Closed-loop management method and system for engineering material transportation, cloud server, and medium

Abstract

This invention discloses a closed-loop control method for engineering material transportation, comprising: receiving data from the shipping node including a first weight, a first time, a vehicle image, a first state, a second weight, a second time, vehicle and material images, a first identification result, and a second state; receiving data from the receiving node including a third weight, a third time, vehicle and material images, a second identification result, a third state, a fourth weight, a fourth time, vehicle images, a third identification result, and a fourth state; after the vehicle completes the fourth state, tare weight consistency verification, net weight consistency verification, and material consistency verification are performed respectively. After all three cross-verifications pass, it is determined whether the vehicle transitioned through the first to fourth states during transportation. If any state is missing or skipped, an abnormal alarm is triggered. If the state sequence is normal, the transportation task is confirmed to be completed. This method achieves full-process prevention of material theft, accurate measurement, and auxiliary verification of material quality during engineering material transportation.

Description

Technical Field

[0001] This invention relates to the field of intelligent logistics technology, specifically to a closed-loop management method, system, cloud server, and medium for the transportation of engineering materials. Background Technology

[0002] In the field of engineering construction, the management of bulk material transportation has long been a pain point. Currently, it mainly relies on single-point weighbridges, which involves a high degree of manual intervention in the process, making it prone to errors and fraud. The main problems are as follows:

[0003] 1. Weak anti-cheating capabilities in the measurement process: Drivers can interfere with the weighing results by "skipping the scale", "pressing the edge", "changing the license plate", or unload some materials midway;

[0004] 2. Lack of unloading verification: The consignee cannot objectively verify whether the vehicle has been completely unloaded, which often leads to disputes such as "goods arrive but invoice does not, invoice arrives but goods are insufficient";

[0005] 3. Material quality cannot be verified remotely: The system only records the weight and cannot confirm whether the transported materials are consistent with the order requirements (such as concrete grade, asphalt type), which poses a risk of "substituting inferior materials for superior ones";

[0006] 4. Data silos: Data is not shared among the three parties involved in shipping, transportation, and receiving, making reconciliation complex and increasing trust costs.

[0007] While some existing dual-weighbridge solutions can partially solve the routing problem, they lack the ability to verify the materials themselves and do not form a complete and reliable closed loop connecting the shipping and receiving ends. Summary of the Invention

[0008] The purpose of this invention is to provide a closed-loop management method, system, cloud server, and medium for the transportation of engineering materials, which can prevent theft of engineering materials throughout the transportation process, accurately measure the materials, and assist in verifying the quality of the materials.

[0009] This invention is achieved through the following technical solution:

[0010] In a first aspect, the present invention provides a closed-loop management method for the transportation of engineering materials, comprising:

[0011] Receive the first weight, first time, vehicle image and first status of the vehicle as it passes through the first weighing device in the direction of entry from the shipping node;

[0012] The system receives information from the shipping node, including the second weight, second time, vehicle and material images, first identification result, and second status of the vehicle passing through the second weighing device in the departure direction, all marked with a first status.

[0013] Receive the third weight, third time, vehicle and material images, second identification result and third status of the vehicle passing through the third weighing device in the direction of entry, which are marked with the second status, sent by the receiving end node;

[0014] The receiving end node sends the fourth weight, fourth time, vehicle image, third identification result, and fourth status of the vehicle passing through the fourth weighing device in the departure direction, which is marked with the third status.

[0015] After the vehicle completes the fourth state, tare weight consistency verification and net weight consistency verification are performed based on the first weight, second weight, third weight, and fourth weight. Material consistency verification is performed based on the first identification result, second identification result, and third identification result. After all three cross-verifications pass, it is determined whether the vehicle transitioned to the first state, second state, third state, and fourth state in sequence during transportation. If any state is missing or skipped, an abnormal alarm is triggered. If the state sequence is normal, the transportation task is confirmed to be completed.

[0016] Furthermore, the specific method for verifying tare weight consistency includes:

[0017] Calculate the tare weight difference based on the fourth weight and the first weight;

[0018] The tare weight difference is compared with a preset tare weight difference threshold. If the tare weight difference exceeds the threshold, it is determined that the unloading is incomplete or the weighing is incorrect.

[0019] Furthermore, the specific method for verifying net weight consistency includes:

[0020] Calculate the net weight of shipment based on the second weight and the first weight;

[0021] Calculate the net weight of the received goods based on the third and fourth weights;

[0022] Calculate the net weight difference based on the shipped net weight and the received net weight;

[0023] The net weight difference is compared with a preset net weight difference threshold. If the net weight difference exceeds the net weight difference threshold, it is determined that there is an abnormal loss during transit.

[0024] Furthermore, the specific methods for verifying material consistency include:

[0025] Compare the material identification results from the first, second, and third identification results with the material information specified in the electronic waybill;

[0026] If they are the same, they are the same material; if they are different, they are different materials.

[0027] Secondly, another embodiment of the present invention provides a closed-loop control system for the transportation of engineering materials, comprising: a dispatching node, a receiving node, and a cloud server. The dispatching node is used to acquire the first weight, first time, vehicle image, and first status of a vehicle passing through a first weighing device in the direction of entry; acquire the second weight, second time, vehicle and material image, first identification result, and second status of a vehicle marked with the first status passing through a second weighing device in the direction of departure; and send the acquired data to the cloud server.

[0028] The receiving terminal node is used to acquire the third weight, third time, vehicle and material images, second recognition result and third status of vehicles marked with the second status passing through the third weighing device in the direction of entry, and to acquire the fourth weight, fourth time, vehicle image, third recognition result and fourth status of vehicles marked with the third status passing through the fourth weighing device in the direction of exit, and to send the acquired data to the cloud server.

[0029] The cloud server executes the method described in the first embodiment.

[0030] Furthermore, the shipping end node includes a first weighing device, a second weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. Both the first and second weighing devices are weighbridges. The direction detection device is located in front of and behind the weighbridge to determine the vehicle's driving direction. The image acquisition device is located above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information.

[0031] Furthermore, the receiving terminal node includes a third weighing device, a fourth weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. The third and fourth weighing devices are both weighbridges. The direction detection device is set in front of and behind the weighbridge to determine the vehicle's driving direction. The image acquisition device is set above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information.

[0032] Furthermore, both the shipping node and the receiving node include an AI recognition device, which is used to identify the material category based on the image acquisition device.

[0033] Thirdly, another embodiment of the present invention provides a cloud server comprising: a processor, an input device, an output device, and a memory, wherein the processor, the input device, the output device, and the memory are interconnected, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to invoke the program instructions to execute the method described in the first embodiment above.

[0034] Fourthly, another embodiment of the present invention provides a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method described in the first embodiment above.

[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0036] This invention provides a closed-loop management method, system, cloud server, and medium for engineering material transportation. By constructing a three-in-one closed-loop management system integrating "physical-data-visual" components, it achieves a leapfrog transformation from traditional manual supervision to intelligent and automated management of engineering material transportation. The system, driven by a state machine, enforces standardized vehicle operation procedures, significantly reducing reliance on on-site personnel and the management and ethical risks associated with human intervention.

[0037] By accurately measuring and cross-validating the entire transportation process, we can effectively identify and curb behaviors such as material theft and incomplete unloading, thus eliminating material loss at the source.

[0038] The system automatically aggregates multi-source data from the shipper, transporter, and receiver, and generates an immutable, end-to-end credible evidence chain through multi-dimensional verification, including tare weight consistency, net weight consistency, material consistency, and status sequence integrity. This data chain provides neutral, objective, and traceable digital credit credentials for upstream and downstream partners in the supply chain, completely eliminating reconciliation disputes and reducing transaction trust costs.

[0039] The embodiments of the present invention realize fully automated data collection and verification from vehicle entry to unloading and departure, without the need for manual intervention or post-event reconciliation.

[0040] By introducing AI visual recognition technology at the shipping end and key transportation nodes, the system can verify material type, loading status, and unloading integrity in real time, shifting quality control from traditional on-site inspection to the front end of transportation. This mechanism can provide early warning of risks, offering proactive technical support for ensuring project quality. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0042] Figure 1A structural block diagram of a closed-loop control system for engineering material transportation provided in the first embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram illustrating the process of engineering transportation by vehicles in the first embodiment of the present invention;

[0044] Figure 3 A flowchart of a closed-loop management method for the transportation of engineering materials is provided in another embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0046] like Figure 1 As shown, the first embodiment of the present invention provides a closed-loop control system for engineering material transportation, including: a shipping node, a receiving node, and a cloud server. The shipping node is used to acquire the first weight, first time, vehicle image, and first status of a vehicle passing through a first weighing device in the direction of entry; acquire the second weight, second time, vehicle and material image, first identification result, and second status of a vehicle marked with the first status passing through a second weighing device in the direction of departure; and send the acquired data to the cloud server. The receiving node is used to acquire the third weight, third time, vehicle and material image, second identification result, and third status of a vehicle marked with the second status passing through a third weighing device in the direction of entry; acquire the fourth weight, fourth time, vehicle image, third identification result, and fourth status of a vehicle marked with the third status passing through a fourth weighing device in the direction of departure; and send the acquired data to the cloud server.

[0047] The cloud server receives the first weight, first time, vehicle image and first status of the vehicle as it enters the first weighing device from the shipping node.

[0048] The system receives information from the shipping node, including the second weight, second time, vehicle and material images, first identification result, and second status of the vehicle passing through the second weighing device in the departure direction, all marked with a first status.

[0049] Receive the third weight, third time, vehicle and material images, second identification result and third status of the vehicle passing through the third weighing device in the direction of entry, which are marked with the second status, sent by the receiving end node;

[0050] The receiving end node sends the fourth weight, fourth time, vehicle image, third identification result, and fourth status of the vehicle passing through the fourth weighing device in the departure direction, which is marked with the third status.

[0051] After the vehicle completes the fourth state, tare weight consistency verification and net weight consistency verification are performed based on the first weight, second weight, third weight, and fourth weight. Material consistency verification is performed based on the first identification result, second identification result, and third identification result. After all three cross-verifications pass, it is determined whether the vehicle transitioned to the first state, second state, third state, and fourth state in sequence during transportation. If any state is missing or skipped, an abnormal alarm is triggered. If the state sequence is normal, the transportation task is confirmed to be completed.

[0052] The shipping node includes a first weighing device, a second weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. Both the first and second weighing devices are weighbridges. The direction detection device is positioned before and after the weighbridge to determine the vehicle's direction of travel. The image acquisition device is positioned above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information. The first weighing device (weighbridge A) is deployed at the sole entrance to the shipping area (such as a mixing plant or material yard) to perform the initial weighing (tare weight) of all empty trucks entering. The second weighing device (weighbridge B) is deployed at the exit of the shipping area to weigh (tare weight) all loaded trucks leaving. The direction detection device uses dual-channel inductive loops buried before and after the weighbridge. By determining the sequence in which the vehicle triggers the loops, the direction of travel is accurately determined, thus indicating whether the vehicle is entering or leaving the shipping area. The image acquisition device uses a high-definition industrial camera and supplementary lighting, installed above or tilted to the side of the weighbridge, with a view covering the license plate, the entire vehicle, and the interior of the cargo compartment, to capture high-definition images and record video. License plate recognition devices can use RFID reader / writer units to identify vehicle identities.

[0053] The receiving node includes a third weighing device, a fourth weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. Both the third and fourth weighing devices are weighbridges. The direction detection device is positioned before and after the weighbridge to determine the vehicle's direction of travel. The image acquisition device is positioned above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information. The third weighing device (weighbridge C) is deployed at the entrance of the receiving area (e.g., a construction site) to weigh incoming loaded vehicles (gross weight upon arrival). The fourth weighing device (weighbridge D) is deployed at the exit of the receiving area to weigh outgoing empty vehicles (tare weight after unloading). The direction detection device uses dual-channel inductive loops, buried before and after the weighbridge. By determining the sequence in which the vehicle triggers the loops, the device accurately determines the vehicle's direction of travel, thus indicating whether the vehicle is entering or leaving the receiving area.

[0054] Both the shipping and receiving nodes include AI recognition devices. These devices use the YOLO object detection model to identify the material category from images captured by the image acquisition device from the roof of the vehicle, such as "C30 concrete" or "Asphalt AC-13".

[0055] like Figure 2 As shown, vehicles are considered to be in normal transport only if they strictly follow the sequence of the following states: empty vehicle entering at the dispatching end, loaded vehicle leaving at the dispatching end, loaded vehicle entering at the receiving end, and empty vehicle leaving at the receiving end. Loading occurs at the dispatching end, and unloading occurs at the receiving end. Any missing state or skipped step will trigger an abnormal alarm.

[0056] Status S1: Shipper side - Empty vehicle enters:

[0057] Action: The vehicle is weighed on weighbridge A in the "entering" direction. If the direction is incorrect, an alarm will be triggered.

[0058] The system records: tare weight W1, license plate, time, and captured image of the empty vehicle. The AI ​​recognition device identifies the vehicle as empty and marks it as S1.

[0059] Verification: No historical status or the previous task has been completed.

[0060] Status S2: Shipper End - Loaded Vehicle Departs:

[0061] The prerequisite is that the vehicle status must be S1;

[0062] Action: The vehicle is weighed on weighbridge B in the "departure" direction; an alarm is triggered if the direction is incorrect.

[0063] The system records: gross weight W2, time, and images of the loaded vehicle and materials captured.

[0064] AI recognition: The AI ​​recognition model is called to identify the material type (such as "C30 concrete" or "AC-13 asphalt") and compared with the waybill;

[0065] Calculation and Status Update: Calculate the net weight of the shipment Ns = W2 - W1, and update the status to S2. This AI recognition result is linked to the weight data.

[0066] Status S3: Receiving end - Loaded vehicle enters:

[0067] Prerequisite: The vehicle status must be S2;

[0068] Action: The vehicle is weighed in the "entering" direction at weighbridge C; an alarm is triggered if the direction is incorrect.

[0069] System records: gross weight upon arrival (W3), time, and captured image;

[0070] Status Update: The status has been updated to S3. The system can then send a "vehicle has arrived" notification to the recipient.

[0071] Status S4: Receiving end - Empty vehicle departs:

[0072] Prerequisite: The vehicle status must be S3.

[0073] Action: The vehicle is weighed on weighbridge D in the "departure" direction; an alarm is triggered if the direction is incorrect.

[0074] The system records: tare weight W4 after unloading, time, and captured images of the empty truck after unloading;

[0075] Status Update: Status updated to S4 (Task Completed).

[0076] Once the vehicle completes state S4, the cloud server initiates an automatic audit process, performing triple cross-validation:

[0077] 1. Tare weight consistency verification: Calculate the tare weight difference w41 based on the fourth weight and the first weight, using the following formula:

[0078] w41 = |W4 - W1|;

[0079] Wherein, W4 is the weight of the vehicle after unloading in state S4, and W1 is the weight of the empty vehicle entering the site in state S1. If the tare weight difference w41 exceeds the preset threshold (such as 0.3% of the vehicle's own weight), it is determined that "unloading is incomplete" or "weighing is incorrect".

[0080] 2. Net weight consistency verification: Calculate the weight increase of the vehicle after loading, which is the net shipping weight Ns. The formula is:

[0081] Ns = W2 - W1;

[0082] The net weight difference w34 between the loading weight and the unloading weight is calculated using the following formula:

[0083] w34 = |Ns - (W3 - W4)|;

[0084] Nr = W3 - W4;

[0085] In this context, W2 represents the weight of the loaded vehicle leaving in state S2, W1 represents the weight of the empty vehicle entering in state S1, W3 represents the weight of the loaded vehicle arriving at the unloading point in state S3, W4 represents the weight of the vehicle after unloading in state S4, and Nr represents the net weight received. If the net weight difference w34 exceeds the reasonable transit loss (e.g., considering water evaporation in concrete, set at 0.5% in this embodiment), a message will be displayed indicating "abnormal losses may exist en route."

[0086] 3. Material Consistency Verification: Compare the material results identified by AI with the material information specified in the electronic waybill. If they are the same, they are the same material; if they are different, they are different materials.

[0087] 4. Logical Integrity Verification: During transportation, the system records the vehicle's time at each node. When node S4 is reached, unloading is completed, forming a single vehicle's transportation node trajectory and time in the system. If the nodes are not ordered by time as S1->S2->S3->S4, it is considered abnormal. Otherwise, it is considered normal.

[0088] Only after all the above verifications pass will the system confirm that the transportation is complete.

[0089] This invention provides a closed-loop management system for engineering material transportation. By constructing a three-in-one closed-loop management system integrating "physical, data, and visual" elements, it achieves a leapfrog transformation from traditional manual supervision to intelligent and automated management of engineering material transportation. The system, driven by a state machine, enforces standardized vehicle operation procedures, significantly reducing reliance on on-site personnel and the management and ethical risks associated with human intervention.

[0090] By accurately measuring and cross-validating the entire transportation process, we can effectively identify and curb behaviors such as material theft and incomplete unloading, thus eliminating material loss at the source.

[0091] The system automatically aggregates multi-source data from the shipper, transporter, and receiver, and generates an immutable, end-to-end credible evidence chain through multi-dimensional verification, including tare weight consistency, net weight consistency, material consistency, and status sequence integrity. This data chain provides neutral, objective, and traceable digital credit credentials for upstream and downstream partners in the supply chain, completely eliminating reconciliation disputes and reducing transaction trust costs.

[0092] The embodiments of the present invention realize fully automated data collection and verification from vehicle entry to unloading and departure, without the need for manual intervention or post-event reconciliation.

[0093] By introducing AI visual recognition technology at the shipping end and key transportation nodes, the system can verify material type, loading status, and unloading integrity in real time, shifting quality control from traditional on-site inspection to the front end of transportation. This mechanism can provide early warning of risks, offering proactive technical support for ensuring project quality.

[0094] like Figure 3 As shown, another embodiment of the present invention provides a closed-loop management method for the transportation of engineering materials, applicable to cloud servers, including the following steps:

[0095] Receive the first weight, first time, vehicle image and first status of the vehicle as it passes through the first weighing device in the direction of entry from the shipping node;

[0096] The system receives information from the shipping node, including the second weight, second time, vehicle and material images, first identification result, and second status of the vehicle passing through the second weighing device in the departure direction, all marked with a first status.

[0097] Receive the third weight, third time, vehicle and material images, second identification result and third status of the vehicle passing through the third weighing device in the direction of entry, which are marked with the second status, sent by the receiving end node;

[0098] The receiving end node sends the fourth weight, fourth time, vehicle image, third identification result, and fourth status of the vehicle passing through the fourth weighing device in the departure direction, which is marked with the third status.

[0099] After the vehicle completes the fourth state, tare weight consistency verification and net weight consistency verification are performed based on the first weight, second weight, third weight, and fourth weight. Material consistency verification is performed based on the first identification result, second identification result, and third identification result. After all three cross-verifications pass, it is determined whether the vehicle transitioned to the first state, second state, third state, and fourth state in sequence during transportation. If any state is missing or skipped, an abnormal alarm is triggered. If the state sequence is normal, the transportation task is confirmed to be completed.

[0100] The specific methods for verifying tare weight consistency include:

[0101] Calculate the tare weight difference based on the fourth weight and the first weight;

[0102] The tare weight difference is compared with a preset tare weight difference threshold. If the tare weight difference exceeds the threshold, it is determined that the unloading is incomplete or the weighing is incorrect.

[0103] The specific methods for verifying net weight consistency include:

[0104] Calculate the net weight of shipment based on the second weight and the first weight;

[0105] Calculate the net weight of the received goods based on the third and fourth weights;

[0106] Calculate the net weight difference based on the shipped net weight and the received net weight;

[0107] The net weight difference is compared with a preset net weight difference threshold. If the net weight difference exceeds the net weight difference threshold, it is determined that there is an abnormal loss during transit.

[0108] The specific methods for material consistency verification include:

[0109] Compare the material identification results from the first, second, and third identification results with the material information specified in the electronic waybill;

[0110] If they are the same, they are the same material; if they are different, they are different materials.

[0111] The following describes in detail the working process of a closed-loop control system for engineering material transportation provided by an embodiment of the present invention, taking the transportation of sand and gravel from a quarry to a construction site as an example. The transport vehicle is a dump truck with license plate number Lu M-XXXXX, and the transported material is 5-25mm graded crushed stone.

[0112] Scenario 1: Normal Transportation

[0113] Step S101 (Empty Truck Enters Loading Yard): An empty dump truck, license plate number Lu M-XXXXX, enters the sand and gravel yard. As the vehicle passes the entrance weighbridge A, the direction detection device determines the direction of travel as "entering," and the system records its tare weight W1 as 18.25 tons. The AI ​​recognition device simultaneously confirms that the vehicle is empty, the cargo box is clean, and the tarpaulin is rolled up. The system marks the vehicle status as "S1: Shipping End - Empty Truck Entering" and assigns it to loading position 3. Step S102 (Loaded Truck Leaves Loading Yard): After loading approximately 25 tons of crushed stone and covering it with a tarpaulin, the vehicle drives towards the exit weighbridge B. The direction detection device confirms the direction as "leaving," and the system records the gross weight W2 as 43.18 tons, calculating the net shipping weight Ns as 24.93 tons. At this point, the AI ​​recognition device sub-process is triggered: the camera captures an image, and the AI ​​model analyzes and confirms that the material is "graded crushed stone," with a loading fullness of approximately 98%, and the tarpaulin covering is tight, consistent with the waybill requirements. The system then updates the status to "S2: Shipper - Loaded Vehicle Departs" and generates an electronic shipping document. Step S103 (Loaded Vehicle Enters Unloading Yard): The truck arrives at the unloading yard entrance. When passing through weighbridge C, the direction detection device confirms the direction as "entering," and the system records the gross weight W3 as 43.05 tons, a decrease of 0.13 tons from the shipment weight, which is considered a reasonable minor spillage during transportation. The system verifies its status as the valid S2 and updates it to "S3: Receiving End - Loaded Vehicle Enters," guiding it to the unloading area.

[0114] Step S104 (Empty Truck Departs from Unloading Yard): Unloading completed, the empty truck departs. At the weighbridge D at the unloading yard exit, the direction detection is "departure," and the system records the tare weight W4 after unloading as 18.28 tons, calculating the received net weight Nr as 24.77 tons. The AI ​​visual recognition sub-process analyzes the truck bed image and concludes that "unloading is complete, with only a very small amount of dust remaining in the gaps between the truck beds." The status is finally updated to "S4: Receiving End - Empty Truck Departure." Subsequent automatic system verification shows that the tare weight difference (0.03 tons) and net weight difference (0.16 tons, transit loss rate 0.64%) are both within the reasonable threshold for sand and gravel, the AI ​​recognition results are consistent, the status sequence is complete, and an acceptance report is automatically generated and settlement is completed.

[0115] Scenario 2: Driver steals materials midway

[0116] Steps S101 and S102 are completed normally: the empty vehicle enters the loading yard, with a tare weight W1 = 18.25 tons; the loaded vehicle leaves the yard, with a gross weight W2 = 43.18 tons and a net weight Ns = 24.93 tons. AI identifies the loading as full. Step S103 (Abnormal entry into the unloading area): When the vehicle arrives at the unloading area and passes weighbridge C, although the direction detection shows "entering," the weighing shows that the gross weight W3 is only 41.50 tons, significantly lower than the gross weight shipped. AI identification detects this, and the loading fullness estimated based on the image has dropped to approximately 85%. The system still updates the status to S3, but the weight data and visual cues trigger an internal warning flag. Step S104: After unloading, the vehicle passes weighbridge D, with the direction showing "leaving." The tare weight after unloading is W4 = 18.26 tons, and the calculated net weight Nr = 23.24 tons. Step S105: During automatic system verification, it was discovered that the net weight difference was as high as |24.93-23.24|=1.69 tons, with a transit loss rate of 6.78%, far exceeding the reasonable threshold for sand and gravel (e.g., 0.7%). Meanwhile, although the tare weight was normal, the AI ​​recognition result in step S103 (decreased fullness) was significantly inconsistent with the record in step S102. Although the state sequence was complete, the multimodal data was contradictory. The system immediately triggered a Level 1 alarm, "Suspected theft of materials en route," froze the settlement for this transportation, and pushed the complete chain of evidence, including the weight difference, AI image comparison, and abnormal GPS track stop points, to the administrator for further action.

[0117] The closed-loop management method and closed-loop management system for engineering material transportation provided in this invention are based on the same inventive concept and have the same beneficial effects, and will not be described again here.

[0118] Another embodiment of the present invention provides a cloud server. The platform includes a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the method described in the second embodiment above.

[0119] It should be understood that, in the embodiments of the present invention, the processor may be a Central Processing Unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0120] Input devices may include touchpads, microphones, etc., and output devices may include displays (LCDs, etc.), speakers, etc.

[0121] The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store information about the device type.

[0122] In specific implementations, the processor, input device, and output device described in the embodiments of the present invention can execute the implementation of the method embodiments described in the embodiments of the present invention, or they can execute the implementation of the system embodiments described in the embodiments of the present invention, which will not be repeated here.

[0123] The present invention also provides an embodiment of a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the method described in the second embodiment above.

[0124] The computer-readable storage medium can be an internal storage unit of the terminal described in the foregoing embodiments, such as the terminal's hard drive or memory. The computer-readable storage medium can also be an external storage device of the terminal, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal. Furthermore, the computer-readable storage medium can include both internal storage units and external storage devices of the terminal. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0125] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0126] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the terminals and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, or may be electrical, mechanical or other forms of connection.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A closed-loop management and control method for engineering material transportation, characterized in that, include: Receive the first weight, first time, vehicle image and first status of the vehicle as it passes through the first weighing device in the direction of entry from the shipping node; The system receives information from the shipping node, including the second weight, second time, vehicle and material images, first identification result, and second status of the vehicle passing through the second weighing device in the departure direction, all marked with a first status. Receive the third weight, third time, vehicle and material images, second identification result and third status of the vehicle passing through the third weighing device in the direction of entry, which are marked with the second status, sent by the receiving end node; The receiving end node sends the fourth weight, fourth time, vehicle image, third identification result, and fourth status of the vehicle passing through the fourth weighing device in the departure direction, which is marked with the third status. After the vehicle completes the fourth state, tare weight consistency verification and net weight consistency verification are performed based on the first weight, second weight, third weight, and fourth weight. Material consistency verification is performed based on the first identification result, second identification result, and third identification result. After all three cross-verifications pass, it is determined whether the vehicle transitioned to the first state, second state, third state, and fourth state in sequence during transportation. If any state is missing or skipped, an abnormal alarm is triggered. If the state sequence is normal, the transportation task is confirmed to be completed.

2. The method as described in claim 1, characterized in that, The specific methods for verifying tare weight consistency include: Calculate the tare weight difference based on the fourth weight and the first weight; The tare weight difference is compared with a preset tare weight difference threshold. If the tare weight difference exceeds the threshold, it is determined that the unloading is incomplete or the weighing is incorrect.

3. The method as described in claim 1, characterized in that, The specific methods for verifying net weight consistency include: Calculate the net weight of shipment based on the second weight and the first weight; Calculate the net weight of the received goods based on the third and fourth weights; Calculate the net weight difference based on the shipped net weight and the received net weight; The net weight difference is compared with a preset net weight difference threshold. If the net weight difference exceeds the net weight difference threshold, it is determined that there is an abnormal loss during transit.

4. The method as described in claim 1, characterized in that, The specific methods for verifying material consistency include: Compare the material identification results from the first, second, and third identification results with the material information specified in the electronic waybill; If they are the same, they are the same material; if they are different, they are different materials.

5. A closed-loop control system for the transportation of engineering materials, characterized in that, include: The system includes a shipping node, a receiving node, and a cloud server. The shipping node is used to acquire the first weight, first time, vehicle image, and first status of a vehicle passing through a first weighing device in the direction of entry; acquire the second weight, second time, vehicle and material image, first identification result, and second status of a vehicle passing through a second weighing device in the direction of departure, and send the acquired data to the cloud server. The receiving terminal node is used to acquire the third weight, third time, vehicle and material images, second recognition result and third status of vehicles marked with the second status passing through the third weighing device in the direction of entry, and to acquire the fourth weight, fourth time, vehicle image, third recognition result and fourth status of vehicles marked with the third status passing through the fourth weighing device in the direction of exit, and to send the acquired data to the cloud server. The cloud server performs the method as described in any one of claims 1-4.

6. The system as described in claim 5, characterized in that, The shipping end node includes a first weighing device, a second weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. Both the first and second weighing devices are weighbridges. The direction detection device is located in front of and behind the weighbridge to determine the vehicle's driving direction. The image acquisition device is located above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information.

7. The system as described in claim 6, characterized in that, The receiving terminal node includes a third weighing device, a fourth weighing device, a direction detection device, an image acquisition device, and a license plate recognition device. The third and fourth weighing devices are both weighbridges. The direction detection device is set in front of and behind the weighbridge to determine the vehicle's driving direction. The image acquisition device is set above the weighbridge to capture vehicle images. The license plate recognition device is used to identify vehicle information.

8. The system as described in claim 6 or 7, characterized in that, Both the shipping and receiving nodes include AI recognition devices, which are used to identify material categories based on image acquisition devices.

9. A cloud server, comprising: The processor, input device, output device, and memory are interconnected, the memory being used to store a computer program, the computer program including program instructions, characterized in that the processor is configured to invoke the program instructions to perform the method as described in any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-4.

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