CN117575476A

CN117575476A - Intelligent monitoring management system based on Internet of things

Info

Publication number: CN117575476A
Application number: CN202410061159.8A
Authority: CN
Inventors: 秦碧龙; 兰振东; 张亚娟
Original assignee: Shaanxi Tianlin Ruiteng Network Technology Co ltd
Current assignee: Xi'an Tuoda Electronic Technology Co ltd
Priority date: 2024-01-16
Filing date: 2024-01-16
Publication date: 2024-02-20
Anticipated expiration: 2044-01-16
Also published as: CN117575476B

Abstract

The invention relates to the technical field of warehouse monitoring management, and discloses an intelligent monitoring management system based on the Internet of things, which comprises the following components: the intelligent monitoring management system based on the Internet of things determines the position of a target object placed on the target goods shelf and the position of the gravity center of the target goods shelf after the target object is placed, analyzes whether the placed target object can cause goods shelf tipping at the position or not, so that more goods shelves are tipped, prevents accidents from happening, judges whether the target object in the warehouse of other buildings needs to be coordinated borrowed or not, and accordingly analyzes and determines the position of the other building with the shortest borrowing distance and capable of being borrowed so as to coordinate borrowing to the warehouse of the other building when the quantity of the target object is insufficient for a target user.

Description

Intelligent monitoring management system based on Internet of things

Technical Field

The invention relates to the technical field of warehouse monitoring management, in particular to an intelligent monitoring management system based on the Internet of things.

Background

The intelligent monitoring management system for building warehouse based on the Internet of things is a system for realizing monitoring and management of warehouse facilities by utilizing the Internet of things technology, and is used for data acquisition, transmission and analysis by connecting sensors, equipment and networks in the warehouse so as to improve warehouse efficiency, optimize operation and increase safety, and generally comprises real-time monitoring, data acquisition and analysis, remote monitoring and control, alarm and early warning, data management and decision support and the like;

the system is used for collecting and analyzing a large amount of warehouse data, providing a data interface and a decision support tool for managers, helping the managers to know and optimize warehouse operation conditions, improving operation efficiency and reducing cost, realizing fine management and intelligent control of the warehouse, improving warehouse efficiency and safety, and realizing data sharing and flow optimization;

the existing intelligent monitoring management system for building storage based on the Internet of things cannot determine the position of a target object placed on a target goods shelf according to the size and weight of the target object and the condition of stored goods in the warehouse, and cannot analyze and judge the gravity center position of the target goods shelf after the target object is placed according to the weight of the stored goods on the target goods shelf and the weight of the target object, so that whether the situation that the goods shelf is tilted or not is judged, whether the storage coordination borrowing with other buildings is needed or not cannot be determined according to historical use data of the target object by a target user and the current storage quantity, and therefore the position of the other buildings with the shortest borrowing distance and capable of being borrowed is determined and the practicability is limited.

Disclosure of Invention

The invention provides an intelligent monitoring management system based on the Internet of things, which is used for facilitating solving of the problems in the background technology.

The invention provides the following technical scheme: an intelligent monitoring management system based on the internet of things, comprising:

and the acquisition module is used for: acquiring target warehouse data of a target building;

and an analysis module: the acquisition module is in communication connection with the analysis module, and forms analysis data according to the target storage data so as to determine the placement position of the target object;

and (5) warehousing the module: the analysis module is in communication connection with the warehousing module, and judges the gravity center point of the target goods shelf according to the analysis data, so that the target goods can be placed on the target goods shelf while the goods shelf balance is kept;

and a coordination module: the warehousing module is in communication connection with the coordination module, acquires historical data of target users on target objects, and forms presumed coordination data for coordinating and borrowing the target objects for warehousing of other buildings.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the acquiring the target warehouse data of the target building specifically comprises the following steps:

acquiring the number of shelves of the warehouse in the target building, and recording as B (B1., bn);

Acquiring the length, width and layer number of each shelf, which are respectively marked as C (C1, cn), D (D1, dn), F (F1 (F11-F1 n), fn (Fn 1-Fnn));

the number of shelves B, the shelf length C, the shelf width D and the shelf layer number F are integrated into a storage data set.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: forming analysis data according to the target warehouse data to determine the placement position of the target object;

acquiring the weight of a target object, and marking the weight as G;

acquiring the length, width and height of a target object, which are respectively marked as L, W, H;

acquiring a placeable space in a target building;

executing a target object placement determination strategy;

and extracting the number of the target goods shelf and the number of the layer corresponding to the target layer number in the storage data set.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the method for obtaining the placeable space in the target building specifically comprises the following steps:

acquiring a storage data set of a target building;

extracting a goods shelf B and a layer number F of the goods which are not placed in the warehouse, and determining the goods shelf B and the layer number F as a target judgment goods shelf and a target judgment layer number;

Respectively acquiring the number of the placed articles of the target judgment layer number of each target judgment shelf, and marking the number as I1;

setting the placement number, and marking as I2;

setting a first judgment number, a second judgment number and a third judgment number, which are respectively marked as I3, I4 and I5;

if the placement number I2-the number of placed articles I1=the first judgment number I3, acquiring the layer height of the target judgment layer number of the target judgment shelf, and marking the layer height as J;

acquiring the length of the placed articles of the target judgment layer number of the target judgment shelf, and marking the length as K1;

calculating the idle length of the target judgment layer number of the target judgment shelf, namely M, wherein the idle length M=the shelf length C-the length K1 of the placed article;

if the placement number I2-the number of placed articles I1=the second judgment number I4, acquiring the layer height J of the target judgment layer number of the target judgment shelf;

acquiring the length of the placed articles of the target judgment layer number of the target judgment shelf, and marking the length as K2;

calculating the idle length M of the target judgment layer number of the target judgment shelf, wherein the idle length M is equal to the shelf length C-the length K2 of the placed articles;

if the placement number I2-the number of placed articles I1=the third judgment number I5, acquiring the layer height J of the target judgment layer number of the target judgment shelf;

Acquiring the length of the placed articles of the target judgment layer number of the target judgment shelf, and marking the length as K3;

calculating the idle length M of the target judgment layer number of the target judgment shelf, wherein the idle length M is equal to the shelf length C-the length K3 of the placed articles;

the layer height J, the idle length M and the shelf width D of the target judgment layer number of each target judgment shelf are formed into a placeable space data set.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the implementation target object placement judgment strategy specifically comprises the following steps:

acquiring a placeable spatial data set;

setting a length difference threshold;

if the idle length M-the target article length L is more than or equal to the length difference threshold value, determining that the first judging result meets the article placement length requirement, and marking as E11;

if the idle length M-the target article length L is less than the length difference threshold value, determining that the first judging result does not meet the article placement length requirement, and marking as E12;

setting a width difference threshold;

if the goods shelf width D-the target goods width W is more than or equal to the width difference threshold value, determining that the second judging result meets the goods placement width requirement, and marking as E21;

if the goods shelf width D-target goods width W is smaller than the width difference threshold value, determining that the second judging result does not meet the goods placement width requirement, and marking as E22;

Setting a height difference threshold;

if the height H of the goods shelf layer is greater than or equal to the height difference threshold value, determining that the third judging result meets the goods placing height requirement, and marking as E31;

if the height H of the goods shelf layer is less than the height difference threshold value, determining that the first judging result meets the goods placing height requirement, and marking as E32;

acquiring all target judgment shelves and target judgment layer numbers which reach the first judgment result E11, the second judgment result E21 and the third judgment result E31 at the same time, and determining the target judgment shelves and the target judgment layer numbers as placeable shelves and placeable layer numbers;

and executing a gravity center simulation strategy.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the executing the gravity center simulation strategy specifically comprises the following steps:

establishing a gravity center simulation model for each placeable shelf;

acquiring a gravity center point of a placeable goods shelf when no goods exist, and determining the gravity center point as a first gravity center point;

setting a balance distance, namely Q1, wherein the balance distance is the maximum offset distance of a gravity center point, which is offset in the gravity center point but the goods shelf cannot be overturned, and the maximum offset distance is the maximum offset distance which is set according to the safety, wherein the length and the height of the goods shelf are obtained, the midpoint of the length and the midpoint of the height are respectively taken as vertical lines, the point where the two vertical lines intersect is taken as an origin, and the length of the goods shelf is taken as a radius to form a range, namely 0.6 times the length of the goods shelf is the maximum offset distance set according to the safety;

Forming an offset range by taking the first gravity center point as an origin and taking the balance distance as a radius;

connecting the first gravity center point and the second gravity center point, and acquiring the length of the connecting line, wherein the length is the distance between the first gravity center point and the second gravity center point, and is determined as the gravity center offset distance and is recorded as Q2;

setting a judgment value;

if the gravity center offset distance Q2-the balance distance Q1 are less than or equal to the judgment value, judging that the target object can be placed;

if the gravity center offset distance Q2-balance distance Q1 is larger than the judgment value, judging that the target object can not be placed;

acquiring the number of shelf which can be placed and is judged to be capable of placing the target object;

setting a shelf quantity judgment value;

if the number of the shelf to be placed and the shelf number judgment value = judgment value, acquiring the number of layers to be placed of the shelf to be placed;

setting a space quantity judgment value;

if the number of layers which can be placed-space number judgment value is less than the judgment value, the judgment is not formed;

if the number of placeable layers-the number of space determination value = determination value, then the placeable shelf is determined as a target shelf and the number of placeable layers is determined as a target layer;

if the number of the placeable layers-the space number judgment value is larger than the judgment value, randomly extracting the placeable layers of the placeable shelves which are judged to be the placeable target objects, determining the placeable shelves as target shelves, and determining the placeable layers as target layers;

If the number of the shelf which can be placed, the shelf number judgment value is smaller than the judgment value, the judgment is not formed;

if the number of the placeable shelves and the number of the shelves are determined to be greater than the determined value, randomly extracting the number of the placeable layers of the placeable shelves which are determined to be the placeable target articles, determining the placeable shelves as target shelves, and determining the number of the placeable layers as target layers.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the method for obtaining the historical data of the target user on the target object forms speculative coordination data for borrowing the target object for storage coordination of other buildings specifically comprises the following steps:

acquiring the stock quantity of target articles of a target building and marking the stock quantity as U2;

acquiring the historical loss of a target object of a target building, and marking the historical loss as V2;

acquiring historical peak use time periods of target users of the target building on target articles, and marking the historical peak use time periods as (T3 and T4);

the method comprises the steps of obtaining the usage amount of a target object by a target user of a target building, and marking the usage amount as S2;

if the consumption S2+ historical consumption V2 is less than or equal to the inventory U2, judging that the target articles of the target building are enough to be used without coordination borrowing;

if the using amount S < 2+ > historical loss amount V < 2+ > is larger than the stock amount U < 2 >, judging that the target articles of the target building are in tension, and coordinating borrowing;

Acquiring the position of a target building, and determining the position as a first position;

setting a coordination distance, wherein the coordination distance is the distance between the office point which is the same area with the office point of the user and is farthest away from the office point of the user in other office points of the work unit which do not need to apply coordination borrowing through an upper department under the same grade obtained by the work unit of the user;

forming a coordination range by taking the first position as an origin and the coordination distance as a radius;

acquiring the positions of all other buildings in the coordination range, and determining the positions as second positions;

calculating the distance between the first position and each second position, determining the distance as a target distance, and marking the target distance as P;

comparing the values of all the target distances P, sequencing the values in sequence from small to large, and determining the target distance P with the smallest value as the nearest target distance;

extracting second positions corresponding to all the nearest target distances, and determining the second positions as target coordination positions;

acquiring the number of target coordination positions, and determining the number as the target coordination number;

if the target coordination quantity-1 is smaller than the judgment value, not forming judgment;

if the target coordination number-1=the judgment value, taking the building corresponding to the target coordination position as a target coordination building for coordinating and borrowing the target object;

If the target coordination building has no target article, selecting the building with the shortest target distance in the rest buildings in the coordination range as an alternative coordination building borrowing target article;

executing a borrowing judgment strategy when borrowing the target object;

and if the target coordination number-1 is larger than the judgment value, executing a coordination judgment strategy.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the executing coordination judgment strategy specifically comprises the following steps:

acquiring a first position and all target coordination positions;

acquiring a using place of a target user and determining the using place as a third position;

connecting the first position and the third position to form a target straight line;

the target coordination position on one side of the target straight line is set as a first target coordination position;

taking each first target coordination position as an origin, and making a vertical line to a target straight line to be defined as a target vertical line;

calculating the length of each target vertical line and determining the length as a target length R;

comparing the values of all the target lengths R, sequentially sequencing the values from small to large to form a target coordination sequence, determining a first target coordination position corresponding to the target length R with the smallest value as the nearest coordination position, and determining a first target coordination position corresponding to the target length R with the largest value as the farthest coordination position;

Extracting a building corresponding to the nearest coordination position, and determining the building as a target coordination building;

extracting a building corresponding to the target length of the second order in the target coordination sequence, and determining the building as an alternative coordination building;

if the target coordination building does not have the target object, borrowing the target object from the alternative coordination building;

if all the buildings in the target coordination sequence do not have target articles, selecting the building with the shortest target distance in the rest buildings in the coordination range as an alternative coordination building borrowing target article;

and executing borrowing judgment strategies when borrowing the target object.

As an alternative scheme of the intelligent monitoring management system based on the Internet of things, the invention comprises the following steps: the executing borrowing judgment strategy specifically comprises the following steps:

s1, acquiring a target coordinated building;

s2, obtaining alternative coordination buildings;

s3, acquiring storage history data of the target coordination building, wherein the storage history data comprise the use amount of target articles of the target coordination building, and the use amount is recorded as S1;

s4, acquiring storage history data of the target coordination building, wherein the storage history data comprise peak use time periods of target objects of the target coordination building, and the peak use time periods are marked as (T1, T2);

s5, acquiring the inventory quantity of target articles of the target coordination building, and marking the inventory quantity as U1;

S6, acquiring the historical loss of a target object of the target coordination building, and recording the historical loss as V1;

s7, if the time periods (T1 and T2) and the time periods (T3 and T4) are coincident, judging whether the target coordination building is in tension or not;

s8, if the using amount S1+ historical loss amount V1 is less than or equal to the stock amount U1, no judgment is formed;

s9, judging that the first judgment condition is met if the using amount S1+ historical consumption V1 is larger than the stock U1;

s10, if the using amount S2+ historical consumption V2-stock quantity U2 is more than or equal to stock quantity U1- (using amount S1+ historical consumption V1), no judgment is formed;

s11, if the using amount S2+ historical consumption V2-stock quantity U2 is smaller than the stock quantity U1- (the using amount S1+ historical consumption V1), judging that the second judging condition is met;

s12, if only the second judging condition is met, judging that the target coordination building is in tension, converting the alternative coordination building into the target coordination building, and executing S1-S11;

s13, if the first judging condition and the second judging condition are not met, judging that the target coordination building is in tension, converting the alternative coordination building into the target coordination building, and executing S1-S11;

s14, if only the first judging condition is met, judging that the target coordination building is in tension, converting the alternative coordination building into the target coordination building, and executing S1-S11;

S15, if the first judging condition and the second judging condition are met at the same time, judging that the target coordination building is not tensed to use;

s16, acquiring historical return time and historical promise return time of a target user;

s17, if the historical return time=the historical promise return time, not performing calculation;

s18, if the historical return time is less than the historical promised return time, the target coordination building is used by a target user of the target building;

s19, if the historical return time is more than the historical promised return time, the target coordination building is not borrowed, the alternative coordination building is converted into the target coordination building, and S1-S18 are executed;

s20, if the time periods (T1 and T2) and the time periods (T3 and T4) do not coincide, acquiring the historical return time and the historical promise return time of the target user;

s21, if the historical return time=the historical promise return time, not performing calculation;

s22, if the historical return time is less than the historical promised return time, the target coordination building is used by a target user of the target building;

s23, if the historical return time is greater than the historical promised return time, the target coordination building is not borrowed, the alternative coordination building is converted into the target coordination building, and S1-S22 are executed.

The invention has the following beneficial effects:

1. according to the intelligent monitoring management system based on the Internet of things, the position of the target object on the target goods shelf is determined according to the size and the weight of the target object and the condition of the stored goods in the warehouse by acquiring the size of the target object, the size of the goods shelf and the stored goods, so that warehouse management is facilitated.

2. According to the intelligent monitoring management system based on the Internet of things, through obtaining the weight of a target object and the position of the gravity center point when the center of the target goods shelf is balanced, the gravity center point position of the target goods shelf after the target object is placed is analyzed and judged according to the weight of goods stored on the target goods shelf and the weight of the target object, and whether the goods shelf is tipped over or not caused by placing the target object at the position is judged, so that more goods shelf tipping is caused, and accidents are prevented.

3. According to the intelligent monitoring management system based on the Internet of things, whether the target user needs to coordinate with the storage of other buildings or not is determined according to the historical use data of the target user on the target objects and the historical use data of the crowd in other buildings on the target objects, the historical use data of the target user on the target objects and the current inventory quantity, the peak use time period is determined according to the use condition of the target objects of other buildings and the historical consumption quantity of the target objects, and accordingly whether the use of the target objects in other buildings is tension or not is analyzed and judged, and then the position of the other buildings with the shortest borrowing distance and capable of borrowing is adaptively determined, so that the storage of the other buildings is coordinated and borrowed when the quantity of the target objects is insufficient for the target user.

Drawings

FIG. 1 is a block diagram of an intelligent monitoring management system based on the Internet of things;

FIG. 2 is a schematic diagram of a placeable space according to the present invention;

FIG. 3 is a schematic view of a second center of gravity when the center of gravity of the present invention is balanced;

FIG. 4 is a schematic view of a second center of gravity when the center of gravity of the present invention is unbalanced;

fig. 5 is a schematic diagram of a targeted coordinated building and an alternative coordinated building of the present invention.

Detailed Description

An intelligent monitoring management system based on internet of things, referring to fig. 1, includes:

Through the module, the position of the target object placed on the target goods shelf is determined according to the size and the weight of the target object and the conditions of goods stored in the warehouse, the gravity center position of the target goods shelf after the target object is placed is analyzed and judged, and whether the goods shelf is overturned or not is judged to be caused by placing the target object on the position, so that more goods shelf is overturned, accidents are prevented, whether the target object needs to be borrowed in a coordinated manner with the warehouse of other buildings is determined according to the historical use data of the target object by the target user and the current stock quantity, the peak use time period is determined according to the use cycle of the target object by the target user and the crowd in other buildings, whether the use of the target object in other buildings is tense is analyzed and judged, and the position of other buildings with the shortest borrowing distance and capable of borrowing is determined in a suitable manner, so that the target object quantity is not enough for the target user to use the warehouse of other buildings in a coordinated manner.

In a second embodiment, the present embodiment is an improvement made on the basis of the first embodiment, referring to fig. 2, and the intelligent monitoring and management system based on the internet of things, where the obtaining target warehouse data of a target building specifically includes:

Acquiring the number of shelves of a warehouse in a target building, and recording as B (B1, bn), wherein B1-Bn are the numbers of all the shelves in the warehouse;

acquiring the length, the width and the layer number of each shelf, and respectively recording as C (C1, cn), D (D1, dn), F (F1 (F11-F1 n), fn (Fn 1-Fnn)), wherein C1-Cn is the length corresponding to each shelf in the warehouse, D1-Dn is the width corresponding to each shelf in the warehouse, F1-F1 is the layer number corresponding to each shelf in the warehouse, fn1-Fnn and Fn1-Fnn in F1-Fn are the corresponding numbers of each layer under the layer number corresponding to each shelf, as shown in FIG. 2, wherein the shelf is 5 layers, as shown in the figure, F1 is 5, and F11-F15 are the first layer to the fifth layer from top to bottom in sequence;

In the third embodiment, referring to fig. 2-4, analysis data is formed according to the target warehouse data to determine the placement position of the target article;

acquiring the weight of a target object, and marking the weight as G;

Acquiring a placeable space in a target building;

executing a target object placement determination strategy;

and extracting the target goods shelf, the goods shelf corresponding to the target layer number in the storage data set and the layer number, and placing the target goods in a third layer of the B1 goods shelf in the target building warehouse if the target goods shelf is B1 and the target layer number is F1F 13.

The method for obtaining the placeable space in the target building specifically comprises the following steps:

acquiring a storage data set of a target building;

extracting a goods shelf B and a layer number F of the goods which are not placed in the warehouse, and determining the goods shelf B and the layer number F as a target judgment goods shelf and a target judgment layer number, wherein the target judgment layer number is a specific certain layer of the target judgment goods shelf;

setting the placement quantity, namely I2, wherein the placement quantity is the maximum quantity of the placement of the articles on each layer of each goods shelf, such as the maximum quantity of 3 articles on each layer of each goods shelf;

setting a first judging number, a second judging number and a third judging number which are respectively marked as I3, I4 and I5, wherein if the placement number I2 is 3, the first judging number is 0, the second judging number is 1, and the third judging number is 2, so as to determine the number of articles which can be placed again at present in the target judging layer number of each target judging shelf;

acquiring the length of the placed article of the target judgment layer number of the target judgment shelf, which is denoted by K1, as shown in the length of the placed article in FIG. 2;

calculating the idle length of the target judgment layer number of the target judgment shelf, which is marked as M, wherein the idle length M=the shelf length C-the length K1 of the placed article, as shown in the idle length in fig. 2;

acquiring the length of the placed article of the target judgment layer number of the target judgment shelf, and marking the length as K2, wherein the length of the placed article is shown in fig. 2;

calculating an idle length M of the target judgment layer number of the target judgment shelf, wherein the idle length M is equal to the shelf length C which is equal to the length K2 of the placed article, as shown in the idle length in fig. 2;

acquiring the length of the placed article of the target judgment layer number of the target judgment shelf, and marking the length as K3, wherein the length of the placed article is shown in fig. 2;

Calculating an idle length M of the target judgment layer number of the target judgment shelf, wherein the idle length M is equal to the shelf length C which is equal to the length K3 of the placed article, as shown in the idle length in fig. 2;

The implementation of the target object placement determination strategy specifically includes:

acquiring a placeable spatial data set;

setting a length difference threshold value, wherein the length difference threshold value is 0, so as to judge whether the idle length is the length capable of placing the target object;

setting a width difference threshold value, wherein the width difference threshold value is 0, so as to judge whether the width of the goods shelf is the width capable of placing the target goods;

setting a height difference threshold value which is 0 to judge whether the height of the shelf layer is the height capable of placing the target object;

acquiring all target judgment shelves and target judgment layer numbers which reach the first judgment result E11, the second judgment result E21 and the third judgment result E31 at the same time, and determining the target judgment shelves and the target judgment layer numbers as placeable shelves and placeable layer numbers, wherein the placeable layer numbers are a specific layer of the placeable shelves;

and executing a gravity center simulation strategy.

The gravity center simulation strategy is executed, and specifically comprises the following steps:

building a gravity center simulation model for each placeable shelf, as shown in fig. 3-4;

acquiring a gravity center point of a placeable goods shelf when no goods exist, and determining the gravity center point as a first gravity center point, wherein the first gravity center point is shown in fig. 3-4;

forming an offset range by taking the first gravity center point as an origin and taking the balance distance as a radius, wherein the offset range is shown in fig. 3-4;

acquiring four corner points capable of placing a shelf, and respectively determining the four corner points as a first corner point, a second corner point, a third corner point and a fourth corner point;

connecting the first corner point with the second corner point to form a first connecting line;

connecting the third corner point with the fourth corner point to form a second connecting line;

taking the first gravity center point as an origin, respectively making vertical lines to the first connecting line and the second connecting line, and respectively determining the first vertical line and the second vertical line;

respectively acquiring an intersection point of the first vertical line and the first connecting line and an intersection point of the second vertical line and the second connecting line, and respectively determining the intersection point as a first hanging point and a second hanging point;

the first hanging point and the second hanging point are connected to form a third connecting line, and the shelf capable of being placed is divided into two areas which are respectively defined as a first area and a second area;

Acquiring the weight G, the length L, the width W and the height H of a target object;

simulating and placing the target object on the layer number which can be placed on the shelf;

acquiring a region in which the target object is placed in a simulation manner, wherein the region in which the target object is placed in a simulation manner is a first region, and the region in which the target object is not placed in a simulation manner is a second region;

connecting the first corner point with the second vertical point to form a first analysis line;

connecting the fourth corner point with the first vertical point to form a second analysis line;

extracting an intersection point of the first analysis line and the second analysis line, wherein the intersection point is a center of gravity point of the second area and is determined as a third center of gravity point;

acquiring the net weight of a shelf capable of being placed, and recording as GH;

calculating a gravity center value of the first gravity center point, determining the gravity center value as a first gravity center value, and recording the first gravity center value as GZ1, wherein the first gravity center value gz1=gh;

calculating a gravity center value of the third gravity center point, determining the gravity center value as a third gravity center value, and recording the third gravity center value as GZ3, wherein the third gravity center value GZ3 = GH/2;

acquiring the number of layers of the placeable shelf for simulating placement of the target object, and determining the number of layers as the target simulation number of layers;

the other areas of the first area, from which the target simulation layer number is removed, are defined as a third area;

connecting the second corner point with the third corner point to form a fourth connecting line;

extracting intersection points of the shelf laminate corresponding to the target simulation layer number, the third connecting line and the fourth connecting line, and respectively determining the intersection points as a first analysis point and a second analysis point;

Connecting the first analysis point with the third corner point to form a third analysis line;

connecting the second analysis point with the second vertical point to form a fourth analysis line;

extracting an intersection point of the third analysis line and the fourth analysis line, wherein the intersection point is a center of gravity point of the third area and is defined as a fourth center of gravity point;

the total height of the shelf capable of being placed is obtained and is set as a first height which is marked as A1;

acquiring the height between a second analysis point and a third corner point in the placeable shelf, determining the height as a second height, and marking the second height as A2;

calculating a center of gravity value of the fourth center of gravity point, and determining the center of gravity value as a fourth center of gravity value, and recording the fourth center of gravity value as GZ4, wherein the fourth center of gravity value GZ 4= (a2≡a1) ×gz3;

connecting the first vertical point and the second analysis point to form a fifth analysis line;

connecting the second angular point with the first analysis point to form a sixth analysis line;

the area of the target simulation layer number in the first area is defined as a fourth area;

extracting an intersection point of the fifth analysis line and the sixth analysis line, wherein the intersection point is a center of gravity point of the fourth area and is defined as a fifth center of gravity point;

acquiring the height between a second angular point and a second analysis point in the placeable shelf, and determining the height as a third height, and marking the third height as A3;

calculating a gravity center value of a fifth gravity center point, determining the gravity center value as a fifth gravity center value, and marking the fifth gravity center value as GZ5, wherein the fifth gravity center value GZ 5= (A3/A1) multiplied by GZ 3+the weight G of the target object;

Connecting a fourth center of gravity point and a fifth center of gravity point to form a seventh analysis line, obtaining the length of the seventh analysis line, determining the length as a first analysis length, and marking the first analysis length as LF1;

calculating a gravity center value of a gravity center point of the first region, determining a sixth gravity center value, and recording the sixth gravity center value as GZ6, wherein the sixth gravity center value gz6=a fifth gravity center value gz5+a fourth gravity center value GZ4;

calculating a first weight ratio, denoted as GB1, the first weight ratio GB1 = fifth centroid value GZ5 ≡sixth centroid value GZ6;

calculating a second analysis length, denoted as LF2, the second analysis length lf2=the first analysis length lf1×the first weight ratio GB1;

forming a first analysis range by taking a fourth center point as an origin and taking a second analysis length LF2 as a radius;

extracting an intersection point of the first analysis range and the seventh analysis line, wherein the intersection point is a gravity center point of the first area and is defined as a sixth gravity center point;

connecting a sixth center point with the third center point to form an eighth analysis line, obtaining the length of the eighth analysis line, determining the length as a third analysis length, and marking the third analysis length as LF3;

calculating a gravity center value of a gravity center point of the shelf capable of being placed when the object is placed, determining the gravity center value as a second gravity center value, and marking the second gravity center value as GZ2, wherein the second gravity center value GZ2 = the first gravity center value GZ1 plus the weight G of the object;

calculating a second weight ratio, denoted as GB2, the second weight ratio GB2 = sixth centroid value gz6 +% second centroid value GZ2;

Calculating a fourth analysis length, denoted as LF4, the fourth analysis length lf4=the third analysis length lf3×the second weight ratio GB2;

forming a second analysis range by taking the third center point as an origin and the fourth analysis length LF4 as a radius;

extracting an intersection point of the second analysis range and the eighth analysis line, wherein the intersection point is a gravity center point of the shelf capable of being placed when the object article exists, and is determined as a second gravity center point, as shown by the second gravity center point in fig. 3-4;

setting a judgment value which is 0 and is used for comparing the sizes of two data or comparing whether the two data are equal, wherein all the judgment values in the patent are the same judgment value;

setting a shelf number judgment value, wherein the shelf number judgment value is 1, and is used for judging whether the shelf capable of placing the target object is single or multiple, if the shelf is single, judging the layer number capable of placing the shelf, and if the shelf is multiple, randomly selecting;

setting a space quantity judgment value, wherein the space quantity judgment value is 1, and is used for judging whether the space for placing the target object is single or multiple, if only one space can be placed, the space is directly placed, and if a plurality of spaces can be placed, the space is randomly selected;

In a fourth embodiment, referring to fig. 5, in the improvement made on the basis of the third embodiment, the obtaining the historical data of the target user on the target object forms speculative coordination data for borrowing the target object for storage coordination of other buildings, which specifically includes:

acquiring the position of a target building, and determining the position as a first position, wherein the first position is shown in fig. 5;

Forming a coordination range by taking the first position as an origin and the coordination distance as a radius, as shown in the coordination range in fig. 5;

acquiring the positions of all other buildings in the coordination range, and determining the positions as a second position, wherein the second position is shown in fig. 5;

calculating the distance between the first position and each second position, and determining the distance as a target distance, and marking the target distance as P, as shown in the target distance in FIG. 5;

comparing the values of all the target distances P, sequencing the values in sequence from small to large, and determining the target distance P with the smallest value as the nearest target distance, as shown in the nearest target distance in FIG. 5;

extracting second positions corresponding to all the nearest target distances, and determining the second positions as target coordination positions, wherein the target coordination positions are shown in fig. 5;

Executing a borrowing judgment strategy when borrowing the target object;

The embodiment further provides that the executing the coordination determination policy specifically includes:

acquiring a first position and all target coordination positions;

acquiring a using place of a target user, and determining the using place as a third position, wherein the third position is shown in fig. 5;

connecting the first position and the third position to form a target straight line, as shown by the target straight line in fig. 5;

the target coordination position on one side of the target straight line is set as a first target coordination position, as shown in the first target coordination position in fig. 5;

and executing borrowing judgment strategies when borrowing the target object.

The embodiment further provides that the executing the borrowing determination policy specifically includes:

s1, acquiring a target coordinated building;

s2, obtaining alternative coordination buildings;

According to the embodiment, the position of the target object placed on the target goods shelf is determined according to the size and weight of the target object and the condition of goods stored in a warehouse, the gravity center position of the target goods shelf after the target object is placed is analyzed and judged, and whether the goods shelf is tilted or not is judged to be caused by placing the target object on the position, so that more goods shelf is prevented from being tilted, whether the target object needs to be borrowed in a coordinated manner with the warehouse of other buildings is determined according to the historical use data of the target object by a target user and the current stock quantity, the peak use time period is determined according to the use cycle of the target object by the target user and the crowd in other buildings, whether the use of the target object in other buildings is tension is analyzed and judged, and the position of other buildings with the shortest borrowing distance and capable of borrowing is determined in a suitable manner, so that the target object is not enough to be borrowed from the warehouse of other buildings.

Claims

1. An intelligent monitoring management system based on thing networking, its characterized in that: comprising the following steps:

2. The intelligent monitoring management system based on the internet of things according to claim 1, wherein: the acquiring the target warehouse data of the target building specifically comprises the following steps:

3. The intelligent monitoring management system based on the internet of things according to claim 2, wherein: forming analysis data according to the target warehouse data to determine the placement position of the target object;

acquiring the weight of a target object, and marking the weight as G;

acquiring a placeable space in a target building;

executing a target object placement determination strategy;

4. The intelligent monitoring and management system based on the internet of things according to claim 3, wherein: the method for obtaining the placeable space in the target building specifically comprises the following steps:

acquiring a storage data set of a target building;

setting the placement number, and marking as I2;

5. The intelligent monitoring and management system based on the internet of things according to claim 3, wherein: the implementation target object placement judgment strategy specifically comprises the following steps:

acquiring a placeable spatial data set;

setting a length difference threshold;

setting a width difference threshold;

setting a height difference threshold;

and executing a gravity center simulation strategy.

6. The intelligent monitoring and management system based on the internet of things according to claim 5, wherein: the executing the gravity center simulation strategy specifically comprises the following steps:

establishing a gravity center simulation model for each placeable shelf;

setting a judgment value;

setting a shelf quantity judgment value;

setting a space quantity judgment value;

7. The intelligent monitoring and management system based on the internet of things according to claim 6, wherein: the method for obtaining the historical data of the target user on the target object forms speculative coordination data for borrowing the target object for storage coordination of other buildings specifically comprises the following steps:

executing a borrowing judgment strategy when borrowing the target object;

8. The intelligent monitoring and management system based on the internet of things according to claim 7, wherein: the executing coordination judgment strategy specifically comprises the following steps:

acquiring a first position and all target coordination positions;

and executing borrowing judgment strategies when borrowing the target object.

9. The intelligent monitoring and management system based on the internet of things according to claim 8, wherein: the executing borrowing judgment strategy specifically comprises the following steps:

s1, acquiring a target coordinated building;

s2, obtaining alternative coordination buildings;