CN113083693A - Intelligent sorting, regulating and controlling management system of intelligent logistics center based on machine vision and artificial intelligence - Google Patents

Intelligent sorting, regulating and controlling management system of intelligent logistics center based on machine vision and artificial intelligence Download PDF

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CN113083693A
CN113083693A CN202110321891.0A CN202110321891A CN113083693A CN 113083693 A CN113083693 A CN 113083693A CN 202110321891 A CN202110321891 A CN 202110321891A CN 113083693 A CN113083693 A CN 113083693A
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王亮
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Wuhan Wisdom Xiaoqi Technology Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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Abstract

The invention discloses an intelligent sorting, regulating and managing system of an intelligent logistics center based on machine vision and artificial intelligence. The system comprises a commodity information acquisition module, a placement area commodity quantity counting module, a commodity basic parameter detection module, a commodity weight detection module, a delivery automobile parameter detection module, a delivery automobile load amount pre-estimation module, a processing server, a database and a remote control center, wherein the problem that the rapidity and the accuracy of the sorting of commodities cannot be guaranteed when the commodities are classified is solved by comprehensively detecting and analyzing basic parameters corresponding to the sorted commodities in each sorted commodity placement area, basic parameters corresponding to the delivery automobile in each sorted commodity placement area and the pre-estimated load amount of the delivery automobile corresponding to each sorted commodity placement area, meanwhile, the commodity delivery efficiency is effectively improved, and intelligent sorting and efficient regulation and control management of the commodities are realized.

Description

Intelligent sorting, regulating and controlling management system of intelligent logistics center based on machine vision and artificial intelligence
Technical Field
The invention belongs to the technical field of logistics sorting regulation and control management, and relates to an intelligent logistics center intelligent sorting regulation and control management system based on machine vision and artificial intelligence.
Background
Water conservancy is with the arrival of electricity merchant's era, and the shopping mode of many contemporary people has changed from off-line shopping to on-line shopping, and the change of shopping mode has promoted the development of logistics industry, and the efficiency of express delivery commodity circulation has directly been influenced in the letter sorting of commodity, therefore, is very necessary when managing to the commodity letter sorting regulation and control.
Present commodity letter sorting mode divide into total manual sorting and half manual sorting mode, total manual sorting mainly sorts through whole manual work of personnel, sort through personnel's auxiliary machine when half personnel's letter sorting is grabbed, these two kinds of letter sorting work all carry out simple extraction and classification to commodity, do not carry out the analysis according to the parameter of commodity self, unable effectual letter sorting efficiency and the delivery efficiency that promotes commodity, therefore, present commodity letter sorting mode has still existed certain drawback, on the one hand, present commodity letter sorting efficiency receives the influence of letter sorting personnel self proficiency, can't ensure the rapidity and the accuracy of commodity letter sorting when categorised, on the other hand does not combine the basic parameter of delivery car to carry out the analysis, and then can't effectual promotion letter sorting commodity go out warehouse efficiency.
Disclosure of Invention
In view of the above, in order to solve the problems in the background art, an intelligent logistics center intelligent sorting regulation and control management system based on machine vision and artificial intelligence for commodity sorting efficiency is provided, so that intelligent sorting and efficient regulation and control management of commodities are realized;
the purpose of the invention can be realized by the following technical scheme:
the invention provides an intelligent sorting regulation and control management system of an intelligent logistics center based on machine vision and artificial intelligence, which comprises: the system comprises a commodity information acquisition module, a placement area commodity quantity counting module, a commodity basic parameter detection module, a commodity weight detection module, a delivery automobile parameter detection module, a delivery automobile load amount pre-estimation module, a processing server, a database and a remote control center;
the processing server is respectively connected with a commodity quantity counting module, a commodity weight detection module, a delivery automobile loading capacity pre-estimation module and a database in a placement area, the delivery automobile loading capacity pre-estimation module is respectively connected with a delivery automobile parameter detection module, a commodity basic parameter detection module and a remote control center, and the placement area acquisition module is respectively connected with a commodity information acquisition module and a commodity quantity counting module in the placement area;
the commodity information acquisition module is used for scanning a bar code of a commodity through a scanner when a worker sorts the commodity, and further acquiring information corresponding to the commodity, wherein the commodity information comprises a commodity category and a commodity harvesting address;
the placement area acquisition module is used for acquiring position placement areas corresponding to the sorted commodities, marking the position placement areas corresponding to the sorted commodities as sorted commodity placement areas and further acquiring the number of the sorted commodity placement areas corresponding to the warehouse, wherein the sorted commodity placement areas correspond to the cities where the goods receiving addresses corresponding to the sorted commodities are located one by one, and further numbering the sorted commodity placement areas corresponding to the warehouse according to a preset sequence, wherein the marks are 1,2, a.
The commodity quantity counting module in the placement area is used for counting the quantity of sorted commodities in each sorted commodity placement area in the collection time period, comparing and screening the harvest address of each sorted commodity according to the harvest address corresponding to each sorted commodity, further counting the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, further acquiring the quantity of the sorted commodities corresponding to each sorted commodity placement area in the collection time period according to the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, numbering the sorted commodities corresponding to the sorted commodity placement areas in the collection time period according to a preset sequence, sequentially marking the sorted commodities as 1,2, u, v, and further constructing a sorted commodity quantity set S (S1, s2.. Sj.. Sm), Sj represents the number of sorted goods corresponding to the jth sorted goods placement region in the collection time period, and sends the collection of the number of sorted goods in each placement region in the collection time period to the processing server;
the commodity weight detection module comprises a plurality of pressure sensors which are respectively installed in each sorted commodity placing area and used for detecting the weight of each sorted commodity in each sorted commodity placing area in the acquisition time period, further acquiring the weight corresponding to each sorted commodity in each sorted commodity placing area in the acquisition time period, and further constructing each sorted commodity weight set in each sorted commodity placing area in the acquisition time periodZ in combinationt(Zt1，Zt2，...Ztj,...Ztm),Ztj represents the weight corresponding to the tth sorted goods in the jth sorted goods placement area in the acquisition time period, t represents the serial number of the sorted goods in each sorted goods placement area, and t is 1,2,. u,. v, so that the weight set of each sorted goods in each sorted goods placement area in the acquisition time period is sent to the processing server;
the commodity basic parameter detection module comprises a plurality of parameter detection devices which are respectively installed inside each sorted commodity placing area and used for detecting the basic parameters of each sorted commodity in each sorted commodity placing area in the acquisition time period, and then a three-dimensional laser scanner in the parameter detection devices is used for scanning and shooting each sorted commodity in each sorted commodity placing area in the acquisition time period, so that the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area in the acquisition time period are obtained, the length, the width and the height corresponding to each sorted commodity are respectively recorded as a, b and c, and then each sorted commodity basic parameter set T is constructede t(Te t1,Te t2,...Te tj,...Te tm)，Te tj represents the e-th parameter corresponding to the t-th sorted commodity in the jth sorted commodity placement area in the acquisition time period, e represents the sorted commodity parameter, and e is a, b, c, a, b and c respectively represent the length, width and height corresponding to the sorted commodity, so that the constructed basic parameter set of each sorted commodity is sent to the distribution automobile load estimation module;
the distribution automobile parameter detection module is used for detecting parameters of distribution automobiles corresponding to the sorted commodities in each sorted commodity placement area, and further acquiring parameters of the distribution automobiles corresponding to each sorted commodity placement area of the warehouse, wherein the distribution automobile parameters comprise the length, the width and the height of a distribution automobile loading compartment corresponding to each sorted commodity placement area, and further constructing a distribution automobile parameter set Pq(Pq1,Pq2,...Pqj,...Pqm)，Pqj indicates that j is the corresponding of the jth sorted-article placing areaThe q-th parameter of the delivery automobile, wherein q represents the parameter of the delivery automobile, and q is equal to a ', b', c ', a', b 'and c' which respectively represent the length, the width and the height of a loading compartment of the delivery automobile corresponding to each sorted goods placement area, and sends each delivery automobile parameter set to a delivery automobile loading amount estimation module;
the distribution automobile loading capacity pre-estimation module is used for receiving each sorted commodity basic parameter set sent by the commodity basic parameter detection module and each distribution automobile parameter set sent by the distribution automobile parameter detection module, further acquiring the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area and the length, the width and the height of a distribution automobile loading carriage corresponding to each sorted commodity placing area according to each sorted commodity basic parameter set and each distribution automobile parameter set, and further acquiring the volume corresponding to each sorted commodity in each sorted commodity placing area according to the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area, wherein the volume calculation formula corresponding to each sorted commodity in each sorted commodity placing area is Vr t＝ar t*br t*cr t，Vr tRepresents the volume corresponding to the t-th sorted goods in the r-th sorted goods placement area, ar tIndicating the length corresponding to the tth sorted goods in the tth sorted goods placement area, br tWidth corresponding to the t-th sorted goods in the r-th sorted goods placement area, cr tThe system comprises a first sorting commodity placing area, a second sorting commodity placing area, a third sorting commodity placing area, a fourth sorting commodity placing area, a fifth sorting commodity placing area, a sixth sorting commodity'r＝a′r*b′r*c′r，V′vIndicating placement of the r-th sorted itemVolume of delivery car load compartment corresponding to region, a'rIndicates the length, b ', of the carriage of the delivery vehicle corresponding to the r-th sorted-article placement region'rIndicates the width c 'of the delivery car loading compartment corresponding to the r-th sorted goods placement area'rThe method comprises the steps of representing the height of a delivery automobile loading compartment corresponding to an r-th sorted commodity placing area, comparing and screening volumes corresponding to sorted commodities, counting the number of the sorted commodities with the same volume, sequencing the volumes of the sorted commodities in the sorted commodity placing areas from large to small, dividing the volumes of the sorted commodities into various grades according to the sequence of the volumes of the sorted commodities, and sequentially marking the grades as 1,2, f, h, wherein 1 is 1>2>...>f>...>h, further acquiring the number of the sorted goods corresponding to each volume grade, numbering the sorted goods corresponding to each volume grade according to a preset sequence, sequentially marking the number of the sorted goods as 1,2,. g,. s, further estimating the loading capacity of the distribution automobile corresponding to the sorted goods placement area according to the preset loading sequence, counting the residual volume of the distribution automobile loading compartment corresponding to the sorted goods of each volume grade in each sorted goods placement area after loading, further counting the estimated loading capacity of the distribution automobile corresponding to each sorted goods placement area, marking the estimated loading capacity as lambda, extracting the number of the sorted goods placement area and the current time point after the volume of the sorted goods in each sorted goods placement area reaches the estimated loading capacity of the distribution automobile corresponding to the sorted goods placement area, and sending the number of the sorted goods placement area and the current time point to a remote control center, meanwhile, the estimated loading capacity of the delivery vehicles corresponding to each sorted goods placement area is sent to the processing server,
the processing server is used for receiving the sorted goods quantity sets of the collection time period, sent by the goods quantity statistical module of the placement area, of the placement areas and the sorted goods weight sets of the collection time period, sent by the goods weight detection module, of the placement areas, acquiring the quantity of the sorted goods corresponding to the sorted goods placement areas of the collection time period according to the sorted goods quantity sets of the placement areas of the collection time period, and then counting the collected goodsThe comprehensive sorting amount of the commodities corresponding to the time period is acquired according to the calculation formula
Figure BDA0002993186600000051
Gamma represents the comprehensive sorting quantity of the commodities corresponding to the acquisition time period, SrThe method comprises the steps of representing the quantity of sorted commodities corresponding to the r-th sorted commodity placing area in the collection time period, comparing the comprehensive commodity sorting quantity corresponding to the collection time period with the minimum commodity sorting quantity corresponding to the collection time period stored in a database, counting commodity sorting quantity influence coefficients corresponding to a warehouse in the time period, meanwhile, according to the weight set of each sorted commodity in each sorted commodity placing area in the collection time period, further obtaining the weight corresponding to each sorted commodity in each sorted commodity placing area in the collection time period, comparing and screening the weight corresponding to each sorted commodity in each sorted commodity placing area in the collection time period with the weight grade corresponding to each commodity in the database, further obtaining the weight grade corresponding to each sorted commodity, wherein the weight grades of the commodities are divided into light weight, medium weight and weight, and further comparing and screening the weight grades of each sorted commodity in each sorted commodity placing area in the collection time period Counting the quantity of sorted goods corresponding to each weight grade, recording the quantity of the sorted goods corresponding to the light grade in each sorted goods placement area in the acquisition time period as x, recording the quantity of the sorted goods corresponding to the medium grade in each sorted goods placement area in the acquisition time period as z, recording the quantity of the sorted goods corresponding to the weight grade in each sorted goods placement area in the acquisition time period as y, counting the goods weight sorting influence coefficient of each sorted goods placement area according to the quantity of the goods corresponding to the weight grade of each goods in each sorted goods placement area in the acquisition time period, and counting the goods sorting comprehensive influence coefficient according to the goods sorting quantity influence coefficient and the goods sorting weight influence coefficient corresponding to the warehouse in the time period;
the processing server is used for receiving the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area sent by the delivery vehicle loading capacity estimation module, comparing the number of the sorted goods corresponding to each sorted goods placement area in the acquisition time period with the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area, and further counting the accurate influence coefficient of the matching of the loading capacity of each sorted goods placement area;
the processing server matches the accurate influence coefficient according to the counted commodity sorting comprehensive influence coefficient and the loading capacity of each sorted commodity placing area so as to count the commodity sorting efficiency comprehensive influence coefficient;
the database is used for storing the commodity weight grade corresponding to each commodity weight and the commodity minimum sorting amount corresponding to the acquisition time period;
the remote control center is used for receiving the serial number of the sorted goods placement area and the current time point sent by the delivery automobile load amount pre-estimation module, recording the time point as a delivery and goods taking time point, further sending the time point of the delivery area and the serial number of the sorted goods placement area to corresponding delivery personnel, and completing goods taking.
Specifically, the calculation formula of the influence coefficient of the sorting quantity of the commodities corresponding to the warehouse is
Figure BDA0002993186600000061
Alpha represents the influence coefficient of the sorting quantity of the corresponding goods in the warehouse, FminAnd the minimum sorting quantity of the commodities corresponding to the acquisition time period is represented.
Specifically, the commodity sorting weight influence coefficient calculation formula is
Figure BDA0002993186600000071
β represents a commodity sorting weight influence coefficient, y represents the number of sorted commodities corresponding to the weight class in each sorted commodity placing region in the collection time period, x represents the number of sorted commodities corresponding to the light class in each sorted commodity placing region in the collection time period, and z represents the number of sorted commodities corresponding to the medium class in each sorted commodity placing region in the collection time period.
Specifically, the calculation formula of the comprehensive influence coefficient of commodity sorting is
Figure BDA0002993186600000072
And x represents the comprehensive influence coefficient corresponding to the commodity sorting.
Specifically, the calculation formula of the residual volume of the loading compartment of the distribution automobile corresponding to the loaded sorted goods of each volume grade in each sorted goods placement area is
Figure BDA0002993186600000073
Vr"d" represents the remaining volume of the loading compartment of the delivery vehicle corresponding to the kth sorted goods corresponding to the kth individual volume grade of the r-th sorted goods placement area after loading, Vr dk represents the volume corresponding to the kth sorted goods in the kth sorted goods placement area in the kth volume level, Vr d-1k represents the volume corresponding to the kth sorted goods in the d-1 th individual volume grade of the mth sorted goods placement area, k represents the sorted goods number corresponding to each volume grade, k is 1,2,. g,. s, d represents the sorted goods volume grade number, and d is 1,2,. f,. h.
Specifically, the calculation formula of the load matching accurate influence coefficient of each sorted goods placing area is
Figure BDA0002993186600000074
φrShows the accurate influence coefficient, lambda, of the load matching corresponding to the r-th sorted goods placement arearAnd the estimated load capacity of the delivery automobile corresponding to the sorted goods placing area in the r-th sorted goods placing area is shown.
Specifically, the calculation formula of the comprehensive influence coefficient of the commodity sorting efficiency is
Figure BDA0002993186600000081
X represents the overall influence coefficient of the commodity sorting efficiency, m represents the number of the sorted commodity placing areas, r represents the sorted commodity placing area number, and r is 1, 2.
The invention has the beneficial effects that:
(1) the invention provides an intelligent sorting regulation and control management system of an intelligent logistics center based on machine vision and artificial intelligence, through a sorted goods number counting module, a goods basic parameter detection module, a delivery automobile parameter detection module and a delivery automobile loading amount pre-estimation module and combining a processing server, further, the basic parameters corresponding to the sorted commodities in the sorted commodity placing areas, the basic parameters corresponding to the delivery vehicles in the sorted commodity placing areas and the estimated loading capacity of the delivery vehicles corresponding to the sorted commodity placing areas are comprehensively detected and analyzed, so that the problems that the commodity sorting efficiency is influenced by the proficiency of sorting personnel and the rapidity and the accuracy of commodity sorting cannot be guaranteed during sorting are solved, meanwhile, the commodity delivery efficiency is effectively improved, and intelligent sorting and efficient regulation and control management of commodities are realized.
(2) According to the invention, the commodity weight detection module detects the weight of each sorted commodity through the pressure sensor, so that the corresponding weight detection efficiency of the sorted commodity is effectively improved, and meanwhile, the accuracy of the weight detection result of the sorted commodity is also improved;
(3) the invention effectively saves the loading time and the delivery time of the commodity and greatly improves the delivery efficiency of the commodity by sending the instruction to the relevant staff at the remote control center.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, the present invention provides an intelligent sorting, regulating and managing system for an intelligent logistics center based on machine vision and artificial intelligence, comprising: the system comprises a commodity information acquisition module, a placement area commodity quantity counting module, a commodity basic parameter detection module, a commodity weight detection module, a delivery automobile parameter detection module, a delivery automobile load amount pre-estimation module, a processing server, a database and a remote control center;
the processing server is respectively connected with a commodity quantity counting module, a commodity weight detection module, a delivery automobile loading capacity pre-estimation module and a database in a placement area, the delivery automobile loading capacity pre-estimation module is respectively connected with a delivery automobile parameter detection module, a commodity basic parameter detection module and a remote control center, and the placement area acquisition module is respectively connected with a commodity information acquisition module and a commodity quantity counting module in the placement area;
the commodity information acquisition module is used for scanning a bar code of a commodity through a scanner when a worker sorts the commodity, and further acquiring information corresponding to the commodity, wherein the commodity information comprises a commodity category and a commodity harvesting address;
the placement area acquisition module is used for acquiring position placement areas corresponding to the sorted commodities, marking the position placement areas corresponding to the sorted commodities as sorted commodity placement areas and further acquiring the number of the sorted commodity placement areas corresponding to the warehouse, wherein the sorted commodity placement areas correspond to the cities where the goods receiving addresses corresponding to the sorted commodities are located one by one, and further numbering the sorted commodity placement areas corresponding to the warehouse according to a preset sequence, wherein the marks are 1,2, a.
The commodity quantity counting module in the placement area is used for counting the quantity of sorted commodities in each sorted commodity placement area in the collection time period, comparing and screening the harvest address of each sorted commodity according to the harvest address corresponding to each sorted commodity, further counting the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, further acquiring the quantity of the sorted commodities corresponding to each sorted commodity placement area in the collection time period according to the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, numbering the sorted commodities corresponding to the sorted commodity placement areas in the collection time period according to a preset sequence, sequentially marking the sorted commodities as 1,2, u, v, and further constructing a sorted commodity quantity set S (S1, s2.. Sj.. Sm), Sj represents the number of sorted goods corresponding to the jth sorted goods placement region in the collection time period, and sends the collection of the number of sorted goods in each placement region in the collection time period to the processing server;
the commodity weight detection module comprises a plurality of pressure sensors which are respectively installed in each sorted commodity placing area and used for detecting the weight of each sorted commodity in each sorted commodity placing area in the acquisition time period, further acquiring the weight corresponding to each sorted commodity in each sorted commodity placing area in the acquisition time period, and further constructing each sorted commodity weight set Z in each sorted commodity placing area in the acquisition time periodt(Zt1，Zt2，...Ztj,...Ztm),Ztj represents the weight corresponding to the tth sorted goods in the jth sorted goods placement area in the acquisition time period, t represents the serial number of the sorted goods in each sorted goods placement area, and t is 1,2,. u,. v, so that the weight set of each sorted goods in each sorted goods placement area in the acquisition time period is sent to the processing server;
according to the embodiment of the invention, the weight of each sorted commodity is detected by the commodity weight detection module through the pressure sensor, so that the weight detection efficiency corresponding to the sorted commodity is effectively improved, and meanwhile, the accuracy of the weight detection result of the sorted commodity is also improved.
The commodity basic parameter detection module comprises a plurality of parameter detection devices which are respectively arranged in each sorted commodity placing area and used for detecting the basic parameters of each sorted commodity in each sorted commodity placing area in the acquisition time period, and then a three-dimensional laser scanner in the parameter detection devices is used for detecting each sorted commodity placing area in the acquisition time periodScanning and shooting each sorted commodity in the region, further acquiring the length, width and height corresponding to each sorted commodity in each sorted commodity placement region in the acquisition time period, respectively recording the length, width and height corresponding to each sorted commodity as a, b and c, and further constructing a basic parameter set T of each sorted commoditye t(Te t1,Te t2,...Te tj,...Te tm)，Te tj represents the e-th parameter corresponding to the t-th sorted commodity in the jth sorted commodity placement area in the acquisition time period, e represents the sorted commodity parameter, and e is a, b, c, a, b and c respectively represent the length, width and height corresponding to the sorted commodity, so that the constructed basic parameter set of each sorted commodity is sent to the distribution automobile load estimation module;
according to the embodiment of the invention, the basic parameter detection module of the commodity detects the basic parameter of each sorted commodity in each sorted commodity placing area in the acquisition time period, so that a data basis is provided for the subsequent analysis of commodity parameters.
The distribution automobile parameter detection module is used for detecting parameters of distribution automobiles corresponding to the sorted commodities in each sorted commodity placement area, and further acquiring parameters of the distribution automobiles corresponding to each sorted commodity placement area of the warehouse, wherein the distribution automobile parameters comprise the length, the width and the height of a distribution automobile loading compartment corresponding to each sorted commodity placement area, and further constructing a distribution automobile parameter set Pq(Pq1,Pq2,...Pqj,...Pqm)，Pqj represents the q-th parameter of the delivery automobile corresponding to the j-th sorted goods placement area, q represents the delivery automobile parameter, and q is a length, a width and a height of a loading compartment of the delivery automobile corresponding to each sorted goods placement area respectively, and sends each delivery automobile parameter set to a delivery automobile loading amount estimation module;
according to the embodiment of the invention, the data basis is provided for the subsequent estimation of the loading capacity of the delivery automobile by detecting the parameters of the delivery automobile corresponding to the sorted commodities in each sorted commodity placing area.
The distribution automobile loading capacity pre-estimation module is used for receiving each sorted commodity basic parameter set sent by the commodity basic parameter detection module and each distribution automobile parameter set sent by the distribution automobile parameter detection module, further acquiring the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area and the length, the width and the height of a distribution automobile loading carriage corresponding to each sorted commodity placing area according to each sorted commodity basic parameter set and each distribution automobile parameter set, and further acquiring the volume corresponding to each sorted commodity in each sorted commodity placing area according to the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area, wherein the volume calculation formula corresponding to each sorted commodity in each sorted commodity placing area is Vr t＝ar t*br t*cr t，Vr tRepresents the volume corresponding to the t-th sorted goods in the r-th sorted goods placement area, ar tIndicating the length corresponding to the tth sorted goods in the tth sorted goods placement area, br tWidth corresponding to the t-th sorted goods in the r-th sorted goods placement area, cr tThe system comprises a first sorting commodity placing area, a second sorting commodity placing area, a third sorting commodity placing area, a fourth sorting commodity placing area, a fifth sorting commodity placing area, a sixth sorting commodity'r＝a′r*b′r*c′r，V′rIndicates the volume a 'of the delivery vehicle loading compartment corresponding to the r-th sorted goods placement area'rIndicates the length, b ', of the carriage of the delivery vehicle corresponding to the r-th sorted-article placement region'rIndicates the width c 'of the delivery car loading compartment corresponding to the r-th sorted goods placement area'rIndicates the r-th sorterThe height of a distribution automobile loading compartment corresponding to the goods placement area is compared and screened with the volume corresponding to each sorted goods, the quantity of the sorted goods with the same volume is counted, meanwhile, the volumes of the sorted goods in the goods placement area are sorted from large to small, the volumes of the sorted goods are divided into various grades according to the arrangement sequence of the volumes of the sorted goods, and the grades are sequentially marked as 1,2, f, h, wherein 1>2>...>f>...>h, further acquiring the quantity of the sorted commodities corresponding to each volume grade, numbering the sorted commodities corresponding to each volume grade according to a preset sequence, sequentially marking the sorted commodities as 1,2, g, s, further estimating the loading capacity of a distribution automobile corresponding to the sorted commodity placing area according to the preset loading sequence, and counting the residual volume of the distribution automobile loading compartment corresponding to the sorted commodities of each volume grade in each sorted commodity placing area after loading, wherein the calculation formula of the residual volume of the distribution automobile loading compartment corresponding to the sorted commodities of each volume grade in each sorted commodity placing area after loading is as follows
Figure BDA0002993186600000131
Vr"d" represents the remaining volume of the loading compartment of the delivery vehicle corresponding to the kth sorted goods corresponding to the kth individual volume grade of the r-th sorted goods placement area after loading, Vr dk represents the volume corresponding to the kth sorted goods in the kth sorted goods placement area in the kth volume level, Vr d-1k represents the volume corresponding to the kth sorted goods in the d-1 th individual volume grade of the r-th sorted goods placement area, k represents the sorted goods number corresponding to each volume grade, k is 1,2, g, s, d represents the sorted goods volume grade number, d is 1,2, f, h, the estimated loading capacity of the distribution automobile corresponding to each sorted goods placement area is further counted, and is recorded as lambda, when the volume of the sorted goods in each sorted goods placement area reaches the estimated loading capacity of the distribution automobile corresponding to the sorted goods placement area, the number and the current time point of the sorted goods placement area are extracted, the number and the current time point of the sorted goods placement area are sent to a remote control center, and meanwhile, each sorted goods placement area is sent to a remote control centerThe estimated loading of the corresponding delivery vehicles in the area is sent to the processing server,
the processing server is used for receiving the sorted goods quantity sets of the collection time period, sent by the goods quantity statistical module of the placement area, of the placement areas and the sorted goods weight sets of the collection time period, sent by the goods weight detection module, acquiring the quantity of the sorted goods corresponding to the sorted goods placement areas of the collection time period according to the sorted goods quantity sets of the collection time period, and further counting the comprehensive goods sorting quantity corresponding to the collection time period, wherein the calculation formula of the comprehensive goods sorting quantity corresponding to the collection time period is
Figure BDA0002993186600000132
Gamma represents the comprehensive sorting quantity of the commodities corresponding to the acquisition time period, SrThe quantity of the sorted commodities corresponding to the r-th sorted commodity placement area in the collection time period is represented, the comprehensive commodity sorting quantity corresponding to the collection time period is compared with the minimum commodity sorting quantity corresponding to the collection time period stored in the database, and then the commodity sorting quantity influence coefficient corresponding to the warehouse in the time period is counted, wherein the commodity sorting quantity influence coefficient corresponding to the warehouse is calculated according to the formula
Figure BDA0002993186600000133
Alpha represents the influence coefficient of the sorting quantity of the corresponding goods in the warehouse, FminShowing the minimum sorting amount of the commodities corresponding to the acquisition time period, simultaneously collecting the weight set of each sorted commodity in each sorted commodity placement area according to the acquisition time period, further obtaining the weight corresponding to each sorted commodity in each sorted commodity placement area of the acquisition time period, comparing and screening the weight corresponding to each sorted commodity in each sorted commodity placement area of the acquisition time period with the commodity weight grade corresponding to each commodity weight in the database, further obtaining the commodity weight grade corresponding to each sorted commodity, wherein the commodity weight grade is divided into light weight, medium weight and weight, further comparing and screening the weight grade of each sorted commodity in each sorted commodity placement area of the acquisition time periodCounting the quantity of sorted goods corresponding to each weight grade, recording the quantity of the sorted goods corresponding to the light grade in each sorted goods placement area in the acquisition time period as x, recording the quantity of the sorted goods corresponding to the medium grade in each sorted goods placement area in the acquisition time period as z, recording the quantity of the sorted goods corresponding to the weight grade in each sorted goods placement area in the acquisition time period as y, and counting the weight sorting influence coefficient of the goods in each sorted goods placement area according to the quantity of the goods corresponding to the weight grade of each goods in each sorted goods placement area in the acquisition time period, wherein the goods sorting weight influence coefficient calculation formula is that
Figure BDA0002993186600000141
β represents a commodity sorting weight influence coefficient, y represents the number of sorted commodities corresponding to the weight class in each sorted commodity placing region in the collection time period, x represents the number of sorted commodities corresponding to the light class in each sorted commodity placing region in the collection time period, and z represents the number of sorted commodities corresponding to the medium class in each sorted commodity placing region in the collection time period. According to the commodity sorting quantity influence coefficient and the commodity sorting weight influence coefficient corresponding to the warehouse in the time period, further counting the commodity sorting comprehensive influence coefficient, wherein the commodity sorting comprehensive influence coefficient calculation formula is
Figure BDA0002993186600000142
And x represents the comprehensive influence coefficient corresponding to the commodity sorting. (ii) a
The processing server is used for receiving the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area sent by the delivery vehicle loading capacity estimation module, comparing the number of the sorted goods corresponding to each sorted goods placement area in the acquisition time period with the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area, and further counting the accurate matching influence coefficient of the loading capacity of each sorted goods placement area, wherein the accurate matching influence coefficient calculation formula of the loading capacity of each sorted goods placement area is
Figure BDA0002993186600000151
φrShows the accurate influence coefficient, lambda, of the load matching corresponding to the r-th sorted goods placement arearThe estimated loading capacity of the delivery automobile corresponding to the sorted goods placing area in the r-th sorted goods placing area is represented;
the processing server matches the accurate influence coefficient according to the counted commodity sorting comprehensive influence coefficient and the load capacity of each sorted commodity placing area so as to count the commodity sorting efficiency comprehensive influence coefficient, wherein the calculation formula of the commodity sorting efficiency comprehensive influence coefficient is
Figure BDA0002993186600000152
X represents a commodity sorting efficiency comprehensive influence coefficient, m represents the number of sorted commodity placing areas, r represents a sorted commodity placing area number, and r is 1,2,. j,. m;
the embodiment of the invention comprehensively detects and analyzes the basic parameters corresponding to the sorted commodities in each sorted commodity placing area, the basic parameters corresponding to the delivery vehicles in each sorted commodity placing area and the estimated load capacity of the delivery vehicles corresponding to each sorted commodity placing area, solves the problems that the commodity sorting efficiency is influenced by the proficiency of sorting personnel and the rapidness and the accuracy of commodity sorting cannot be guaranteed during classification, effectively improves the commodity ex-warehouse efficiency, and realizes intelligent sorting and efficient regulation and control management of commodities.
The database is used for storing the commodity weight grade corresponding to each commodity weight and the commodity minimum sorting amount corresponding to the acquisition time period;
the remote control center is used for receiving the serial number of the sorted goods placement area and the current time point sent by the delivery automobile load amount pre-estimation module, recording the time point as a delivery and goods taking time point, further sending the time point of the delivery area and the serial number of the sorted goods placement area to corresponding delivery personnel, and completing goods taking.
According to the embodiment of the invention, the remote control center sends the instruction to the relevant staff, so that the loading time and the delivery time of the commodity are effectively and slightly saved, and meanwhile, the delivery efficiency of the commodity is greatly improved.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.

Claims (7)

1. Wisdom logistics center intelligence letter sorting regulation and control management system based on machine vision and artificial intelligence, its characterized in that: the system comprises a commodity information acquisition module, a placement area commodity quantity counting module, a commodity basic parameter detection module, a commodity weight detection module, a delivery automobile parameter detection module, a delivery automobile loading capacity pre-estimation module, a processing server, a database and a remote control center;
the processing server is respectively connected with a commodity quantity counting module, a commodity weight detection module, a delivery automobile loading capacity pre-estimation module and a database in a placement area, the delivery automobile loading capacity pre-estimation module is respectively connected with a delivery automobile parameter detection module, a commodity basic parameter detection module and a remote control center, and the placement area acquisition module is respectively connected with a commodity information acquisition module and a commodity quantity counting module in the placement area;
the commodity information acquisition module is used for scanning a bar code of a commodity through a scanner when a worker sorts the commodity, and further acquiring information corresponding to the commodity, wherein the commodity information comprises a commodity category and a commodity harvesting address;
the placement area acquisition module is used for acquiring position placement areas corresponding to the sorted commodities, marking the position placement areas corresponding to the sorted commodities as sorted commodity placement areas and further acquiring the number of the sorted commodity placement areas corresponding to the warehouse, wherein the sorted commodity placement areas correspond to the cities where the goods receiving addresses corresponding to the sorted commodities are located one by one, and further numbering the sorted commodity placement areas corresponding to the warehouse according to a preset sequence, wherein the marks are 1,2, a.
The commodity quantity counting module in the placement area is used for counting the quantity of sorted commodities in each sorted commodity placement area in the collection time period, comparing and screening the harvest address of each sorted commodity according to the harvest address corresponding to each sorted commodity, further counting the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, further acquiring the quantity of the sorted commodities corresponding to each sorted commodity placement area in the collection time period according to the quantity of the sorted commodities corresponding to the city where each harvest address in the collection time period is located, numbering the sorted commodities corresponding to the sorted commodity placement areas in the collection time period according to a preset sequence, sequentially marking the sorted commodities as 1,2, u, v, and further constructing a sorted commodity quantity set S (S1, s2.. Sj.. Sm), Sj represents the number of sorted goods corresponding to the jth sorted goods placement region in the collection time period, and sends the collection of the number of sorted goods in each placement region in the collection time period to the processing server;
the commodity weight detection module comprises a plurality of pressure sensors which are respectively installed in each sorted commodity placing area and used for detecting the weight of each sorted commodity in each sorted commodity placing area in the acquisition time period, further acquiring the weight corresponding to each sorted commodity in each sorted commodity placing area in the acquisition time period, and further constructing each sorted commodity weight set Z in each sorted commodity placing area in the acquisition time periodt(Zt1，Zt2，...Ztj,...Ztm),Ztj represents the weight corresponding to the tth sorted goods in the jth sorted goods placement area in the acquisition time period, t represents the serial number of the sorted goods in each sorted goods placement area, and t is 1,2,. u,. v, so that the weight set of each sorted goods in each sorted goods placement area in the acquisition time period is sent to the processing server;
the commodity basic parameter detection module comprises a plurality of parameter detection devices which are respectively arranged in each sorted commodity placing area and are used for detecting the basic parameters of each sorted commodity in each sorted commodity placing area in the acquisition time period, thereby being beneficial toScanning and shooting each sorted commodity in each sorted commodity placing area in the acquisition time period by using a three-dimensional laser scanner in the parameter detection equipment, further acquiring the length, width and height corresponding to each sorted commodity in each sorted commodity placing area in the acquisition time period, respectively recording the length, width and height corresponding to each sorted commodity as a, b and c, and further constructing a basic parameter set T of each sorted commoditye t(Te t1,Te t2,...Te tj,...Te tm)，Te tj represents the e-th parameter corresponding to the t-th sorted commodity in the jth sorted commodity placement area in the acquisition time period, e represents the sorted commodity parameter, and e is a, b, c, a, b and c respectively represent the length, width and height corresponding to the sorted commodity, so that the constructed basic parameter set of each sorted commodity is sent to the distribution automobile load estimation module;
the distribution automobile parameter detection module is used for detecting parameters of distribution automobiles corresponding to the sorted commodities in each sorted commodity placement area, and further acquiring parameters of the distribution automobiles corresponding to each sorted commodity placement area of the warehouse, wherein the distribution automobile parameters comprise the length, the width and the height of a distribution automobile loading compartment corresponding to each sorted commodity placement area, and further constructing a distribution automobile parameter set Pq(Pq1,Pq2,...Pqj,...Pqm)，Pqj represents the q-th parameter of the delivery automobile corresponding to the j-th sorted goods placement area, q represents the delivery automobile parameter, and q is a length, a width and a height of a loading compartment of the delivery automobile corresponding to each sorted goods placement area respectively, and sends each delivery automobile parameter set to a delivery automobile loading amount estimation module;
the distribution automobile loading capacity pre-estimation module is used for receiving each sorted commodity basic parameter set sent by the commodity basic parameter detection module and each distribution automobile parameter set sent by the distribution automobile parameter detection module, and further acquiring the length, width and height corresponding to each sorted commodity in each sorted commodity placement area according to each sorted commodity basic parameter set and each distribution automobile parameter setAnd the length, the width and the height of the loading carriage of the delivery automobile corresponding to each sorted commodity placing area, and further acquiring the volume corresponding to each sorted commodity in each sorted commodity placing area according to the length, the width and the height corresponding to each sorted commodity in each sorted commodity placing area, wherein the volume calculation formula corresponding to each sorted commodity in each sorted commodity placing area is Vr t＝ar t*br t*cr t，Vr tRepresents the volume corresponding to the t-th sorted goods in the r-th sorted goods placement area, ar tIndicating the length corresponding to the tth sorted goods in the tth sorted goods placement area, br tWidth corresponding to the t-th sorted goods in the r-th sorted goods placement area, cr tThe system comprises a first sorting commodity placing area, a second sorting commodity placing area, a third sorting commodity placing area, a fourth sorting commodity placing area, a fifth sorting commodity placing area, a sixth sorting commodity'r＝a′r*b′r*c′r，Vr'represents the volume of the delivery vehicle loading compartment corresponding to the r-th sorted-article placing area, a'rIndicates the length, b ', of the carriage of the delivery vehicle corresponding to the r-th sorted-article placement region'rIndicates the width c 'of the delivery car loading compartment corresponding to the r-th sorted goods placement area'rThe height of a delivery automobile loading carriage corresponding to the r-th sorted commodity placing area is represented, the volumes corresponding to the sorted commodities are compared and screened, the quantity of the sorted commodities with the same volume is counted, meanwhile, the volumes of the sorted commodities in the sorted commodity placing areas are sequenced from large to small, and the volumes of the sorted commodities are divided into the sorted commodities according to the sequence of the volumes of the sorted commoditiesLevels, and labeled 1,2,. f,. h, in that order, where 1>2>...>f>...>h, further acquiring the number of the sorted goods corresponding to each volume grade, numbering the sorted goods corresponding to each volume grade according to a preset sequence, sequentially marking the number of the sorted goods as 1,2,. g,. s, further estimating the loading capacity of the distribution automobile corresponding to the sorted goods placement area according to the preset loading sequence, counting the residual volume of the distribution automobile loading compartment corresponding to the sorted goods of each volume grade in each sorted goods placement area after loading, further counting the estimated loading capacity of the distribution automobile corresponding to each sorted goods placement area, marking the estimated loading capacity as lambda, extracting the number of the sorted goods placement area and the current time point after the volume of the sorted goods in each sorted goods placement area reaches the estimated loading capacity of the distribution automobile corresponding to the sorted goods placement area, and sending the number of the sorted goods placement area and the current time point to a remote control center, meanwhile, the estimated loading capacity of the delivery vehicles corresponding to each sorted goods placement area is sent to the processing server,
the processing server is used for receiving the sorted goods quantity sets of the collection time period, sent by the goods quantity statistical module of the placement area, of the placement areas and the sorted goods weight sets of the collection time period, sent by the goods weight detection module, acquiring the quantity of the sorted goods corresponding to the sorted goods placement areas of the collection time period according to the sorted goods quantity sets of the collection time period, and further counting the comprehensive goods sorting quantity corresponding to the collection time period, wherein the calculation formula of the comprehensive goods sorting quantity corresponding to the collection time period is
Figure FDA0002993186590000041
Gamma represents the comprehensive sorting quantity of the commodities corresponding to the acquisition time period, SrThe quantity of the sorted commodities corresponding to the r-th sorted commodity placement area in the acquisition time period is represented, the comprehensive commodity sorting quantity corresponding to the acquisition time period is compared with the minimum commodity sorting quantity corresponding to the acquisition time period stored in the database, the commodity sorting quantity influence coefficient corresponding to the warehouse in the time period is counted, and meanwhile, the distribution quantity influence coefficient is divided according to the acquisition time periodSorting the weight set of each sorted commodity in the commodity placing area, further obtaining the weight corresponding to each sorted commodity in each sorted commodity placing area in the collection time period, comparing and screening the weight corresponding to each sorted commodity in each sorted commodity placing area in the collection time period with the commodity weight grade corresponding to each commodity weight in the database, further obtaining the commodity weight grade corresponding to each sorted commodity, wherein the commodity weight grade is divided into light weight, medium weight and weight, further comparing and screening the weight grade of each sorted commodity in each sorted commodity placing area in the collection time period, further counting the number of the sorted commodities corresponding to each weight grade, recording the number of the sorted commodities corresponding to the light weight grade in each sorted commodity placing area in the collection time period as x, and recording the number of the sorted commodities corresponding to the medium weight grade in each sorted commodity placing area in the collection time period as z, recording the quantity of the sorted commodities corresponding to the weight grade in each sorted commodity placing area in the acquisition time period as y, counting commodity weight sorting influence coefficients of each sorted commodity placing area according to the quantity of the commodities corresponding to the weight grade of the commodities in each sorted commodity placing area in the acquisition time period, and counting commodity sorting comprehensive influence coefficients according to the commodity sorting quantity influence coefficients and the commodity sorting weight influence coefficients corresponding to the warehouse in the time period;
the processing server is used for receiving the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area sent by the delivery vehicle loading capacity estimation module, comparing the number of the sorted goods corresponding to each sorted goods placement area in the acquisition time period with the estimated loading capacity of the delivery vehicle corresponding to each sorted goods placement area, and further counting the accurate influence coefficient of the matching of the loading capacity of each sorted goods placement area;
the processing server matches the accurate influence coefficient according to the counted commodity sorting comprehensive influence coefficient and the loading capacity of each sorted commodity placing area so as to count the commodity sorting efficiency comprehensive influence coefficient;
the database is used for storing the commodity weight grade corresponding to each commodity weight and the commodity minimum sorting amount corresponding to the acquisition time period;
the remote control center is used for receiving the serial number of the sorted goods placement area and the current time point sent by the delivery automobile load amount pre-estimation module, recording the time point as a delivery and goods taking time point, further sending the time point of the delivery area and the serial number of the sorted goods placement area to corresponding delivery personnel, and completing goods taking.
2. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the commodity sorting quantity influence coefficient calculation formula corresponding to the warehouse is
Figure FDA0002993186590000061
Alpha represents the influence coefficient of the sorting quantity of the corresponding goods in the warehouse, FminAnd the minimum sorting quantity of the commodities corresponding to the acquisition time period is represented.
3. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the commodity sorting weight influence coefficient calculation formula is
Figure FDA0002993186590000062
β represents a commodity sorting weight influence coefficient, y represents the number of sorted commodities corresponding to the weight class in each sorted commodity placing region in the collection time period, x represents the number of sorted commodities corresponding to the light class in each sorted commodity placing region in the collection time period, and z represents the number of sorted commodities corresponding to the medium class in each sorted commodity placing region in the collection time period.
4. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the calculation formula of the comprehensive influence coefficient of commodity sorting is
Figure FDA0002993186590000063
X represents the comprehensive influence of commodity sortingAnd (4) the coefficient.
5. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the calculation formula of the residual volume of the distribution automobile loading compartment corresponding to the sorted goods of each volume grade in each sorted goods placement area after being loaded is as follows
Figure FDA0002993186590000064
Vr"d" represents the remaining volume of the loading compartment of the delivery vehicle corresponding to the kth sorted goods corresponding to the kth individual volume grade of the r-th sorted goods placement area after loading, Vr dk represents the volume corresponding to the kth sorted goods in the kth sorted goods placement area in the kth volume level, Vr d -1k represents the volume corresponding to the kth sorted goods in the d-1 th individual volume grade of the mth sorted goods placement area, k represents the sorted goods number corresponding to each volume grade, k is 1,2,. g,. s, d represents the sorted goods volume grade number, and d is 1,2,. f,. h.
6. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the calculation formula of the load matching accurate influence coefficient of each sorted commodity placing area is
Figure FDA0002993186590000071
φrShows the accurate influence coefficient, lambda, of the load matching corresponding to the r-th sorted goods placement arearAnd the estimated load capacity of the delivery automobile corresponding to the sorted goods placing area in the r-th sorted goods placing area is shown.
7. The intelligent sorting regulation and management system of intelligent logistics center based on machine vision and artificial intelligence as claimed in claim 1, wherein: the calculation formula of the comprehensive influence coefficient of the commodity sorting efficiency is
Figure FDA0002993186590000072
X represents the overall influence coefficient of the commodity sorting efficiency, m represents the number of the sorted commodity placing areas, r represents the sorted commodity placing area number, and r is 1, 2.
CN202110321891.0A 2021-03-25 2021-03-25 Intelligent sorting, regulating and controlling management system of intelligent logistics center based on machine vision and artificial intelligence Pending CN113083693A (en)

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