CN109948979A - A kind of method, equipment and the storage medium of inventory's detection - Google Patents
A kind of method, equipment and the storage medium of inventory's detection Download PDFInfo
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Abstract
The invention discloses a kind of inventory's detection method, equipment and computer readable storage mediums, belong to storehouse management technical field.This method is suitable for inventory's detection device, including is explored in warehouse, is scanned to the article of discovery；Multiple articles comprising stock article are identified as stock article heap when judging the article of discovery for new stock article by map match operation；The all items in stock article heap are mapped, and the data that mapping obtains are analyzed；Based on the analysis results, the quantity of stock article is obtained.Using the present invention, no matter whether user is known in advance type and modes of emplacement that warehouse increases stock article newly in this way, can fast and accurately count to newly-increased stock article.
Description
Technical field
The present invention relates to inventory's detection method, equipment and the storages in storehouse management technical field more particularly to a kind of warehouse
Medium.
Background technique
Stock control is process step important in warehousing system, is needed often in daily stock control work to existing
Quantity in stock make an inventory, to ensure the accuracy of inventory.
Existing inventory management techniques are usually to count in pre-set region to product, the product in warehouse
Usually place in a particular manner.And product is usually specific type, such as medicine bottle, food etc..
But as people's living needs become increasingly abundant, the class for the cargo that the warehouse of many manufacturers and retailer need to store
Type is various, and in order to time saving and energy saving, often arbitrarily places.Goods can not be known in advance for this in existing inventory management techniques
The type of object and the unstructured moving grids of modes of emplacement can not solve the problems, such as to count warehouse goods in warehouse.
Summary of the invention
In view of this, the purpose of the present invention is to provide method, equipment and the storage medium of a kind of inventory detection, to solve
The problem of prior art can only count the warehouse goods of specific type and fixed placement mode.
It is as follows that the present invention solves technical solution used by above-mentioned technical problem:
According to the first aspect of the invention, a kind of method of inventory's detection is provided, inventory's detection device is suitable for, it is described
Method the following steps are included:
It is explored in warehouse, when finding article, article is scanned；
By map match operation, judge whether found article is new stock article；
When judging the article of discovery for new stock article, multiple articles comprising the stock article are identified as library
Deposit stack of articles；
All stock articles in the stock article heap are mapped, and the data that mapping obtains are analyzed；
Based on the analysis results, the quantity of the stock article in the stock article heap is obtained.
According to the second aspect of the invention, a kind of inventory's detection device is provided, the equipment includes: memory, processing
Device and it is stored in the computer program that can be run on the memory and on the processor, the computer program is by institute
State the step realized as described in first aspect when processor executes.
According to the third aspect of the present invention, a kind of computer readable storage medium is provided, which is characterized in that the calculating
It is stored with computer program on machine readable storage medium storing program for executing, such as first aspect is realized when the computer program is executed by processor
Or described in the second aspect the step of inventory's detection method.
Inventory's detection method method, equipment and the storage medium of the embodiment of the present invention, regardless of whether it is new that warehouse is known in advance
The type and modes of emplacement for increasing stock article, can fast and accurately count newly-increased stock article, improve warehouse pipe
The convenience and timeliness of reason.
Detailed description of the invention
Fig. 1 is a kind of flow chart for inventory's detection method that the embodiment of the present invention one provides；
Fig. 2 is the flow chart of another inventory's detection method provided by Embodiment 2 of the present invention；
Fig. 3 is a kind of structural schematic diagram for inventory's detection device that the embodiment of the present invention three provides.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
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.
In subsequent description, if using the suffix for indicating such as " module ", " component " or " unit " of element
Only for being conducive to explanation of the invention, itself there is no specific meaning.Therefore, " module ", " component " or " unit " can be with
Mixedly use.
The embodiment of the present invention one provides a kind of inventory's detection method.Inventory's detection of the present embodiment is suitable for inventory and detects
Equipment.Referring to Fig. 1, method flow includes:
Step S101, it is explored in warehouse, when finding article, article is scanned；
Step S102, by map match operation, judge whether found article is new stock article；
Step S103, when judging the article of discovery for new stock article, by multiple objects comprising the stock article
Product are identified as stock article heap；
Step S104, all stock articles in the stock article heap are mapped, and the data that mapping obtains are divided
Analysis；
Step S105, the quantity of the stock article in the stock article heap based on the analysis results, is obtained.
It in a feasible scheme, step S101, is explored in warehouse, when finding article, from different directions
Article is scanned, comprising:
Using semi-random tactful data warehouse explored environment, forward rectilinear traveling is explored；
When finding article in the distance for being less than predetermined threshold, different angle sweeps article from different directions
It retouches.
Laser radar (LIDAR, Light Detection and Ranging), is laser acquisition and the letter of range-measurement system
Claim, is the radar system to emit the characteristic quantities such as the position of detecting laser beam target, speed.Its working principle is that objective emission
Then the reflected signal of slave target received is compared by detectable signal (laser beam) with transmitting signal, it is appropriate to make
After processing, detection target is obtained for information about.
In practical application, in addition to using other than laser radar scanning, also can be used conventional microwave radar, spatial digitizer etc. its
Its arrangement for detecting, scanning obtain one or more of parameter combination information such as distance, orientation, size, shape, color of article.
In a feasible scheme, step S102, by map match operation, judge whether found article is new
Stock article, comprising:
The data conversion that scanning obtains is corresponded to each point coordinate on map；
Point on all maps being converted to is clustered, different classes of cluster point is generated；
The cluster point is matched with the point in the map datum prestored, judge cluster point whether with pre-stored map number
According to matching.
The equipment of inventory's detection stores inventory's initial data in warehouse in advance, and is deposited in the form of map datum
Storage.In practical application, which be can be grid map (Grip Map), and net can be used in the spatial information of warehouse goods in warehouse
Case form storage and expression.It is divided into grid unit by plane coordinates system, to each various objects of grid unit recording and storage
Product element.The map datum prestored can also record area, volume and the various environmental parameters in warehouse etc..
In a feasible scheme, the point on all maps being converted to is clustered, is generated different classes of
Cluster point, concrete mode are as follows:
Default cluster threshold value, is set as the first cluster point for be converted to first point；
When being greater than cluster threshold value with the distance between first point of adjacent second point and at first point, it is poly- to be set as second
Class point, when with the second cluster point is adjacent the distance between be thirdly greater than cluster threshold values when, be set as third cluster point, according to
It is secondary to be compared, when the nth point the distance between adjacent with the (n-1)th cluster point is greater than cluster threshold values, it is poly- to generate n-th
Class point.
In practical application, two adjacent points are judged, judge between two points whether to be same category, it is referred to as poly-
Class.The distance between adjacent two o'clock limit value can be set in advance, this Distance l imit is to cluster threshold values, when between adjacent two o'clock
Distance be less than cluster threshold values when, this two o'clock be same attribute point, when the distance between adjacent two o'clock be greater than cluster threshold values when,
This two o'clock is different classes of cluster point.
Different classes of cluster point is stored in the form of a list in the memory of the equipment.
In a feasible scheme, the cluster point is matched with the point in the map datum prestored, judgement is poly-
Whether class point is point in pre-stored map data, comprising:
First time sampling is carried out to cluster point, presets an inspection window, judges to check the quantity of the cluster point in window
Whether the ratio between the cluster point quantity of sampling is greater than preset window percentage threshold value, and the window percentage threshold value is used
In identification sampling cluster point whether with the Data Matching that is stored in pre-stored map；
If so, output Data Matching cluster point and stored in pre-stored map；
If it is not, then increasing default cluster threshold values, to increase the cluster point quantity of sampling, cluster point is adopted for the second time
Sample, and judge to check whether the ratio between the quantity of cluster point and the cluster point quantity of sampling in window is greater than preset window
Mouth percentage threshold is greater than preset mismatch count threshold until clustering threshold values, then judges cluster point and pre-stored map data
In point mismatch.
In practical application, the inspection window is where the article explored in the spatial dimension of grid map.It is default
One inspection window presets the size for checking window, typically refers to mark off a certain number of grid cells on map,
To judge whether the cluster point of sampling matches with the data on map in a certain range.
In a feasible scheme, all stock articles in the stock article heap step S104, are mapped, and will reflect
The data penetrated are analyzed, comprising:
Be moved near new stock article, by the position be recorded as mapping initial position, and to new stock article into
Row mapping；
Since initial position, all stock articles are successively mapped around stock article heap, until returning to starting
Position；
The information for all stock articles that mapping obtains is merged into operation, obtains the overall volume of stock article heap.
Wherein, mapping concrete mode is successively carried out to all stock articles around stock article heap are as follows:
Around stock article heap, at a certain distance, the information such as image, color, the size of stock article are recorded, every time
The data of record all be stored in map datum as a cloud.Will the information of all stock articles be mapped in equipment one by one
In the map datum of storage.
In practical applications, when detection obtains the quantity and other Item Information of the stock article in the stock article heap
Afterwards, also pre-stored map datum is updated and is saved.
In a feasible scheme, step S105, based on the analysis results, the oddment in the stock article heap is obtained
The quantity of product, comprising:
Based on the analysis results, the volume of stock article heap and the volume of single stock article are obtained；
By the volume of stock article heap divided by the volume of single stock article, the oddment in the stock article heap is obtained
The quantity of product.
Inventory's detection method of the present embodiment, by being scanned in warehouse to the article of discovery, by scanning information and
The inventory data prestored carries out map match operation, identifies whether the stock article heap to increase newly, and by stock article heap
Mapping, the overall volume of stock article heap and the volume of single stock article are obtained, to calculate newly-increased stock article heap
In stock article quantity, in this way, also can regardless of whether the size and placement location of warehouse inventory article is known in advance
The newly-increased stock article quantity of accurate detection, improves the convenience and timeliness of storehouse management.
On the basis of previous embodiment, second embodiment of the present invention provides the methods of another inventory detection, are suitable for
Inventory's detection device.Referring to Fig. 2, method includes the following steps:
Step S201, inventory's detection device straight-line travelling in warehouse, and semi-random tactful data warehouse explored environment is used, when
When finding article in the distance for being less than reservation threshold, calling laser radar, different angle sweeps article from different directions
It retouches；
Scanning direction is randomly choosed from a section equation, and the equation is as follows:
Newheading=currentheading+randow ([0.6pi, 1.4pi])
In the present embodiment, article refers to stock keeping unit (SKU, Stock Keeping Unit), stack of articles (SKU in warehouse
Pile) refer to that the article of identical size and kind is put together at one.In the present embodiment, inventory's detection device is robot,
It can be other smart machines.
The scanning device that inventory's detection device calls can be laser radar, conventional microwave radar or spatial digitizer etc.
It is other to scan to obtain the detection equipment of the information such as distance, orientation, size, shape, the color of article.In the present embodiment,
Think and is illustrated for laser radar.
The concrete mode of scanning, which is laser radar, launches outward signal according to some angle, and reception is reflected by article
Signal, to obtain the location information for the article that laser radar is detected in each angle.
Step S202, the coordinate points being converted into the data information of laser radar detection on map；
This conversion is completed by using the conversion from map frame to laser radar frame.Each coordinate points are to stress
Coordinate (x, y) of the object that optical radar detects in map.These coordinate points can be stored by way of list.
Step S203, default cluster threshold value, is set as the first cluster point for be converted to first point, when with described first point
When the distance between adjacent second point and are greater than cluster threshold value, be set as the second cluster point at first point, when with second cluster
Point is adjacent when the distance between being thirdly greater than cluster threshold values, is set as third cluster point, is successively compared, until with it is described
When adjacent the distance between the nth point of (n-1)th cluster point is greater than cluster threshold values, the n-th cluster point is generated；
Different classes of cluster point can also be stored by way of list.Due to newly-increased stock article size and position
It is all unknown for the information such as setting, and in unknown pattern identification, it usually needs do not have to find wherein in the data of label from a pile
Association, to find the similitude between data.Such as: by laser radar detection article, article can be obtained in map
On various spatial information datas, some are related to the length of article, some are related to the height of article, also some be related to the width etc. of article
Deng.These data and the map datum prestored can be compared one by one in order to subsequent, so herein first by different classes of number
Strong point is clustered.
Under normal conditions, two points are more similar, and similarity S is bigger, and distance between two points D is smaller；On the contrary, two points are got over
Unlike similarity S is smaller, and distance between two points D is bigger.Therefore my door can preset a cluster threshold values.Cluster valve
Value can be customized by the user setting.It therefore, can be by will be compared between the distance between adjacent two o'clock and cluster threshold values
To be clustered.
The specific algorithm of cluster there are also there are many kinds of, such as exclusive formula clustering algorithm (Exclusive Clustering),
Eclipsed form clustering algorithm (Overlapping Clustering), grade classification formula clustering algorithm (Hierarchical
Clustering), probabilistic type clustering algorithm (Probabilistic Clustering) etc., does not just repeat one by one here.
Step S204, the cluster point is matched with the point in the map datum prestored, judge cluster point whether with
Point in pre-stored map data matches；
The equipment of inventory's detection stores the inventory data in warehouse in advance, and is stored in the form of map datum.
In the present embodiment, which is grid map, and grid configuration storage and table can be used in the spatial information of warehouse goods in warehouse
Show.It is divided into grid unit by plane coordinates system, to the element of each various articles of grid unit recording and storage.
Judge whether cluster point matches with the point in pre-stored map data, concrete mode are as follows:
The grid map stored in advance is called, and first time sampling is carried out to cluster point；
An inspection window is preset, judges to check between the quantity of cluster point and the cluster point quantity of sampling in window
Whether ratio is greater than preset window percentage threshold value, the cluster point that the window percentage threshold value samples for identification whether and
The Data Matching stored in pre-stored map；
If so, output Data Matching cluster point and stored in pre-stored map；
If it is not, then increasing cluster threshold values, to increase the cluster point quantity of sampling, cluster point is sampled again, and judges
Check whether the ratio between the quantity of the cluster point in window and the cluster point quantity of sampling is greater than preset window percentage
Threshold value is greater than preset mismatch count threshold until clustering threshold values, then judges cluster point with the point in pre-stored map data not
Matching.
Such as the quantity of the cluster point of an article is 100,20 cluster points is sampled, to reduce calculation amount.Default window
Mouth percentage threshold values is 0.8, if 20 points of sampling, wherein having 18 in checking window, then the cluster point in window
Quantity and sampling cluster point quantity between ratio be 0.9, be greater than preset window percentage threshold values 0.8, therefore judge
Cluster point matches with the point in pre-stored map data., whereas if the quantity of the cluster point in window and the cluster point of sampling
Ratio between quantity is less than preset window percentage threshold values, it may be possible to the cluster threshold values between preset two neighboring point
It is less than normal, at this time by increase cluster threshold value, i.e., cluster point quantity increase by 200, again sample 40 points, and judge this 40
Whether a point matches with the point on map；If still mismatched, increases cluster threshold value again, i.e., the quantity of cluster point is increased
Add 400, sample 80 points, the population size at this moment clustered a little is more than to mismatch count threshold (to mismatch count threshold user
Can customize setting), then judge that cluster point is mismatched with the point in map datum, which is that inventory increases article newly.And it will gather
Intermediate point in class point in group is considered as the position of article.
Step S205, when cluster point is mismatched with the point in pre-stored map data, the article found is identified as newly
The stock article of increasing；
Step S206, multiple articles comprising the newly-increased stock article are identified as stock article heap；
Step S207, it is moved near new stock article, which is recorded as mapping initial position, and to new library
Storage product are mapped；
Step S208, since initial position, all stock articles are successively mapped around stock article heap, until
Return to initial position；
Around stock article heap, at a certain distance, the information such as image, color, the size of stock article are recorded, every time
The data of record all be stored in map datum as.
Since inventory's detection device does not know that the size and shape of stock article heap uses LIDAR as it moves in advance
Observation is to keep a certain distance separate with stack of articles.For inventory's detection device around stock article heap, every traveling is certain
Distance just stops and measures image, and the instrument for measuring image can be onboard Kinect sensor, is also possible to other images
Recording equipment；The data measured every time are all saved in file as point, and are saved along the position of inventory's detection device traveling.
When inventory's detection device is in the certain distance that it starts the initial place for surrounding stock article heap, it identifies and has completed
One complete circulation stops and continues to explore a new round for warehouse item along other directions.
Step S209, the information for all stock articles that mapping obtains is merged into operation, obtains stock article heap
The volume of overall volume and single stock article；
Our point of use clouds merge all measured values carried out during algorithm carrys out combined running, obtain the whole of stock article heap
Body volume.
Step S210, the volume of stock article heap is obtained into the stock article heap divided by the volume of single stock article
In stock article quantity；
Step S211, pre-stored map datum is updated and is saved.
Inventory's detection method of the present embodiment, by being scanned in warehouse to the article of discovery, by scanning information and
The inventory data prestored carries out map match operation, identifies whether the stock article heap to increase newly, and by stock article heap
Mapping, the overall volume of stock article heap and the volume of single stock article are obtained, to calculate newly-increased stock article heap
In stock article quantity, in this way, also can regardless of whether the size and placement location of warehouse inventory article is known in advance
The newly-increased stock article quantity of accurate detection, improves the convenience and timeliness of storehouse management.
On the basis of previous embodiment, the embodiment of the present invention three provides another inventory's detection device.
Referring to Fig. 3, inventory's detection device includes: memory 301, processor 302 and is stored in the memory 301
It 302 computer program 303 run, the computer program 303 can be held above and by the processor 302 on the processor
The step of detecting such as the inventory such as first embodiment or second embodiment is realized when row.
Inventory's detection device of the present embodiment, by being scanned in warehouse to the article of discovery, by scanning information and
The inventory data prestored carries out map match operation, identifies whether the stock article heap to increase newly, and by stock article heap
Mapping, the overall volume of stock article heap and the volume of single stock article are obtained, to calculate newly-increased stock article heap
In stock article quantity, in this way, also can regardless of whether the size and placement location of warehouse inventory article is known in advance
The newly-increased stock article quantity of accurate detection, improves the convenience and timeliness of storehouse management.
On the basis of previous embodiment, the embodiment of the present invention four provides a kind of computer readable storage medium, special
Sign is, computer program is stored on the computer readable storage medium, when the computer program is executed by processor
It realizes such as the step of the inventory of first embodiment or second embodiment detection.
The computer readable storage medium of the present embodiment will be scanned by being scanned in warehouse to the article of discovery
Information and the inventory data prestored carry out map match operation, identify whether the stock article heap to increase newly, and by inventory
The mapping of stack of articles obtains the overall volume of stock article heap and the volume of single stock article, to calculate newly-increased inventory
The quantity of stock article in stack of articles, in this way, regardless of whether the size of warehouse inventory article be known in advance and places position
It sets, can accurately also detect newly-increased stock article quantity, improve the convenience and timeliness of storehouse management.
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 a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal (can be mobile phone, computer, service
Device, 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 method of inventory's detection, is suitable for inventory's detection device, the described method comprises the following steps:
It is explored in warehouse, when finding article, article is scanned；
By map match operation, judge whether found article is new stock article；
When judging the article of discovery for new stock article, multiple articles comprising the stock article are identified as oddment
Product heap；
All stock articles in the stock article heap are mapped, and the data that mapping obtains are analyzed；
Based on the analysis results, the quantity of the stock article in the stock article heap is obtained.
2. inventory's detection method as described in claim 1, which is characterized in that based on the analysis results, obtain the stock article
The quantity of stock article in heap, comprising:
Based on the analysis results, the volume of stock article heap and the volume of single stock article are obtained；
By the volume of stock article heap divided by the volume of single stock article, the stock article in the stock article heap is obtained
Quantity.
3. inventory's detection method as described in claim 1, which is characterized in that it is explored in warehouse, when finding article,
Article is scanned, comprising:
Using semi-random tactful data warehouse explored environment, forward rectilinear traveling is explored；
When finding article in the distance for being less than predetermined threshold, different angle is scanned article from different directions.
4. inventory's detection method as described in claim 1, which is characterized in that original inventory data is pre-stored in map datum,
By map match operation, judge whether found article is new stock article, comprising:
The data conversion that scanning obtains is corresponded to each point coordinate on map；
Point on all maps being converted to is clustered, different classes of cluster point is generated；
The cluster point is matched with the point in the map datum prestored, judge cluster point whether with pre-stored map data phase
Matching.
5. inventory's detection method as claimed in claim 4, which is characterized in that the point on the described pair of all maps being converted to
It is clustered, generates different classes of cluster point, concrete mode are as follows:
Default cluster threshold value, is set as the first cluster point for be converted to first point；
When being greater than cluster threshold value with the distance between first point of adjacent second point and at first point, it is set as the second cluster
Point, when with the second cluster point is adjacent the distance between be thirdly greater than cluster threshold values when, be set as third cluster point, successively
It is compared, when the nth point the distance between adjacent with the (n-1)th cluster point is greater than cluster threshold values, generates the n-th cluster
Point.
6. inventory's detection method as claimed in claim 5, which is characterized in that by the cluster point in the map datum that prestores
Point matched, judge whether cluster point is point in pre-stored map data, comprising:
First time sampling is carried out to cluster point, presets an inspection window, judge to check the quantity of the cluster point in window and is adopted
Whether the ratio between the cluster point quantity of sample is greater than preset window percentage threshold value, and the window percentage threshold value is for knowing
The cluster point not sampled whether with the Data Matching that is stored in pre-stored map；
If so, output Data Matching cluster point and stored in pre-stored map；If it is not, then increase default cluster threshold values,
Second is carried out to cluster point to sample, and judges to check between the quantity of cluster point and the cluster point quantity of sampling in window
Whether ratio is greater than preset window percentage threshold value, is greater than preset mismatch count threshold until clustering threshold values, then judges
Cluster point is mismatched with the point in pre-stored map data.
7. inventory's detection method as described in claim 1, which is characterized in that the institute in the mapping stock article heap is in stock
Article, and the data that mapping obtains are analyzed, comprising:
It is moved near new stock article, which is recorded as mapping initial position, and reflect to new stock article
It penetrates；
Since initial position, all stock articles are successively mapped around stock article heap, until returning to initial position；
The information for all stock articles that mapping obtains is merged into operation, obtains the overall volume of stock article heap.
8. inventory's detection method as claimed in claim 7, which is characterized in that around stock article heap to all stock articles according to
It is secondary to carry out mapping concrete mode are as follows:
Around stock article heap, at a certain distance, the information such as image, color, the size of stock article are recorded, recorded every time
Data all as point a cloud be stored in map datum.
9. a kind of inventory's detection device, which is characterized in that the equipment includes: memory, processor and is stored in described deposit
On reservoir and the computer program that can run on the processor, the computer program are realized when being executed by the processor
Step as described in any in claim 1 to 8.
10. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program realizes such as step described in any item of the claim 1 to 8 when the computer program is executed by processor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111626660A (en) * | 2020-04-21 | 2020-09-04 | 普洛斯企业发展(上海)有限公司 | Method and device for determining inventory of bearing device and computer readable storage medium |
| CN116029536A (en) * | 2023-03-28 | 2023-04-28 | 深圳市实佳电子有限公司 | NFC technology-based intelligent warehouse cargo scheduling method, NFC technology-based intelligent warehouse cargo scheduling device, NFC technology-based intelligent warehouse cargo scheduling equipment and NFC technology-based intelligent warehouse cargo scheduling medium |
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