Intelligent environment-friendly waste transfer method and system based on Internet of Things

Abstract

The invention relates to the technical field of the Internet of Things and intelligent environmental protection, and discloses an intelligent environmental protection waste transfer method and system based on the Internet of Things, and the system comprises a real-time transfer system which comprises a dynamic partitioning module, a multi-region weight monitoring module, a carrying vehicle real-time state monitoring module, and a central control unit. According to the invention, a service area is scientifically divided into a plurality of sub-area recovery units according to historical data and geographic positions through a dynamic partition module, so that the initial task load of each unit tends to be balanced, a solid foundation is laid for subsequent efficient scheduling, and the problem of non-uniform transport capacity distribution is avoided from the source; real-time traffic data are accessed into the path planning module, dynamic path planning is carried out by taking'vehicle load factor optimization 'and'lowest comprehensive transportation cost' as targets, so that the system can actively adapt to the dynamic change of an urban road network, a global optimal solution is sought, and the overall transportation cost is further reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of Internet of Things and intelligent environmental protection technology, more particularly to a waste intelligent environmental protection transfer method and system based on Internet of Things, which specifically realizes the optimization of waste transfer process through dynamic zoning, real-time monitoring and intelligent scheduling. BACKGROUND

[0002] With the acceleration of urbanization, the amount of household garbage, industrial waste and other waste increases dramatically, and higher requirements are put forward for the efficiency and environmental protection of the waste transfer system. The traditional waste transfer mode mainly relies on fixed route, fixed frequency pre-scheduling scheme, which has many inherent defects: Firstly, the scheduling is not scientific and the resources are wasted. The existing system cannot realize real-time sensing of the waste accumulation of each recycling station, and the vehicle is collected and transported according to the fixed route, which often appears the phenomenon of "empty running" (the garbage can is not full and is cleaned and transported, resulting in waste of transport capacity) or "explosion of the barrel" (the garbage is too much to be cleaned and transported in time, polluting the environment), low transportation efficiency and high operating cost.

[0003] Secondly, the environmental protection is difficult to guarantee. In the transportation process, because the closed state of the car and the leachate cannot be monitored in real time, there may be secondary pollution risks such as garbage scattering, leachate leakage and odor diffusion.

[0004] Therefore, there is an urgent need for a waste intelligent environmental protection transfer method and system based on Internet of Things to solve the above technical problems. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a waste intelligent environmental protection transfer method and system based on Internet of Things to solve the technical problems proposed in the background art.

[0006] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme: a waste intelligent environmental protection transfer system based on Internet of Things, comprising a real-time transfer system, wherein the real-time transfer system comprises a dynamic zoning module, a multi-region weight monitoring module, a vehicle real-time state monitoring module and a central control unit; The dynamic zoning module collects the historical average waste recycling weight data of each waste recycling station in the carrying area and the position information of each group of waste recycling stations, and performs region division calculation through the above-mentioned collected weight data and position information, forming a plurality of sub-regional recycling units; The multi-region weight monitoring module is arranged at each waste recycling station and is used for monitoring and reporting the weight data of the waste to be transferred at each station; The vehicle real-time state monitoring module is installed on the waste transfer vehicle and is used for real-time monitoring and reporting the remaining volume data of the vehicle box; The central control unit is in communication connection with the multi-region weight monitoring module and the real-time state monitoring module of the carrying vehicle, for monitoring the real-time waste recovery total weight data in each sub-region recovery unit, and adjusting the number and route of the carrying vehicle in real time.

[0007] Preferably, the multi-region weight monitoring module adopts a high-precision load cell sensor array and an edge computing node cooperative architecture, and a double-redundancy weighing system is deployed at each waste recovery station, and the weight data is uploaded to the central control unit in real time through a 5G communication module.

[0008] Preferably, the multi-region weight monitoring module has an embedded outlier detection algorithm, which can automatically identify and filter error data of ±3% or more caused by equipment failure or human interference, and simultaneously fuse GIS geographic information and historical production data of the recovery station.

[0009] Preferably, the real-time state monitoring module of the carrying vehicle has a dual-mode volume scanning unit integrated with a laser radar and an ultrasonic sensor, which scans the internal space of the cargo box in real time with millimeter-level precision, and combines with the edge computing node to perform real-time filtering and compression processing on the volume data, and uploads the data to the central control unit through a 5G communication module, to realize low-latency transmission and dynamic visual display of the remaining volume data.

[0010] Preferably, the specific criteria for the dynamic partition module to perform region division calculation are: Based on the geographic location information and historical average waste recovery amount of each waste recovery station in the carrying area, the space clustering algorithm is used for division, so that each group of sub-region recovery units generated finally satisfies the following two conditions: a. The sum of the geographic distances between all waste recovery stations in the unit is minimized; b. The total sum of the variance of the historical average waste recovery amount between units is minimized.

[0011] Preferably, the central control unit is internally provided with a carrying evaluation unit, a task coordination unit, and a path planning module; The carrying evaluation unit is used to calculate the theoretical number of vehicles required for each unit according to the total real-time recovery amount of each sub-region recovery unit. The task coordination module is used to make task decisions based on the theoretical number of vehicles: For a sub-region recovery unit with an integer theoretical number of vehicles, the task coordination module directly generates a corresponding task decision to control a corresponding number of waste transfer vehicles to enter the sub-region recovery unit for waste recovery work.

[0012] Preferably, the task coordination module makes task decisions for a non-integer unit with a theoretical number of vehicles greater than 1 in the following manner: Numerical decomposition step: the theoretical vehicle number N is split into an integer part I and a decimal part F, wherein N=I+F, and 0<F<1; Integer task generation step: control I number of waste transfer vehicles to enter the sub-area recycling unit to perform preliminary waste recycling work; Decimal task processing step: mark the remaining recycling amount corresponding to the decimal part F in the sub-area recycling unit as a to-be-merged sub-task, and dynamically combine the to-be-merged sub-tasks generated by two groups of sub-area recycling units adjacent in position to form a group of temporary merged transport tasks, and control the corresponding number of waste transfer vehicles to execute the temporary merged transport tasks.

[0013] Preferably, the path planning module: after the integer task and the temporary merged transport task are generated, real-time traffic data is accessed, and the vehicle full load rate optimization and the comprehensive transport cost minimization are taken as the target, so that the optimal collection route for the vehicle executing the task is planned, and the route is issued to the corresponding vehicle.

[0014] Preferably, the real-time state monitoring module of the carrying vehicle is provided with an abnormal volume fluctuation early warning unit, which automatically triggers the vehicle-mounted alarm device and sends an abnormal event notification to the dispatching center when detecting that the cargo box volume change rate exceeds the preset threshold range.

[0015] A waste intelligent environmental protection transfer method based on the Internet of Things is applied to a waste intelligent environmental protection transfer system based on the Internet of Things, and includes the following operation steps: Step one, based on the historical data and position information of each recycling station, a spatial clustering algorithm is used to generate multiple groups of sub-area recycling units with compact distance and balanced recycling amount; Step two, real-time collection of waste weight data of each station by high-precision sensors, and synchronous monitoring of the remaining volume data of the transfer vehicle, after processing, uploading to the central control unit; Step three, according to the real-time total weight of the sub-area, calculate the theoretical vehicle number, generate standard tasks for integer units, and perform task splitting and dynamic merging for non-integer units; Step four, in combination with real-time traffic data, taking improving the full load rate and reducing the transportation cost as the target, planning the optimal collection route for each task and issuing the execution; Step five, real-time state monitoring of the carrying vehicle is carried out through the abnormal volume fluctuation early warning unit, which is used for monitoring the internal volume fluctuation change of the carrying vehicle in the transportation state, and warning the abnormal volume fluctuation, to ensure the safe and reliable operation of the system.

[0016] The technical effects and advantages of the present application are as follows: The application divides the service area into multiple sub-regional recycling units according to historical data and geographical position through a dynamic partition module, so that the initial task amount of each unit tends to be balanced, which lays a solid foundation for subsequent efficient scheduling and avoids uneven distribution of transport capacity from the source; The central control unit can accurately calculate the theoretical vehicle number and intelligently split and dynamically combine non-integer tasks through the dual data sensing of multi-region weight monitoring and vehicle state monitoring. The method changes the "fixed route" to "demand-driven", so that each trip is as full as possible, greatly reducing the empty mileage and half-load transportation, significantly reducing fuel consumption, vehicle wear and labor cost; The path planning module accesses real-time traffic data to dynamically plan the path with the goal of "vehicle full load rate optimization" and "lowest comprehensive transportation cost", so that the system can actively adapt to the dynamic changes of the urban road network, seek the global optimal solution and further reduce the overall transportation cost. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 The overall flowchart of the real-time transfer system of the application.

[0018] Figure 2 The overall flowchart of the waste intelligent environmental protection transfer method of the application. DETAILED DESCRIPTION

[0019] The technical solutions in the application will be described clearly and completely in combination with the drawings in the application, and the forms of each structure described in the following embodiments are only examples. The waste intelligent environmental protection transfer method and system based on the Internet of Things are not limited to the structures described in the following embodiments.

[0020] The application provides a waste intelligent environmental protection transfer system based on the Internet of Things, which comprises a real-time transfer system. The dynamic partition module collects historical average waste recycling weight data of each waste recycling station in the transport area and position information of each group of waste recycling stations, and performs regional division calculation through the collected weight data and position information to form multiple groups of sub-regional recycling units. The multi-region weight monitoring module is deployed at each waste recycling station and is used for monitoring and reporting the weight data of the waste to be transferred at each station. The vehicle-carrying real-time state monitoring module is installed on the waste transfer vehicle and is used for monitoring and reporting the residual volume data of the vehicle container in real time. The central control unit is in communication connection with the multi-region weight monitoring module and the vehicle-carrying real-time state monitoring module, is used for monitoring the real-time total weight data of the waste in each sub-region recycling unit, and is used for adjusting the number of vehicle carriers and the carrying route in real time.

[0021] Referring to Figure 1 As shown in the figure, the application provides a waste intelligent environmental protection transfer system based on the Internet of Things, and the specific criteria for the dynamic partition module to perform region division calculation are: Based on the geographical position information and the historical average waste recycling amount of each waste recycling station in the carrying region, the space clustering algorithm is used for division, so that each group of sub-region recycling units generated finally meets the following two conditions: a. The sum of the geographical distances between all waste recycling stations in the unit is minimum; b. The total sum variance of the historical average recycling amount of waste between units is minimum.

[0022] Referring to Figure 1 As shown in the figure, the application provides a waste intelligent environmental protection transfer system based on the Internet of Things, and the central control unit is internally provided with a carrying evaluation unit, a task coordination unit and a path planning module; The carrying evaluation unit is used for calculating the theoretical number of vehicles required by each unit according to the total real-time recycling amount of each sub-region recycling unit. The task coordination module is used for making task decisions based on the theoretical number of vehicles: For the sub-region recycling unit with an integer theoretical number of vehicles, the task coordination module directly generates the corresponding task decision to control the corresponding number of waste transfer vehicles to enter the sub-region recycling unit to carry out waste recycling work; The task coordination module makes task decisions for the non-integer unit with a theoretical number of vehicles greater than 1 in the following way: Numerical decomposition step: the theoretical number of vehicles N is split into an integer part I and a decimal part F, where N=I+F, and 0 Integer task generation step: control I number of waste transfer vehicles to enter the sub-region recycling unit to carry out preliminary waste recycling work; Decimal task processing step: mark the residual recycling amount corresponding to the decimal part F in the sub-region recycling unit as a to-be-merged sub-task, dynamically combine the to-be-merged sub-tasks generated by two groups of sub-region recycling units adjacent in position to form a group of temporary merged transportation tasks, and control the corresponding number of waste transfer vehicles to execute the temporary merged transportation tasks; Path planning module: after the integer task and the temporary combined transportation task are generated, access real-time traffic data, and plan the optimal collection route for the vehicle executing the task with the goal of "vehicle full load rate optimization" and "lowest comprehensive transportation cost", and issue the route to the corresponding vehicle.

[0023] In the embodiments of the present application, when the required vehicle for the temporary combined transportation task is non-integer data, R waste carrying vehicles with a carrying capacity greater than and adjacent to the required carrying capacity of the temporary combined transportation task are controlled to execute the temporary combined transportation task; The specific way of achieving "lowest comprehensive transportation cost" by the path planning module is as follows: A comprehensive cost function Cert is constructed and solved, and its expression is as follows: ; Wherein, Ω1, Ω2, Ω3 and Ω4 are preset weight coefficients corresponding to each cost item of the comprehensive cost function Cert, and the optimal weight ratio is determined by historical data training; Wherein, L is the total driving distance of the planned route; T is the total driving time predicted based on real-time traffic data; F is the fuel consumption and vehicle wear model function value dynamically calculated based on the real-time load W of the vehicle, driving distance L and road condition R (including slope, congestion level); V is the additional loss evaluation value caused by vehicle idling and frequent start-stop due to traffic congestion in the route; The construction of the fuel consumption and vehicle wear model function value F and the congestion additional loss evaluation value V is based on the mature vehicle dynamics model and traffic engineering theory in the art, which belongs to the existing technical category.

[0024] In this part of the application embodiments, the "High-tech Park" transfer area of a city is taken as an example to demonstrate the specific operation process of the task coordination module of the present application. The area is divided into a.b.C three sub-regional recycling units; The carrying evaluation unit calculates the theoretical number of vehicles: Wherein, the capacity of the waste carrying vehicle is 5 tons; The amount of waste recovered in unit A is 12.3 tons; the amount of waste recovered in unit B is 3.2 tons; the amount of waste recovered in unit C is 4.1 tons; The required carrying vehicle data for unit A is: 12.3÷5=2.46 vehicles; the required carrying vehicle data for unit B is: 3.2÷5=0.64 vehicles; the required carrying vehicle data for unit C is: 4.1÷5=0.82 vehicles; Task coordination module decision process: Unit A processing (theoretical number of vehicles 2.46>1) Numerical decomposition steps: Integer part I = 2; decimal part F = 0.46; Integer task generation step: Immediately dispatch 2 transfer vehicles into unit A; each vehicle is loaded to the rated load of 5 tons, a total of 10 tons of waste is transported away; the remaining recovery amount of unit A: 2.3 tons; Decimal task processing step: mark 2.3 tons as "to-be-merged subtask A-remaining" Unit b.C is identified as a to-be-merged unit Unit B: 0.64 < 1, marked as "to-be-merged unit B" Unit C: 0.82 < 1, marked as "to-be-merged unit C" Step 3: Temporary merged transportation task generation: Dynamic combination calculation: To-be-merged subtask A-remaining: 2.3 tons; To-be-merged subtask B-remaining: 3.2 tons To-be-merged unit C: 4.1 tons Total recovery amount: 2.3 + 3.2 + 4.1 = 9.6 tons Temporary merged transportation task analysis: Theoretically required number of vehicles: 9.6 ÷ 5 = 1.92 vehicles Actual number of vehicles arranged R = 2 vehicles (because the total capacity of 2 vehicles is 10 tons > 9.6 tons, and it is the closest integer number of vehicles) Path planning module optimizes the route: The path planning module plans the optimal collection route for the 2 vehicles performing the temporary merged task based on real-time traffic data.

[0025] Reference Figure 1 As shown, the application provides a waste intelligent environmental protection transfer system based on Internet of Things, the multi-region weight monitoring module adopts high-precision load cell type sensor array and edge computing node cooperative architecture, double redundant weighing system is deployed at each waste recycling station, weight data is uploaded to the central control unit in real time through the 5G communication module; The multi-region weight monitoring module has an embedded outlier detection algorithm, which can automatically identify and filter error data of ±3% or more caused by equipment failure or human interference, and simultaneously fuse GIS geographic information and historical production data of recycling stations; In the embodiment of the application, the multi-region weight monitoring module is internally provided with an LSTM neural network to construct a dynamic weight prediction model, which is beneficial to predicting the weight change trend of waste to be transferred at each station 2 hours in advance, and providing real-time and forward-looking weight data support for the dynamic path optimization engine; In the embodiments of the application, the double-redundancy weighing system described above belongs to the prior art, and its core is to realize high-reliability weighing through double-scales, double sensors or double-mode redundancy design, which has been widely applied in many fields such as industry, logistics and transportation.

[0026] In the embodiments of the application, the outlier detection algorithm in the multi-region weight monitoring module adopts a prior art method based on statistics or machine learning, such as Z-score standard score method, IQR quartile range method, isolated forest unsupervised model or LSTM time series analysis, for identifying and filtering error data of ±3% or more caused by equipment failure or human interference.

[0027] Referring to Figure 1 As shown in the figure, the application provides a waste intelligent environmental protection transfer system based on Internet of Things, a dual-mode volume scanning unit integrating laser radar and ultrasonic sensor inside the real-time state monitoring module of the carrying vehicle, which realizes real-time scanning of the internal space change of the cargo box with millimeter-level precision, real-time filtering and compression processing of the volume data combined with the edge computing node, uploads the remaining volume data to the central control unit through the 5G communication module, and realizes low-delay transmission and dynamic visual display of the remaining volume data.

[0028] In the embodiments of the application, the abnormal volume fluctuation early warning unit is built-in the real-time state monitoring module of the carrying vehicle, and when it is detected that the cargo box volume change rate exceeds the preset threshold range, the vehicle-mounted alarm device is automatically triggered and an abnormal event notification is sent to the dispatch center, so as to ensure the safety and controllability of the transportation process. The preset threshold range is set by the user himself / herself, and the preset threshold range of the application is: the internal volume change rate is 0%-3.65%, and the abnormal event notification: the abnormal event notification indicates that the waste carrying vehicle has the phenomenon of goods falling off or abnormal increase of internal goods during transportation.

[0029] Referring to Figure 2 As shown in the figure, the application provides a waste intelligent environmental protection transfer method based on Internet of Things, which is applied to a waste intelligent environmental protection transfer system based on Internet of Things and includes the following operation steps: Step one, based on the historical data and location information of each recycling station, a spatial clustering algorithm is used to generate multiple groups of sub-regional recycling units with compact distance and balanced recycling amount; Step two, real-time collection of waste weight data of each station by high-precision sensors, and synchronous monitoring of the remaining volume data of the cargo box of the transfer vehicle, uploading to the central control unit after processing; Step three, calculating the theoretical number of vehicles according to the real-time total weight of the sub-regions, generating standard tasks for integer units, and performing task splitting and dynamic merging for non-integer units; Step four, in combination with real-time traffic data, to improve the full load rate and reduce transportation costs, for each task to plan the optimal collection route and issue execution; Step five, through the abnormal volume fluctuation early warning unit, the real-time state of the carrying vehicle is monitored, which is used for monitoring the volume fluctuation change of the carrying vehicle in the transportation state, and the abnormal volume fluctuation is warned to ensure the safe and reliable operation of the system.

[0030] The above embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solutions. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application. Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0031] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be realized by other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0032] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0033] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0034] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, and all of them should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0035] Finally, the above merely provides the preferred embodiments of the present application, and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. An intelligent and environmentally friendly waste transfer system based on the Internet of Things, characterized in that: The real-time transfer system comprises a dynamic partition module, a multi-region weight monitoring module, a vehicle real-time state monitoring module, and a central control unit. The dynamic partition module collects historical average waste recycling weight data of each waste recycling station in the transfer region and position information of each group of waste recycling stations, and performs region division calculation based on the collected weight data and position information to form a plurality of sub-region recycling units. The multi-region weight monitoring module is arranged at each waste recycling station and is used for monitoring and reporting the weight data of the waste to be transferred at each station. The vehicle real-time state monitoring module is installed on the waste transfer vehicle and is used for real-time monitoring and reporting of the remaining volume data of the vehicle box. The central control unit is in communication connection with the multi-region weight monitoring module and the vehicle real-time state monitoring module, and is used for monitoring the real-time total weight data of waste recycling in each sub-region recycling unit, and adjusting the number and route of the vehicle in real time.

2. The IoT-based intelligent environmental-protection waste transfer system according to claim 1, characterized in that: The multi-region weight monitoring module adopts a high-precision load cell sensor array and an edge computing node cooperative architecture, and a double-redundancy weighing system is arranged at each waste recycling station. The weight data is uploaded to the central control unit in real time through a 5G communication module.

3. The IoT-based intelligent environmental-protection waste transfer system according to claim 2, characterized in that: The multi-region weight monitoring module has an embedded outlier detection algorithm, which can automatically identify and filter error data of ±3% or more caused by equipment failure or human interference, and simultaneously fuse GIS geographic information and historical production data of the recycling station.

4. The intelligent environment-friendly waste transfer system based on the Internet of Things according to claim 1, characterized in that: The vehicle real-time state monitoring module integrates a dual-mode volume scanning unit of laser radar and ultrasonic sensor, which scans the internal space of the box in real time with millimeter-level precision, and combines the edge computing node to perform real-time filtering and compression processing on the volume data. The volume data is uploaded to the central control unit through a 5G communication module, realizing low-delay transmission and dynamic visual display of the remaining volume data.

5. The intelligent environment-friendly waste transfer system based on the Internet of Things according to claim 1, characterized in that: The specific criteria for the dynamic partition module to perform region division calculation are as follows: Based on the geographical position information and historical average waste recycling amount of each waste recycling station in the transfer region, the space clustering algorithm is used for division, so that each sub-region recycling unit generated finally satisfies the following two conditions: a. The sum of the geographical distances between all waste recycling stations in the unit is minimized; b. The total sum of variance of the historical average recycling amount of waste between units is minimized.

6. The intelligent environment-friendly transfer system for waste based on the Internet of Things according to claim 1, characterized in that: The central control unit is internally provided with a vehicle evaluation unit, a task coordination unit, and a path planning module. The vehicle evaluation unit is used to calculate the theoretical number of vehicles required for each unit based on the total real-time recycling amount of each sub-region recycling unit. The task coordination module is used for task decision based on the theoretical number of vehicles: For a sub-region recycling unit with an integer theoretical number of vehicles, the task coordination module directly generates a corresponding task decision to control a corresponding number of waste transfer vehicles to enter the sub-region recycling unit for waste recycling work.

7. The IoT-based intelligent environmental-protection waste transfer system according to claim 6, characterized in that: For a non-integer unit with a theoretical number of vehicles greater than 1, the task coordination module makes a task decision in the following manner: Numerical decomposition step: the theoretical vehicle number N is split into an integer part I and a fractional part F, where N=I+F, and 0 Integer task generation step: control I number of waste transfer vehicles to enter the sub-area recycling unit to carry out preliminary waste recycling work; Fractional task processing step: mark the remaining recycling amount corresponding to the fractional part F in the sub-area recycling unit as a to-be-merged sub-task, and dynamically combine the to-be-merged sub-tasks generated by two groups of sub-area recycling units adjacent in position to form a group of temporary merged transportation tasks, and control the corresponding number of waste transfer vehicles to execute the temporary merged transportation tasks.

8. The waste intelligent environmental protection transfer system based on the Internet of Things according to claim 6, characterized in that: The path planning module is used to access real-time traffic data after the integer task and the temporary merged transportation task are generated, and to plan the optimal collection route for the vehicle executing the task with the goals of "vehicle full load rate optimization" and "comprehensive transportation cost minimization", and to issue the route to the corresponding vehicle.

9. The intelligent environment-friendly transfer system for waste based on the Internet of Things according to claim 4, characterized in that: The abnormal volume fluctuation early warning unit is built in the real-time state monitoring module of the carrying vehicle, and when the detection of the cargo box volume change rate exceeds the preset threshold range, the vehicle-mounted alarm device is automatically triggered and an abnormal event notification is sent to the dispatch center.

10. The IoT-based intelligent environmental-protection waste transfer method is applied to the IoT-based intelligent environmental-protection waste transfer system of any one of claims 1-9, characterized in that, The following operation steps are included: Step one: based on the historical data and position information of each recycling station, a spatial clustering algorithm is used to generate multiple groups of sub-area recycling units with compact distance and balanced recycling amount; Step two: real-time collection of waste weight data of each station by high-precision sensors, and synchronous monitoring of the remaining volume data of the transfer vehicle, after processing, uploaded to the central control unit; Step three: calculate the theoretical vehicle number according to the real-time total weight of the sub-area, generate standard tasks for integer units, and perform task splitting and dynamic merging for non-integer units; Step four: combine real-time traffic data, and plan the optimal collection route for each task with the goals of improving full load rate and reducing transportation cost, and issue the execution; Step five: real-time state monitoring of the carrying vehicle by the abnormal volume fluctuation early warning unit, which is used to monitor the internal volume fluctuation change of the carrying vehicle in the transportation state, and to warn the volume abnormal fluctuation, to ensure the safe and reliable operation of the system.

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