computing unit, for calculating commodity amount according to the commodity total volume and the commodity single-item volume；
4th computing unit, for calculating Out of Stock rate according to the quantity out of stock and the commodity amount.
Optionally, the sending module further include:
Generation unit, if it is greater than the first trigger value for the commodity vacancy volume, and/or,
The commodity amount less than the second trigger value, and/or,
The commodity vacancy rate is greater than third trigger value, and/or,
The Out of Stock rate is greater than the 4th trigger value, then generates the warning information that replenishes according to the information out of stock.
Optionally, the commodity intelligence goods compensator further include:
Detection module, if obtaining the amendment number for detecting based on the amendment data for the warning information feedback that replenishes
According to data correction attribute；
Correction module for obtaining trigger condition corresponding with the data correction attribute, and is based on the amendment data
Modify the trigger condition.
Optionally, the commodity intelligence goods compensator further include:
Preserving module, for generating commodity according to the absence information, merchandise news, information out of stock and the warning information that replenishes
Replenish record, and the commodity are replenished to record and are saved to the preset model；
Analysis module, for being mended every the first preset duration to the record that replenishes of all commodity in the preset model
Goods data analysis, to generate the trend analysis report that replenishes in different preset time sections.
Optionally, the commodity intelligence goods compensator further include:
Second obtains module, for every the second preset duration from the trend analysis report that replenishes in the first preset time section
The frequency that replenishes is obtained in announcement less than first threshold, and the quantity that replenishes is less than first type of merchandise of second threshold；
First generation module replenishes record for the first merchandise news and the first commodity according to first type of merchandise
Generate commodity suggestion table to be replaced.
Optionally, the commodity intelligence goods compensator further include:
Third obtains module, for every third preset duration from the trend analysis report that replenishes in the second preset time section
The frequency that replenishes is obtained in announcement greater than third threshold value, and the quantity that replenishes is greater than second type of merchandise of the 4th threshold value；
Second generation module replenishes record for the second merchandise news and the second commodity according to second type of merchandise
Generate commodity suggestion table to be expanded.
In addition, the embodiment of the present invention also proposes that a kind of terminal, terminal include: memory 109, processor 110 and be stored in
On memory 109 and the commodity that can run on processor 110 intelligently replenish program, and the commodity program that intelligently replenishes is processed
Device 110 realizes the step of each embodiment of above-mentioned commodity intelligence replenishing method when executing.
In addition, the present invention also provides a kind of computer storage medium, the computer storage medium be stored with one or
More than one program of person, the one or more programs can also be executed by one or more than one processor with
In the step of realizing each embodiment of above-mentioned commodity intelligence replenishing method.
The expansion content of terminal of the present invention and the specific embodiment of storage medium (i.e. computer storage medium) with it is above-mentioned
Each embodiment of commodity intelligence replenishing method is essentially identical, and this will not be repeated here.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the device that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or device.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal (can be mobile phone, calculate
Machine, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (10)
1. a kind of commodity intelligence replenishing method, which is characterized in that the commodity intelligence replenishing method is applied to terminal, the commodity
Intelligent replenishing method includes:
If obtaining the commodity vacant locations based on there are commodity vacant locations in default camera detection to default shelf
Absence information and the type of merchandise, and determine from preset model the merchandise news of the type of merchandise；
It is calculated according to the merchandise news and the absence information, to obtain information out of stock；
If detecting, the information out of stock reaches trigger condition, generates the warning information that replenishes according to the information out of stock, and will
The warning information that replenishes is sent to the default server that replenishes.
2. commodity intelligence replenishing method as described in claim 1, which is characterized in that the shortage of goods information include out of stock quantity,
Commodity vacancy rate, commodity amount and Out of Stock rate,
It is described to be calculated according to the merchandise news and the absence information, include: the step of information out of stock to obtain
The commodity single-item volume in the commodity vacancy volume and merchandise news in absence information is obtained, and according to the commodity vacancy
Volume and the commodity single-item volume calculate quantity out of stock；
According in merchandise news commodity total volume and the commodity vacancy volume, calculate commodity vacancy rate；
Commodity amount is calculated according to the commodity total volume and the commodity single-item volume；
Out of Stock rate is calculated according to the quantity out of stock and the commodity amount.
3. commodity intelligence replenishing method as claimed in claim 2, which is characterized in that
If described detect that the information out of stock reaches trigger condition, the warning information that replenishes is generated according to the information out of stock
Step further include:
If the commodity vacancy volume is greater than the first trigger value, and/or,
The commodity amount less than the second trigger value, and/or,
The commodity vacancy rate is greater than third trigger value, and/or,
The Out of Stock rate is greater than the 4th trigger value, then generates the warning information that replenishes according to the information out of stock.
4. commodity intelligence replenishing method as described in claim 1, which is characterized in that
If described detect that the information out of stock reaches trigger condition, the warning information that replenishes is generated according to the information out of stock,
And by the warning information that replenishes be sent to it is default replenish server the step of after further include:
If detecting the amendment data based on the warning information feedback that replenishes, the data correction attribute of the amendment data is obtained；
Trigger condition corresponding with the data correction attribute is obtained, and based on trigger condition described in the amendment data modification.
5. commodity intelligence replenishing method as described in claim 1, which is characterized in that
If described detect that the information out of stock reaches trigger condition, the warning information that replenishes is generated according to the information out of stock,
And by the warning information that replenishes be sent to it is default replenish server the step of after further include:
Commodity are generated according to the absence information, merchandise news, information out of stock and the warning information that replenishes to replenish record, and will described in
Commodity replenish to record and save to the preset model；
The record that replenishes of all commodity in the preset model replenish data analysis every the first preset duration, to generate
The trend analysis report that replenishes in different preset time sections.
6. commodity intelligence replenishing method as claimed in claim 5, which is characterized in that
If described detect that the information out of stock reaches trigger condition, the warning information that replenishes is generated according to the information out of stock,
And by the warning information that replenishes be sent to it is default replenish server the step of after further include:
The frequency that replenishes is obtained from the trend analysis report that replenishes in the first preset time section every the second preset duration to be less than
First threshold, and the quantity that replenishes is less than first type of merchandise of second threshold；
It is replenished to record according to the first merchandise news of first type of merchandise and the first commodity and generates commodity suggestion table to be replaced.
7. commodity intelligence replenishing method as claimed in claim 5, which is characterized in that
If described detect that the information out of stock reaches trigger condition, the warning information that replenishes is generated according to the information out of stock,
And by the warning information that replenishes be sent to it is default replenish server the step of after further include:
The frequency that replenishes is obtained from the trend analysis report that replenishes in the second preset time section every third preset duration to be greater than
Third threshold value, and the quantity that replenishes is greater than second type of merchandise of the 4th threshold value；
Commodity suggestion table to be expanded is generated according to the second merchandise news of second type of merchandise and the second commodity record that replenishes.
8. a kind of commodity intelligence goods compensator, which is characterized in that the commodity intelligence goods compensator is applied to terminal, the commodity
Intelligent goods compensator includes:
First obtains module, if obtaining for based on presetting in camera detection to default shelf there are commodity vacant locations
The absence information and the type of merchandise of the commodity vacant locations, and determine that the commodity of the type of merchandise are believed from preset model
Breath；
Computing module, for being calculated according to the merchandise news and the absence information, to obtain information out of stock；
Sending module, if being replenished for detecting that the information out of stock reaches trigger condition according to the information generation out of stock
Warning information, and the warning information that replenishes is sent to the default server that replenishes.
9. a kind of terminal, which is characterized in that the terminal includes: memory, processor and is stored on the memory and can
The commodity run on a processor intelligently replenish program, and the commodity intelligently replenish when program is executed by the processor and realize such as
Described in any one of claims 1 to 7 the step of commodity intelligence replenishing method.
10. a kind of storage medium, which is characterized in that it is stored with commodity on the storage medium and intelligently replenishes program, the commodity
Realizing the commodity intelligence replenishing method as described in any one of claims 1 to 7 when the program that intelligently replenishes is executed by processor
Step.
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