CN117436851B - Garbage collection supervision method and system based on Internet of things - Google Patents

Garbage collection supervision method and system based on Internet of things Download PDF

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CN117436851B
CN117436851B CN202311457012.2A CN202311457012A CN117436851B CN 117436851 B CN117436851 B CN 117436851B CN 202311457012 A CN202311457012 A CN 202311457012A CN 117436851 B CN117436851 B CN 117436851B
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CN117436851A (en
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黄宇飞
刘书南
王金
何长虹
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Zhejiang Zhenshan Technology Co ltd
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Abstract

The invention discloses a garbage collection supervision method and system based on the Internet of things, and belongs to the technical field of garbage collection. The system comprises a data acquisition module, a data analysis module, an operation processing module and a visualization module; the data acquisition module is used for acquiring all the garbage collection point information and garbage collection vehicle information; the data analysis module analyzes the garbage collection point information, screens out garbage collection points with transportation requirements, analyzes the garbage collection vehicle information, and matches the garbage collection points with transportation requirements with proper garbage collection vehicles; the operation processing module is used for calculating a matching index between the garbage collection points and the matched garbage truck, selecting a transportation object for each garbage collection point according to the matching index, and generating a transportation task to be added into a transportation plan of the transportation object; the visualization module displays the position and the garbage loading capacity of each garbage collection point and the real-time position and the garbage loading capacity of all garbage collection vehicles in real time through a large screen of the data center.

Description

Garbage collection supervision method and system based on Internet of things
Technical Field
The invention relates to the technical field of garbage collection, in particular to a garbage collection supervision method and system based on the Internet of things.
Background
Waste recycling refers to a series of actions that collect, sort, dispose of and utilize waste. Along with the acceleration of the urban process and the increase of population, the garbage yield is also continuously increased, and the garbage recovery efficiency becomes a problem to be solved urgently. The transportation route and time of the garbage truck are optimized, the coverage range of the garbage collection point and the garbage collection efficiency are improved, and the garbage recycling efficiency can be effectively improved.
At present, in a traditional garbage recycling method, a garbage collection point is usually arranged in each residential area, and a garbage recycling center is used for arranging a fixed garbage truck to transport the garbage to each garbage collection point at intervals. This method has the following problems: 1. the total garbage collection speed of each garbage collection point is uneven due to different population densities. Some garbage collection points have large population density and large garbage loss, and the garbage collection speed is high; some garbage collection points have small population density and small garbage loss, and the garbage collection speed is low; the adoption of the traditional garbage recycling mode can lead to long-term stacking of garbage at some garbage collection points, and long-term dissatisfaction of garbage at some garbage collection points. 2. The garbage collection speed of each garbage collection point is obviously different in each time period due to the fact that the main ages or living habits of people are different. Some garbage collection points have more working crowds, and the garbage collection speeds in the daytime period and the evening period are obviously different; some garbage collection points have more people for cooking, and the garbage collection speeds of the dining time period and the non-dining time period are obviously different; the adoption of the traditional garbage recycling mode can lead to large difference in the garbage amount transported by the garbage truck in different time periods, and brings difficulty to transportation work. 3. The garbage collection vehicle cannot know the garbage amount of each garbage collection point, and only the site is known. This way of transporting the information block necessarily results in a macroscopic regulation of the transport scheme for the different transport demands of the individual refuse collection points being impossible. There is a need for a more efficient waste recycling solution to the above problems.
Disclosure of Invention
The invention aims to provide a garbage collection supervision method and system based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the garbage collection supervision method based on the Internet of things comprises the following steps:
s1, collecting information of all garbage collection points and garbage collection vehicle information;
s2, identifying garbage collection points with transportation requirements, and matching garbage collection points with garbage collection vehicles;
s3, calculating a matching index between the garbage collection point and the matched garbage truck so as to select a transportation object;
s4, generating a transportation task, adding the transportation task into a transportation plan of a transportation object, and executing transportation by the transportation object according to the transportation plan;
and S5, displaying dynamic information of all garbage collection points and garbage collection vehicles in real time by a visual large screen.
In S1, the garbage collection point information includes a position of each garbage collection point, a put log, and a maximum loading weight; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the garbage weight from zero, the weight value is collected through a weight sensor arranged at the bottom of the garbage collection container, and the maximum loading weight is the maximum weight of the garbage which can be loaded at the garbage collection point.
The garbage truck information includes an identifier, a real-time location, an actual loading weight, a transportation plan, and a maximum loading weight; the identifier is used for distinguishing different garbage truck, the actual loading weight refers to the actual weight of garbage loaded by the garbage truck, the transportation plan refers to a list of tasks executed by the garbage truck, the garbage truck executes transportation according to task information on the task list, and the maximum loading weight refers to the maximum weight of garbage which can be loaded by the garbage truck.
In S2, the specific steps are as follows:
s201, acquiring all historical release records in release logs under each garbage collection point, and recording the current time T a Setting a call duration T at the same time, and adding the current time to the call duration to obtain a cut-off time T end Retrieving slave T in each historical impression record a To T end And taking the extremely poor weight as a weight change value according to the weight in the time period, wherein each historical input record corresponds to one weight change value.
S202, summing weight change values of all historical delivery records in the delivery logs, and calculating an average value to obtain average increase weight, wherein each delivery log corresponds to one average increase weight, and the calculation formula is as follows:
in the formula, WG ave For average weight increase, the unit is kg, W max For T in history delivery record a To T end Maximum weight in kg, W during a period of time min For T in history delivery record a To T end The minimum weight in the time period is kg, and S is the historical input record number.
S203, acquiring a current throwing record in a throwing log under each garbage collection point, summing the maximum weight in the current throwing record and the average increment weight of the throwing log to obtain a predicted weight, judging whether the predicted weight is greater than or equal to the maximum loading weight of the corresponding garbage collection point, if so, marking the corresponding garbage collection point, and taking the cut-off time as the matching time P of the garbage collection point; and if not, not processing.
S204, regarding the marked garbage collection points as having transportation requirements, setting a section of transportation distance R as a radius by taking the positions of the garbage collection points having the transportation requirements as circle centers, and dividing a circular area for each garbage collection point having the transportation requirements as a transportation range area; and acquiring transportation plans of all the garbage collection vehicles, screening the garbage collection vehicles which are not performing transportation tasks, acquiring real-time positions of the garbage collection vehicles, and matching the garbage collection vehicles in a transportation range area with corresponding garbage collection points.
S205, setting a lowest matching number M, and marking the garbage collection points with the number of matched garbage truck smaller than the lowest matching number as abnormal; gradually increasing the transportation distance R of each abnormal garbage collection point until the number of garbage truck matched with the abnormal garbage collection point is no longer smaller than the lowest matching number, stopping increasing, and canceling the abnormal mark of the corresponding abnormal garbage collection point; and if the number of garbage collection vehicles matched with all the garbage collection points is not less than the minimum matching number M, finishing the matching.
In S3, the specific steps are as follows:
s301, acquiring a delivery log of a garbage collection point with a transportation requirement, searching the maximum weight of the current delivery record in the delivery log as the actual loading weight of the corresponding garbage collection point, substituting the actual loading weight of the garbage collection point, the actual loading weight of a matched garbage truck and the distance between the position of the garbage collection point and the real-time position of the matched garbage truck into a formula to obtain a matching index between the garbage collection point and each matched garbage truck, wherein the calculation formula is as follows:
wherein PPD is the index of match between the point of garbage collection and the matching garbage truck, ZCM is the maximum loading weight of the matching garbage truck, ZCS is the actual loading weight of the matching garbage truck, ZD is the actual loading weight of the point of garbage collection, u is the distance influencing coefficient, c is the position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) To match the real-time position coordinates of the garbage truck.
S302, establishing a matched vehicle set for each garbage collection point with transportation requirements, associating identifiers of matched garbage collection vehicles with corresponding matching indexes, and sequentially putting the identifiers and the corresponding matching indexes into the matched vehicle sets of the corresponding garbage collection points according to the sequence of the matching indexes from large to small, wherein the sets comprise { (BSF) 1 ,PPD 1 ),(BSF 2 ,PPD 2 ),(BSF 3 ,PPD 3 ),...,(BSF n ,PPD n ) Wherein n represents the number of matched vehicle aggregate elements, BSF n Representing the nth identifier, PPD n Representing an nth matching index, each garbage collection point corresponding to a set of matching vehicles.
S303, acquiring the matching time P of each garbage collection point with transportation requirements, and recording the current time T b Substituting the matching threshold value into a formula, and calculating the matching threshold value of each garbage collection point; the formula is as follows:
wherein PYZ is a matching threshold value and PBZ is a standard matching index.
S304, marking identifiers with all matching indexes larger than the matching threshold value of the corresponding garbage collection points in a matched vehicle set of the garbage collection points, and selecting the marked identifier with the highest ranking as a preselected object of the garbage collection points; a garbage collection point having a preselected object is placed into a preselected collection.
S305, judging whether the preselected objects of all the garbage collection points in the preselected set have the same condition, and if so, entering a step S307; if the result is yes, the matching threshold value of each garbage collection point with the same preselected object is obtained, the preselected object and the matching index of each garbage collection point are brought into a formula together, and the priority index of each garbage collection point is calculated; the calculation formula is as follows:
Wherein YX is a priority index and f is a constant.
S306, comparing the priority indexes of the garbage collection points with the same pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object from the matched vehicle sets of all the garbage collection points, deleting the matched vehicle set of the garbage collection point with the transportation object, and entering into step S304 to reselect the pre-selected object for other garbage collection points with low priority indexes.
S307, changing the preselection objects of all the garbage collection points into transportation objects.
In S4, a transport task is generated for each garbage collection point with a transport object, and the transport task is added to a transport plan of a garbage truck corresponding to the transport object, and the garbage truck executes the transport task according to information on the transport plan.
The garbage collection supervision system based on the Internet of things comprises a data acquisition module, a data analysis module, an operation processing module and a visualization module.
The data acquisition module is used for acquiring garbage collection point information and garbage truck information; the data analysis module analyzes the garbage collection point information, screens out garbage collection points with transportation requirements, analyzes the garbage collection vehicle information, and matches the garbage collection points with transportation requirements with the garbage collection vehicle; the operation processing module is used for calculating a matching index between the garbage collection points and the matched garbage truck, selecting a transportation object for each garbage collection point according to the matching index, and generating a transportation task to be added into a transportation plan of the transportation object; the visualization module is used for displaying dynamic information of all garbage collection points and garbage collection vehicles.
The data acquisition module comprises a garbage collection point information acquisition unit and a garbage truck information acquisition unit.
The garbage collection point information acquisition unit is used for acquiring the position, the put log and the maximum loading weight of each garbage collection point; the position refers to a fixed position of the garbage collection point; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the weight of garbage from zero, and the weight value is acquired through a weight sensor arranged at the bottom of the garbage collection container; the maximum loading weight refers to the maximum weight of the refuse that can be loaded by the refuse collection point.
When the garbage at the garbage collection point is transported by the garbage truck, the weight is cleared, the current throwing record is automatically used as the historical throwing record, and a new current throwing record is regenerated. When someone puts garbage into the garbage collection container, the weight and the time of putting garbage are automatically recorded. Only one current release record and a plurality of historical release records exist in the release log.
The garbage truck information acquisition unit is used for acquiring identifiers, real-time positions, actual loading weights, transportation plans and maximum loading weights of all garbage trucks; the identifier is used for distinguishing different garbage truck; the real-time position refers to the GPS dynamic position of each garbage truck; the actual loading weight refers to the actual weight of the garbage truck loading garbage; the transportation plan refers to a list of tasks executed by the garbage truck; the maximum loading weight refers to the maximum weight of the garbage truck that can load garbage.
The data analysis module comprises a garbage collection point screening unit and a garbage truck matching unit.
The garbage collection point screening unit is used for screening garbage collection points with transportation requirements. First, the current time T is recorded a Setting a call duration at the same time, and setting the current time T a Adding the call duration to obtain the deadline; secondly, acquiring all historical release records in release logs of each garbage collection point, and respectively calculating the current time T in each historical release record a The weight range in the time period reaching the deadline is summed up, and the average value is calculated as the average increment weight of the release log; and finally, summing the maximum weight in the current delivery record under the delivery log and the average increment weight of the corresponding delivery log to obtain a predicted weight, screening out a garbage collection point corresponding to the predicted weight which is greater than or equal to the maximum loading weight, and taking the screened garbage collection point as the garbage collection point with the transportation requirement.
The current time and the deadline are the time of a day, and the calling duration is less than 24 hours.
The call duration is set for a certain waiting transportation time for the garbage collection points, and the specific value is inversely proportional to the number of the garbage collection vehicles and directly proportional to the number of the garbage collection points. Avoiding the situation that the garbage reaches the maximum loading weight at the garbage collection point in the calling time.
The garbage truck matching unit is used for matching the garbage truck for the garbage collection points with transportation requirements. Firstly, setting a section of transportation distance as a radius by taking the position of a garbage collection point with transportation requirements as a circle center, and dividing a circular area for each garbage collection point with transportation requirements as a transportation range area; secondly, matching the garbage collection vehicles which are in the transportation range area and are not performing the transportation task with the corresponding garbage collection points, setting a lowest matching number, and gradually increasing the transportation distance of the garbage collection points with the matched garbage collection vehicle number smaller than the lowest matching number until the matched garbage collection vehicle number is no longer smaller than the lowest matching number; and finally, if the number of garbage collection vehicles matched with all the garbage collection points is not less than the lowest matching number, finishing the matching.
The transportation distance is set so that each garbage collection point can be matched with a certain number of garbage collection vehicles, and the value is in direct proportion to the calling time and the running speed of the garbage collection vehicles. Different transportation distances are set for different garbage collection points, so that the number of garbage collection points matched with garbage collection vehicles is not less than the lowest matching number.
The operation processing module comprises a transportation object selection unit and a transportation task generation unit.
The transportation object selection unit is used for selecting a transportation object for each garbage collection point with transportation requirements.
Firstly, taking the maximum weight of a current throwing record in a throwing log with a garbage collection point with a transportation requirement as the actual loading weight ZD of the corresponding garbage collection point, and simultaneously obtaining the maximum loading weight ZCM and the actual loading weight ZCS of a garbage collection point matched garbage truck to be substituted into a formula to calculate a matching index PPD, wherein the formula is as follows:where u is a distance influence coefficient, c is a position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) To match the real-time position coordinates of the garbage truck.
Second, record the current time T b Respectively calculating the current time T b Obtaining a residual time length by the difference value of the matching time of each garbage collection point with transportation requirements, dividing each residual time length by the calling time length, and multiplying the residual time length by a standard matching index again to obtain a matching threshold value, wherein each garbage collection point with transportation requirements corresponds to one matching threshold value; establishing a matched vehicle set for each garbage collection point with transportation requirements, associating identifiers of matched garbage collection vehicles with corresponding matching indexes, and sequentially putting the identifiers into the matched vehicle sets of the corresponding garbage collection points according to the sequence from the big to the small of the matching indexes; the identifier of the set of matching vehicles that is top ranked and has a matching index greater than a matching threshold for the corresponding garbage collection point is selected as the pre-selected object.
Since the positions of the garbage collection vehicles are constantly changed and the garbage collection vehicles which are performing the transportation tasks are not matched, there is a certain variation in the garbage collection vehicles which can be matched with each garbage collection point. The setting of the matching threshold is to enable each garbage collection point to be matched with the garbage truck with the highest matching index, and the matching threshold of each garbage collection point gradually approaches the matching time along with time and gradually decreases to zero, so that the garbage collection points can be matched with the garbage truck finally.
Then, when the preselected objects of the garbage collection points are the same, the matching threshold PYZ of the garbage collection points with the same preselected objects and the matching index PPD of the preselected objects and the garbage collection points are brought into a formula, and the priority index YX of the garbage collection points is calculated, wherein the formula isWhere f is a constant.
Under the condition that the same preselected objects exist at different garbage collection points, the priority index is used as a judging index, the preselected objects can be preferentially distributed to time urgency, and the garbage collection points with high matching indexes are used as matching objects.
And finally, comparing the priority indexes of the garbage collection points with the same pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object in the matched vehicle set of all the garbage collection points, reselecting the pre-selected object and judging whether the same condition exists at the garbage collection point with the low priority index, continuously calculating the priority index to determine the attribution of the transportation object until the pre-selected object of each garbage collection point is different, and changing the pre-selected object of the rest garbage collection points into the transportation object.
The transportation task generating unit is used for generating transportation tasks for each garbage collection point with the transportation objects and adding the transportation tasks into a transportation plan of the garbage truck corresponding to the transportation objects.
The visualization module displays the position and the garbage loading capacity of each garbage collection point and the real-time position and the garbage loading capacity of all garbage collection vehicles in real time through a large screen of the data center.
Compared with the prior art, the invention has the following beneficial effects:
1. accurate demand recognition: the method for judging the transportation demand of the garbage collection point by adopting historical data and fixed time. By setting the calling time length, enough waiting transportation time is reserved for the garbage collection point; and calculating average increase weight according to the historical input records, and predicting whether the weight of the garbage collection point in the calling time exceeds the standard so as to realize accurate identification of the transportation demand.
2. Efficient matching system: the garbage collection point with the transportation requirement is divided into a transportation range area according to the position of the garbage collection point, a certain number of garbage collection vehicles are matched for the garbage collection point according to the state of an execution task, then the matching index is calculated according to the loadable garbage weight of the garbage collection vehicle and the distance, the matching degree between the garbage collection point and the garbage collection vehicle is displayed efficiently and intuitively, the matching threshold value which changes along with time is set finally, and a transportation object with high matching index can be selected for the garbage collection point as much as possible.
3. Reasonable priority principle: when the same preselected object exists at the garbage collection point, the preselected object is needed to be judged more at the garbage collection point by adopting the mode of the ratio of the matching index to the matching threshold value, and transportation resources are reasonably distributed under the condition that the number of garbage collection vehicles is limited.
In conclusion, compared with the traditional technology, the garbage recycling method has the advantages of accurate requirement recognition, efficient matching system and reasonable priority principle, and can improve garbage recycling efficiency.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow diagram of a garbage collection supervision method based on the Internet of things;
fig. 2 is a schematic structural diagram of the garbage collection supervision system based on the internet of things.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a garbage collection supervision method based on the internet of things, which comprises the following steps:
s1, collecting information of all garbage collection points and garbage collection vehicle information;
s2, identifying garbage collection points with transportation requirements, and matching garbage collection points with garbage collection vehicles;
s3, calculating a matching index between the garbage collection point and the matched garbage truck so as to select a transportation object;
s4, generating a transportation task, adding the transportation task into a transportation plan of a transportation object, and executing transportation by the transportation object according to the transportation plan;
and S5, displaying dynamic information of all garbage collection points and garbage collection vehicles in real time by a visual large screen.
In S1, the garbage collection point information includes a position of each garbage collection point, a put log, and a maximum loading weight; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the garbage weight from zero, the weight value is collected through a weight sensor arranged at the bottom of the garbage collection container, and the maximum loading weight is the maximum weight of the garbage which can be loaded at the garbage collection point.
The garbage truck information includes an identifier, a real-time location, an actual loading weight, a transportation plan, and a maximum loading weight; the identifier is used for distinguishing different garbage truck, the actual loading weight refers to the actual weight of garbage loaded by the garbage truck, the transportation plan refers to a list of tasks executed by the garbage truck, the garbage truck executes transportation according to task information on the task list, and the maximum loading weight refers to the maximum weight of garbage which can be loaded by the garbage truck.
In S2, the specific steps are as follows:
s201, acquiring all historical release records in release logs under each garbage collection point, and recording the current time T a Setting a call duration T at the same time, and adding the current time to the call duration to obtain a cut-off time T end Retrieving slave T in each historical impression record a To T end And taking the extremely poor weight as a weight change value according to the weight in the time period, wherein each historical input record corresponds to one weight change value.
S202, summing weight change values of all historical delivery records in the delivery logs, and calculating an average value to obtain average increase weight, wherein each delivery log corresponds to one average increase weight, and the calculation formula is as follows:
in the formula, WG ave For average weight increase, the unit is kg, W max For T in history delivery record a To T end Maximum weight in kg, W during a period of time min For T in history delivery record a To T end The minimum weight in the time period is kg, and S is the historical input record number.
S203, acquiring a current throwing record in a throwing log under each garbage collection point, summing the maximum weight in the current throwing record and the average increment weight of the throwing log to obtain a predicted weight, judging whether the predicted weight is greater than or equal to the maximum loading weight of the corresponding garbage collection point, if so, marking the corresponding garbage collection point, and taking the cut-off time as the matching time P of the garbage collection point; and if not, not processing.
S204, regarding the marked garbage collection points as having transportation requirements, setting a section of transportation distance R as a radius by taking the positions of the garbage collection points having the transportation requirements as circle centers, and dividing a circular area for each garbage collection point having the transportation requirements as a transportation range area; and acquiring transportation plans of all the garbage collection vehicles, screening the garbage collection vehicles which are not performing transportation tasks, acquiring real-time positions of the garbage collection vehicles, and matching the garbage collection vehicles in a transportation range area with corresponding garbage collection points.
S205, setting a lowest matching number M, and marking the garbage collection points with the number of matched garbage truck smaller than the lowest matching number as abnormal; gradually increasing the transportation distance R of each abnormal garbage collection point until the number of garbage truck matched with the abnormal garbage collection point is no longer smaller than the lowest matching number, stopping increasing, and canceling the abnormal mark of the corresponding abnormal garbage collection point; and if the number of garbage collection vehicles matched with all the garbage collection points is not less than the minimum matching number M, finishing the matching.
In S3, the specific steps are as follows:
s301, acquiring a delivery log of a garbage collection point with a transportation requirement, searching the maximum weight of the current delivery record in the delivery log as the actual loading weight of the corresponding garbage collection point, substituting the actual loading weight of the garbage collection point, the actual loading weight of a matched garbage truck and the distance between the position of the garbage collection point and the real-time position of the matched garbage truck into a formula to obtain a matching index between the garbage collection point and each matched garbage truck, wherein the calculation formula is as follows:
Wherein PPD is the index of match between the point of garbage collection and the matching garbage truck, ZCM is the maximum loading weight of the matching garbage truck, ZCS is the actual loading weight of the matching garbage truck, ZD is the actual loading weight of the point of garbage collection, u is the distance influencing coefficient, c is the position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) To match the real-time position coordinates of the garbage truck.
S302, establishing a matching vehicle for each garbage collection point with transportation requirementsA vehicle set, after the identifier of the matched garbage truck and the corresponding matching index are associated, the matched garbage truck is sequentially put into the matched vehicle set of the corresponding garbage collection point according to the sequence of the matching index from big to small, wherein the set comprises { (BSF) 1 ,PPD 1 ),(BSF 2 ,PPD 2 ),(BSF 3 ,PPD 3 ),...,(BSF n ,PPD n ) Wherein n represents the number of matched vehicle aggregate elements, BSF n Representing the nth identifier, PPD n Representing an nth matching index, each garbage collection point corresponding to a set of matching vehicles.
S303, acquiring the matching time P of each garbage collection point with transportation requirements, and recording the current time T b Substituting the matching threshold value into a formula, and calculating the matching threshold value of each garbage collection point; the formula is as follows:
wherein PYZ is a matching threshold value and PBZ is a standard matching index.
S304, marking identifiers with all matching indexes larger than the matching threshold value of the corresponding garbage collection points in a matched vehicle set of the garbage collection points, and selecting the marked identifier with the highest ranking as a preselected object of the garbage collection points; a garbage collection point having a preselected object is placed into a preselected collection.
S305, judging whether the preselected objects of all the garbage collection points in the preselected set have the same condition, and if so, entering a step S307; if the result is yes, the matching threshold value of each garbage collection point with the same preselected object is obtained, the preselected object and the matching index of each garbage collection point are brought into a formula together, and the priority index of each garbage collection point is calculated; the calculation formula is as follows:
wherein YX is a priority index and f is a constant.
S306, comparing the priority indexes of the garbage collection points with the same pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object from the matched vehicle sets of all the garbage collection points, deleting the matched vehicle set of the garbage collection point with the transportation object, and entering into step S304 to reselect the pre-selected object for other garbage collection points with low priority indexes.
S307, changing the preselection objects of all the garbage collection points into transportation objects.
In S4, a transport task is generated for each garbage collection point with a transport object, and the transport task is added to a transport plan of a garbage truck corresponding to the transport object, and the garbage truck executes the transport task according to information on the transport plan.
Referring to fig. 2, the invention provides a garbage collection supervision system based on the internet of things, which comprises a data acquisition module, a data analysis module, an operation processing module and a visualization module.
The data acquisition module is used for acquiring garbage collection point information and garbage truck information; the data analysis module analyzes the garbage collection point information, screens out garbage collection points with transportation requirements, analyzes the garbage collection vehicle information, and matches the garbage collection points with transportation requirements with the garbage collection vehicle; the operation processing module is used for calculating a matching index between the garbage collection points and the matched garbage truck, selecting a transportation object for each garbage collection point according to the matching index, and generating a transportation task to be added into a transportation plan of the transportation object; the visualization module is used for displaying dynamic information of all garbage collection points and garbage collection vehicles.
The data acquisition module comprises a garbage collection point information acquisition unit and a garbage truck information acquisition unit.
The garbage collection point information acquisition unit is used for acquiring the position, the put log and the maximum loading weight of each garbage collection point; the position refers to a fixed position of the garbage collection point; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the weight of garbage from zero, and the weight value is acquired through a weight sensor arranged at the bottom of the garbage collection container; the maximum loading weight refers to the maximum weight of the refuse that can be loaded by the refuse collection point.
When the garbage at the garbage collection point is transported by the garbage truck, the weight is cleared, the current throwing record is automatically used as the historical throwing record, and a new current throwing record is regenerated. When someone puts garbage into the garbage collection container, the weight and the time of putting garbage are automatically recorded. Only one current release record and a plurality of historical release records exist in the release log.
The garbage truck information acquisition unit is used for acquiring identifiers, real-time positions, actual loading weights, transportation plans and maximum loading weights of all garbage trucks; the identifier is used for distinguishing different garbage truck; the real-time position refers to the GPS dynamic position of each garbage truck; the actual loading weight refers to the actual weight of the garbage truck loading garbage; the transportation plan refers to a list of tasks executed by the garbage truck; the maximum loading weight refers to the maximum weight of the garbage truck that can load garbage.
The data analysis module comprises a garbage collection point screening unit and a garbage truck matching unit.
The garbage collection point screening unit is used for screening garbage collection points with transportation requirements. First, the current time T is recorded a Setting a call duration at the same time, and setting the current time T a Adding the call duration to obtain the deadline; secondly, acquiring all historical release records in release logs of each garbage collection point, and respectively calculating the current time T in each historical release record a The weight range in the time period reaching the deadline is summed up, and the average value is calculated as the average increment weight of the release log; and finally, summing the maximum weight in the current delivery record under the delivery log and the average increment weight of the corresponding delivery log to obtain a predicted weight, screening out a garbage collection point corresponding to the predicted weight which is greater than or equal to the maximum loading weight, and taking the screened garbage collection point as the garbage collection point with the transportation requirement.
The current time and the deadline are the time of a day, and the calling duration is less than 24 hours.
The call duration is set for a certain waiting transportation time for the garbage collection points, and the specific value is inversely proportional to the number of the garbage collection vehicles and directly proportional to the number of the garbage collection points. Avoiding the situation that the garbage reaches the maximum loading weight at the garbage collection point in the calling time.
The garbage truck matching unit is used for matching the garbage truck for the garbage collection points with transportation requirements. Firstly, setting a section of transportation distance as a radius by taking the position of a garbage collection point with transportation requirements as a circle center, and dividing a circular area for each garbage collection point with transportation requirements as a transportation range area; secondly, matching the garbage collection vehicles which are in the transportation range area and are not performing the transportation task with the corresponding garbage collection points, setting a lowest matching number, and gradually increasing the transportation distance of the garbage collection points with the matched garbage collection vehicle number smaller than the lowest matching number until the matched garbage collection vehicle number is no longer smaller than the lowest matching number; and finally, if the number of garbage collection vehicles matched with all the garbage collection points is not less than the lowest matching number, finishing the matching.
The transportation distance is set so that each garbage collection point can be matched with a certain number of garbage collection vehicles, and the value is in direct proportion to the calling time and the running speed of the garbage collection vehicles. Different transportation distances are set for different garbage collection points, so that the number of garbage collection points matched with garbage collection vehicles is not less than the lowest matching number.
The operation processing module comprises a transportation object selection unit and a transportation task generation unit.
The transportation object selection unit is used for selecting a transportation object for each garbage collection point with transportation requirements.
Firstly, taking the maximum weight of a current throwing record in a throwing log with a garbage collection point with a transportation requirement as the actual loading weight ZD of the corresponding garbage collection point, and simultaneously obtaining the maximum loading weight ZCM and the actual loading weight ZCS of a garbage collection point matched garbage truck to be substituted into a formula to calculate a matching index PPD, wherein the formula is as follows:where u is a distance influence coefficient, c is a position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) To match the real-time position coordinates of the garbage truck.
Second, record the current time T b Respectively calculating the current time T b Obtaining a residual time length by the difference value of the matching time of each garbage collection point with transportation requirements, dividing each residual time length by the calling time length, and multiplying the residual time length by a standard matching index again to obtain a matching threshold value, wherein each garbage collection point with transportation requirements corresponds to one matching threshold value; establishing a matched vehicle set for each garbage collection point with transportation requirements, associating identifiers of matched garbage collection vehicles with corresponding matching indexes, and sequentially putting the identifiers into the matched vehicle sets of the corresponding garbage collection points according to the sequence from the big to the small of the matching indexes; the identifier of the set of matching vehicles that is top ranked and has a matching index greater than a matching threshold for the corresponding garbage collection point is selected as the pre-selected object.
Since the positions of the garbage collection vehicles are constantly changed and the garbage collection vehicles which are performing the transportation tasks are not matched, there is a certain variation in the garbage collection vehicles which can be matched with each garbage collection point. The setting of the matching threshold is to enable each garbage collection point to be matched with the garbage truck with the highest matching index, and the matching threshold of each garbage collection point gradually approaches the matching time along with time and gradually decreases to zero, so that the garbage collection points can be matched with the garbage truck finally.
Then, when the preselected objects of the garbage collection points are the same, the matching threshold PYZ of the garbage collection points with the same preselected objects and the matching index PPD of the preselected objects and the garbage collection points are brought into a formula, and the priority index YX of the garbage collection points is calculated, wherein the formula isWhere f is a constant.
Under the condition that the same preselected objects exist at different garbage collection points, the priority index is used as a judging index, the preselected objects can be preferentially distributed to time urgency, and the garbage collection points with high matching indexes are used as matching objects.
And finally, comparing the priority indexes of the garbage collection points with the same pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object in the matched vehicle set of all the garbage collection points, reselecting the pre-selected object and judging whether the same condition exists at the garbage collection point with the low priority index, continuously calculating the priority index to determine the attribution of the transportation object until the pre-selected object of each garbage collection point is different, and changing the pre-selected object of the rest garbage collection points into the transportation object.
The transportation task generating unit is used for generating transportation tasks for each garbage collection point with the transportation objects and adding the transportation tasks into a transportation plan of the garbage truck corresponding to the transportation objects.
The visualization module displays the position and the garbage loading capacity of each garbage collection point and the real-time position and the garbage loading capacity of all garbage collection vehicles in real time through a large screen of the data center.
Embodiment one:
assuming that a certain area has two total garbage collection points A1 and A2, and B1 is a garbage truck; the actual loading weight of the garbage of A1 and A2 is 20kg and 30kg respectively, and the position coordinates of the garbage collection points are (250, 500) and (500, 250) respectively; b1 has the position coordinates of (500 ), the maximum loading weight of the garbage is 80kg, and the actual loading weight of the garbage is 60kg; the distance influence coefficient is 0.001, the position constant is 1, and the matching indexes of A1-B1 and A2-B1 are calculated by substituting the formula:
matching index of A1-B1:
matching index of A2-B1:
assuming that the current time is 14 points, the A1 matching time is 16 points, the A2 matching time is 15 points, the call duration is 3 hours, and the standard matching index is 5, the A1 and A2 matching thresholds are as follows:
a1 match threshold:
a2 match threshold:
if only one identifier and matching index corresponding to B1 exist in the matched vehicle sets of A1 and A2, B1 is simultaneously used as a preselected object of A1 and A2; assuming a constant of 0.01, the substitution formula calculates the priority index of A1 and A2, respectively:
Priority index of A1:
priority index of A2:
since the priority index of A2 is greater than A1, the preselected object B1 of the A2 garbage collection point is changed to a transportation object, and B1 is no longer the preselected object of A1.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. The garbage collection supervision method based on the Internet of things is characterized by comprising the following steps of: the method comprises the following steps:
s1, collecting information of all garbage collection points and garbage collection vehicle information;
s2, identifying garbage collection points with transportation requirements, and matching garbage collection points with garbage collection vehicles;
s3, calculating a matching index between the garbage collection point and the matched garbage truck so as to select a transportation object;
s4, generating a transportation task, adding the transportation task into a transportation plan of a transportation object, and executing transportation by the transportation object according to the transportation plan;
s5, displaying dynamic information of all garbage collection points and garbage collection vehicles in real time by a visual large screen;
in S2, the specific steps are as follows:
s201, acquiring all historical release records in release logs under each garbage collection point, and recording the current time T a Setting a call duration T at the same time, and adding the current time to the call duration to obtain a cut-off time T end Retrieving slave T in each historical impression record a To T end Taking the extremely poor weight as a weight change value according to the weight in the time period, wherein each historical input record corresponds to one weight change value;
s202, summing weight change values of all historical delivery records in the delivery logs, and calculating an average value to obtain average increase weight, wherein each delivery log corresponds to one average increase weight, and the calculation formula is as follows:
In the formula, WG ave To increase weight average, W max For T in history delivery record a To T end Maximum weight in time period, W min For T in history delivery record a To T end The minimum weight in the time period is S which is the number of historical input records;
s203, acquiring a current throwing record in a throwing log under each garbage collection point, summing the maximum weight in the current throwing record and the average increment weight of the throwing log to obtain a predicted weight, judging whether the predicted weight is greater than or equal to the maximum loading weight of the corresponding garbage collection point, if so, marking the corresponding garbage collection point, and taking the cut-off time as the matching time P of the garbage collection point; if the result is negative, the processing is not performed;
s204, regarding the marked garbage collection points as having transportation requirements, setting a section of transportation distance R as a radius by taking the positions of the garbage collection points having the transportation requirements as circle centers, and dividing a circular area for each garbage collection point having the transportation requirements as a transportation range area; acquiring transportation plans of all garbage collection vehicles, screening garbage collection vehicles which are not executing transportation tasks, acquiring real-time positions of the garbage collection vehicles, and matching the garbage collection vehicles in a transportation range area with corresponding garbage collection points;
S205, setting a lowest matching number M, and marking the garbage collection points with the number of matched garbage truck smaller than the lowest matching number as abnormal; gradually increasing the transportation distance R of each abnormal garbage collection point until the number of garbage truck matched with the abnormal garbage collection point is no longer smaller than the lowest matching number, stopping increasing, and canceling the abnormal mark of the corresponding abnormal garbage collection point; the number of garbage collection vehicles matched with all garbage collection points is not less than the minimum matching number M, and the matching is finished;
in S3, the specific steps are as follows:
s301, acquiring a delivery log of a garbage collection point with a transportation requirement, searching the maximum weight of the current delivery record in the delivery log as the actual loading weight of the corresponding garbage collection point, substituting the actual loading weight of the garbage collection point, the actual loading weight of a matched garbage truck and the distance between the position of the garbage collection point and the real-time position of the matched garbage truck into a formula to obtain a matching index between the garbage collection point and each matched garbage truck, wherein the calculation formula is as follows:
wherein PPD is the index of the match between the garbage collection point and the matched garbage truck, ZCM is the maximum loading weight of the matched garbage truck, ZCS is the actual loading weight of the matched garbage truck, ZD is the actual loading weight of the garbage collection point, u is the distance influencing coefficient, c is the position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) Matching real-time position coordinates of the garbage truck;
s302, establishing a matched vehicle set for each garbage collection point with transportation requirements, associating identifiers of matched garbage collection vehicles with corresponding matching indexes, and sequentially putting the identifiers and the corresponding matching indexes into the matched vehicle sets of the corresponding garbage collection points according to the sequence of the matching indexes from large to small, wherein the sets comprise { (BSF) 1 ,PPD 1 ),(BSF 2 ,PPD 2 ),(BSF 3 ,PPD 3 ),...,(BSF n ,PPD n ) Wherein n represents the number of matched vehicle aggregate elements, BSF n Representing the nth identifier, PPD n Representing an nth matching index, wherein each garbage collection point corresponds to one matching vehicle set;
s303, acquiring the matching time P of each garbage collection point with transportation requirements, and recording the current time T b Substituting the matching threshold value into a formula, and calculating the matching threshold value of each garbage collection point; the formula is as follows:
wherein PYZ is a matching threshold value, and PBZ is a standard matching index;
s304, marking identifiers with all matching indexes larger than the matching threshold value of the corresponding garbage collection points in a matched vehicle set of the garbage collection points, and selecting the marked identifier with the highest ranking as a preselected object of the garbage collection points; placing garbage collection points with preselected objects into a preselected collection;
s305, judging whether the preselected objects of all the garbage collection points in the preselected set have the same condition, and if so, entering a step S307; if the result is yes, the matching threshold value of each garbage collection point with the same preselected object is obtained, the preselected object and the matching index of each garbage collection point are brought into a formula together, and the priority index of each garbage collection point is calculated; the calculation formula is as follows:
Wherein YX is a priority index and f is a constant;
s306, comparing the priority indexes of the garbage collection points with the same pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object from the matched vehicle sets of all the garbage collection points, deleting the matched vehicle set of the garbage collection point with the transportation object, and entering into the step S304 to reselect the pre-selected object for other garbage collection points with low priority indexes;
s307, changing the preselection objects of all the garbage collection points into transportation objects.
2. The internet of things-based garbage collection supervision method according to claim 1, wherein the method comprises the following steps: in S1, the garbage collection point information includes a position of each garbage collection point, a put log, and a maximum loading weight; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the garbage weight from zero, the weight value is collected through a weight sensor arranged at the bottom of the garbage collection container, and the maximum loading weight is the maximum weight of the garbage which can be loaded at the garbage collection point; the garbage truck information includes an identifier, a real-time location, an actual loading weight, a transportation plan, and a maximum loading weight; the identifier is used for distinguishing different garbage truck, the actual loading weight refers to the actual weight of garbage loaded by the garbage truck, the transportation plan refers to a list of tasks executed by the garbage truck, the garbage truck executes transportation according to task information on the task list, and the maximum loading weight refers to the maximum weight of garbage which can be loaded by the garbage truck.
3. The internet of things-based garbage collection supervision method according to claim 1, wherein the method comprises the following steps: in S4, a transport task is generated for each garbage collection point with a transport object, and the transport task is added to a transport plan of a garbage truck corresponding to the transport object, and the garbage truck executes the transport task according to information on the transport plan.
4. The garbage collection supervision system based on the Internet of things is applied to the garbage collection supervision method based on the Internet of things as set forth in claim 1, and is characterized in that: the system comprises a data acquisition module, a data analysis module, an operation processing module and a visualization module;
the data acquisition module is used for acquiring garbage collection point information and garbage truck information; the data analysis module analyzes the garbage collection point information, screens out garbage collection points with transportation requirements, analyzes the garbage collection vehicle information, and matches the garbage collection points with transportation requirements with the garbage collection vehicle; the operation processing module is used for calculating a matching index between the garbage collection points and the matched garbage truck, selecting a transportation object for each garbage collection point according to the matching index, and generating a transportation task to be added into a transportation plan of the transportation object; the visualization module is used for displaying dynamic information of all garbage collection points and garbage collection vehicles.
5. The internet of things-based garbage collection and supervision system according to claim 4, wherein: the data acquisition module comprises a garbage collection point information acquisition unit and a garbage truck information acquisition unit;
the garbage collection point information acquisition unit is used for acquiring the position, the put log and the maximum loading weight of each garbage collection point; the position refers to a fixed position of the garbage collection point; the release log comprises a current release record and a historical release record, each record records the weight value and time of each increase of the weight of garbage from zero, and the weight value is acquired through a weight sensor arranged at the bottom of the garbage collection container; the maximum loading weight refers to the maximum weight of the garbage that can be loaded by the garbage collection point;
the garbage truck information acquisition unit is used for acquiring identifiers, real-time positions, actual loading weights, transportation plans and maximum loading weights of all garbage trucks; the identifier is used for distinguishing different garbage truck; the real-time position refers to the GPS dynamic position of each garbage truck; the actual loading weight refers to the actual weight of the garbage truck loading garbage; the transportation plan refers to a list of tasks executed by the garbage truck; the maximum loading weight refers to the maximum weight of the garbage truck that can load garbage.
6. The internet of things-based garbage collection and supervision system according to claim 5, wherein: the data analysis module comprises a garbage collection point screening unit and a garbage truck matching unit;
the garbage collection point screening unit is used for screening garbage collection points with transportation requirements; first, the current time T is recorded a Setting a call duration at the same time, and setting the current time T a Adding the call duration to obtain the deadline; secondly, acquiring all historical release records in release logs of each garbage collection point, and respectively calculating the current time T in each historical release record a The weight range in the time period reaching the deadline is summed up, and the average value is calculated as the average increment weight of the release log; finally, the maximum weight in the current delivery record under the delivery log and the average increase weight of the corresponding delivery log are carried outObtaining predicted weight after summation, screening out a garbage collection point corresponding to the predicted weight being greater than or equal to the maximum loading weight, wherein the screened garbage collection point is regarded as a garbage collection point with transportation requirements;
the garbage collection and transportation vehicle matching unit is used for matching the garbage collection points with transportation requirements with the garbage collection and transportation vehicle; firstly, setting a section of transportation distance as a radius by taking the position of a garbage collection point with transportation requirements as a circle center, and dividing a circular area for each garbage collection point with transportation requirements as a transportation range area; secondly, matching the garbage collection vehicles which are in the transportation range area and are not performing the transportation task with the corresponding garbage collection points, setting a lowest matching number, and gradually increasing the transportation distance of the garbage collection points with the matched garbage collection vehicle number smaller than the lowest matching number until the matched garbage collection vehicle number is no longer smaller than the lowest matching number; and finally, if the number of garbage collection vehicles matched with all the garbage collection points is not less than the lowest matching number, finishing the matching.
7. The internet of things-based garbage collection and supervision system according to claim 6, wherein: the operation processing module comprises a transport object selection unit and a transport task generation unit;
the transport object selection unit is used for selecting transport objects for each garbage collection point with transport requirements;
firstly, taking the maximum weight of a current throwing record in a throwing log with a garbage collection point with a transportation requirement as the actual loading weight ZD of the corresponding garbage collection point, and simultaneously obtaining the maximum loading weight ZCM and the actual loading weight ZCS of a garbage collection point matched garbage truck to be substituted into a formula to calculate a matching index PPD, wherein the formula is as follows:where u is a distance influence coefficient, c is a position constant, (x) d ，y d ) Coordinates of the position of the garbage collection point (x) c ，y c ) Matching real-time position coordinates of the garbage truck;
secondRecording the current time T b Respectively calculating the current time T b Obtaining a residual time length by the difference value of the matching time of each garbage collection point with transportation requirements, dividing each residual time length by the calling time length, and multiplying the residual time length by a standard matching index again to obtain a matching threshold value, wherein each garbage collection point with transportation requirements corresponds to one matching threshold value; establishing a matched vehicle set for each garbage collection point with transportation requirements, associating identifiers of matched garbage collection vehicles with corresponding matching indexes, and sequentially putting the identifiers into the matched vehicle sets of the corresponding garbage collection points according to the sequence from the big to the small of the matching indexes; selecting an identifier which is ranked the most top in the matched vehicle set and has a matching index greater than a matching threshold value of the corresponding garbage collection point as a preselected object;
Then, when the preselected objects of the garbage collection points are the same, the matching threshold PYZ of the garbage collection points with the same preselected objects and the matching index PPD of the preselected objects and the garbage collection points are brought into a formula, and the priority index YX of the garbage collection points is calculated, wherein the formula isWherein f is a constant;
finally, comparing the priority indexes of the same garbage collection points of the pre-selected objects, changing the pre-selected object of the garbage collection point with the highest priority index into a transportation object, deleting the identifier corresponding to the transportation object in the matched vehicle set of all the garbage collection points, re-selecting the pre-selected object and judging whether the same condition exists at the garbage collection point with the low priority index, continuously calculating the priority index to determine the attribution of the transportation object until the pre-selected object of each garbage collection point is different, and changing the pre-selected object of the rest garbage collection points into the transportation object;
the transportation task generating unit is used for generating transportation tasks for each garbage collection point with the transportation objects and adding the transportation tasks into a transportation plan of the garbage truck corresponding to the transportation objects.
8. The internet of things-based garbage collection and supervision system according to claim 4, wherein: the visualization module displays the position and the garbage loading capacity of each garbage collection point and the real-time position and the garbage loading capacity of all garbage collection vehicles in real time through a large screen of the data center.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106950904A (en) * 2017-05-02 2017-07-14 广州聚澜健康产业研究院有限公司 A kind of kitchen waste processing equipment and vehicle management system based on Internet of Things
CN110002139A (en) * 2019-05-23 2019-07-12 丁波 A kind of sorting rubbish based on Internet of Things intelligently clears monitoring system, cloud platform and method
CN111652783A (en) * 2020-06-11 2020-09-11 贵州小黑科技有限公司 Rural garbage collection and transportation management system based on geographical positioning information
CN111931986A (en) * 2020-07-08 2020-11-13 淮阴工学院 Garbage clearing and transporting vehicle route optimization method and urban garbage clearing and transporting ecological system
CN113344262A (en) * 2021-05-28 2021-09-03 淮阴工学院 Intelligent clearing system and method based on urban garbage classification
CN114751113A (en) * 2022-03-17 2022-07-15 浙江科技学院 Weighing calculation method of multi-barrel intelligent garbage classification kiosk

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106950904A (en) * 2017-05-02 2017-07-14 广州聚澜健康产业研究院有限公司 A kind of kitchen waste processing equipment and vehicle management system based on Internet of Things
CN110002139A (en) * 2019-05-23 2019-07-12 丁波 A kind of sorting rubbish based on Internet of Things intelligently clears monitoring system, cloud platform and method
CN111652783A (en) * 2020-06-11 2020-09-11 贵州小黑科技有限公司 Rural garbage collection and transportation management system based on geographical positioning information
CN111931986A (en) * 2020-07-08 2020-11-13 淮阴工学院 Garbage clearing and transporting vehicle route optimization method and urban garbage clearing and transporting ecological system
CN113344262A (en) * 2021-05-28 2021-09-03 淮阴工学院 Intelligent clearing system and method based on urban garbage classification
CN114751113A (en) * 2022-03-17 2022-07-15 浙江科技学院 Weighing calculation method of multi-barrel intelligent garbage classification kiosk

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