CN115730954A - E-commerce product logistics tracing analysis system based on big data - Google Patents
E-commerce product logistics tracing analysis system based on big data Download PDFInfo
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Abstract
The invention discloses a logistics tracing analysis system for electronic commerce products, which relates to the field of electronic commerce and is used for solving the problems that the existing logistics tracing analysis system for electronic commerce products can only trace the real-time position of the products in transportation, and customers and merchants can know the damage of the products only after the products reach the destination; through product outline area in the product X-ray photo after will adjusting and the product outline area size comparison and coincidence in the standard product X-ray photo compare, later overhauls through the maintainer, can the state of accurate judgement product to impel the trade company to in time make the solution, can give trade company and customer good online shopping experience, can standardize the management to the commodity circulation simultaneously, improve the quality of electronic commerce service when avoiding economic loss, promote the electronic commerce development.
Description
Technical Field
The invention relates to the field of electronic commerce, in particular to an electronic commerce product logistics tracing analysis system based on big data.
Background
At present, electronic commerce generally refers to a novel business operation mode in which, in wide commercial and trade activities worldwide, in an internet environment open to the internet, buyers and sellers indiscriminately perform various commercial and trade activities, and various commercial activities, transaction activities, financial activities, and related comprehensive service activities are implemented, such as online shopping by consumers, online transactions between merchants, and online electronic payments. With the rapid development of electronic commerce, the electronic commerce system not only includes the main connotation of shopping, but also includes subsidiary services such as logistics distribution and the like.
At present, the logistics method of electronic commerce mainly adopts a delivery mode of 'hand delivery', namely, a delivery person of a seller must directly deliver goods ordered by a customer to the customer or a receiver appointed by the customer according to appointed time and place. The general implementation process is as follows: after a customer orders goods on the network and is confirmed by a seller, ordering information is transferred to a goods distribution center, the goods are delivered to delivery personnel after being prepared, the delivery personnel firstly directly communicate with the customer according to an instant contact mode registered by the customer to appoint or verify the exact time and place of the delivered goods, then the delivery personnel arrive at the appointed place at the appointed time to search the customer or the appointed consignee, the consignee signs up, and the logistics process is finished.
The existing electronic commerce product logistics tracing analysis system can only trace back the real-time position of a product in transportation to know the logistics location and the expected delivery arrival time, but the package is thrown away and thrown away or extrusion collision exists in the product logistics transportation process, so that the product is damaged in the transportation process, and a customer and a merchant can know the product damage only after the product reaches the destination, thereby influencing the mood of the customer, influencing the planning and arrangement of the customer and causing economic loss to the merchant.
Therefore, a big data-based e-commerce product logistics traceability analysis system is needed to solve the above problems.
Disclosure of Invention
In order to overcome the technical problems, the invention aims to provide an electronic commerce product logistics traceability analysis system based on big data, which comprises the following steps: the method comprises the steps of comparing the product outline area in an adjusted product X-ray photo with the product outline area in a standard product X-ray photo, preliminarily judging that a product is seriously deformed if the difference is too large, further judging if the difference is not too large, carrying out coincidence comparison on the product outline area in the zoomed product X-ray photo and the standard product area, generating an area coincidence rate, preliminarily judging that the product is broken if the area coincidence rate does not exceed a preset area coincidence rate, and then sending the adjusted product X-ray photo to a merchant for further confirmation, thereby accurately judging whether the product is damaged or not, and making a solution in time.
The purpose of the invention can be realized by the following technical scheme:
a big data-based electronic commerce product logistics tracing analysis system comprises a processor and an image adjusting module;
the processor is used for calculating according to the express bill number photo to obtain a scaling coefficient, sending the scaling coefficient to the image adjusting module, receiving the zoomed product X-ray photo fed back by the image adjusting module, then comparing the zoomed product X-ray photo with the standard product X-ray photo, judging the product, generating a product abnormal signal, and then sending the product abnormal signal to the merchant terminal and the user terminal, wherein the specific process is as follows:
the method comprises the following steps: the processor marks the received first express order number photo as a standard express order number photo, marks the received first product X-ray photo as a standard product X-ray photo, marks the area of the standard express order number photo as a standard comparison area, and marks the product outline area in the standard product X-ray photo as a standard product area S 0 The processor compares the area of the received express bill number photo with a standard comparison area to obtain a scaling factor, and the processor sends the scaling factor to the image adjusting module; the scaling factor means that the size of the standard express bill number photo is fixed, and then the subsequently received express bill number photo is enlarged or reduced to be overlapped with the standard express bill number photo, so that the enlargement or reduction times, namely the scaling factor, are obtained;
step two: the image adjusting module receives the scaling factor, scales the received product X-ray photo according to the scaling factor, and then sends the scaled product X-ray photo to the processor;
step three: the processor receives the scaled product radiograph and marks the product outline area in the scaled product radiograph as S i The product outline area S in the zoomed product X-ray picture i And standard product area S 0 Comparing the sizes of the two signals, and generating a product abnormal signal after judging;
step four: the processor sends the product abnormal signal and the zoomed product X-ray picture to a merchant terminal and a user terminal;
the image adjusting module is used for adjusting the subsequently acquired product X-ray photos according to the scaling coefficient to obtain the scaled product X-ray photos and sending the scaled product X-ray photos to the processor.
As a further scheme of the invention: the processor determination process in step three is specifically as follows:
if it is
Generating a product abnormal signal, wherein both alpha and beta are preset proportionality coefficients, beta is more than 1 and more than alpha and more than 0, and alpha + beta =2.177, taking beta =1.204 and alpha =0.973;
indicates the product outline area S i And standard product area S 0 The size of (2) is too large, which indicates that the product is damaged;
if S i ∈(αS 0 ，βS 0 ) Then, generate deformation and judge the signal, the product profile area in the product X-ray photo after the treater will zoom carries out the coincidence comparison with the product profile area in the standard product X-ray photo, and the area coincidence ratio Sc is generated, compares area coincidence ratio Sc and predetermines area coincidence ratio Sy:
if Sc is larger than Sy, generating a normal signal of the product;
if Sc is less than or equal to Sy, generating a product abnormal signal; if S i ∈(αS 0 ，βS 0 ) Then the product outline area S is represented i And standard product area S 0 If Sc is larger than Sy, it is indicated that the area coincidence rate Sc is larger than a preset value, the product is further determined not to be seriously deformed, and the product is not damaged, and if Sc is smaller than or equal to Sy, it is indicated that the product is seriously deformed, and the product is damaged.
As a further scheme of the invention: the user terminal is used for acquiring order information generated by ordering of a user, the user terminal sends the order information to the processor, then the processor sends the order information to the merchant terminal, and the merchant terminal is used for receiving the order information from the processor and printing an express bill according to the order information; the order information comprises a name, a telephone number and a receiving address; the merchant terminal and the user terminal are further used for determining whether the product is damaged or not according to the received product abnormal signal, the zoomed product X-ray photo, the overhaul result and the overhaul video.
As a further scheme of the invention: the system is characterized by further comprising a data acquisition module, wherein the data acquisition module is used for scanning the express bill, acquiring logistics information and sending the logistics information to the processor, the merchant terminal and the user terminal, and the logistics information comprises the express bill number and a real-time address where the express bill number is located when the express bill number is acquired.
As a further scheme of the invention: still include the image acquisition module, the image acquisition module includes that first picture is adopted the unit and the unit is adopted to the second picture, the image acquisition module is used for gathering express delivery number photo and product X-ray photo to send express delivery number photo and product X-ray photo to the image regulation module, the image regulation module sends express delivery number photo and first product X-ray photo to the treater, and concrete process is as follows:
the first image acquisition unit shoots an express bill to obtain an express bill number photo, and sends the express bill number photo to the image regulation module, and the image regulation module sends the express bill number photo to the processor;
the second image acquisition unit is used for photographing the inside of the express box by utilizing X-rays to acquire a photo of the inside of the express box, marking the photo of the inside of the express box as a product X-ray photo, sending the product X-ray photo to the image adjusting module, and sending the first product X-ray photo to the processor after the image adjusting module receives the product X-ray photo.
As a further scheme of the invention: the quality inspection system further comprises a quality inspection selection module, wherein the quality inspection selection module is used for obtaining a selected maintenance point through analysis after receiving a quality inspection selection instruction, and sending the selected maintenance point to the processor, and the quality inspection selection module comprises the following specific steps:
the quality inspection selection module starts to collect the positions of a plurality of inspection points after receiving a quality inspection selection instruction, sequentially marks the inspection points as Jd, d =1 and 2 … … m, wherein m is a natural number, obtains routes between a transit point where an express box is located and the inspection points, sequentially marks the distances between the transit point and the inspection points as point transport distances JZd, obtains routes between a transit point where the express box is located and a merchant, marks the distances between the transit point and the customer as point quotient distances JSd, obtains routes between the transit point where the express box is located and the customer, marks the distances as point passenger distances JKd, substitutes values of the point transport distances JZd, the point quotient distances JSd and the point passenger distances 3264 zxft Into a formula YXd + q3 × 3638 to obtain values 3224 zxft, substitutes the values into 3224 zxft 3224, preferably processes the inspection points as point selection coefficients 3724, and sends the inspection points as optimal inspection point selection coefficients, wherein the optimal inspection points are marked as point selection coefficients 3224 and the optimal inspection point selection coefficient.
As a further scheme of the invention: a working process of an electronic commerce product logistics traceability analysis system based on big data comprises the following steps:
the method comprises the following steps: a user uses a user terminal to place an order, the user terminal sends order information generated by placing the order to a processor, and then the processor sends the order information to a merchant terminal; the order information comprises a name, a telephone number and a receiving address;
step two: the method comprises the steps that a merchant selects products according to order information, a first image acquisition unit is used for acquiring product photos, then an image acquisition module sends the product photos to a user terminal, the user terminal receives the product photos and sends a product confirmation instruction to a processor after the user confirms that the goods are correct, the processor sends the product confirmation instruction to the merchant terminal after receiving the product confirmation instruction, and the merchant terminal reminds the merchant to package the products after receiving the confirmation instruction and prints express orders according to order information and attaches the express orders to an express box;
step three: scanning an express bill, acquiring logistics information by a data acquisition module, and sending the logistics information to a processor, a merchant terminal and a user terminal by the data acquisition module;
step four: the first image acquisition unit shoots an express bill to obtain an express bill number photo, and sends the express bill number photo to the image regulation module, and the image regulation module sends the express bill number photo to the processor; the second image acquisition unit acquires the pictures inside the express box by using X-rays to obtain product X-ray pictures, the second image acquisition unit sends the product X-ray pictures to the image adjusting module, and the image adjusting module sends the first product X-ray pictures to the processor;
step five: the processor marks the received first express order number photo as a standard express order number photo, marks the received first product X-ray photo as a standard product X-ray photo, marks the area of the standard express order number photo as a standard comparison area, and marks the product outline area in the standard product X-ray photo as a standard product area S 0 The processor compares the area of the received express bill number photo with a standard comparison area to obtain a scaling coefficient, and sends the scaling coefficient to the image adjusting module;
step six: the image adjusting module receives the scaling coefficient, scales the received product X-ray photo according to the scaling coefficient, and then sends the scaled product X-ray photo to the processor;
step seven: the processor receives the scaled product radiograph and marks the product outline area in the scaled product radiograph as S i The product outline area S in the zoomed product X-ray picture i And standard product area S 0 Is compared with the size of (1) if
Generating a product abnormal signal, wherein alpha and beta are preset proportionality coefficients, beta is more than 1 and more than alpha and more than 0, and alpha + beta =2.177; if S i ∈(αS 0 ，βS 0 ) Generating a deformation judgment signal, and performing coincidence comparison on the product contour area in the zoomed product X-ray picture and the product contour area in the standard product X-ray picture by using the processor to generate an area coincidence rate Sc; comparing the area coincidence rate Sc with a preset area coincidence rate: if Sc is larger than Sy, generating a normal signal of the product; if Sc is less than or equal to Sy, generating a product abnormal signal; the processor sends the product abnormal signal and the zoomed product X-ray picture to a merchant terminal and a user terminal;
step eight: the merchant terminal and the user terminal receive the product abnormal signal and then check the zoomed product X-ray photo to determine whether the product is damaged, if so, the user and the merchant negotiate, the merchant selects to withdraw the product and simultaneously re-deliver the product or continue transportation, and if not, the merchant terminal generates a quality inspection selection instruction and sends the quality inspection selection instruction to the quality inspection selection module;
step nine: the quality inspection selection module starts to collect the positions of a plurality of inspection points after receiving a quality inspection selection instruction, sequentially marks the positions as Jd, d =1 and 2 … … m as natural numbers, obtains routes between a transfer point where the express box is located and the plurality of inspection points, sequentially marks the distances between the transfer point and the plurality of inspection points as point transport distances JZd, obtains a route between the transfer point where the express box is located and a merchant, marks the distances between the transfer point and the merchant as point merchant distances JSd, obtains a route between the transfer point where the express box is located and a customer, and marks the distances between the transfer point and the customer as point-customer distances JKd, substituting numerical values of a point transport distance JZd, a point quotient distance JSd and a point passenger distance JKd into a formula to obtain a YXd = q1 × JZd + q2 × JSd + q3 × JKd preferred value YXd, wherein q1, q2 and q3 are preset weight coefficients, q1+ q2+ q3=1, q1=0.68, q2=0.21 and q3=0.11, marking a selected overhaul point corresponding to the maximum preferred value YXd as the selected overhaul point, sending the selected overhaul point to a processor, changing order information according to information of the selected overhaul point after the processor receives the selected overhaul point, and then transporting an express box to the selected overhaul point;
step ten: the express box reaches and selects after the maintenance point, the maintainer unpacks the express box apart and overhauls the product, judge whether the product is damaged, and shoot the video, later will overhaul result and maintenance video transmission to the treater through overhauing the terminal, and transmit to trade company terminal and user terminal, if confirm that the product is damaged, the user passes through the negotiation with the trade company, the trade company chooses to withdraw the product and deliver again or continue the transportation at the same time, if confirm that the product is not damaged, the user passes through the negotiation with the trade company, the trade company chooses to continue the transportation, withdraw or from selecting the maintenance point and delivering to other customers.
The invention has the beneficial effects that:
the invention relates to an electronic commerce product logistics tracing analysis system based on big data, which collects an express item number photo and a product X-ray photo through an image collection module, adjusts the product X-ray photo by arranging a first image collection unit and a second image collection unit at the same position, uses the express item number photo as a reference, synchronously obtains the change of the product X-ray photo according to the change of the express item number photo, compares the product outline area in the adjusted product X-ray photo with the product outline area in a standard product X-ray photo, preliminarily judges that the product is seriously deformed if the difference is too large, generates a product abnormal signal if the difference is not large, further judges whether the product outline area in the zoomed product X-ray photo is overlapped with the standard product area and generates an area coincidence rate, preliminarily judges that the product is cracked if the area coincidence rate does not exceed the preset area coincidence rate, generates a product abnormal signal if the product is cracked, then sends the adjusted product X-ray photo to a merchant for further confirmation, thereby accurately judges whether the product is damaged, and can be timely determined that the product is damaged and the merchant can receive corresponding damage of the commodity, thereby avoiding the real-time acquisition of the electronic commerce product and the commodity management system can determine the damage of the merchant can be carried out when the merchant can receive the commodity in real-time, and the commodity management system can be carried out the damage, the system can provide good online shopping experience for merchants and customers, and promote the development of electronic commerce;
whether the uncertain product of trade company damaged the condition can be examined and repaired through quality control selection module at the suitable maintenance point of selection under the comprehensive condition, later according to maintainer's the maintenance result and overhauld the condition of video to the product result and carried out accurate judgement, avoided the condition that misjudges appears in the product state, lead to the increase of logistics cost, cause economic loss, further improvement electronic commerce service's quality promotes electronic commerce development.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of a big data-based e-commerce product logistics traceability analysis system in the present invention.
FIG. 2 is a schematic diagram of a quality inspection selection module according to the present invention.
Fig. 3 is a flowchart of the work flow of the big data-based e-commerce product logistics traceability analysis system in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
referring to fig. 1-3, the present embodiment is a big data-based system for tracing and analyzing the logistics of electronic commerce products, which includes a user terminal, a merchant terminal, and an overhaul terminal;
the system comprises a user terminal, a processor and a merchant terminal, wherein the user terminal is used for acquiring order information generated by order placement of a user, sending the order information to the processor by the user terminal, and then sending the order information to the merchant terminal by the processor;
the merchant terminal is used for receiving the order information from the processor and printing the express bill according to the order information; the order information comprises a name, a telephone number and a receiving address;
the overhaul terminal is used for enabling an overhaul worker to overhaul a product which is uncertain whether damage occurs or not, and sending an overhaul result and an overhaul video to the user terminal and the merchant terminal;
the merchant terminal and the user terminal are also used for determining whether the product is damaged or not according to the received product abnormal signal, the zoomed product X-ray photo, the overhaul result and the overhaul video, and the merchant selects to withdraw the product and re-deliver the product or continue to transport the product after negotiation between the user and the merchant.
Example 2:
referring to fig. 1 to 3, the present embodiment is a big data-based system for tracing and analyzing logistics of electronic commerce products, which includes a processor, a data acquisition module, an image adjustment module, an image acquisition module, and a quality inspection selection module; the image acquisition module comprises a first image acquisition unit and a second image acquisition unit;
the data acquisition module comprises an express scanning gun, scans an express bill through the express scanning gun, acquires logistics information and sends the logistics information to the processor, the merchant terminal and the user terminal, wherein the logistics information comprises an express bill number and a real-time address where the express bill number is obtained;
the image acquisition module is used for acquiring an express sheet number photo and a product X-ray photo, and sending the express sheet number photo and the product X-ray photo to the image adjusting module, and the image adjusting module sends the express sheet number photo and a first product X-ray photo to the processor, and the specific process is as follows:
the first image acquisition unit shoots an express bill to obtain an express bill number photo, and sends the express bill number photo to the image regulation module, and the image regulation module sends the express bill number photo to the processor;
the second image acquisition unit is used for photographing the inside of the express box by utilizing X-rays to obtain a photo of the inside of the express box, marking the photo of the inside of the express box as a product X-ray photo, sending the product X-ray photo to the image adjusting module, and sending the first product X-ray photo to the processor after the image adjusting module receives the product X-ray photo;
the processor is used for calculating according to the express bill number photo to obtain a scaling coefficient, sending the scaling coefficient to the image adjusting module, receiving the scaled product X-ray photo fed back by the image adjusting module, comparing the scaled product X-ray photo with a standard product X-ray photo, judging the product, generating a product abnormal signal, and sending the product abnormal signal to a merchant terminal and a user terminal, wherein the specific process is as follows:
the processor marks the received first express bill number photo as a standard expressThe method comprises the steps of taking a single-number photo, marking a received first product X-ray photo as a standard product X-ray photo, marking the area of the standard express single-number photo as a standard comparison area by a processor, and marking the product outline area in the standard product X-ray photo as a standard product area S 0 The processor compares the area of the received express bill number photo with a standard comparison area to obtain a scaling coefficient, and sends the scaling coefficient to the image adjusting module;
the image adjusting module receives the scaling coefficient, scales the received product X-ray photo according to the scaling coefficient, and then sends the scaled product X-ray photo to the processor;
the processor receives the scaled product radiograph and marks the product outline area in the scaled product radiograph as S i The product outline area S in the zoomed product X-ray picture i And standard product area S 0 The size of (c) is compared:
if it is
Generating a product abnormal signal, wherein both alpha and beta are preset proportionality coefficients, beta is more than 1 and more than alpha and more than 0, and alpha + beta =2.177, taking beta =1.204 and alpha =0.973;
if S i ∈(αS 0 ，βS 0 ) Then generate deformation and judge the signal, the product profile area in the product X-ray photo after the treater will be zoomed carries out the coincidence with the product profile area in the standard product X-ray photo and compares, and generate area coincidence rate Sc, compares area coincidence rate Sc and predetermine area coincidence rate Sy:
if Sc is greater than Sy, generating a normal signal of the product;
if Sc is less than or equal to Sy, generating a product abnormal signal;
the processor sends the product abnormal signal and the zoomed product X-ray photo to a merchant terminal and a user terminal;
the image adjusting module is used for adjusting the subsequently acquired product X-ray photos according to the scaling coefficient to obtain the scaled product X-ray photos and sending the scaled product X-ray photos to the processor;
the quality inspection selection module is used for obtaining a selected maintenance point through analysis after receiving a quality inspection selection instruction and sending the selected maintenance point to the processor, and the quality inspection selection module specifically comprises the following steps:
the quality inspection selection module starts to collect the positions of a plurality of inspection points after receiving a quality inspection selection instruction, sequentially marks the inspection points as Jd, d =1 and 2 … … m, wherein m is a natural number, obtains routes between a transit point where an express box is located and the inspection points, sequentially marks the distances between the transit point and the inspection points as point transport distances JZd, obtains routes between a transit point where the express box is located and a merchant, marks the distances between the transit point and the customer as point quotient distances JSd, obtains routes between the transit point where the express box is located and the customer, marks the distances as point passenger distances JKd, substitutes values of the point transport distances JZd, the point quotient distances JSd and the point passenger distances 3264 zxft Into a formula YXd + q3 × 3638 to obtain values 3224 zxft, substitutes the values into 3224 zxft 3224, preferably processes the inspection points as point selection coefficients 3724, and sends the inspection points as optimal inspection point selection coefficients, wherein the optimal inspection points are marked as point selection coefficients 3224 and the optimal inspection point selection coefficient.
Example 3:
referring to fig. 1 to 3, in combination with embodiment 1 and embodiment 2, this embodiment is a working process of a big data-based electronic commerce product logistics tracing analysis system, and includes the following steps:
the method comprises the following steps: a user uses a user terminal to place an order, the user terminal sends order information generated by placing the order to a processor, and then the processor sends the order information to a merchant terminal; the order information comprises a name, a telephone number and a receiving address;
step two: the method comprises the steps that a merchant selects products according to order information, a first image acquisition unit is used for acquiring product photos, then an image acquisition module sends the product photos to a user terminal, the user terminal receives the product photos and sends a product confirmation instruction to a processor after the user confirms that the goods are correct, the processor sends the product confirmation instruction to the merchant terminal after receiving the product confirmation instruction, and the merchant terminal reminds the merchant to package the products after receiving the confirmation instruction, prints express orders according to order information and attaches the express orders to an express box;
step three: scanning an express bill, acquiring logistics information by a data acquisition module, and sending the logistics information to a processor, a merchant terminal and a user terminal by the data acquisition module;
step four: the first image acquisition unit shoots an express bill to obtain an express bill number photo, and sends the express bill number photo to the image regulation module, and the image regulation module sends the express bill number photo to the processor; the second image acquisition unit acquires the pictures in the express box by using X-rays to obtain X-ray pictures of the product, the second image acquisition unit sends the X-ray pictures of the product to the image adjusting module, and the image adjusting module sends the X-ray pictures of the first product to the processor;
step five: the processor marks the received first express order number photo as a standard express order number photo, marks the received first product X-ray photo as a standard product X-ray photo, marks the area of the standard express order number photo as a standard comparison area, and marks the product outline area in the standard product X-ray photo as a standard product area S 0 The processor compares the area of the received express bill number photo with a standard comparison area to obtain a scaling coefficient, and sends the scaling coefficient to the image adjusting module;
step six: the image adjusting module receives the scaling factor, scales the received product X-ray photo according to the scaling factor, and then sends the scaled product X-ray photo to the processor;
step seven: the processor receives the scaled product radiograph and marks the product outline area in the scaled product radiograph as S i The product outline area S in the zoomed product X-ray picture i And standard product area S 0 Is compared with the size of (1) if
Generating a product abnormal signal, wherein alpha and beta are preset proportionality coefficients, beta is more than 1 and more than alpha and more than 0, and alpha + beta =2.177; if S i ∈(αS 0 ，βS 0 ) Generating a deformation judgment signal, and carrying out coincidence comparison on the product outline area in the zoomed product X-ray photo and the product outline area in the standard product X-ray photo by the processor to generate an area coincidence rate Sc; comparing the area coincidence rate Sc with a preset area coincidence rate: if Sc is greater than Sy, generating a normal signal of the product; if Sc is less than or equal to Sy, generating a product abnormal signal; the processor sends the product abnormal signal and the zoomed product X-ray photo to a merchant terminal and a user terminal;
step eight: the merchant terminal and the user terminal receive the product abnormal signal and then check the zoomed product X-ray photo to determine whether the product is damaged, if so, the user and the merchant negotiate, the merchant selects to withdraw the product and simultaneously re-deliver the product or continue transportation, and if not, the merchant terminal generates a quality inspection selection instruction and sends the quality inspection selection instruction to the quality inspection selection module;
step nine: the quality inspection selection module starts to collect the positions of a plurality of inspection points after receiving a quality inspection selection instruction, sequentially marks the positions as Jd, d =1 and 2 … … m as natural numbers, obtains routes between a transit point where the express box is located and the plurality of inspection points, sequentially marks the distances between the transit point and the plurality of inspection points as point-transport distances JZd, obtains routes between the transit point where the express box is located and a merchant, marks the distances between the transit point and the merchant as point-merchant distances JSd, obtains routes between the transit point where the express box is located and a customer, and marks the distances between the transit point and the customer as point-customer distances JKd, substituting numerical values of a point transport distance JZd, a point quotient distance JSd and a point passenger distance JKd into a formula YXd = q1 × JZd + q2 × JSd + q3 × JKd to obtain a preferred value YXd, wherein q1, q2 and q3 are preset weight coefficients, q1+ q2+ q3=1, taking q1=0.68, q2=0.21 and q3=0.11, marking a maintenance point corresponding to the largest preferred value YXd as a selected maintenance point, sending the selected maintenance point to a processor, changing order information according to information of the selected maintenance point after the processor receives the selected maintenance point, and then transporting an express box to the selected maintenance point;
step ten: the express box reaches and selects after the maintenance point, the maintainer unpacks the express box apart and overhauls the product, judge whether the product is damaged, and shoot the video, later will overhaul result and maintenance video transmission to the treater through overhauing the terminal, and transmit to trade company terminal and user terminal, if confirm that the product is damaged, the user passes through the negotiation with the trade company, the trade company chooses to withdraw the product and deliver again or continue the transportation at the same time, if confirm that the product is not damaged, the user passes through the negotiation with the trade company, the trade company chooses to continue the transportation, withdraw or from selecting the maintenance point and delivering to other customers.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is illustrative and explanatory only and is not intended to be exhaustive or to limit the invention to the precise embodiments described, and various modifications, additions, and substitutions may be made by those skilled in the art without departing from the scope of the invention or exceeding the scope of the claims.
Claims (6)
1. A big data-based electronic commerce product logistics tracing analysis system is characterized by comprising a processor and an image adjusting module;
the processor is used for calculating according to the express bill number photo to obtain a scaling coefficient, sending the scaling coefficient to the image adjusting module, receiving the zoomed product X-ray photo fed back by the image adjusting module, then comparing the zoomed product X-ray photo with the standard product X-ray photo, judging the product, generating a product abnormal signal, and then sending the product abnormal signal to the merchant terminal and the user terminal, wherein the specific process is as follows:
the method comprises the following steps: the processor marks the received first express waybill number photo as a standard express waybill number photoMarking the received first product X-ray photo as a standard product X-ray photo, marking the area of the standard express bill number photo as a standard comparison area by the processor, and marking the product outline area in the standard product X-ray photo as a standard product area S 0 The processor compares the area of the received express bill number photo with a standard comparison area to obtain a scaling coefficient, and sends the scaling coefficient to the image adjusting module;
step two: the image adjusting module receives the scaling coefficient, scales the received product X-ray photo according to the scaling coefficient, and then sends the scaled product X-ray photo to the processor;
step three: the processor receives the scaled product radiograph and marks the product outline area in the scaled product radiograph as S i The product outline area S in the zoomed product X-ray picture i And standard product area S 0 Comparing the sizes of the two signals, and generating a product abnormal signal after judging;
step four: the processor sends the product abnormal signal and the zoomed product X-ray photo to a merchant terminal and a user terminal;
the image adjusting module is used for adjusting the subsequently acquired product X-ray photos according to the scaling coefficient to obtain the scaled product X-ray photos and sending the scaled product X-ray photos to the processor.
2. The system of claim 1, wherein the processor determines the following steps in step three:
if it is
Generating a product abnormal signal, wherein alpha and beta are preset proportionality coefficients, beta is more than 1 and more than alpha and more than 0, and alpha + beta =2.177;
if S i ∈(αS 0 ，βS 0 ) Generating a deformation judgment signal, and irradiating the scaled product with X-ray by a processorProduct profile area in the piece and the product profile area in the standard product X-ray photo coincide and compare to generate area coincidence rate Sc, compare area coincidence rate Sc and predetermine area coincidence rate Sy:
if Sc is larger than Sy, generating a normal signal of the product;
and if the Sc is less than or equal to Sy, generating a product abnormal signal.
3. The big-data-based electronic commerce product logistics traceability analysis system as claimed in claim 1, wherein the user terminal is configured to obtain order information generated by order placement of the user, the user terminal sends the order information to the processor, and then the processor sends the order information to the merchant terminal, and the merchant terminal is configured to receive the order information from the processor and print an express delivery order according to the order information; the merchant terminal and the user terminal are further used for determining whether the product is damaged or not according to the received product abnormal signal, the zoomed product X-ray picture, the overhaul result and the overhaul video.
4. The system of claim 3, further comprising a data collection module, wherein the data collection module is configured to scan the courier receipt, collect the logistics information, and send the logistics information to the processor, the merchant terminal, and the user terminal.
5. The big-data-based electronic commerce product logistics traceability analysis system as claimed in claim 4, further comprising an image acquisition module, wherein the image acquisition module comprises a first image acquisition unit and a second image acquisition unit, the image acquisition module is configured to acquire the delivery order number photo and the product X-ray photo and send the delivery order number photo and the product X-ray photo to the image adjustment module, and the image adjustment module sends the delivery order number photo and the first product X-ray photo to the processor, and the specific process is as follows:
the first image acquisition unit shoots an express bill to obtain an express bill number photo, and sends the express bill number photo to the image regulation module, and the image regulation module sends the express bill number photo to the processor;
the second image acquisition unit is used for photographing the inside of the express box by utilizing X-rays to acquire a photo of the inside of the express box, marking the photo of the inside of the express box as a product X-ray photo, sending the product X-ray photo to the image adjusting module, and sending the first product X-ray photo to the processor after the image adjusting module receives the product X-ray photo.
6. The big-data-based electronic commerce product logistics traceability analysis system as claimed in claim 5, further comprising a quality inspection selection module, wherein the quality inspection selection module is configured to obtain a selected inspection point through analysis after receiving a quality inspection selection instruction, and send the selected inspection point to the processor, and the specific steps are as follows:
the quality inspection selection module starts to collect the positions of a plurality of inspection points after receiving a quality inspection selection instruction, sequentially marks the inspection points as Jd, d =1 and 2 … … m, wherein m is a natural number, obtains routes between a transit point where an express box is located and the inspection points, sequentially marks the distances between the transit point and the inspection points as point transport distance JZd, obtains routes between the transit point where the express box is located and a merchant, marks the distances between the transit point and the customer as point quotient distance JSd, obtains routes between the transit point where the express box is located and the customer, marks the distances as point passenger distance JKd, obtains a preferred value YXd by analyzing the point transport distance JZd, the point quotient distance JSd and the point passenger distance JKd, marks the inspection point corresponding to the maximum preferred value YXd as a selected inspection point, and sends the selected inspection point to the processor 3234.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117172796A (en) * | 2023-08-07 | 2023-12-05 | 北京智慧大王科技有限公司 | Big data electronic commerce management system |
| CN117273579A (en) * | 2023-08-16 | 2023-12-22 | 江苏多飞网络科技有限公司 | Big data-based electronic commerce commodity traceability management system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117172796A (en) * | 2023-08-07 | 2023-12-05 | 北京智慧大王科技有限公司 | Big data electronic commerce management system |
| CN117273579A (en) * | 2023-08-16 | 2023-12-22 | 江苏多飞网络科技有限公司 | Big data-based electronic commerce commodity traceability management system |
| CN117273579B (en) * | 2023-08-16 | 2024-02-09 | 江苏多飞网络科技有限公司 | Big data-based electronic commerce commodity traceability management system |
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