A digital government management platform and method

Abstract

The application discloses a kind of digital government management platform and method, it is related to digital management technical field, the method includes the following steps: obtaining the position data of garbage delivery point;The position data is clustered, and garbage transfer station is set with cluster center;The garbage delivery point is monitored in real time, and the garbage weight and overflow state are obtained;According to the garbage delivery point and the garbage transfer station, road network structure is constructed;According to the garbage weight and the overflow state, garbage collection and transportation are managed.The application is clustered to the garbage delivery point, and the garbage delivery point is managed by dividing multiple regions, respectively, the garbage delivery point is monitored in real time, the garbage weight and overflow state of garbage delivery point are obtained, and the garbage weight and overflow state are managed according to garbage collection and transportation, to provide reasonable decision for garbage collection and transportation, improve the efficiency of garbage collection and transportation.

Description

Technical Field

[0001] This invention relates to the field of digital management technology, specifically to a digital government management platform and method. Background Technology

[0002] Digital government management refers to the use of information technologies such as cloud computing, big data, artificial intelligence, or the Internet of Things to optimize and improve services and management. For example, it involves modeling and evaluating digital information to provide more rational decision-making for management; or improving the level of intelligence in management through the construction of smart infrastructure. Waste management, as a crucial aspect of government environmental status management, benefits from the integration of digital information technology to achieve rational waste management and improve government efficiency and management level. Therefore, a digital management method for waste is needed.

[0003] Currently, the collection and transportation of waste is based on pre-planned routes, without considering whether there is overflow at the collection points. This leads to long-term accumulation of waste, resulting in unreasonable waste collection and transportation planning and low efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a digital government management platform and method. This invention manages garbage collection points by clustering them and dividing them into multiple areas. It also monitors the garbage collection points in real time to obtain the weight and overflow status of the garbage at each point. Based on the weight and overflow status, the invention manages garbage collection and transportation, providing reasonable decision-making for garbage collection and transportation and improving the efficiency of garbage collection and transportation.

[0005] The objective of this invention is achieved through the following technical means:

[0006] In a first aspect, the present invention provides a digital government management method, comprising the following steps:

[0007] Obtain the location data of garbage collection points;

[0008] The location data is clustered, and waste transfer stations are set up with the cluster centers;

[0009] The garbage collection points are monitored in real time to obtain the garbage weight and overflow status;

[0010] Construct a road network structure based on the garbage collection points and the garbage transfer stations;

[0011] Waste collection and transportation are managed based on the weight of the waste and the overflow status.

[0012] Preferably, the real-time monitoring of the waste disposal point to obtain the waste weight and overflow status includes the following steps:

[0013] A gravity sensor is installed at the bottom of the waste disposal point;

[0014] The weight of the waste is obtained by detecting the waste disposal point using the gravity sensor.

[0015] Acquire image data of the garbage disposal point;

[0016] The image data is identified to obtain the delivery status;

[0017] When the weight of the waste is greater than or equal to the weight threshold and / or the delivery status is full, the overflow status is overflow.

[0018] When the weight of the waste is less than the weight threshold and / or the delivery status is half full, the overflow status is not full.

[0019] Preferably, the management of waste collection and transportation based on the weight of the waste and the overflow status includes the following steps:

[0020] The number of trips for the collection vehicles is calculated based on the weight of the garbage and the load capacity of the collection vehicles, and the constraints are determined.

[0021] Calculate the overflow time based on the weight of the waste;

[0022] Calculate the overflow penalty cost based on the overflow time and the overflow state;

[0023] Based on the number of trips of the collection vehicles and the overflow penalty cost, a minimum objective function is constructed;

[0024] The minimum objective function is solved using the particle swarm optimization algorithm based on the constraints, resulting in a waste collection and transportation scheme with minimal cost.

[0025] Waste collection and transportation shall be managed in accordance with the aforementioned waste collection and transportation plan.

[0026] Preferably, calculating the overflow time based on the weight of the waste includes the following steps:

[0027] Obtain the historical waste weight at the waste disposal point;

[0028] Calculate the growth rate of the historical waste weight based on the historical waste weight;

[0029] The overflow time is calculated based on the weight of the waste, the growth rate of the historical waste weight, and the weight threshold.

[0030] The formula for calculating the overflow time is as follows:

[0031]

[0032] Where T is the overflow time, W th Where W is the weight threshold, W is the weight of the waste, and v is the historical rate of increase in waste weight.

[0033] Preferably, the formula for the minimum objective function is expressed as follows:

[0034] minF = minC + minP

[0035]

[0036] Where, minF is the objective function, C is the collection and transportation cost, P is the overflow penalty cost; c is the unit distance transportation cost, N is the number of times the collection and transportation vehicles make their trips, S is the set of garbage transfer stations, D is the set of garbage drop-off points, and l si Let x be the distance between the garbage transfer station s and the garbage collection point i. sin To determine whether the nth departure passes through the path s→i, l is Let x be the distance between garbage collection point i and garbage transfer station s. isn To determine whether the nth departure passes through the path i→s, l ij Let x be the distance between garbage collection point i and garbage collection point j. ijn To determine whether the nth departure passes through the path i→j, θ is the unit cost of dispatching a collection vehicle; θ is the first overflow penalty cost coefficient; M is the set of overflowing garbage collection points; y mn Let σ be the cost coefficient for the second overflow penalty, K be the set of garbage collection points that are not full, and t be the number of garbage collection points. i Let T be the departure time of the i-th vehicle. k Let y be the overflow time of garbage collection point k. kn Let n be the number of times the vehicle will travel to the garbage collection point k.

[0037] Preferably, the constraint condition is expressed as follows:

[0038]

[0039] f n ≤L,

[0040]

[0041] Where N represents the number of trips made by the collection vehicles, D represents the set of garbage collection points, and x ijn To determine whether the nth departure passes through the path i→j, f n Let L be the amount of garbage collected during the nth trip, and W be the load capacity of the collection vehicle. i Let represent the weight of the garbage at garbage collection point i.

[0042] Preferably, the step of solving the minimum objective function using a particle swarm optimization algorithm based on the constraints to obtain a cost-minimizing waste collection and transportation scheme includes the following steps:

[0043] Initialize particle parameters;

[0044] The waste collection points are coded, and the codes are randomly sorted.

[0045] The code is decoded based on the load of the collection vehicle to generate an initial collection plan;

[0046] The particle position is updated based on the particle parameters, and the particle's fitness is calculated.

[0047] The optimal value of the particle is iteratively updated based on the fitness.

[0048] When the number of iterations reaches a preset value, the optimal value of the particle is output, thus obtaining the waste collection and transportation scheme with the minimum cost.

[0049] Secondly, the present invention provides a digital government management platform that applies the above-mentioned digital government management method, including: a location acquisition module, a clustering processing module, a waste monitoring module, a road network construction module, and a collection and transportation management module;

[0050] The location acquisition module is used to acquire the location data of the garbage disposal point;

[0051] The clustering processing module is used to perform clustering processing on the location data, and to set up garbage transfer stations with cluster centers;

[0052] The waste monitoring module is used to monitor the waste disposal point in real time to obtain the waste weight and overflow status;

[0053] The road network construction module is used to construct a road network structure based on the garbage disposal points and the garbage transfer stations;

[0054] The collection and transportation management module is used to manage the collection and transportation of waste based on the weight of the waste and the overflow status.

[0055] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory being used to store computer program code, the computer program code including computer instructions, and when the processor executes the computer instructions, the electronic device executes the aforementioned digital government management method.

[0056] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to perform the aforementioned digital government management method.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0058] This invention clusters waste collection points, divides them into multiple regions for management, and monitors each point in real time to obtain the weight and overflow status of the waste. Based on the weight and overflow status, the invention manages waste collection and transportation, providing rational decision-making and improving efficiency.

[0059] This invention obtains the weight and disposal status of garbage at garbage collection points, and determines the overflow status of garbage collection points based on the weight and disposal status, providing a data foundation for garbage collection and transportation and improving the efficiency of garbage collection and transportation.

[0060] This invention constructs a minimum objective function based on the number of trips of collection vehicles and the cost of overflow penalties, and solves the minimum objective function to obtain the waste collection and transportation scheme with the lowest cost, thereby managing waste collection and transportation, reducing the cost of waste collection and transportation, and improving the efficiency of waste collection and transportation.

[0061] This invention employs a particle swarm optimization algorithm to solve the minimum objective function and outputs the optimal solution of the particles as the optimal waste collection and transportation scheme, thereby improving the rationality and efficiency of the waste collection and transportation scheme. Attached Figure Description

[0062] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a flowchart illustrating a digital government management method provided in this embodiment;

[0065] Figure 2 The flowchart for step S3 in this embodiment, which involves real-time monitoring of the garbage disposal point to obtain the garbage weight and overflow status, is shown below.

[0066] Figure 3 Step S5 of this embodiment is a flowchart illustrating the process of managing waste collection and transportation based on waste weight and overflow status.

[0067] Figure 4 This embodiment provides a flowchart illustrating step S52, which calculates the overflow time based on the weight of the waste.

[0068] Figure 5 Step S55 in this embodiment involves solving the minimum objective function using a particle swarm optimization algorithm based on constraints to obtain a flowchart illustrating the waste collection and transportation scheme with minimized costs.

[0069] Figure 6 This is a schematic diagram of the structure of a digital government management platform provided in this embodiment;

[0070] Figure 7 This is a schematic diagram of the structure of an electronic device provided in this embodiment. Detailed Implementation

[0071] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0072] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0073] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" and "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. When the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0074] Example 1

[0075] This embodiment provides a digital government management method, such as... Figure 1 As shown, it includes the following steps:

[0076] S1, Obtain the location data of the garbage disposal point;

[0077] S2, cluster the location data and set up garbage transfer stations with the cluster centers;

[0078] S3 monitors garbage collection points in real time to obtain garbage weight and overflow status;

[0079] S4, construct the road network structure based on garbage drop-off points and garbage transfer stations;

[0080] S5 manages waste collection and transportation based on waste weight and overflow status.

[0081] It should be noted that conventional clustering algorithms are used for clustering garbage collection points. Location data of these points is acquired and analyzed to create multiple clusters, each categorizing the points. A garbage transfer station is located at the cluster center to manage the collection and transportation of garbage from the points within that cluster. Real-time monitoring of each garbage collection point provides data on garbage weight and overflow status. Garbage weight represents the real-time amount of garbage collected at that point, while overflow status indicates whether the point's capacity has reached its limit, including both overflow and not full states. The road network structure describes the layout and connection of garbage collection points and transfer stations, and the acquired garbage weight and overflow status are displayed on the screen.

[0082] In this embodiment, by clustering the garbage collection points and dividing them into multiple regions for management, the garbage collection points are monitored in real time to obtain the garbage weight and overflow status. Based on the garbage weight and overflow status, the garbage collection and transportation is managed, providing reasonable decision-making for garbage collection and transportation and improving the efficiency of garbage collection and transportation.

[0083] In some embodiments, step S3 involves real-time monitoring of the waste disposal point to obtain the waste weight and overflow status, such as... Figure 2 As shown, it includes the following steps:

[0084] S31, Install a gravity sensor at the bottom of the garbage disposal point;

[0085] S32 uses a gravity sensor to detect the weight of the garbage at the garbage disposal point.

[0086] S33, acquire image data of the garbage disposal point;

[0087] S34, Recognize the image data to obtain the delivery status;

[0088] S35, when the weight of the waste is greater than or equal to the weight threshold and / or the delivery status is full, the overflow status is overflow;

[0089] S36, when the weight of the waste is less than the weight threshold and / or the delivery status is half full, the overflow status is not full.

[0090] It should be noted that the gravity sensor is located at the bottom of the garbage collection point to detect the weight of the garbage. The collection status reflects the garbage accumulation at the collection point, including two states: half full and full. Based on the garbage weight and the collection status, the overflow status of the garbage collection point is determined. Specifically, the overflow status of the garbage collection point is reflected in two aspects: whether the garbage weight reaches the weight threshold and whether the garbage collection reaches the capacity limit. Some garbage is small in size but heavy in weight, which may result in the garbage collection reaching the weight threshold before reaching the capacity limit, in which case the garbage collection point has reached its load-bearing limit. In addition, some garbage is large in size but light in weight, which may result in the garbage weight reaching the capacity limit before reaching the weight threshold. Continuing to collect garbage in both of these situations will lead to difficulties in garbage collection or garbage overflow. Therefore, both of the above situations are considered overflow.

[0091] In this embodiment, by obtaining the weight and delivery status of the garbage at the garbage collection point, the overflow status of the garbage collection point is determined based on the weight and delivery status, providing a data basis for garbage collection and transportation and improving the efficiency of garbage collection and transportation.

[0092] In some embodiments, step S5 involves managing waste collection and transportation based on waste weight and overflow status, such as... Figure 3 As shown, it includes the following steps:

[0093] S51, calculate the number of trips of the collection vehicle based on the weight of the garbage and the load of the collection vehicle, and determine the constraints.

[0094] S52, calculate the overflow time based on the weight of the waste;

[0095] S53, calculate the overflow penalty cost based on the overflow time and overflow status;

[0096] S54. Based on the number of trips of the collection vehicles and the cost of overflow penalty, construct the minimum objective function;

[0097] S55. Based on the constraints, the particle swarm optimization algorithm is used to solve the minimum objective function, resulting in a waste collection and transportation scheme with minimal cost.

[0098] S56, manage waste collection and transportation according to the waste collection and transportation plan.

[0099] In some embodiments, the minimum objective function is expressed as follows:

[0100] minF = minC + minP

[0101]

[0102] Where, minF is the objective function, C is the collection and transportation cost, P is the overflow penalty cost; c is the unit distance transportation cost, N is the number of times the collection and transportation vehicles make their trips, S is the set of garbage transfer stations, D is the set of garbage drop-off points, and l si Let x be the distance between the garbage transfer station s and the garbage collection point i. sin To determine whether the nth departure passes through the path s→i, l is Let x be the distance between garbage collection point i and garbage transfer station s. isn To determine whether the nth departure passes through the path i→s, l ij Let x be the distance between garbage collection point i and garbage collection point j. ijn To determine whether the nth departure passes through the path i→j, θ is the unit cost of dispatching a collection vehicle; θ is the first overflow penalty cost coefficient; M is the set of overflowing garbage collection points; y mn Let σ be the cost coefficient for the second overflow penalty, K be the set of garbage collection points that are not full, and t be the number of garbage collection points. i Let T be the departure time of the i-th vehicle. k Let y be the overflow time of garbage collection point k. kn Let n be the number of times the vehicle will travel to the garbage collection point k.

[0103] It should be noted that the minimum objective function includes collection costs and overflow penalty costs. Collection costs include the cost of the distance traveled by collection vehicles and the cost of the number of times collection vehicles make their trips. Overflow penalty costs include the overflow penalty cost for delayed collection from overflowing garbage collection points and the overflow penalty cost for garbage collection points that are about to overflow but reach overflow during the collection process. Specifically, the overflow penalty cost for overflowing garbage collection points increases with the number of trips. For garbage collection points that are not yet full, the overflow time is predicted based on historical data, and the system calculates whether they have reached overflow at the time of collection, while also calculating the collection overtime. The overflow penalty cost increases with the increase of the overtime.

[0104] In some embodiments, step S52 involves calculating the overflow time based on the weight of the waste, such as... Figure 4 As shown, it includes the following steps:

[0105] Obtain the historical weight of garbage at the garbage collection point;

[0106] Calculate the growth rate of historical waste weight based on historical waste weight;

[0107] The overflow time is calculated based on the weight of the waste, the rate of increase in historical waste weight, and the weight threshold.

[0108] The formula for calculating overflow time is as follows:

[0109]

[0110] Where T is the overflow time, W th Where W is the weight threshold, W is the weight of the waste, and v is the historical rate of increase in waste weight.

[0111] In some embodiments, the constraint conditions are expressed as follows:

[0112]

[0113] f n ≤L,

[0114]

[0115] Where N represents the number of trips made by the collection vehicles, D represents the set of garbage collection points, and x ijn To determine whether the nth departure passes through the path i→j, f n Let L be the amount of garbage collected during the nth trip, and W be the load capacity of the collection vehicle. i Let represent the weight of the garbage at garbage collection point i.

[0116] It should be noted that the constraints include three points: first, the garbage at the garbage collection point can be collected multiple times; second, the amount of garbage collected in one trip is less than or equal to the load capacity of the collection vehicle; and third, the total amount of garbage collected in one trip is equal to the weight of the garbage at the garbage collection point.

[0117] In this embodiment, a minimum objective function is constructed based on the number of trips of collection vehicles and the cost of overflow penalties. The minimum objective function is solved to obtain the waste collection and transportation scheme with the lowest cost, thereby reducing the cost of waste collection and transportation and improving the efficiency of waste collection and transportation.

[0118] In some embodiments, step S55 involves solving the minimum objective function using a particle swarm optimization algorithm based on the constraints to obtain a waste collection and transportation scheme that minimizes cost, such as... Figure 5 As shown, it includes the following steps:

[0119] S551, initialize particle parameters;

[0120] S552, Encode the garbage collection points and randomly sort the codes;

[0121] S553, decode the code according to the load of the collection vehicle to generate an initial collection plan;

[0122] S554 updates the particle's position based on the particle parameters and calculates the particle's fitness.

[0123] S555, the optimal value of the particle is iteratively updated based on fitness;

[0124] S556: When the number of iterations reaches a preset value, the optimal value of the particle is output, resulting in a waste collection and transportation scheme with minimized cost.

[0125] It should be noted that the particle swarm optimization (PSO) algorithm is used to solve the minimum objective function, and the parameters of the final particles are the optimal solution of the PSO algorithm, i.e., the optimal waste collection and transportation scheme. Specifically, the initial particle parameters include the number of particles, speed limit, position limit, learning factor, inertia weight, and number of iterations. Waste collection points are sequentially encoded, and the codes are randomly arranged according to the road network structure to sort the waste collection points. After obtaining the waste collection point encoding sequence, the encoding sequence is truncated according to the constraints to obtain the waste collection points that the vehicle needs to pass through and the amount of waste collected each time as the initial collection and transportation scheme. The cost of the initial collection and transportation scheme is calculated as the historical best fitness. The particle position is updated according to the number of iterations, and the cost of updating the collection and transportation scheme is calculated as the particle fitness. The fitness is compared with the best fitness, and the fitness with the smaller value is selected as the best fitness. When the number of iterations reaches a preset value, the obtained best fitness is the minimum cost, and the particle position is the optimal waste collection and transportation scheme.

[0126] In this embodiment, the particle swarm optimization algorithm is used to solve the minimum objective function, and the optimal solution of the particles is output as the optimal waste collection and transportation scheme, which improves the rationality of the waste collection and transportation scheme and the efficiency of waste collection and transportation.

[0127] Example 2

[0128] This embodiment provides a digital government management platform, applying one of the digital government management methods described above, such as... Figure 6 As shown, it includes: a location acquisition module, a clustering processing module, a waste monitoring module, a road network construction module, and a collection and transportation management module;

[0129] The location acquisition module is used to acquire the location data of garbage disposal points;

[0130] The clustering module is used to cluster location data and set up waste transfer stations based on the cluster centers.

[0131] The waste monitoring module is used to monitor waste disposal points in real time to obtain waste weight and overflow status;

[0132] The road network construction module is used to build the road network structure based on garbage drop-off points and garbage transfer stations;

[0133] The collection and transportation management module is used to manage waste collection and transportation based on waste weight and overflow status.

[0134] In this embodiment, by clustering the garbage collection points and dividing them into multiple regions for management, the garbage collection points are monitored in real time to obtain the garbage weight and overflow status. Based on the garbage weight and overflow status, the garbage collection and transportation is managed, providing reasonable decision-making for garbage collection and transportation and improving the efficiency of garbage collection and transportation.

[0135] It should be understood that the disclosed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the module division described above is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, each functional module can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0136] Example 3

[0137] This embodiment provides an electronic device 2, such as... Figure 7 As shown, there is a processor 21 and a memory 22. The memory 22 is used to store computer program code, which includes computer instructions. When the processor 21 executes the computer instructions, the electronic device performs the aforementioned digital government management method.

[0138] The electronic device 2 includes a processor 21, a memory 22, an output device 23, and an input device 24. The processor 21, memory 22, output device 23, and input device 24 are coupled together via connectors, which may include various interfaces, transmission lines, or buses, etc., and are not limited in this embodiment of the invention. It should be understood that in various embodiments of the invention, coupling refers to mutual connection through a specific method, including direct connection or indirect connection through other devices, such as through various interfaces, transmission lines, buses, etc.

[0139] Processor 21 can be one or more graphics processing units (GPUs). If processor 21 is a GPU, the GPU can be a single-core GPU or a multi-core GPU. Optionally, processor 21 can be a processor group composed of multiple GPUs, with the multiple processors coupled to each other via one or more buses. Optionally, processor 21 can also be other types of processors, etc., which are not limited in this embodiment of the invention.

[0140] The memory 22 can be used to store computer program instructions, as well as various types of computer program code, including program code for executing the present invention. Optionally, the memory 22 includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact disc read-only memory (CD-ROM), and the memory 22 is used for related instructions and data.

[0141] Input device 24 is used to input data and / or signals, and output device 23 is used to output data and / or signals. Output device 23 and input device 24 can be independent devices or an integrated device.

[0142] This embodiment provides a computer-readable storage medium storing a computer program, which includes program instructions. When executed by a processor of an electronic device, the program instructions cause the processor to perform the aforementioned digital government management method.

[0143] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A digital government management method, characterized in that, Includes the following steps: Obtain the location data of garbage collection points; The location data is clustered to calculate the distance from each waste disposal point to the cluster center, and a waste transfer station is set up with the cluster center as the reference point. A gravity sensor is installed at the bottom of the garbage disposal point to detect the weight of the garbage. The image data of the garbage disposal point is acquired, and the disposal status is obtained by recognizing the image data. When the weight of the garbage is greater than or equal to the weight threshold and / or the delivery status is full, the garbage delivery point is determined to be in an overflow state. Construct a road network structure based on the garbage collection points and the garbage transfer stations; The management of waste collection and transportation, based on the weight of the waste and the overflow status, specifically includes the following steps: The number of trips for the collection vehicles is calculated based on the weight of the garbage and the load capacity of the collection vehicles, and the constraints are determined. Calculate the overflow time based on the weight of the waste; Based on the overflow time and the overflow status, the overflow penalty cost is calculated. The overflow penalty cost includes the overflow penalty cost for late collection from overflowing garbage collection points and the overflow penalty cost for garbage collection points that are about to overflow and reach overflow during the collection process. Specifically, the overflow penalty cost for overflowing garbage collection points increases with the increase of the number of truck trips. For garbage collection points that are not full, the overflow time is predicted based on historical data, and it is calculated whether they have reached overflow at the time of collection. At the same time, the timeout period for collection is calculated, and the overflow penalty cost increases with the increase of the timeout period. Based on the number of trips of the collection vehicles and the overflow penalty cost, a minimum objective function is constructed; The minimum objective function is solved using the particle swarm optimization algorithm based on the constraints, resulting in a waste collection and transportation scheme with minimal cost. Waste collection and transportation shall be managed in accordance with the aforementioned waste collection and transportation plan.

2. The digital government management method according to claim 1, characterized in that, When the weight of the waste is less than the weight threshold and / or the delivery status is half full, the overflow status is not full.

3. The digital government management method according to claim 1, characterized in that, The calculation of the overflow time based on the weight of the waste includes the following steps: Obtain the historical waste weight at the waste disposal point; Calculate the growth rate of the historical waste weight based on the historical waste weight; The overflow time is calculated based on the weight of the waste, the growth rate of the historical waste weight, and the weight threshold. The formula for calculating the overflow time is as follows: ， in, For overflow time, For weight threshold, For the weight of the garbage, This represents the rate of increase in the weight of historical waste.

4. The digital government management method according to claim 1, characterized in that, The formula for the minimum objective function is expressed as follows: ， ， ， ， ， in, Let be the objective function. For collection and transportation costs, To cover the cost of excessive penalties; For unit distance transportation cost, This refers to the number of trips made by the collection vehicles. For collection at the garbage transfer station For collection of garbage drop-off points, Waste transfer station With garbage collection points distance, For the first Did the vehicle travel along the same route on its next trip? , For garbage collection points With garbage transfer station distance, For the first Did the vehicle travel along the same route on its next trip? , For garbage collection points With garbage collection points distance, For the first Did the vehicle travel along the same route on its next trip? , Cost of dispatching a single collection vehicle; The first overflow penalty cost coefficient, For overflowing garbage collection points, For the first Does the vehicle go to the garbage collection point on the next trip? , The second overflow penalty cost coefficient, For collection points that are not yet full, For the first The departure time of the next trip. For garbage collection points The overflow time, For the first Does the vehicle go to the garbage collection point on the next trip? .

5. A digital government management method according to claim 1, characterized in that, The formula for the constraint condition is expressed as follows: ， ， ， ， in, This refers to the number of trips made by the collection vehicles. For collection of garbage drop-off points, For the first Did the vehicle travel along the same route on its next trip? , For the first The amount of garbage collected per trip To determine the load capacity of the collection vehicles, For garbage collection points The weight of the garbage.

6. A digital government management method according to claim 3, characterized in that, The step of solving the minimum objective function using the particle swarm optimization algorithm based on the constraints to obtain a waste collection and transportation scheme with minimal cost includes the following steps: Initialize particle parameters; The waste collection points are coded, and the codes are randomly sorted. The encoding is decoded based on the load of the collection vehicle to generate an initial collection plan; The particle position is updated based on the particle parameters, and the particle's fitness is calculated. The optimal value of the particle is iteratively updated based on the fitness. When the number of iterations reaches a preset value, the optimal value of the particle is output, thus obtaining the waste collection and transportation scheme with the minimum cost.

7. A digital government management platform, employing a digital government management method as described in any one of claims 1 to 6, characterized in that, include: The system includes a location acquisition module, a clustering processing module, a waste monitoring module, a road network construction module, and a collection and transportation management module. The location acquisition module is used to acquire the location data of the garbage disposal point; The clustering processing module is used to perform clustering processing on the location data, and to set up garbage transfer stations with cluster centers; The waste monitoring module is used to monitor the waste disposal point in real time to obtain the waste weight and overflow status; The road network construction module is used to construct a road network structure based on the garbage disposal points and the garbage transfer stations; The collection and transportation management module is used to manage the collection and transportation of waste based on the weight of the waste and the overflow status.

8. An electronic device, characterized in that, The device includes a processor and a memory, the memory being used to store computer program code, the computer program code including computer instructions, wherein when the processor executes the computer instructions, the electronic device performs a digital government management method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to perform a digital government management method as described in any one of claims 1 to 6.

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