CN116485313A - Big data-based warehouse commodity flow commercial commodity monitoring and management method - Google Patents
Big data-based warehouse commodity flow commercial commodity monitoring and management method Download PDFInfo
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Abstract
The invention discloses a warehouse logistics commercial commodity monitoring and managing method based on big data, which comprises the following steps: s1, acquiring a warehouse-in operation instruction; s2, detecting the quality of the agricultural products corresponding to the types of the agricultural products; s3, collecting the freshness of the agricultural products in each current electronic tag, and grading the freshness of the agricultural products; s4, obtaining sales parameters of all agricultural products in the electronic commerce commodities; s5, selecting a proper warehouse, distributing a farm product warehouse area and a storage position according to the pricing of the farm product, and uploading data information to a PFID reader-writer; s6, reading information of each electronic tag by using a PFID reader-writer, comparing actual warehousing information with pre-warehousing information, and judging whether the actual warehousing information is consistent with the pre-warehousing information; s7, uploading data to a database through the RFID reader-writer. The invention directly reads the needed information from the electronic tag through the reader-writer, the information processing process is simplified, and the gray level image improves the visual quality of the image.
Description
Technical Field
The invention relates to the field of logistics management, in particular to a warehouse logistics commodity monitoring and management method based on big data.
Background
Electronic commerce generally refers to a novel business operation mode for realizing online shopping of consumers, online transaction and online electronic payment among merchants, various business activities, transaction activities, financial activities and related comprehensive service activities based on client/server application modes in a global and wide-ranging business trade activities in an internet open network environment.
In modern society, various new agricultural products appear at every moment, and the quality inspection of the products which are taken as the agricultural products to be taken care of needs to detect the quality of the new appearance, so that the agricultural products are guaranteed to flow into society to be qualified, if only a traditional manual inspection method is used, the processes of receiving, sampling, detecting statistical data, analyzing data and making reports of the agricultural products are carried out for a long period, thus the production process of the products is prolonged, the development speed is reduced, the product quality inspection system is a system which improves the busy situation, the staff only needs to scan the samples of the system, then the inspection, the statistical data, the analyzing data and the making reports are finished by the system instead of manpower, the workload of the staff is reduced, the inspection speed of the products is also improved, and the inspection period is shortened.
However, the conventional warehouse management mode generally has the defects of high labor cost, more business processes, difficult tracking of goods, lower turnover efficiency of funds and goods, lagged informatization means of logistics management and the like, and can not ensure quick and correct stock feeding and inventory control and delivery, so that the management cost is increased, the service quality is difficult to ensure, and the competitiveness of enterprises is affected. The traditional logistics storage management system can only realize the static management of goods information, but cannot realize the real-time tracking and monitoring of the whole logistics process.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a warehouse commodity flow commercial product monitoring and managing method based on big data, which aims to overcome the technical problems existing in the related art.
For this purpose, the invention adopts the following specific technical scheme:
a warehouse commodity flow commercial commodity monitoring and managing method based on big data comprises the following steps:
s1, acquiring a warehouse-in operation instruction, and counting the types of agricultural products in an electronic commerce industry of each agricultural product;
s2, quality detection is carried out on the agricultural products corresponding to the agricultural product types, classification is carried out on the agricultural products according to quality detection results, and corresponding electronic labels are given to the agricultural products;
s3, collecting the freshness of the agricultural products in each current electronic tag, and grading the freshness of the agricultural products;
s4, acquiring sales parameters of all agricultural products in the electronic commerce commodities, and pertinently pricing the classified agricultural products according to the sales parameters;
s5, selecting a proper warehouse, distributing a farm product warehouse area and a storage position according to the pricing of the farm product, and uploading data information to a PFID reader-writer;
s6, during warehousing, reading information of each electronic tag by using a PFID reader-writer, comparing actual warehousing information with pre-warehousing information, and judging whether the actual warehousing information is consistent with the pre-warehousing information;
and S7, after warehousing, uploading data to a database through the RFID reader-writer, and updating the electronic tag information.
Further, the warehouse-in operation instruction comprises agricultural product delivery time, delivery vehicle information and an agricultural product list.
Further, the quality detection of the agricultural products corresponding to the agricultural product types, the classification of the agricultural products according to the quality detection result, and the assignment of the electronic labels to the agricultural products comprise the following steps:
s21, placing the detected agricultural products on a conveyor belt of an object stage, and conveying the agricultural products to an image sensor at a set speed;
s22, utilizing the irradiation of the image sensor, imaging the detected agricultural product on the image sensor, and obtaining a three-dimensional image of the agricultural product;
s23, uploading the three-dimensional image to an image processor for preprocessing, calculating whether the detected agricultural products are qualified or not, and eliminating unqualified agricultural products.
Further, the uploading the three-dimensional image to an image processor for preprocessing, calculating whether the detected agricultural product is qualified or not, and eliminating the unqualified agricultural product comprises the following steps:
s231, determining three components of pixel gray levels in the three-dimensional stereoscopic image in an image processor, and adjusting the pixel gray levels of the three components so that the three pixel components are the same;
s232, carrying out gray scale processing on the pixel components by adopting a weighted average value to obtain a matched gray scale image;
s233, processing the gray level image by adopting an image processing technology, and judging whether the detected agricultural product is qualified or not.
Further, the processing the gray level image by adopting the image processing technology and judging whether the detected agricultural product is qualified or not comprises the following steps:
s2331, constructing a gray level image into a gray level function set with pixel points;
s2332, dividing a set of points with discontinuous gray level functions in the gray level image into edges of the divided areas, and reserving areas with severe gray level variation of the image;
s2333, constructing a gradient algorithm, detecting the change of the gray level of the image, and dividing the region of the image;
s2334, regarding the gray level image as a two-dimensional discrete function, wherein the image gradient is the first derivative of the two-dimensional discrete function, and constructing a gradient coordinate;
s2335, comparing the divided areas with standard agricultural products to obtain a comparison result, and judging whether the agricultural products are qualified or not according to the comparison result.
Further, the gradient coordinates are expressed as follows:
the expression of the gradient amplitude is:
in the formula, G [ f (x, y) ] is gradient amplification of (x, y) pixel points, f (x, y) is a two-dimensional discrete function, and x, y is the pixel point in the gray level image.
Further, the step of collecting the freshness of the agricultural products in each current electronic tag and grading the freshness of the agricultural products comprises the following steps:
s31, constructing a classical perishable commodity inventory model, and regarding the deterioration rate as a variable which changes along with the initial freshness of the product and the change of the insurance package cost;
s32, calculating the deterioration rate of the agricultural products and the fresh-keeping coefficient after fresh-keeping packaging, and constructing a new deterioration inventory model;
s33, dividing different freshness grades according to the new metamorphic inventory model.
Further, the obtaining sales parameters of each agricultural product in the electronic commerce commodity, and the pertinently pricing the classified agricultural products according to the sales parameters comprises the following steps:
s41, calculating the demand rate of the agricultural product market according to the relation between the demand rate and the existing retail price of the agricultural product;
s42, recording purchasing information in the current order and the transportation cost of the agricultural products;
s43, pricing with different price according to the freshness grade of the agricultural products and the demands of the agricultural products with different freshness so as to meet the demands of different crowds.
Further, during the warehousing, the PFID reader-writer is utilized to read the information of each electronic tag, the actual warehousing information is compared with the pre-warehousing information, and whether the information accords with the pre-warehousing information is judged, and the method comprises the following steps:
s61, when an article arrives at a zone to be detected, a PFID reader-writer at a warehouse entry gate reads the novel electronic tag;
s62, the PFID reader automatically compares the actual warehouse-in information with the pre-warehouse-in information, and judges whether the electronic tag is consistent with the warehouse-in information according to the related logic;
s63, if errors occur, sending out voice prompts by the PFID reader-writer, and processing by staff of related departments;
and S64, if no error exists, distributing according to the pre-selected agricultural product storage area and the storage position.
Further, after the warehouse entry, uploading data to a database through an RFID reader-writer, and updating the electronic tag information, wherein the updating operation comprises the following steps:
s71, selecting a warehouse and a warehouse area to be checked, making a checking list, and generating a checking list;
s72, the information system controls the RFID reader-writer to start reading data through a wireless network;
s72, the RFID reader transmits the disk data to the information system through a wireless network;
s72, the information system calculates the difference between the statistical quantity and the inventory quantity of the goods in each goods space, and performs inventory adjustment management, inventory browsing, goods inventory distribution query and goods analysis in the goods space.
The beneficial effects of the invention are as follows:
1. the invention combines the mechanical vision technology and the gray processing technology, the object of the image of the agricultural product is picked up, the image is converted into the image through a machine and transmitted to an image processing system, the image signal is converted into the digital signal according to various information such as pixel distribution, brightness, color and the like in the image, the image system processes the digital signals, the characteristics of the digital signal are found through operation, the reading speed is high, random sampling can be carried out, the data obtained by the machine vision technology is high-precision and high-speed, compared with the manual operation, the computer has stronger calculation capability, the obtained calculation data is more precise, the gray image improves the visual quality of the image, so that the image processing meets the observation requirements of a visual system, such as brightness enhancement of the gray image, color conversion of the gray image, shadow removal of the gray image, encoding, compression and decoding of the image data, the image data can be encrypted through encoding, compression and decoding, the image data can be encrypted through encoding and decoding, and the stability and safety of transmission are ensured.
2. After the RFID technology is applied, data can be directly written in the same label through the reader-writer, data related to each processing process can be uniformly stored in the label, when related data of the past goods processing is needed in the subsequent processing process, a related database is not needed to be accessed, needed information can be directly read out from the electronic label through the reader-writer, and the information processing process is simplified.
3. The RFID reader can be used for carrying out wireless identification on the warehoused goods, the acquired data are immediately transmitted to the computer system, and the system compares the acquired goods data with the pre-warehouse-housed goods data of the computer network system to obtain a detailed difference state table for acceptance; if the difference is not found, the checking and accepting work is completed, so that the work efficiency is greatly improved, after the RFID technology is applied, the data can be directly written in the same label through the reader-writer, the data related to each processing process can be uniformly stored on the label, when the related data of the past goods processing is needed in the subsequent processing process, the related database is not needed to be accessed, the needed information can be directly read out from the electronic label through the reader-writer, and the information processing process is simplified.
4. The RFID reader can be used for carrying out wireless identification on warehoused goods, and the acquired data are immediately transmitted to the computer system; comparing the collected goods data with pre-warehouse-in goods data of a computer network system by the system to obtain a detailed difference state table of acceptance; if the difference is not found, the acceptance work is finished, so that the working efficiency is greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a warehouse logistics business commodity monitoring and management method based on big data according to an embodiment of the present invention.
Detailed Description
For the purpose of further illustrating the various embodiments, the present invention provides the accompanying drawings, which are a part of the disclosure of the present invention, and which are mainly used to illustrate the embodiments and, together with the description, serve to explain the principles of the embodiments, and with reference to these descriptions, one skilled in the art will recognize other possible implementations and advantages of the present invention, wherein elements are not drawn to scale, and like reference numerals are generally used to designate like elements.
According to the embodiment of the invention, a warehouse logistics business commodity monitoring and management method based on big data is provided.
The invention will be further described with reference to the accompanying drawings and detailed description, as shown in fig. 1, a warehouse logistics business commodity monitoring and management method based on big data according to an embodiment of the invention, the method comprises the following steps:
s1, acquiring a warehouse-in operation instruction, and counting the types of agricultural products in an electronic commerce industry of each agricultural product;
in one embodiment, the warehousing operation instructions include a time of delivery of the agricultural product, delivery vehicle information, and a manifest of the agricultural product.
Specifically, the conventional warehouse management mode generally has the defects of high labor cost, more business processes, difficult tracking of goods, lower turnover efficiency of funds and goods, lagged informatization means of logistics management and the like, and can not ensure quick and correct goods feeding, inventory control and delivery, so that the management cost is increased, the service quality is difficult to ensure, and the competitiveness of enterprises is affected. The traditional logistics storage management system can only realize the static management of goods information, but cannot realize the real-time tracking and monitoring of the whole logistics process. The RFID technology has the characteristics of no contact, large capacity, rapidness, high fault tolerance, interference resistance, corrosion resistance, safe and reliable information identification and the like, and is well applied to flow warehouse management.
S2, quality detection is carried out on the agricultural products corresponding to the agricultural product types, classification is carried out on the agricultural products according to quality detection results, and corresponding electronic labels are given to the agricultural products;
in one embodiment, the quality detection of the agricultural products corresponding to the agricultural product types, classification of the agricultural products according to the quality detection result, and giving the electronic labels corresponding to the agricultural products include the following steps:
s21, placing the detected agricultural products on a conveyor belt of an object stage, and conveying the agricultural products to an image sensor at a set speed;
s22, utilizing the irradiation of the image sensor, imaging the detected agricultural product on the image sensor, and obtaining a three-dimensional image of the agricultural product;
s23, uploading the three-dimensional image to an image processor for preprocessing, calculating whether the detected agricultural products are qualified or not, and eliminating unqualified agricultural products;
in one embodiment, the uploading the three-dimensional image to the image processor for preprocessing, calculating whether the detected agricultural product is qualified, and rejecting the unqualified agricultural product comprises the following steps:
s231, determining three components of pixel gray levels in the three-dimensional stereoscopic image in an image processor, and adjusting the pixel gray levels of the three components so that the three pixel components are the same;
s232, carrying out gray scale processing on the pixel components by adopting a weighted average value to obtain a matched gray scale image;
s233, processing the gray level image by adopting an image processing technology, and judging whether the detected agricultural product is qualified or not;
in one embodiment, the processing the gray image by using the image processing technology and judging whether the detected agricultural product is qualified comprises the following steps:
s2331, constructing a gray level image into a gray level function set with pixel points;
s2332, dividing a set of points with discontinuous gray level functions in the gray level image into edges of the divided areas, and reserving areas with severe gray level variation of the image;
s2333, constructing a gradient algorithm, detecting the change of the gray level of the image, and dividing the region of the image;
s2334, regarding the gray level image as a two-dimensional discrete function, wherein the image gradient is the first derivative of the two-dimensional discrete function, and constructing a gradient coordinate;
s2335, comparing the divided areas with standard agricultural products to obtain a comparison result, and judging whether the agricultural products are qualified or not according to the comparison result;
in one embodiment, the gradient coordinates are expressed as:
the expression of the gradient amplitude is:
in the formula, G [ f (x, y) ] is gradient amplification of (x, y) pixel points, f (x, y) is a two-dimensional discrete function, and x, y is the pixel point in the gray level image.
In particular, in order to enable the magnitude of the gradient to be calculated relatively simply, the formula is optimized,
specifically, the gray image is represented by the gray level of each pixel point, if we define the gray image as the gray level function set of the pixel point, the discontinuous point set of the gray level function in the image is the edge of the area to be segmented of the image, that is, the edge detection of the gray image is to keep the area with the severe change of the gray level of the image.
The problem is analyzed from the digital image angle, the edge detection method is differential, and the extreme value of the first derivative or the zero crossing point of the second derivative of the gray level function of the image pixel point is taken as the basis for detecting the edge. Therefore, for the implementation process of the method, only the gray level of the adjacent pixel points in the image needs to be compared, and the place with large gray level difference is the boundary of the region where the image should be segmented.
The classical edge detection method is to construct gradient operators to detect the gray level change of the image and divide the image into areas. If we consider a gray image as a two-dimensional discrete function f (x, y), the image gradient is the first derivative f' (x, y) of this two-dimensional discrete function.
S3, collecting the freshness of the agricultural products in each current electronic tag, and grading the freshness of the agricultural products;
in one embodiment, the collecting the freshness of the agricultural product in each current electronic tag and grading the freshness of the agricultural product comprises the following steps:
s31, constructing a classical perishable commodity inventory model, and regarding the deterioration rate as a variable which changes along with the initial freshness of the product and the change of the insurance package cost;
specifically, the formula for constructing the classical perishable commodity inventory model is:
wherein, I (t) is the stock change rate of the agricultural products at the moment t; d (t) is the market demand rate of the agricultural products at the moment t; lambda (t) is the deterioration rate of agricultural products at time t.
S32, calculating the deterioration rate of the agricultural products and the fresh-keeping coefficient after fresh-keeping packaging, and constructing a new deterioration inventory model;
the calculation formula of the fresh-keeping coefficient is as follows:
wherein f (r) is a fresh-keeping effort coefficient after fresh-keeping packaging;taking = 1 for the coefficient of the decrease in freshness over time of the product without freshness preservation packaging; r is the fresh-keeping packaging cost of the unit product; k is an investment cost coefficient, k represents a capital utilization level, and k is more than or equal to 0 and less than or equal to 1;
the formula of the new qualitative inventory model is:
wherein, I (t) is the stock change rate of the agricultural products at the moment t; d (t) is the market demand rate of the agricultural products at the moment t, and r is the unit product fresh-keeping packaging cost; k is an investment cost coefficient, k represents capital utilization level, beta 0 Is the initial freshness of the agricultural product.
S33, dividing different freshness grades according to the new metamorphic inventory model.
Specifically, the quality variable of the current agricultural product can be obtained according to the quality variable inventory model, and the grade of freshness is divided according to the existing quality variable.
S4, acquiring sales parameters of all agricultural products in the electronic commerce commodities, and pertinently pricing the classified agricultural products according to the sales parameters;
in one embodiment, the obtaining sales parameters of each agricultural product in the e-commerce commodity, and the pertinently pricing the graded agricultural products according to the sales parameters includes the following steps:
s41, calculating the demand rate of the agricultural product market according to the relation between the demand rate and the existing retail price of the agricultural product;
s42, recording purchasing information in the current order and the transportation cost of the agricultural products;
s43, pricing with different price according to the freshness grade of the agricultural products and the demands of the agricultural products with different freshness so as to meet the demands of different crowds.
In particular, the method comprises the steps of,
and S5, selecting a proper warehouse, distributing the agricultural product warehouse area and the storage position according to the pricing of the agricultural products, and uploading the data information to the PFID reader-writer.
S6, during warehousing, reading information of each electronic tag by using a PFID reader-writer, comparing actual warehousing information with pre-warehousing information, and judging whether the actual warehousing information is consistent with the pre-warehousing information;
in one embodiment, when the electronic tag information is put in storage, the PFID reader-writer is used for reading the electronic tag information, comparing the actual storage information with the pre-storage information, and judging whether the actual storage information is consistent with the pre-storage information or not comprises the following steps:
s61, when an article arrives at a zone to be detected, a PFID reader-writer at a warehouse entry gate reads the novel electronic tag;
s62, the PFID reader automatically compares the actual warehouse-in information with the pre-warehouse-in information, and judges whether the electronic tag is consistent with the warehouse-in information according to the related logic;
s63, if errors occur, sending out voice prompts by the PFID reader-writer, and processing by staff of related departments;
and S64, if no error exists, distributing according to the pre-selected agricultural product storage area and the storage position.
S7, after warehousing, uploading data to a database through an RFID reader-writer, and updating electronic tag information;
in one embodiment, after the warehousing, uploading data to a database through an RFID reader, and updating the electronic tag information, the method comprises the following steps:
s71, selecting a warehouse and a warehouse area to be checked, making a checking list, and generating a checking list;
s72, the information system controls the RFID reader-writer to start reading data through a wireless network;
s72, the RFID reader transmits the disk data to the information system through a wireless network;
s72, the information system calculates the difference between the statistical quantity and the inventory quantity of the goods in each goods space, and performs inventory adjustment management, inventory browsing, goods inventory distribution query and goods analysis in the goods space.
After the RFID technology is applied, data can be directly written in the same label through the reader-writer, data related to each processing process can be uniformly stored in the label, when related data of the past goods processing is needed in the subsequent processing process, a related database is not needed to be accessed, needed information can be directly read out from the electronic label through the reader-writer, and the information processing process is simplified.
During warehousing, the RFID reader can be used for carrying out wireless identification on warehoused goods, and the acquired data are immediately transmitted to the computer system. Comparing the collected goods data with pre-warehouse-in goods data of a computer network system by the system to obtain a detailed difference state table of acceptance; if there is no difference, the acceptance check is completed. The working efficiency is greatly improved. After the RFID technology is applied, the data can be directly written in the same label through the reader-writer, the data related to each processing process can be uniformly stored in the label, when the related data of the conventional goods processing is needed in the subsequent processing process, the related database is not required to be accessed, the required information can be directly read out from the electronic label through the reader-writer, and the information processing process is simplified.
During warehousing, the RFID reader can be used for carrying out wireless identification on warehoused goods, and the acquired data are immediately transmitted to the computer system. Comparing the collected goods data with pre-warehouse-in goods data of a computer network system by the system to obtain a detailed difference state table of acceptance; if there is no difference, the acceptance check is completed. The working efficiency is greatly improved.
After the RFID technology is applied, data can be directly written in the same label through the reader-writer, data related to each processing process can be uniformly stored in the label, when related data of the past goods processing is needed in the subsequent processing process, a related database is not needed to be accessed, needed information can be directly read out from the electronic label through the reader-writer, and the information processing process is simplified.
During warehousing, the RFID reader can be used for carrying out wireless identification on warehoused goods, and the acquired data are immediately transmitted to the computer system. Comparing the collected goods data with pre-warehouse-in goods data of a computer network system by the system to obtain a detailed difference state table of acceptance; if there is no difference, the acceptance check is completed. The working efficiency is greatly improved.
In summary, by means of the above technical scheme of the invention, the invention combines the mechanical vision technology and the gray processing technology, captures the object of the image of the agricultural product, converts the object into the image through a machine, transmits the image to the image processing system, converts the image signal into the digital signal according to various information such as pixel distribution, brightness, color and the like in the image, the image system processes the digital signals to find the characteristics of the digital signal through operation, has fast reading speed, can randomly sample the data obtained by the mechanical vision technology, has high precision and high speed, has more powerful computing capability than manual work, obtains more accurate computing data, improves the visual quality of the image by the gray image, ensures that the image processing meets the observation requirement of the visual system, for example, the brightness of the gray level image is enhanced, the color of the gray level image is transformed, the shadow of the gray level image is removed, the image data can be encrypted through encoding, compressing and decoding, the stability and the safety of transmission are ensured, after the RFID technology is applied, the data related to each processing process can be uniformly stored on the label through a reader-writer, when the related data of the conventional goods processing is needed in the subsequent processing process, the related database is not needed to be accessed, the required information can be directly read from the electronic label through the reader-writer, and the information processing process is simplified; the RFID reader can be used for carrying out wireless identification on the warehoused goods, the acquired data are immediately transmitted to the computer system, and the system compares the acquired goods data with the pre-warehouse-housed goods data of the computer network system to obtain a detailed difference state table for acceptance; if the difference is not found, the acceptance work is finished, so that the working efficiency is greatly improved; the reader-writer can directly write data in the same label, the data related to each processing process can be uniformly stored in the label, when the related data of the previous goods processing is needed in the subsequent processing process, the related database is not needed to be accessed, the reader-writer can directly read the needed information from the electronic label, and the information processing process is simplified; the RFID reader can be used for carrying out wireless identification on the warehoused goods, the acquired data are immediately transmitted to the computer system, and the system compares the acquired goods data with the pre-warehouse-housed goods data of the computer network system to obtain a detailed difference state table for acceptance; if the difference is not found, the acceptance work is finished, so that the working efficiency is greatly improved.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (9)
1. The commodity monitoring and managing method for the warehouse logistics commercial products based on the big data is characterized by comprising the following steps:
s1, acquiring a warehouse-in operation instruction, and counting the types of agricultural products in an electronic commerce industry of each agricultural product;
s2, quality detection is carried out on the agricultural products corresponding to the agricultural product types, classification is carried out on the agricultural products according to quality detection results, and corresponding electronic labels are given to the agricultural products;
s3, collecting the freshness of the agricultural products in each current electronic tag, and grading the freshness of the agricultural products;
the method for collecting the freshness of the agricultural products in the current electronic tags and grading the freshness of the agricultural products comprises the following steps:
s31, constructing a classical perishable commodity inventory model, and regarding the deterioration rate as a variable which changes along with the initial freshness of the product and the change of the insurance package cost;
s32, calculating the deterioration rate of the agricultural products and the fresh-keeping coefficient after fresh-keeping packaging, and constructing a new deterioration inventory model;
s33, dividing different freshness grades according to the new metamorphic inventory model;
s4, acquiring sales parameters of all agricultural products in the electronic commerce commodities, and pertinently pricing the classified agricultural products according to the sales parameters;
s5, selecting a proper warehouse, distributing a farm product warehouse area and a storage position according to the pricing of the farm product, and uploading data information to a PFID reader-writer;
s6, during warehousing, reading information of each electronic tag by using a PFID reader-writer, comparing actual warehousing information with pre-warehousing information, and judging whether the actual warehousing information is consistent with the pre-warehousing information;
and S7, after warehousing, uploading data to a database through the RFID reader-writer, and updating the electronic tag information.
2. The method of claim 1, wherein the warehousing instructions include time for shipping the agricultural product, shipping vehicle information, and inventory of the agricultural product.
3. The method for monitoring and managing commodity of warehouse commodity circulation merchant based on big data according to claim 1, wherein the quality detection of the agricultural products corresponding to the agricultural product types, the classification of the agricultural products according to the quality detection result, and the assignment of the electronic label corresponding to the agricultural products, comprises the following steps:
s21, placing the detected agricultural products on a conveyor belt of an object stage, and conveying the agricultural products to an image sensor at a set speed;
s22, utilizing the irradiation of the image sensor, imaging the detected agricultural product on the image sensor, and obtaining a three-dimensional image of the agricultural product;
s23, uploading the three-dimensional image to an image processor for preprocessing, calculating whether the detected agricultural products are qualified or not, and eliminating unqualified agricultural products.
4. The method for monitoring and managing commodity of warehouse commodity circulation based on big data as set forth in claim 3, wherein said uploading the three-dimensional stereo image to the image processor for preprocessing, and calculating whether the detected agricultural product is qualified, and rejecting the unqualified agricultural product comprises the steps of:
s231, determining three components of pixel gray levels in the three-dimensional stereoscopic image in an image processor, and adjusting the pixel gray levels of the three components so that the three pixel components are the same;
s232, carrying out gray scale processing on the pixel components by adopting a weighted average value to obtain a matched gray scale image;
s233, processing the gray level image by adopting an image processing technology, and judging whether the detected agricultural product is qualified or not.
5. The method for monitoring and managing commodity of warehouse commodity circulation based on big data as set forth in claim 4, wherein said processing the gray level image by using the image processing technique and judging whether the detected agricultural product is acceptable comprises the steps of:
s2331, constructing a gray level image into a gray level function set with pixel points;
s2332, dividing a set of points with discontinuous gray level functions in the gray level image into edges of the divided areas, and reserving areas with severe gray level variation of the image;
s2333, constructing a gradient algorithm, detecting the change of the gray level of the image, and dividing the region of the image;
s2334, regarding the gray level image as a two-dimensional discrete function, wherein the image gradient is the first derivative of the two-dimensional discrete function, and constructing a gradient coordinate;
s2335, comparing the divided areas with standard agricultural products to obtain a comparison result, and judging whether the agricultural products are qualified or not according to the comparison result.
6. The method for monitoring and managing commodity of a warehouse commodity circulation based on big data according to claim 5, wherein the expression of the gradient coordinates is:
the expression of the gradient amplitude is:
in the formula, G [ f (x, y) ] is gradient amplification of (x, y) pixel points, f (x, y) is a two-dimensional discrete function, and x, y is the pixel point in the gray level image.
7. The method for monitoring and managing commodity of a warehouse commodity circulation according to claim 1, wherein the steps of obtaining sales parameters of each agricultural product in commodity circulation and pertinently pricing the classified agricultural products according to the sales parameters comprise the following steps:
s41, calculating the demand rate of the agricultural product market according to the relation between the demand rate and the existing retail price of the agricultural product;
s42, recording purchasing information in the current order and the transportation cost of the agricultural products;
s43, pricing with different price according to the freshness grade of the agricultural products and the demands of the agricultural products with different freshness so as to meet the demands of different crowds.
8. The method for monitoring and managing commodities of a warehouse-in commodity flow commercial product based on big data according to claim 1, wherein the step of reading each electronic tag information by using a PFID reader-writer, comparing the actual warehouse-in information with the pre-warehouse-in information, and judging whether the actual warehouse-in information matches with the pre-warehouse-in information comprises the following steps:
s61, when an article arrives at a zone to be detected, a PFID reader-writer at a warehouse entry gate reads the novel electronic tag;
s62, the PFID reader automatically compares the actual warehouse-in information with the pre-warehouse-in information, and judges whether the electronic tag is consistent with the warehouse-in information according to the related logic;
s63, if errors occur, sending out voice prompts by the PFID reader-writer, and processing by staff of related departments;
and S64, if no error exists, distributing according to the pre-selected agricultural product storage area and the storage position.
9. The method for monitoring and managing commodity of warehouse commodity circulation according to claim 1, wherein after the warehouse entry, the data is uploaded to the database by the RFID reader, and the updating operation of the electronic tag information comprises the following steps:
s71, selecting a warehouse and a warehouse area to be checked, making a checking list, and generating a checking list;
s72, the information system controls the RFID reader-writer to start reading data through a wireless network;
s72, the RFID reader transmits the disk data to the information system through a wireless network;
s72, the information system calculates the difference between the statistical quantity and the inventory quantity of the goods in each goods space, and performs inventory adjustment management, inventory browsing, goods inventory distribution query and goods analysis in the goods space.
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