Garbage clearance scheduling method

Abstract

The invention provides a garbage clearance scheduling method, which comprises the following steps of S1, installing a sensor on a garbage can in a city for monitoring the overflow degree condition of the garbage can in real time; s2, collecting spill degree data of the garbage cans, and visualizing the spill degree data; s3, according to the collected spill degree data, the number of spill garbage cans is counted; s4, garbage can distribution areas are divided, a threshold value of the number of the overflowed garbage cans is set, the number of the overflowed garbage cans in each area is compared with the threshold value of the number of the overflowed garbage cans, and the priority of the garbage collection and transportation areas is determined; s5, the garbage cans with the garbage overflow degree reaching or exceeding the threshold value in each area are set as a node, and the optimal clearing and transporting path in each area is planned; and S6, according to the obtained garbage clearance priority, performing clearance on each area in sequence, thereby not only improving the clearance efficiency and reducing the operation cost, but also better adapting to the actual demand of urban garbage clearance by dynamically adjusting the clearance plan.

Description

Technical Field

[0001] The invention relates to the field of garbage removal and transportation, and in particular to a garbage removal and transportation scheduling method. Background Art

[0002] With the acceleration of urbanization, the field of garbage collection and dispatching faces increasingly complex challenges. At present, many cities still rely on traditional collection and dispatching methods, which often lack real-time data support and optimization algorithms, resulting in low collection and dispatching efficiency and high costs. Existing collection and dispatching methods usually do not consider real-time monitoring of the overflow of garbage bins, but adopt regular or fixed-route collection and dispatching modes, which can easily lead to waste of resources or untimely collection and dispatching when garbage bins are unevenly distributed or the amount of garbage generated fluctuates. Existing garbage collection and dispatching methods do not consider the choice of dispatching routes, resulting in unreasonable collection and dispatching routes, which cannot effectively deal with the uncertainty and variability of garbage volume, increase operating costs, and also affect the cleanliness of the urban environment.

[0003] To address these technical issues, a new type of garbage collection and dispatching solution is urgently needed, which can monitor the overflow level of garbage bins in real time and dynamically optimize the collection routes based on real-time data. Summary of the invention

[0004] The purpose of the present invention is to solve the technical problems in the above background and propose a garbage removal and dispatching method, comprising the following steps: S1. Install sensors on trash cans in the city to monitor the overflow of the trash cans in real time; S2, collect and visualize the overflow data of the trash can; S3. Counting the number of overflowing trash cans according to the collected overflow degree data; S4, dividing the garbage bin distribution area, setting a threshold value for the number of overflowing garbage bins, comparing the number of overflowing garbage bins in each area with the threshold value for the number of overflowing garbage bins, and determining the priority of the garbage removal area; S5. Set the garbage bin in each area whose garbage overflow degree reaches or exceeds the threshold as a node, and plan the optimal removal path in each area; S6. According to the garbage removal priority obtained in step S4, each area is cleared in turn.

[0005] In a preferred solution, in step S5, the location of the trash can, road conditions, traffic regulations and estimated travel time are taken into consideration, and the planned removal route is the route with the lowest comprehensive evaluation result of cost and time.

[0006] In a preferred solution, step S5 specifically includes the following steps: S51, using a path planning algorithm to calculate three relatively shortest paths for each area; S52, design time-cost comprehensive evaluation model; S53, putting the three shortest paths in S51 into the time-cost comprehensive evaluation model, comparing the evaluation results, and taking the path with the best result as the optimal removal path.

[0007] In the preferred solution, the time-cost comprehensive evaluation model design process includes the following steps: S521. Design an objective function that minimizes cleaning time and operating costs; S522, collecting data on the location of garbage bins, road conditions, traffic rules, estimated travel time, speed and capacity of garbage collection vehicles in each area; S523, establishing constraint conditions; S525, design cost function and time function; S526. Solve the objective function through the ant colony algorithm.

[0008] In the preferred solution, the constraints include: Trash bin overflow constraint: Trash bins whose overflow reaches or exceeds the threshold are included in the removal path; Vehicle capacity constraint: The amount of cleanup for each vehicle does not exceed its capacity; Time window constraint: consider the time window in which the trash can can be cleared; Vehicle quantity constraint: Limit the number of removal routes based on the number of available vehicles.

[0009] In a preferred solution, the cost function includes: calculating the travel cost of each path, including fuel consumption and labor costs.

[0010] In a preferred solution, the time function predicts the travel time of each route and the loading and unloading time during the transportation process based on road conditions and traffic regulations.

[0011] In a preferred solution, step S3 specifically includes the following steps: S31, determining the capacity limit value of each trash bin and saving it; S32. Marking four corners of the map of the removal area, the marking points are used to determine the scope of the removal area, determine the location of the garbage bin and record it; S33. Monitor the overflow level of the trash can in real time and visualize it.

[0012] In a preferred solution, step S33 specifically includes: comparing the overflow degree of the trash can with the capacity limit value, and performing visualization based on the comparison result, specifically: When the overflow degree is below a certain percentage of the limit value, the trash can is visualized as green, indicating normal; When the overflow level approaches or reaches the limit, the trash can is visualized as red, indicating that it needs to be cleared immediately; When the overflow exceeds the limit, the trash can is visualized in blue, indicating that the need for removal is urgent.

[0013] In the preferred solution, the optimal path is visualized and the next removal point of the removal vehicle is marked with a green arrow; The subsequent path to the next transfer station or destination is indicated by a solid orange line, providing navigation guidance.

[0014] The beneficial effects of the present invention are: 1) By real-time monitoring of the overflow level of trash cans and dynamically planning the removal routes, it ensures that the removal vehicles can give priority to the most urgent removal tasks, thereby improving the overall removal efficiency.

[0015] 2) Reduce unnecessary driving distance and time through shortest path planning and time-cost comprehensive evaluation model, thereby reducing fuel consumption and labor costs.

[0016] 3) Timely removal of overflowing trash cans and reducing the time that trash stays there will help improve urban sanitation and enhance the living environment of residents.

[0017] 4) The solution can adapt to different traffic conditions and changes in garbage generation, and has strong adaptability and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the garbage removal and dispatching method in the present invention. DETAILED DESCRIPTION

[0019] like Figure 1 Shown is a flow chart of a garbage removal scheduling method in the present invention.

[0020] Example 1 A garbage removal scheduling method comprises the following steps: 1. Determine the capacity limit of the trash can and save it: Determine the capacity limit for each trash bin and save this data in the collection and dispatch system.

[0021] 2. Initialize the cleaning scene: Mark four corner points on the map of the removal area. These points are used to determine the scope of the removal area.

[0022] Determine the location of your trash cans and record them.

[0023] 3. Measure and visualize the overflow of the trash can: Monitor the overflow level of trash cans in real time.

[0024] Compare the overflow level of the trash can to the capacity limit and visualize the comparison: If the overflow is below a certain percentage of the limit, the trash can is visualized as green, indicating normal.

[0025] If the overflow level is close to or reaches the limit, the trash can is visualized as red, indicating that it needs to be emptied immediately.

[0026] If the overflow exceeds the limit, the trash can will be visualized in blue, indicating that the need for removal is urgent.

[0027] 4. Choose the best removal route: According to the current position of the garbage collection vehicle and the overflow degree of the garbage bin, the optimal path selection algorithm is used to calculate the optimal path to the next garbage bin.

[0028] Draw and display the optimal path in the scheduling system.

[0029] 5. Visualize the optimal removal path: Use green arrows to mark the next removal point for the removal vehicle, which can help the driver quickly identify the target.

[0030] The subsequent path to the next transfer station or destination is indicated by a solid orange line, providing clear navigation guidance.

[0031] 6. Dynamic adjustment and optimization: The collection route is adjusted dynamically based on real-time traffic conditions, changes in the fullness of garbage bins, and feedback from collection vehicles.

[0032] Ensure that the dispatch system can update the route in real time and notify the removal vehicles.

[0033] 7. Data Analysis and Reporting: Collect data during the collection process, such as travel distance, collection time, garbage bin overflow, etc.

[0034] Use the dispatching system to generate removal reports to provide data support for future removal plans.

[0035] Through the above method, augmented reality technology can be applied to garbage collection and transportation scheduling, improving collection and transportation efficiency, reducing resource waste, and providing more intuitive decision support. This solution can be used as a value-added service for the existing garbage collection and transportation system to improve the intelligent level of urban garbage management.

[0036] Example 2 When calculating the path, we need to consider the priority removal areas. We need to introduce regional priority logic into the algorithm to ensure that when planning the path, the algorithm gives priority to areas with high garbage overflow or special needs. The path calculation steps that consider regional division and priority include: 1. Regional division and priority setting: The city is divided into different collection areas based on the geographical location of the garbage bins and the degree of garbage overflow.

[0037] Set a priority for each area, which can be based on factors such as garbage overflow, residential density, commercial area demand, etc.

[0038] 2. Data preparation: Collect data on the location, overflow and capacity of trash cans in each area.

[0039] Define vehicle capacities, cost parameters, road networks, and zone priorities.

[0040] 3. Shortest path calculation: For each highest priority area, use a shortest path algorithm (such as Dijkstra or A algorithm) to calculate the shortest path from the transfer station.

[0041] Consider the connections between areas and ensure that the routes in high-priority areas are planned first if the vehicle capacity allows.

[0042] 4. Calculation of the second shortest path and the second shortest path: For areas that are not the highest priority, the second shortest and second shortest paths are calculated for use after the high priority areas are cleared.

[0043] These paths are searched using heuristic algorithms such as genetic algorithms, ant colony algorithms, or simulated annealing algorithms, taking into account regional priorities.

[0044] 5. Cost calculation: For each calculated path, calculate its total cost, including driving distance, time, fuel consumption, and vehicle startup cost.

[0045] Make sure cost calculations include round trips, as well as possible route changes between different areas.

[0046] 6. Comprehensive scoring and path selection: Design a scoring system that takes factors such as the length, cost, service efficiency, and regional priority of the route as parameters.

[0047] Using a weighted scoring approach, each path is assigned a comprehensive score, and the weights can be adjusted based on actual conditions.

[0048] 7. Algorithm adjustment: In the pre-optimization phase, deterministic data is used to generate initial path plans, taking regional priorities into account.

[0049] During the re-optimization phase, the routes are adjusted based on the actual collection situation (such as changes in the overflow level of garbage bins), while taking regional priorities into consideration.

[0050] The above garbage collection and dispatching method is not only efficient and economical, but also can meet the special needs and priorities of different areas, and improve the overall quality and efficiency of collection and transportation services.

[0051] Example 3 In the process of implementing garbage collection and dispatching, the following methods can be used to ensure the balance between the density of garbage bin distribution and the allocation strategy of garbage collection vehicles: Dynamically divide the collection area according to the distribution density of garbage bins and the amount of garbage generated. High-density areas can be divided into smaller sub-areas to allocate vehicles more finely; develop or use existing vehicle routing problem (VRP) algorithms, such as genetic algorithms, ant colony algorithms, or simulated annealing algorithms, to optimize vehicle allocation and route planning; implement a real-time scheduling system that can dynamically adjust vehicle allocation based on the overflow of garbage bins, the current location and status of vehicles, and traffic conditions.

[0052] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A garbage removal and dispatching method, characterized by: The following steps are involved: S1. Install sensors on trash cans in the city to monitor the overflow of the trash cans in real time; S2, collect and visualize the overflow data of the trash can; S3. Counting the number of overflowing trash cans according to the collected overflow degree data; S4, dividing the garbage bin distribution area, setting a threshold value for the number of overflowing garbage bins, comparing the number of overflowing garbage bins in each area with the threshold value for the number of overflowing garbage bins, and determining the priority of the garbage removal area; S5. Set the garbage bin in each area whose garbage overflow degree reaches or exceeds the threshold as a node, and plan the optimal removal path in each area; S6. According to the garbage removal priority obtained in step S4, each area is cleared in turn.

2. A method for dispatching garbage removal according to claim 1, characterized in that: In step S5, the location of the trash can, road conditions, traffic regulations and estimated travel time are taken into consideration, and the planned removal route is the route with the lowest comprehensive evaluation result of cost and time.

3. A method for dispatching garbage removal according to claim 1, characterized in that: Step S5 specifically includes the following steps: S51, using a path planning algorithm to calculate three relatively shortest paths for each area; S52, design time-cost comprehensive evaluation model; S53, putting the three shortest paths in S51 into the time-cost comprehensive evaluation model, comparing the evaluation results, and taking the path with the best result as the optimal removal path.

4. A method for dispatching garbage removal according to claim 3, characterized in that: The design process of the time-cost comprehensive evaluation model includes the following steps: S521. Design an objective function that minimizes cleaning time and operating costs; S522, collecting data on the location of garbage bins, road conditions, traffic rules, estimated travel time, speed and capacity of garbage collection vehicles in each area; S523, establishing constraint conditions; S525, design cost function and time function; S526. Solve the objective function through the ant colony algorithm.

5. A method for dispatching garbage removal according to claim 4, characterized in that: The constraints include: Trash bin overflow constraint: Trash bins whose overflow reaches or exceeds the threshold are included in the removal path; Vehicle capacity constraint: The amount of cleanup for each vehicle does not exceed its capacity; Time window constraint: consider the time window in which the trash can can be cleared; Vehicle quantity constraint: Limit the number of removal routes based on the number of available vehicles.

6. A method for dispatching garbage removal according to claim 4, characterized in that: The cost function includes: calculating the travel cost of each path, including fuel consumption and labor costs.

7. A method for dispatching garbage removal according to claim 4, characterized in that: The time function predicts the travel time of each route as well as the loading and unloading time during the removal process based on road conditions and traffic regulations.

8. The method for dispatching garbage removal according to claim 1, characterized in that: Step S3 specifically includes the following steps: S31, determining the capacity limit value of each trash bin and saving it; S32. Marking four corners of the map of the removal area, the marking points are used to determine the scope of the removal area, determine the location of the garbage bin and record it; S33. Monitor the overflow level of the trash can in real time and visualize it.

9. A method for dispatching garbage removal according to claim 8, characterized in that: Step S33 specifically includes: comparing the overflow degree of the trash can with the capacity limit value, and performing visualization based on the comparison result, specifically: When the overflow degree is below a certain percentage of the limit value, the trash can is visualized as green, indicating normal; When the overflow level approaches or reaches the limit, the trash can is visualized as red, indicating that it needs to be cleared immediately; When the overflow exceeds the limit, the trash can is visualized in blue, indicating that the need for removal is urgent.

10. The method for dispatching garbage removal according to claim 1, characterized in that: Visualize the optimal path and use green arrows to mark the next removal point of the removal vehicle; The subsequent path to the next transfer station or destination is indicated by a solid orange line, providing navigation guidance.

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