Unattended weighing anti-cheating method, device, system and readable medium

Abstract

The present invention relates to the field of automatic weighing, and in particular to an unattended weighing anti-cheating method, device, system and readable medium. An unattended weighing anti-cheating method comprises: acquiring a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed; using a first recognition model to recognize the first image, and obtaining corresponding judgment data of the water outlet pipe image; when the judgment data is that the water pipe is open, performing a weighing operation on the truck to be weighed. By acquiring an image of the water outlet pipe of the water tank of the truck to be weighed, and then recognizing the water outlet pipe image, it is determined whether it is in an open state. If so, it is determined that the water has been drained, and then the truck is weighed, that is, it is ensured that the driver cannot interfere with the accurate weighing by draining water from the water tank. The water tank is fully automatically detected to see if it is empty, without the need for manual participation, effectively saving labor costs, and real-time detection of whether the water tank is empty, without the need for subsequent tracing.

Description

Technical Field

[0001] The present invention relates to the field of automatic weighing, and in particular to an anti-cheating method, device, system and readable medium for unattended weighing. Background Art

[0002] Unattended weighing systems have been widely used in coal mines, coking, steel smelting, mining and metallurgy, petrochemicals, cement, building materials, grain, food, feed, agricultural product procurement, animal husbandry, ports and terminals, etc., and have played a very positive role in improving enterprise management level, plugging management loopholes, reducing consumption, controlling costs, standardizing production order, improving work efficiency, and improving economic benefits. The traditional unattended intelligent weighing system uses a variety of means to replace manual anti-cheating monitoring, including vehicle incomplete weighing monitoring, license plate replacement monitoring, meter remote control interference monitoring, etc. However, in the case of water tank cheating, the driver fills the water tank with water before gross weight and drains the water after unloading the goods, thereby affecting the net weight value and causing losses to the receiving unit.

[0003] The defects and shortcomings of the current automatic weighing system and its monitoring system include: 1. Manual inspection at the weighing site is required to check whether the vehicle's water tank is empty, and the inspectors need to be on duty 24 hours a day, which is a great waste of human resources; 2. Video monitoring and image capture are used to check whether the water tank switch is turned on. This method can only be verified afterwards and cannot achieve real-time monitoring; 3. The vehicle water tank inspection process is time-consuming, and vehicles need to wait in line to be weighed. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide an unattended anti-cheating method, device, system and readable medium for weighing, which can effectively prevent the driver from filling the water tank with water before gross weight and draining the water after unloading the goods, thereby affecting the net weight value and causing losses to the receiving unit.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In one aspect, the present invention provides an unattended weighing and anti-cheating method, comprising:

[0007] Acquire a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed;

[0008] The first image is recognized using a first recognition model to obtain corresponding determination data of the water outlet pipe image; the determination data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model;

[0009] When the determination data indicates that the water pipe is open, a weighing operation is performed on the truck to be weighed.

[0010] Furthermore, before acquiring the first image, the method further includes:

[0011] Acquire the image of the truck to be weighed;

[0012] Using a vehicle type recognition model to identify the image of the truck to be weighed to obtain vehicle type data; the vehicle type recognition model is constructed based on a neural network model;

[0013] determining a water tank position based on the vehicle model data;

[0014] A first image corresponding to the water tank position is acquired.

[0015] Furthermore, after obtaining the vehicle model data, the following steps are performed:

[0016] Acquire multiple risk locations of the truck to be weighed based on the vehicle model data;

[0017] Acquire a second image of each risk location of the truck to be weighed;

[0018] Recognize the second image based on a second recognition model to obtain risk data; the second recognition model is constructed based on a neural network model;

[0019] An alerting operation is performed based on the risk data.

[0020] Furthermore, the risk data includes abnormal information and non-abnormal information;

[0021] Performing warning operations based on the risk data specifically includes:

[0022] When the risk data is abnormal information, a warning message is issued to the outside.

[0023] Further, the second image is identified based on the second identification model to obtain risk data, which specifically includes:

[0024] If the second image is recognized by the second recognition model and it is determined that the second image contains a water tank image, the risk data is abnormal information; otherwise, the risk data is non-abnormal information.

[0025] Furthermore, when the risk data is abnormal information, it also includes:

[0026] The second image is input into the first recognition model for recognition to obtain the corresponding determination data of the water outlet pipe image. When the determination data indicates that the water pipe is open, the truck to be weighed is weighed, otherwise a warning message is issued.

[0027] Furthermore, when the determination data indicates that the water pipe is closed, an alarm message is issued externally.

[0028] On the other hand, the present invention provides an unattended weighing anti-cheating device, comprising:

[0029] An acquisition module, configured to acquire a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed;

[0030] A recognition module, configured to recognize the first image using a first recognition model to obtain determination data of the corresponding water outlet pipe image; the determination data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model;

[0031] The weighing module is used to perform a weighing operation on the truck to be weighed when the determination data indicates that the water pipe is open.

[0032] On the other hand, the present invention provides an unattended weighing and anti-cheating system, comprising:

[0033] Weighbridge;

[0034] One or more cameras, used to obtain detection images; the detection images include a first image including an image of a water outlet pipe of a water tank of a truck to be weighed, a second image corresponding to each risk location, and an image of the truck to be weighed;

[0035] The unattended weighing and anti-cheating device is connected to the floor scale and the camera respectively.

[0036] On the other hand, the present invention provides a computer-readable medium storing a computer program, which, when executed by a processor, implements the unattended weighing and anti-cheating method.

[0037] Compared with the prior art, the unattended anti-cheating method, device, system and readable medium provided by the present invention have the following beneficial effects:

[0038] The unattended weighing and anti-cheating method provided by the present invention obtains an image of the water outlet pipe of the water tank of the truck to be weighed, and then identifies the water outlet pipe image to determine whether it is in an open state. If so, it is determined that the water has been drained, and then the truck is weighed, that is, it is ensured that the driver cannot interfere with accurate weighing by draining water from the water tank. The water tank is automatically tested for emptying water without the need for manual participation, which effectively saves labor costs. Whether the water tank is empty can be detected in real time without the need for subsequent investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The present invention provides a flowchart of an unattended weighing and anti-cheating method.

[0040] Figure 2The present invention provides an unattended weighing and anti-cheating method.

[0041] Figure 3 It is a flow chart of the process of acquiring the first image based on the vehicle type provided by the present invention.

[0042] Figure 4 It is a flow chart of risk detection provided by the present invention.

[0043] Figure 5 It is a structural block diagram of the unattended weighing and anti-cheating device provided by the present invention.

[0044] Figure 6 It is a schematic diagram of the unattended weighing and anti-cheating system provided by the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] Those skilled in the art will appreciate that the foregoing general description and the following detailed description are exemplary and illustrative of specific embodiments of the present invention and are not intended to limit the present invention.

[0047] The terms "comprises," "includes," or any other variations thereof herein are intended to cover a non-exclusive inclusion, such that a process or method that includes a list of steps includes not only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, a reference to one or more devices or subsystems, elements or structures or components preceded by "comprises ... an" does not, without more limitations, exclude the presence of other devices or other subsystems or other elements or other structures or other components or other devices or other subsystems or other elements or other structures or other components. Throughout the specification, appearances of the phrases "in one embodiment," "in another embodiment," and similar language may, but do not necessarily, all refer to the same embodiment.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] When a truck needs to brake for a long time on a downhill slope, the friction between the brake shoe and the drum generates a lot of heat. The brake drum is very hot and needs to be cooled by sending water droplets through the water tank. Temporarily emptying the water tank before the vehicle is weighed will not affect the driving safety of the truck. The water tank will be filled with water when the truck leaves the site. Therefore, in the invention, combined with the requirements of the management system, the driver of the delivery vehicle first opens the water tank switch of the vehicle and empties the water in the water tank before weighing. Then, after the delivery vehicle empties the water in the water tank, keep the water tank switch open for weighing.

[0050] See also Figure 1-Figure 2 , Figure 6 The present invention provides an unattended weight checking and anti-cheating method, which is applied to an automatic weighing system and is suitable for monitoring and use when a truck water tank is installed on both sides of the vehicle and the water tank drainage switch is not blocked.

[0051] The automatic weighing system includes control devices, sound columns, LED display screens, cameras, weighbridges, fill lights and other equipment. It mainly uses camera monitoring and intelligent AI algorithms to identify whether the water tank switch is in the open state. If the water tank switch is in the open state, it is determined that the water in the water tank has been drained. If the water tank switch is in the closed state, the driver is prompted to empty the water tank and keep the water tank drain switch in the open state before weighing again through text prompts on the display screen and voice broadcast reminders. The control device includes intelligent devices such as computers and servers. The various components in the automatic weighing system exchange data based on the industrial Internet.

[0052] Unattended weighing and anti-cheating methods include:

[0053] A first image is obtained; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed; specifically, in this embodiment, the first image is obtained in real time by a camera, and the camera is installed at a position corresponding to the water outlet pipe of the water tank. Furthermore, multiple cameras can be arranged around the weighbridge, and when in use, only data transmitted by one of the cameras is obtained, or among multiple images, each captured image is identified as a first image.

[0054] The first image is recognized using a first recognition model to obtain corresponding judgment data of the water outlet pipe image; the judgment data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model; in specific operations, if images of a truck to be weighed are acquired at multiple angles and orientations, then multiple first images are recognized, and if the judgment data of the first image of the water outlet pipe are all that the water pipe is open, the truck is continued to be weighed.

[0055] When the determination data indicates that the water pipe is open, a weighing operation is performed on the truck to be weighed.

[0056] When the determination data indicates that the water pipe is closed, an alarm message is issued externally.

[0057] The unattended weighing and anti-cheating method provided by the present invention obtains an image of the water outlet pipe of the water tank of the truck to be weighed, and then identifies the water outlet pipe image to determine whether it is in an open state. If so, it is determined that the water has been drained, and then the truck is weighed, that is, it is ensured that the driver cannot interfere with accurate weighing by draining water from the water tank. The water tank is automatically tested for emptying water without the need for manual participation, which effectively saves labor costs. Whether the water tank is empty can be detected in real time without the need for subsequent investigation.

[0058] In some embodiments, the generation process of the first recognition model includes:

[0059] Acquire a first training set, the first training set includes a plurality of first training samples, the first training sample is an image of a water outlet pipe of a water tank of a truck and a corresponding working state label; the working state label includes an open state and a closed state;

[0060] The first training set is used to train the initialized neural network model to obtain the first recognition model. Preferably, the first recognition model is built into the control device.

[0061] Furthermore, in some embodiments, the first recognition model is built into a camera to form a first intelligent camera, and the determination data is output to the control device. After the control device receives the determination data, when the determination data indicates that the water pipe is open, the scale is driven to perform a weighing operation on the truck to be weighed. When the determination data indicates that the water pipe is closed, the sound column or LED display screen is driven to send out a warning message.

[0062] In specific implementation, the delivery vehicle may enter the recognition area of ​​the smart camera after being weighed, and the smart recognition camera may identify the switch status of the water tank and report the recognition result to the control device in the weighing room through the network.

[0063] The computer receives the recognition result returned by the smart camera. If the received result is that the water tank switch is in the off state, the computer program sends a text reminder "Please turn on the water tank switch, empty the water tank and weigh it again" to the LED screen through the network, and at the same time sends a text voice broadcast reminder to the sound column.

[0064] The LED display screen and the sound column receive information sent by the computer and respond.

[0065] For further information, see Figure 3 As a preferred solution, in this embodiment, before acquiring the first image, the method further includes:

[0066] Acquire the image of the truck to be weighed;

[0067] Using a vehicle type recognition model to identify the image of the truck to be weighed to obtain vehicle type data; the vehicle type recognition model is constructed based on a neural network model;

[0068] determining a water tank position based on the vehicle model data;

[0069] Obtain the first image of the corresponding water tank position. In this embodiment, the image of the truck to be weighed is first taken, and then the vehicle type of the truck to be weighed is determined, and then the position of the water outlet pipe of the water tank of the truck of this type is determined, and then the first image of the corresponding water outlet pipe is taken, so that the water tank of the truck can be photographed more flexibly.

[0070] In some embodiments, the process of generating the vehicle type recognition model includes:

[0071] Obtain a vehicle model training set, wherein the vehicle model training set includes multiple vehicle model training samples, and the vehicle model training samples are truck images and vehicle model labels;

[0072] The vehicle type recognition model is obtained by training the initialized neural network model using the vehicle type training set. Preferably, the vehicle type recognition model is built into the control device.

[0073] In some embodiments, corresponding water tank location data is associated with different truck models, that is, as long as the truck model data is obtained, the water tank location data for the model can be quickly known, and then the corresponding water tank position can be quickly found, and the water outlet pipe position can be further found.

[0074] In some embodiments, the vehicle type recognition model is built into a camera to form a vehicle type recognition camera, and the vehicle type data is output to the control device. After receiving the vehicle type data, the control device retrieves the water tank position data of the truck corresponding to the vehicle type data, and drives the corresponding first intelligent camera to obtain the first image data, thereby obtaining the judgment data.

[0075] Furthermore, to further prevent the driver from installing a water tank in another location on the truck that cannot be directly observed, please refer to Figure 4 As a preferred solution, in this embodiment, after obtaining the vehicle model data, the following is further performed:

[0076] Acquire multiple risk locations of the truck to be weighed based on the vehicle model data;

[0077] Acquire a second image of each risk location of the truck to be weighed;

[0078] Recognize the second image based on a second recognition model to obtain risk data; the second recognition model is constructed based on a neural network model;

[0079] Perform a warning operation based on the risk data. In this embodiment, after determining the type of truck with weighing, multiple locations of the truck where water tanks are easily installed can be determined as risk locations, such as chassis, tail and other inconspicuous locations. Further, the camera corresponding to the second image is also installed in a place where the corresponding risk location can be photographed, such as installed on the weighing scale, facing upward to photograph the bottom of the vehicle. Then, the second image of each risk location is obtained, and then it is determined whether there is an external hanging object, and whether the external hanging object is a water tank, bucket, etc. If so, a warning is issued to the outside, which can quickly find out whether the truck has been modified. The warning method can be voice broadcast, such as playing a voice "There is an external water tank. Please open the water outlet pipe and weigh again." The LED display screen displays the text message "Please turn on the water tank switch, empty the water tank and weigh again", and the sound column plays the corresponding sound prompt.

[0080] In some embodiments, the generation process of the second recognition model includes:

[0081] Acquire a second training set, the second training set includes a plurality of second training samples, the second training samples are images of water outlet pipes of a water tank of a truck and corresponding working state labels; the working state labels include an open state and a closed state;

[0082] The initialized neural network model is trained using the second training set to obtain the second recognition model. Preferably, the second recognition model is built into the control device.

[0083] In some embodiments, the first recognition model is built into a camera to form a first smart camera, which outputs the risk data to a control device.

[0084] Further, as a preferred solution, in this embodiment, the risk data includes abnormal information and non-abnormal information;

[0085] Performing warning operations based on the risk data specifically includes:

[0086] When the risk data is abnormal information, a warning message is issued externally;

[0087] When the risk data is non-abnormal information, the truck to be weighed is weighed.

[0088] Further, as a preferred solution, in this embodiment, the second image is identified based on the second recognition model to obtain risk data, which specifically includes:

[0089] If the second image is identified by the second recognition model and it is determined that the second image contains a water tank image, the risk data is abnormal information, otherwise the risk data is non-abnormal information. Specifically, when an external water tank or bucket is hung on the truck, the risk information is abnormal information, otherwise it is non-abnormal information. In this embodiment, as long as there is an external water tank, an alarm message is issued to remind the on-duty personnel to intervene on site, and the image information is archived.

[0090] Further, as a preferred solution, in this embodiment, when the risk data is abnormal information, it also includes:

[0091] The second image is input into the first recognition model for recognition, and the judgment data of the corresponding water outlet pipe image is obtained. When the judgment data indicates that the water pipe is open, the truck to be weighed is weighed, otherwise a warning message is issued. In this embodiment, when an external water tank is hung and the water outlet pipe of the water tank is closed, the risk information is abnormal information, otherwise there is no abnormal information. This ensures that even if an external water tank is hung on the truck, it is still possible to detect whether the water tank has been drained, further improving the anti-cheating effect.

[0092] On-site photos of various vehicle water tanks are taken in advance, and pictures of the water tanks in open and closed states are trained. Using AI technologies such as target detection and motion recognition, a model that can recognize the on-off state of vehicle water tanks is obtained through training.

[0093] Furthermore, in some embodiments, the first recognition model and the second recognition model can be integrated into the same camera to form an AI smart camera.

[0094] Accordingly, see Figure 5 The present invention also provides an unattended weighing and anti-cheating device, comprising:

[0095] An acquisition module, configured to acquire a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed;

[0096] A recognition module, configured to recognize the first image using a first recognition model to obtain determination data of the corresponding water outlet pipe image; the determination data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model;

[0097] The weighing module is used to perform a weighing operation on the truck to be weighed when the determination data indicates that the water pipe is open.

[0098] Accordingly, see Figure 6 The present invention also provides an unattended weighing and anti-cheating system, comprising:

[0099] Weighbridge;

[0100] One or more cameras, used to obtain detection images; the detection images include a first image including an image of a water outlet pipe of a water tank of a truck to be weighed, a second image corresponding to each risk location, and an image of the truck to be weighed;

[0101] The unattended weighing and anti-cheating device is connected to the floor scale and the camera respectively.

[0102] During specific implementation, a computer can be installed in the weighing room for linkage control of unattended weighing equipment. An AI intelligent recognition camera is installed in the center of the left and right sides of the truck scale. The camera's field of view covers the location where the water tank on the side of the truck is installed. The camera is connected to the computer in the weighing room through the network. A fill light is installed next to the camera to illuminate the drain switch of the truck water tank to improve the camera recognition rate. A sound column is installed on the wall of the weighing room, and connected to the computer in the weighing room through the network. An LED display screen is installed at the front and rear of the truck scale, and connected to the computer in the weighing room through the network. A software program is installed on the computer in the weighing room to receive data from the AI ​​intelligent recognition camera and to linkage control the LED display screen and the sound column to send prompt instructions.

[0103] Correspondingly, the present invention also provides a computer-readable medium storing a computer program, and when the computer program is executed by a processor, the unattended weighing and anti-cheating method is implemented.

[0104] More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk-read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0105] In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above.

[0106] It is understandable that those skilled in the art can make equivalent substitutions or changes based on the technical solution and inventive concept of the present invention, and all these changes or substitutions should fall within the protection scope of the claims attached to the present invention.

Claims

1. An unmanned weighing and anti-cheating method for the industrial Internet, characterized in that: include: Acquire a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed; The first image is recognized using a first recognition model to obtain corresponding determination data of the water outlet pipe image; the determination data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model; When the determination data indicates that the water pipe is open, performing a weighing operation on the truck to be weighed; The first recognition model is built into the camera to form a first intelligent camera, and the determination data is output to the control device. After the control device receives the determination data, when the determination data indicates that the water pipe is open, the weighbridge is driven to perform a weighing operation on the truck to be weighed; Before acquiring the first image, the method further includes: Acquire the image of the truck to be weighed; Using a vehicle type recognition model to identify the image of the truck to be weighed to obtain vehicle type data; the vehicle type recognition model is constructed based on a neural network model; determining a water tank position based on the vehicle model data; The first image of the corresponding water tank position is obtained; the vehicle type recognition model is built into the camera to form a vehicle type recognition camera, and the vehicle type data is output to the control device; after receiving the vehicle type data, the control device retrieves the water tank position data of the truck corresponding to the vehicle type data, and drives the corresponding first intelligent camera to obtain the first image data; After obtaining the vehicle model data, the following is also executed: Acquire multiple risk locations of the truck to be weighed based on the vehicle model data; Acquire a second image of each risk location of the truck to be weighed; Recognize the second image based on a second recognition model to obtain risk data; the second recognition model is constructed based on a neural network model; An alerting operation is performed based on the risk data.

2. The industrial Internet unmanned weighing and anti-cheating method according to claim 1 is characterized in that: The risk data includes abnormal information and non-abnormal information; Performing warning operations based on the risk data specifically includes: When the risk data is abnormal information, a warning message is issued to the outside.

3. The industrial Internet unmanned weighing and anti-cheating method according to claim 2 is characterized in that: Recognizing the second image based on the second recognition model to obtain risk data specifically includes: If the second image is recognized by the second recognition model and it is determined that the second image contains a water tank image, the risk data is abnormal information; otherwise, the risk data is non-abnormal information.

4. The industrial Internet unmanned weighing and anti-cheating method according to claim 3 is characterized in that: When the risk data is abnormal information, it also includes: The second image is input into the first recognition model for recognition to obtain the corresponding determination data of the water outlet pipe image. When the determination data indicates that the water pipe is open, the truck to be weighed is weighed, otherwise a warning message is issued.

5. The industrial Internet unmanned weighing and anti-cheating method according to claim 1 is characterized in that: When the determination data indicates that the water pipe is closed, an alarm message is issued externally.

6. An unmanned weighing and anti-cheating device for the industrial Internet, characterized in that: include: An acquisition module, configured to acquire a first image; the first image includes an image of a water outlet pipe of a water tank of a truck to be weighed; A recognition module, configured to recognize the first image using a first recognition model to obtain determination data of the corresponding water outlet pipe image; the determination data includes whether the water pipe is open or closed; the first recognition model is constructed based on a neural network model; A weighing module, used for performing a weighing operation on the truck to be weighed when the determination data indicates that the water pipe is open; The first recognition model is built into the camera to form a first intelligent camera, and the determination data is output to the control device. After the control device receives the determination data, when the determination data indicates that the water pipe is open, the weighbridge is driven to perform a weighing operation on the truck to be weighed; Before acquiring the first image, the method further includes: Acquire the image of the truck to be weighed; Using a vehicle type recognition model to identify the image of the truck to be weighed to obtain vehicle type data; the vehicle type recognition model is constructed based on a neural network model; determining a water tank position based on the vehicle model data; The first image of the corresponding water tank position is obtained; the vehicle type recognition model is built into the camera to form a vehicle type recognition camera, and the vehicle type data is output to the control device; after receiving the vehicle type data, the control device retrieves the water tank position data of the truck corresponding to the vehicle type data, and drives the corresponding first intelligent camera to obtain the first image data; After obtaining the vehicle model data, the following is also executed: Acquire multiple risk locations of the truck to be weighed based on the vehicle model data; Acquire a second image of each risk location of the truck to be weighed; Recognize the second image based on a second recognition model to obtain risk data; the second recognition model is constructed based on a neural network model; Execute a warning operation based on the risk data; the first recognition model is built into the camera to form a first intelligent camera, and the determination data is output to the control device. After the control device receives the determination data, when the determination data indicates that the water pipe is open, the weighbridge is driven to perform a weighing operation on the truck to be weighed; Before acquiring the first image, the method further includes: Acquire the image of the truck to be weighed; Using a vehicle type recognition model to identify the image of the truck to be weighed to obtain vehicle type data; the vehicle type recognition model is constructed based on a neural network model; determining a water tank position based on the vehicle model data; The first image of the corresponding water tank position is obtained; the vehicle type recognition model is built into the camera to form a vehicle type recognition camera, and the vehicle type data is output to the control device; after receiving the vehicle type data, the control device retrieves the water tank position data of the truck corresponding to the vehicle type data, and drives the corresponding first intelligent camera to obtain the first image data; After obtaining the vehicle model data, the following is also executed: Acquire multiple risk locations of the truck to be weighed based on the vehicle model data; Acquire a second image of each risk location of the truck to be weighed; Recognize the second image based on a second recognition model to obtain risk data; the second recognition model is constructed based on a neural network model; An alerting operation is performed based on the risk data.

7. An unmanned weighing and anti-cheating system for the industrial Internet, characterized in that: include: Weighbridge; One or more cameras, used to obtain detection images; the detection images include a first image including an image of a water outlet pipe of a water tank of a truck to be weighed, a second image corresponding to each risk location, and an image of the truck to be weighed; The industrial Internet unmanned weighing and anti-cheating device described in claim 6 is connected to the floor scale and the camera respectively.

8. A computer-readable medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the industrial Internet unmanned weighing and anti-cheating method described in any one of claims 1-5 is implemented.

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