Intelligent scheduling system and method for open-pit mine road transport dust spray dust suppression

Abstract

The application discloses an intelligent scheduling system and method for open-pit mine road transportation dust spraying and dust reduction, which is composed of a multi-source sensing layer, a central scheduling platform, a collaborative execution layer and a digital twin and simulation module. The multi-source sensing layer is used for real-time collection of environmental and vehicle dynamic data. The central scheduling platform predicts future dust concentration by using a dust space-time distribution prediction module, and generates optimal collaborative operation instructions through a dust reduction scheduling optimization engine. The collaborative execution layer includes fixed intelligent spraying devices and mobile intelligent spraying terminals controlled by the instructions, which respectively perform fixed-point and mobile spraying operations. The digital twin and simulation module performs three-dimensional visualization and simulation evaluation on the whole process. Through data-driven predictive scheduling and resource collaboration, the application realizes precise dust reduction from passive response to active prevention, significantly improves the efficiency and intelligent level of open-pit mine road transportation dust control, and effectively saves water resources.

Description

Technical Field

[0001] This invention relates to the field of mine environmental protection and intelligent control technology, specifically to an intelligent scheduling system and method for dust suppression spraying during open-pit mine road transportation. Background Technology

[0002] Road transportation in open-pit mines is a crucial link in mining production, involving frequent trips by heavy trucks along mining roads. During vehicle movement, turning, braking, and the movement of materials, significant amounts of dust pollutants are generated due to tire pressure, road dust, and material spillage. This dust not only severely deteriorates the working environment in the mining area, affecting the occupational health and driving safety of workers, but also accelerates the wear and tear on machinery and equipment, and causes continuous pollution to the atmosphere in and around the mining area.

[0003] To address the problems of severe resource waste, poor dust suppression effect, and slow equipment response in open-pit mine road transport dust control technologies, existing patent CN116905418A discloses an intelligent maintenance system for open-pit mine roads. This system includes a PLC control module, a dust suppression device, and a water supply module. The PLC control module acquires environmental information and controls the dust suppression device using a dust concentration detector, temperature and humidity sensors, and infrared sensors. The dust suppression device employs an underground pre-embedded automatic telescopic structure. The water supply module ensures water supply through a reservoir and a collection pit. This system can dynamically start and stop dust suppression operations based on real-time road conditions. The telescopic design of the dust suppression device does not affect traffic operation, saving water resources while maintaining road conditions. It is suitable for dust control and road maintenance in open-pit mine transport roads. However, this technology only addresses local control and lacks comprehensive consideration of the overall dust diffusion patterns, traffic flow dynamics, and meteorological changes within the mining area. Secondly, patent number CN112012151A discloses an intelligent dust suppression system for open-pit mine transportation roads based on big data. This system includes a data sensing unit, a numerical control unit, and an adaptive spraying unit. The data sensing unit captures multi-dimensional data through position, vibration, temperature, humidity, and wind sensors, as well as road surface image acquisition equipment. The numerical control unit amplifies, integrates, and analyzes the data. The adaptive spraying unit adjusts spraying parameters through a water pressure control unit based on instructions from an intelligent identification module. This system integrates big data and machine learning technologies to achieve simultaneous dust control and dust suppression, intelligently identify spraying conditions, and save water resources and labor costs. It is suitable for open-pit mine transportation roads, spoil heaps, and other areas with thick dust. However, this system primarily focuses on determining the start and stop conditions for single-point spraying, failing to address the coordinated scheduling of multiple mobile resources (water trucks) and fixed resources (spray towers) in time and space.

[0004] In summary, current open-pit mine dust control systems generally suffer from a disconnect between monitoring and execution, as well as inefficient scheduling. Monitoring networks lack comprehensive coverage and rely on limited sensing methods, depending on isolated fixed-point sensors, making it difficult to dynamically capture dust sources and diffusion paths moving with vehicle traffic. Furthermore, there is insufficient data value mining; there is a lack of intelligent linkage between monitoring data and dust suppression equipment control commands. Control models are mostly "post-event response" or "fixed-time, fixed-location" patterns, lacking the ability to predict and optimize dust distribution patterns based on these patterns. This results in poor accuracy in dust suppression operations, significant resource waste (such as excessive watering in dust-free areas or insufficient suppression in high-dust areas), and overall low dust suppression efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent scheduling system and method for dust spraying in open-pit mine road transportation, which is characterized by clear structure, intelligent operation, precise dust suppression, and deep integration of dust control with production and transportation. This system aims to solve the technical problems of severe dust pollution in existing open-pit mine road transportation links, as well as the large resource waste, low operating efficiency, slow response, extensive management, and lack of global collaborative scheduling in traditional water spraying dust suppression methods.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] An intelligent scheduling system for dust suppression spraying during road transportation in open-pit mines includes a multi-source sensing layer, a central scheduling platform, a collaborative execution layer, and a digital twin and simulation module.

[0008] The multi-source sensing layer is used to collect real-time data on dust environment and dynamic data of transport vehicles in the mining area. It includes dust sensors and micro weather stations deployed along the mining area roads, as well as positioning terminals and vehicle status sensors installed on transport trucks.

[0009] The central dispatch platform is connected to the multi-source sensing layer and the collaborative execution layer via a wireless communication network. It includes a data fusion and management module, a dust spatiotemporal distribution prediction module, a dust suppression scheduling optimization engine, and an instruction issuance and monitoring module. The data fusion and management module processes and standardizes multi-source data. The dust spatiotemporal distribution prediction module predicts the spatiotemporal distribution of dust on mining roads within a future time period based on the processed data. The dust suppression scheduling optimization engine generates collaborative dust suppression operation instructions based on the dust prediction results and system resource status. The instruction issuance and monitoring module issues operation instructions and monitors their execution status.

[0010] The collaborative execution layer is used to receive and execute dust suppression instructions issued by the central dispatch platform, and includes fixed intelligent spraying devices and mobile intelligent spraying terminals controlled by the instructions.

[0011] The digital twin and simulation module is connected to the central dispatch platform to build and run a three-dimensional digital twin model synchronized with the physical system, enabling visualization, simulation, and effect evaluation of the operation process.

[0012] Furthermore, the fixed intelligent spraying device includes a controller, a solenoid valve, a pressure regulating valve, a nozzle array, and a local vehicle detection sensor; wherein, the controller is used to receive instructions from the central dispatch platform and control the solenoid valve and the pressure regulating valve to drive the nozzle array to perform spraying operations; the local vehicle detection sensor is used to assist in realizing vehicle sensing start-stop control.

[0013] Furthermore, the mobile intelligent spray terminal is a sprinkler truck integrated with an intelligent control system, which includes an on-board controller, a high-precision positioning module, a flow-adjustable spray system, and an on-board water tank level sensor. The on-board controller is used to receive and execute path and spraying parameter instructions issued by the central dispatch platform; the high-precision positioning module is used to report the vehicle's location in real time; the flow-adjustable spray system is used to perform dynamic spraying; and the on-board water tank level sensor is used to monitor the water tank status.

[0014] Furthermore, the dust spatiotemporal distribution prediction module in the central dispatch platform is embedded with a deep learning-based prediction model, which is used to integrate historical environmental data, real-time meteorological data and vehicle dynamic trajectory data to output a heat map of the spatiotemporal distribution of dust concentration on mining roads within the next 15-30 minutes.

[0015] Furthermore, the optimization objectives of the dust suppression scheduling optimization engine in the central scheduling platform include at least one of minimizing the total water consumption of the system, maximizing the dust suppression coverage rate in areas with excessive dust, and balancing the workload of each dust suppression device. Based on the dust spatiotemporal distribution prediction results, combined with the availability status of each fixed intelligent spray device, the location of each mobile intelligent spray terminal, the remaining water volume, and the operating status, it uses a multi-objective optimization algorithm to generate a collaborative operation instruction set.

[0016] Furthermore, the digital twin and simulation module can import a three-dimensional geographic information model of the mining area and synchronously map and visualize real-time data streams, equipment status, and command streams in a virtual scene, supporting the playback of historical operation scenarios and the simulation and deduction of future scheduling schemes.

[0017] Furthermore, the instruction issuance and monitoring module in the central scheduling platform is used to continuously receive feedback signals from the execution equipment and compare them with the actual concentration change data fed back by the dust sensor. This is used to evaluate the dust reduction effect and drive the adaptive iterative optimization of the dust spatiotemporal distribution prediction module and the dust reduction scheduling optimization engine.

[0018] This invention provides another technical solution: an intelligent scheduling method for dust suppression spraying during open-pit mine road transportation, based on an intelligent scheduling system for dust suppression spraying during open-pit mine road transportation, comprising the following steps:

[0019] S1: Real-time collection of environmental dust concentration, meteorological data, and location, speed, and load status data of transport vehicles in the mining area through a multi-source sensing layer, and transmission to the central dispatch platform via a wireless communication network;

[0020] S2: The data fusion and management module of the central dispatch platform cleans and aligns the received multi-source data in a spatiotemporal manner; subsequently, the dust spatiotemporal distribution prediction module predicts the dust spatiotemporal distribution of the mining area road network in the future based on the processed data;

[0021] S3: The dust suppression scheduling optimization engine generates the optimal collaborative operation instructions for fixed intelligent spray devices and mobile intelligent spray terminals through optimization calculations based on the dust prediction results of S2 and the real-time resource status of each dust suppression device in the system.

[0022] S4: The instruction issuance and monitoring module issues the operation instructions generated by S3 to the corresponding execution equipment; the fixed intelligent spraying device and the mobile intelligent spraying terminal receive and execute the instructions to complete the fixed-point or mobile dust suppression operation;

[0023] S5: The instruction issuance and monitoring module monitors the instruction execution status of each device, while the digital twin and simulation module provides a three-dimensional visualization of the entire process. The system continuously optimizes the prediction model and scheduling strategy based on feedback data from the actual dust reduction effect.

[0024] Furthermore, the optimal collaborative operation instructions generated in S3 include: allocating start and stop times and spray flow parameters for fixed intelligent spraying devices; and planning optimal operation paths and allocating spraying parameters along the way for mobile intelligent spraying terminals.

[0025] Furthermore, the continuous optimization in S5 specifically involves taking the deviation between the predicted and actual dust concentration values ​​and the deviation between the actual and expected resource consumption of dust suppression operations as optimization targets, and using machine learning algorithms to periodically or trigger the updates of the model parameters of the dust spatiotemporal distribution prediction module and the decision rules of the dust suppression scheduling optimization engine.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] 1. The present invention provides an intelligent scheduling system and method for dust suppression spraying on open-pit mine roads. By using a dust spatiotemporal distribution prediction module, the system accurately predicts the future dust concentration on mine roads, transforming dust suppression operations from a traditional "passive response" to "active prevention." This system enables effective intervention before large-scale dust diffusion, significantly improving the timeliness and effectiveness of dust suppression.

[0028] 2. The present invention provides an intelligent scheduling system and method for dust suppression spraying in open-pit mine road transportation. Through a dust suppression scheduling optimization engine, it performs global collaborative optimization scheduling of fixed and mobile dust suppression resources, realizing on-demand and precise spraying, avoiding resource conflicts and blind spots in operation. While ensuring that the dust suppression effect meets environmental protection requirements, it can significantly reduce water and energy consumption and reduce equipment damage caused by ineffective operations.

[0029] 3. The present invention provides an intelligent scheduling system and method for dust suppression spraying in open-pit mine road transportation. Through a digital twin module, it provides intuitive global situational awareness and scheme pre-simulation capabilities. Through a closed-loop feedback mechanism, it continuously optimizes the prediction model, realizing the system's self-learning and self-adaptation. The system is stable and reliable in operation and can significantly reduce the intensity of manual labor. Attached Figure Description

[0030] Figure 1 This is a framework diagram of the scheduling system of the present invention;

[0031] Figure 2 This is a schematic diagram showing the deployment and installation of the fixed intelligent spraying device of the present invention on a mining area road.

[0032] Figure 3 This is a schematic diagram of the integrated structure of the mobile intelligent spray terminal of the present invention;

[0033] Figure 4 This is a schematic diagram illustrating the workflow of the scheduling method according to an embodiment of the present invention.

[0034] In the diagram: 1. Dust sensor; 2. Miniature weather station; 3. Transport truck; 4. Positioning terminal; 5. Vehicle status sensor; 7. Fixed intelligent spraying device; 8. Mobile intelligent spraying terminal; 15-Controller; 16-Solenoid valve; 17-Pressure regulating valve; 18-Nose array; 19-Local vehicle detection sensor; 20-Vehicle controller; 21-High-precision positioning module; 22-Flow adjustable spraying system; 23-Vehicle water tank level sensor; 24-Mining road; 25-Cabin; 26-Vehicle water tank; 27-Truck chassis; 28-Water supply pipeline; 29-Control box. Detailed Implementation

[0035] 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Please see Figure 1-3 This invention provides an intelligent scheduling system for dust suppression spraying during road transportation in open-pit mines. The system comprises a multi-source sensing layer, a central scheduling platform, a collaborative execution layer, and a digital twin and simulation module.

[0037] The multi-source sensing layer comprises environmental sensing units and vehicle sensing units. Environmental sensing units are deployed at key locations along the mining area road 24, including a dust sensor 1 and a miniature weather station 2. Dust sensor 1 monitors the real-time concentrations of total suspended particulate matter, inhalable particulate matter, and fine particulate matter. Miniature weather station 2 monitors meteorological parameters such as wind speed, wind direction, ambient temperature, relative humidity, and atmospheric pressure. Vehicle sensing units are installed on the mining area transport trucks 3, including a GNSS / BeiDou positioning terminal 4 and an onboard status sensor 5. GNSS / BeiDou positioning terminal 4 acquires the vehicle's real-time latitude and longitude coordinates, elevation, speed, and heading angle. Onboard status sensor 5 acquires the vehicle's load status, cargo box lifting status, and engine operating status. All sensing data is uploaded to the central dispatch platform via a wireless communication network.

[0038] The central dispatch platform connects to the multi-source sensing layer and collaborative execution layer via a wireless communication network. It includes a data fusion and management module, a dust spatiotemporal distribution prediction module, a dustfall scheduling optimization engine, and a command issuance and monitoring module. The data fusion and management module receives, cleans, spatiotemporally aligns, and standardizes multi-source heterogeneous data from dust sensor 1, miniature weather station 2, GNSS / BeiDou positioning terminal 4, and vehicle status sensor 5, and stores it in a spatiotemporal database for unified management. The dust spatiotemporal distribution prediction module embeds a deep learning-based prediction model to fuse historical environmental data, real-time meteorological data, and vehicle dynamic trajectory data, outputting a heat map of the spatiotemporal distribution of dust concentration on mining roads for the next 15-30 minutes. The dust suppression scheduling optimization engine generates optimal collaborative dust suppression operation instructions based on the predicted spatiotemporal distribution of dust concentration, combined with preset dust suppression strategies and resource constraints. Its optimization objectives include at least one of minimizing total system water consumption, maximizing dust suppression coverage in areas exceeding dust standards, and balancing the workload of each dust suppression device. Based on the predicted spatiotemporal distribution of dust, combined with the availability status of each fixed intelligent spray device 7, the location, remaining water volume, and operational status of each mobile intelligent spray terminal 8, it uses a multi-objective optimization algorithm to generate a set of collaborative operation instructions. The instruction issuance and monitoring module issues collaborative dust suppression operation instructions to the collaborative execution layer via a wireless communication network and monitors the instruction execution status in real time. Specifically, the instruction issuance and monitoring module continuously receives feedback signals from the execution devices and compares them with the actual concentration change data fed back by the dust sensor 1 to evaluate the dust suppression effect and drive the adaptive iterative optimization of the dust spatiotemporal distribution prediction module and the dust suppression scheduling optimization engine.

[0039] The collaborative execution layer includes fixed intelligent spraying devices 7 and mobile intelligent spraying terminals 8. Figure 2 As can be seen, the fixed intelligent spraying device 7 is deployed along the mining area road 24 or at key dust-generating points, including a controller 15, a solenoid valve 16, a pressure regulating valve 17, a nozzle array 18, and a local vehicle detection sensor 19. The controller 15 receives instructions from the central dispatch platform via a wireless communication network, controlling the on / off state of the solenoid valve 16 and the opening degree of the pressure regulating valve 17, thereby regulating the spraying start / stop and flow rate of the nozzle array 18. The local vehicle detection sensor 19 (such as radar) feeds back the detected vehicles to the controller 15 in real time, assisting in achieving refined control. Figure 3As can be seen, the mobile intelligent spray terminal 8 is integrated on the sprinkler truck, including an on-board controller 20, a high-precision positioning module 21, a flow-adjustable spray system 22, and an on-board water tank level sensor 23. The on-board controller 20 receives and executes route and spraying parameter instructions issued by the central dispatch platform; the high-precision positioning module 21 reports the vehicle's location in real time; the flow-adjustable spray system 22 performs dynamic spraying; and the on-board water tank level sensor 23 monitors the water tank status.

[0040] In the above embodiments, the digital twin and simulation module is connected to the central dispatch platform to construct a three-dimensional virtual scene of the open-pit mine. It can visualize and display multi-source sensing data, vehicle trajectories, and the operating status of dust suppression equipment in real time. It can also simulate and evaluate the dust suppression scheme generated by the dispatch optimization engine in the virtual environment, and predict its dust suppression effect and resource consumption. Specifically, it can import the three-dimensional geographic information model of the mining area and synchronously map and visualize the real-time data stream, equipment status, and command stream in the virtual scene. It supports the playback of historical operation scenarios and the simulation and deduction of future dispatch schemes.

[0041] As the intensity of production and transportation in the mining area changes, the sources and paths of dust generation and diffusion will dynamically change. Therefore, the dust spatiotemporal distribution prediction module of the central dispatch platform needs to continuously update the prediction results based on real-time traffic flow and meteorological data. The dust suppression dispatch optimization engine dynamically adjusts and issues operation instructions based on the latest prediction results and resource status (such as the location of sprinkler trucks and the water volume in the tanks). For example, when it is predicted that dust will exceed the standard on a certain road section due to dense traffic, the optimization engine will instruct the nearby fixed spraying device 7 to enter the "standby" state in advance and dispatch a mobile spraying terminal 8 to supplement the spraying along the road section. The instruction issuance and monitoring module will track the execution of instructions in real time, such as whether the sprinkler truck travels along the planned path and whether the spray flow rate meets the standard, forming a closed-loop control. The digital twin and simulation module will synchronously display and record the above process in a three-dimensional scene, providing managers with global situational awareness and decision support.

[0042] To further explain and illustrate the above implementation system, such as Figure 4 As shown in the figure, this invention also provides an intelligent scheduling method for dust suppression spraying during open-pit mine road transportation, comprising the following steps:

[0043] S1: Real-time Multi-Source Data Sensing and Aggregation: After system startup, dust sensors 1 and miniature weather stations 2 deployed along mining road 24 continuously collect environmental dust concentration and meteorological data. Simultaneously, GNSS / BeiDou positioning terminals 4 and vehicle status sensors 5 installed on all transport trucks 3 report real-time dynamic information such as vehicle location, speed, and load. All data is transmitted in real-time to the central dispatch platform via a wireless communication network.

[0044] S2: Data Fusion and Dust Concentration Prediction: The data fusion and management module of the central dispatch platform cleans, aligns, and standardizes the received multi-source heterogeneous data to form a unified spatiotemporal data sequence. Subsequently, the dust spatiotemporal distribution prediction module calls its embedded deep learning prediction model to predict the spatiotemporal distribution of dust concentration at each node of the mining area road network within the next 15-30 minutes based on historical data, real-time environmental data, and vehicle dynamic data, and generates a dust concentration heat map.

[0045] S3: Intelligent Scheduling Decision Generation: The dust suppression scheduling optimization engine receives dust prediction results. The engine first evaluates the prediction results, identifying high-risk road sections that are about to exceed dust limits or have already exceeded them. Then, combining the system's current resource status (including the availability of each fixed spray device 7, the location of each mobile spray terminal 8, remaining water volume, and operational status) with preset optimization objectives, it uses a multi-objective optimization algorithm to calculate and generate an optimal set of coordinated dust suppression operation instructions.

[0046] S4: Command Issuance and Collaborative Execution: The command issuance and monitoring module sends the generated operation commands to the corresponding fixed intelligent spraying device 7 and mobile intelligent spraying terminal 8 via a wireless communication network. The controller 15 of the fixed intelligent spraying device 7 controls the solenoid valve 16 and pressure regulating valve 17 according to the commands, driving the nozzle array 18 to execute spraying. Its local vehicle detection sensor 19 assists in achieving precise control of "spraying starts when the vehicle arrives and stops when the vehicle leaves." The vehicle-mounted controller 20 of the mobile intelligent spraying terminal 8 controls the adjustable flow spraying system 22 to execute mobile spraying operations according to the issued path and parameters, and transmits the location back in real time through the high-precision positioning module 21.

[0047] S5: Full-Process Monitoring and Closed-Loop Optimization: After the command is issued, the command issuance and monitoring module continuously receives feedback signals from the executing equipment (such as spray status, actual flow rate, vehicle location, and water tank level) and compares them with the command requirements to achieve real-time monitoring of the operation process. Simultaneously, the actual dust concentration change data collected by the multi-source sensing layer is fed back to the system in real time. The digital twin and simulation module synchronously visualizes the above data stream, command stream, and equipment status in a three-dimensional virtual scene, providing managers with a global situational awareness. Based on the deviation between the actual dust reduction effect and the predicted value, as well as resource consumption, the system continuously iterates and adaptively optimizes the dust prediction model and scheduling optimization strategy, forming an intelligent closed loop of "perception-prediction-decision-execution-evaluation-optimization".

[0048] In summary, the present invention provides an intelligent scheduling system and method for dust suppression spraying in open-pit mine road transportation. This system deeply integrates production data from open-pit mine road transportation with environmental dust suppression requirements. Through predictive scheduling and resource coordination, it achieves a fundamental transformation from extensive and responsive watering to refined and preventative intelligent spraying, effectively improving dust suppression efficiency and saving resources.

[0049] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An intelligent scheduling system for dust suppression spraying during open-pit mine road transportation, characterized in that, It includes a multi-source perception layer, a central scheduling platform, a collaborative execution layer, and a digital twin and simulation module: The multi-source sensing layer is used to collect real-time data on dust environment and dynamic data of transport vehicles in the mining area. It includes a dust sensor (1) and a micro weather station (2) deployed along the mining area road, as well as a positioning terminal (4) and vehicle status sensor (5) installed on the transport truck (3). The central dispatch platform is connected to the multi-source sensing layer and the collaborative execution layer via a wireless communication network. It includes a data fusion and management module, a dust spatiotemporal distribution prediction module, a dust suppression scheduling optimization engine, and an instruction issuance and monitoring module. The data fusion and management module is used to process and standardize multi-source data. The dust spatiotemporal distribution prediction module is used to predict the spatiotemporal distribution of dust on mining roads in the future based on the processed data. The dust suppression scheduling optimization engine is used to generate collaborative dust suppression operation instructions based on the dust prediction results and system resource status. The instruction issuance and monitoring module is used to issue work instructions and monitor their execution status; The collaborative execution layer is used to receive and execute dust suppression instructions issued by the central dispatch platform, and includes a fixed intelligent spraying device (7) and a mobile intelligent spraying terminal (8) controlled by the instructions. The digital twin and simulation module is connected to the central dispatch platform to build and run a three-dimensional digital twin model synchronized with the physical system, enabling visualization, simulation, and effect evaluation of the operation process.

2. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 1, characterized in that: The fixed intelligent spraying device (7) includes a controller (15), a solenoid valve (16), a pressure regulating valve (17), a nozzle array (18), and a local vehicle detection sensor (19); wherein, the controller (15) is used to receive instructions from the central dispatch platform and control the solenoid valve (16) and the pressure regulating valve (17) to drive the nozzle array (18) to perform spraying operations; the local vehicle detection sensor (19) is used to assist in realizing vehicle sensing start-stop control.

3. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 1, characterized in that: The mobile intelligent spray terminal (8) is a sprinkler truck with an integrated intelligent control system, which includes an on-board controller (20), a high-precision positioning module (21), a flow-adjustable spray system (22), and an on-board water tank level sensor (23). The on-board controller (20) is used to receive and execute the path and spraying parameter instructions issued by the central dispatch platform; the high-precision positioning module (21) is used to report the vehicle location in real time; the flow-adjustable spray system (22) is used to perform dynamic spraying; and the on-board water tank level sensor (23) is used to monitor the water tank status.

4. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 1, characterized in that: The dust spatiotemporal distribution prediction module in the central dispatch platform is embedded with a deep learning-based prediction model, which is used to integrate historical environmental data, real-time meteorological data and vehicle dynamic trajectory data to output a heat map of the spatiotemporal distribution of dust concentration on mining roads within the next 15-30 minutes.

5. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 4, characterized in that: The optimization objectives of the dust suppression scheduling optimization engine in the central scheduling platform include at least one of minimizing the total water consumption of the system, maximizing the dust suppression coverage rate of the dust-exceeding area, and balancing the workload of each dust suppression device. Based on the dust spatiotemporal distribution prediction results, combined with the availability status of each fixed intelligent spray device (7), the location of each mobile intelligent spray terminal (8), the remaining water volume and the operating status, it uses a multi-objective optimization algorithm to generate a collaborative operation instruction set.

6. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 5, characterized in that: The digital twin and simulation module can import a three-dimensional geographic information model of the mining area and synchronously map and visualize real-time data streams, equipment status, and command streams in a virtual scene, supporting the playback of historical operation scenarios and the simulation and deduction of future scheduling schemes.

7. The intelligent scheduling system for dust suppression spraying in open-pit mine road transportation as described in claim 6, characterized in that: The instruction issuance and monitoring module in the central dispatch platform is used to continuously receive feedback signals from the execution equipment and compare them with the actual concentration change data fed back by the dust sensor (1) to evaluate the dust reduction effect and drive the adaptive iterative optimization of the dust spatiotemporal distribution prediction module and the dust reduction scheduling optimization engine.

8. An intelligent scheduling method for dust suppression spraying during open-pit mine road transport, implemented based on the intelligent scheduling system for dust suppression spraying during open-pit mine road transport as described in any one of claims 1-7, characterized in that: Includes the following steps: S1: Real-time collection of environmental dust concentration, meteorological data, and location, speed, and load status data of transport vehicles in the mining area through a multi-source sensing layer, and transmission to the central dispatch platform via a wireless communication network; S2: The data fusion and management module of the central dispatch platform cleans and aligns the received multi-source data in a spatiotemporal manner; subsequently, the dust spatiotemporal distribution prediction module predicts the dust spatiotemporal distribution of the mining area road network in the future based on the processed data; S3: The dust suppression scheduling optimization engine generates the optimal collaborative operation instructions for the fixed intelligent spray device (7) and the mobile intelligent spray terminal (8) through optimization calculation based on the dust prediction results of S2 and the real-time resource status of each dust suppression device in the system. S4: The instruction issuance and monitoring module issues the operation instructions generated by S3 to the corresponding execution equipment; the fixed intelligent spraying device and the mobile intelligent spraying terminal receive and execute the instructions to complete the fixed-point or mobile dust suppression operation; S5: The instruction issuance and monitoring module monitors the instruction execution status of each device, while the digital twin and simulation module provides a three-dimensional visualization of the entire process. The system continuously optimizes the prediction model and scheduling strategy based on feedback data from the actual dust reduction effect.

9. The intelligent scheduling method for dust suppression spraying in open-pit mine road transportation as described in claim 8, characterized in that: The optimal collaborative operation instructions generated in S3 include: allocating start and stop times and spray flow parameters for fixed intelligent spray devices (7); and planning the optimal operation path and allocating spray parameters along the way for mobile intelligent spray terminals (8).

10. The intelligent scheduling method for dust suppression spraying in open-pit mine road transportation as described in claim 8, characterized in that: The continuous optimization in S5 specifically involves taking the deviation between the predicted and actual dust concentration values, and the deviation between the actual and expected resource consumption of dust suppression operations as optimization targets, and using machine learning algorithms to periodically or trigger the updates of the model parameters of the dust spatiotemporal distribution prediction module and the decision rules of the dust suppression scheduling optimization engine.

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