Ultra-limit Detection Method, Device and Electronic Equipment Combining RPA and AI

Abstract

The present application relates to an overload detection method, device and electronic device combining RPA and AI, belonging to the technical fields of RPA and AI, and is applied to RPA robots. The method includes: obtaining first vehicle information in a first system corresponding to a processing unit; based on NLP technology, parsing the first vehicle information to obtain a first target vehicle whose corresponding first weight value exceeds a first preset weight threshold; sending the vehicle identifier of the first target vehicle to a second system corresponding to a first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station. It realizes the combination of RPA and AI technologies to accurately determine the overloaded vehicles sent from the processing unit, enabling the staff to pre-determine the vehicles to be detected and detect them when the vehicles travel to the first over-limit detection station, without the need to detect all passing vehicles, improving the detection efficiency and reducing the labor cost.

Description

Technical Field

[0001] This application relates to the technical fields of robotic process automation and artificial intelligence, and particularly relates to an over-limit detection method, device, and electronic device that combine RPA and AI. Background Art

[0002] Robotic Process Automation (RPA) is to simulate human operations on a computer through specific "robot software" and automatically execute process tasks according to rules.

[0003] Artificial Intelligence (AI) is a technical science that studies, develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence.

[0004] Overloading refers to the actual loading capacity of a means of transportation exceeding the maximum allowable limit. Freight overloading refers to the goods transported by a motor vehicle exceeding the load weight of the freight motor vehicle. In related technologies, when performing over-limit detection, staff can randomly select main roads and intercept and detect passing vehicles on that road. However, in this over-limit detection method, if each vehicle is intercepted and detected, it will consume a large amount of labor costs and have low detection efficiency. How to improve the detection efficiency of over-limit detection and reduce labor costs has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides an over-limit detection method, device, and electronic device that combine RPA and AI to solve the technical problems of low detection efficiency and high labor costs existing in the over-limit detection method in related technologies.

[0006] The first aspect embodiment of this application provides an over-limit detection method that combines RPA and AI and is applied to an RPA robot. The method includes: obtaining first vehicle information in a first system corresponding to a processing unit; the first vehicle information includes vehicle identifiers and first weight values of at least one first vehicle sent from the processing unit; based on natural language processing (NLP) technology, parsing the first vehicle information to obtain at least one first target vehicle among the at least one first vehicle, where the corresponding first weight value of the first target vehicle exceeds a first preset weight threshold; sending the vehicle identifier of the first target vehicle to a second system corresponding to a first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station.

[0007] In the second aspect of the embodiments of the present application, an over-limit detection device combining RPA and AI is provided, which is applied to an RPA robot. The device includes: a first acquisition module, configured to acquire first vehicle information in a first system corresponding to a processing unit; the first vehicle information includes vehicle identifiers and first weight values of at least one first vehicle sent from the processing unit; a second acquisition module, configured to parse the first vehicle information based on natural language processing (NLP) technology to obtain a first target vehicle in the first vehicles, where the first weight value of the first target vehicle exceeds a first preset weight threshold; a first sending module, configured to send the vehicle identifier of the first target vehicle to a second system corresponding to a first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station.

[0008] In the third aspect of the embodiments of the present application, an electronic device is proposed, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method described in the first aspect of the embodiments of the present application above is implemented.

[0009] In the fourth aspect of the embodiments of the present application, a computer-readable storage medium is proposed, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first aspect of the embodiments of the present application above is implemented.

[0010] In the fifth aspect of the embodiments of the present application, a computer program product is proposed, including a computer program, where the computer program implements the method described in the first aspect of the embodiments of the present application above when executed by a processor.

[0011] The technical solutions provided by the embodiments of the present application may include the following beneficial effects:

[0012] By using an RPA robot to acquire first vehicle information in a first system corresponding to a processing unit, where the first vehicle information includes vehicle identifiers and first weight values of at least one first vehicle sent from the processing unit, and parsing the first vehicle information based on natural language processing (NLP) technology to obtain a first target vehicle in the at least one first vehicle, where the first weight value of the first target vehicle exceeds a first preset weight threshold, the combination of RPA and AI technologies is realized to accurately determine the first target vehicle that is overloaded among the first vehicles sent from the processing unit. Furthermore, by sending the vehicle identifier of the first target vehicle to a second system corresponding to a first over-limit detection station, the staff of the first over-limit detection station can pre-determine the first target vehicle to be detected when the first target vehicle is sent from the processing unit, and detect the first target vehicle when the first target vehicle travels to the first over-limit detection station, and there is no need to detect all passing vehicles, thereby improving the detection efficiency and reducing the labor cost.

[0013] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned by practice of the present application. Description of the Drawings

[0014] In the drawings, unless otherwise specified, the same reference numerals throughout the several views denote the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in accordance with the present application and should not be regarded as limiting the scope of the present application.

[0015] Figure 1 is a schematic flowchart of an over-limit detection method combining RPA and AI according to the first embodiment of the present application;

[0016] Figure 2 is a schematic flowchart of an over-limit detection method combining RPA and AI according to the second embodiment of the present application;

[0017] Figure 3 is a scenario diagram of an over-limit detection method combining RPA and AI according to an embodiment of the present application;

[0018] Figure 4 is a schematic flowchart of an over-limit detection method combining RPA and AI according to the third embodiment of the present application;

[0019] Figure 5 is a schematic structural diagram of an over-limit detection device combining RPA and AI according to the fourth embodiment of the present application;

[0020] Figure 6 is a block diagram of an electronic device for implementing the over-limit detection method combining RPA and AI according to an embodiment of the present application. Detailed Description of the Embodiments

[0021] The embodiments of the present application / disclosure are described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals throughout denote the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the drawings are exemplary only for explaining the present application / disclosure and should not be construed as limiting the present application / disclosure.

[0022] Referring to the following description and drawings, these and other aspects of the embodiments of the present application / disclosure will become clear. In these descriptions and drawings, some specific embodiments of the embodiments of the present application / disclosure are specifically disclosed to represent some ways of implementing the principles of the embodiments of the present application / disclosure. However, it should be understood that the scope of the embodiments of the present application / disclosure is not limited thereto. On the contrary, the embodiments of the present application / disclosure include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0023] It should be noted that in the technical solution of the present application, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0024] In view of the technical problems of low detection efficiency and high labor cost existing in the over-limit detection methods in the related technologies, the present application provides an idea for realizing over-limit detection by combining RPA and AI. The RPA robot is used to obtain the first vehicle information in the first system corresponding to the processing unit. The first vehicle information includes the vehicle identification and the first weight value of at least one first vehicle sent from the processing unit. Based on the natural language processing NLP technology, the first vehicle information is analyzed to obtain at least one first target vehicle among the first vehicles, in which the corresponding first weight value exceeds the first preset weight threshold, thus realizing the accurate determination of the first target overloaded vehicle among the first vehicles sent from the processing unit by combining RPA and AI technologies. Furthermore, by sending the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station, the staff of the first over-limit detection station can pre-determine the first target vehicle to be detected when the first target vehicle is sent from the processing unit, and detect the first target vehicle when the first target vehicle travels to the first over-limit detection station, without detecting all the passing vehicles, thereby improving the detection efficiency, improving the traffic congestion situation, and reducing the labor cost.

[0025] To clearly illustrate the embodiments of the present application, first, the technical terms involved in the embodiments of the present application are explained.

[0026] In the description of the present application, the term "a plurality of" means two or more.

[0027] In the description of the present application, an "RPA robot" refers to a software robot that can automatically perform over-limit detection by combining AI technology and RPA technology. The RPA robot has two characteristics of "connector" and "non-invasive". By simulating the operation method of humans, without changing the information system, in a non-invasive manner, the data of different systems are extracted, integrated, and connected.

[0028] In the description of the present application, a "processing unit" refers to a unit that can process raw materials into products. Such as a concrete processing plant, a food processing plant, etc.

[0029] In the description of the present application, the "first system" is the system used by the processing unit. After the processing unit weighs the vehicle carrying goods such as raw materials or products, the vehicle identification and the weight value can be entered into this system. Among them, the weight value may include the total weight value of the goods such as raw materials or products and the vehicle, or in addition to the total weight value of the goods and the vehicle, it may also include the weight value of the goods and / or the weight value of the vehicle.

[0030] In the description of this application, the "first over-limit detection station" refers to the detection station for over-limit detection. This first over-limit detection station can be set downstream of the processing unit, that is, the first over-limit detection station usually detects the vehicles traveling from the processing unit to the first over-limit detection station.

[0031] In the description of this application, the "second system" refers to the weighing system used by the first over-limit detection station. After the first over-limit detection station weighs the vehicles traveling from the processing unit to the first over-limit detection station, the vehicle identification and weight value can be entered into this weighing system. Among them, when the vehicle traveling from the processing unit to the first over-limit detection station is carrying the products of the processing unit, the weight value can include the total weight value of the products and the vehicle, or, in addition to the total weight value of the products and the vehicle, it can also include the weight value of the products and / or the weight value of the vehicle.

[0032] In the description of this application, the "second over-limit detection station" refers to the detection station for over-limit detection. This second over-limit detection station can be set upstream of the processing unit, that is, the second over-limit detection station usually detects the vehicles traveling from the second over-limit detection station to the processing unit.

[0033] In the description of this application, the "third system" refers to the weighing system used by the second over-limit detection station. After the second over-limit detection station weighs the vehicles traveling from the second over-limit detection station to the processing unit, the vehicle identification and weight value can be entered into this weighing system. Among them, when the vehicle traveling from the second over-limit detection station to the processing unit is carrying the raw materials of the processing unit, the weight value can include the total weight value of the raw materials and the vehicle, or, in addition to the total weight value of the raw materials and the vehicle, it can also include the weight value of the raw materials and / or the weight value of the vehicle.

[0034] In the description of this application, the "vehicle identification" is used to uniquely identify the vehicle and can be the license plate number of the vehicle or other identifiers that can uniquely identify the vehicle. This application does not limit this.

[0035] In the description of this application, the "passing time" refers to the time when the vehicle is weighed at the over-limit detection station. In the embodiments of this application, an over-limit detection system can be set on the road surface at the over-limit detection station. When the vehicle passes through this road surface, the over-limit detection system can weigh the vehicle, thereby realizing non-stop weighing of the vehicle. Therefore, the passing time can also be understood as the time when the vehicle passes through the over-limit detection system of the over-limit detection station.

[0036] In the description of the present application, a "screen management system" is used to manage a display screen, such as controlling the content and display time of the display screen. Among them, the "display screen" can be an LED (Light Emitting Diode) display screen or other display screens, and the present application does not limit this.

[0037] In the description of the present application, "NLP (Natural Language Processing)" refers to the ability of a machine to understand and interpret the way humans write and speak. The goal of NLP is to make a computer / machine as intelligent as a human in understanding language, and the task of NLP is to understand human language and convert it into machine language.

[0038] The following describes a method, device, electronic device, and storage medium for overrun detection that combines RPA and AI according to an embodiment of the present application / disclosure with reference to the accompanying drawings.

[0039] Figure 1 It is a flowchart of a method for overrun detection that combines RPA and AI according to the first embodiment of the present application. As Figure 1 shown, the method may include the following steps:

[0040] Step 101, obtain first vehicle information in a first system corresponding to a processing unit; the first vehicle information includes a vehicle identifier and a first weight value of at least one first vehicle sent from the processing unit.

[0041] It should be noted that the method for overrun detection that combines RPA and AI according to the embodiments of the present application can be executed by an overrun detection device that combines RPA and AI. Hereinafter, the overrun detection device that combines RPA and AI is simply referred to as an overrun detection device. Among them, the overrun detection device can be implemented by an RPA robot. For example, the overrun detection device can be an RPA robot, or the overrun detection device can be configured in an RPA robot, and the present application does not limit this.

[0042] Among them, the RPA robot can be configured in an electronic device, and the electronic device can include, but is not limited to, a terminal device, a server, etc. This embodiment does not specifically limit the electronic device. This embodiment of the present application takes the RPA robot installed in a terminal device as an example for description.

[0043] Among them, the RPA robot in this embodiment can execute this method during a specific time period or in real time throughout the day, and the present application does not limit this. Among them, the specific time period can be set as needed.

[0044] Alternatively, the above RPA robot can also be started based on a received start instruction. For example, the staff at the over-limit detection station can trigger the above start instruction for the RPA robot through a conversation. Among them, triggering the start instruction for the RPA robot can be achieved in various ways. For example, the start instruction of the RPA robot can be triggered by voice and / or text. Another example is that the start instruction of the RPA robot can also be triggered by triggering a specified control on the dialogue interaction interface. The embodiments of the present application do not make specific limitations on this.

[0045] Among them, the first vehicle can refer to a vehicle carrying goods of the processing unit and dispatched from the processing unit. Among them, when the first vehicle carries the products of the processing unit, the first weight value can include the total weight value of the products and the first vehicle; when the first vehicle carries the raw materials of the processing unit, the first weight value can include the total weight value of the raw materials and the first vehicle.

[0046] In the embodiments of the present application, before at least one first vehicle is dispatched from the processing unit, the processing unit can weigh each first vehicle to obtain a first weight value, and enter the vehicle identification and the first weight value of each first vehicle into the corresponding first system, so that the RPA robot can obtain the vehicle identification and the first weight value of each first vehicle from the first system in real time.

[0047] Step 102: Based on the natural language processing NLP technology, parse the first vehicle information to obtain at least one first target vehicle among the first vehicles, where the corresponding first weight value exceeds the first preset weight threshold.

[0048] Among them, the first preset weight threshold is the safe weight value for the first vehicle to drive safely, which can be set as needed. For example, it can be set according to the vehicle type of the first vehicle. It should be noted that the first preset weight threshold is set corresponding to the first weight value. That is, when the first weight value includes the total weight value of the first vehicle and the goods, the first preset weight threshold corresponds to the total safe weight value of the first vehicle and the goods when the first vehicle drives safely; when the first weight value includes the weight value of the goods carried by the first vehicle, the first preset weight threshold corresponds to the maximum allowable value of the goods carried by the first vehicle when the first vehicle drives safely.

[0049] In the embodiments of the present application, the RPA robot can parse the first vehicle information based on the natural language processing NLP technology. For example, it can extract the first weight values of each first vehicle included in the first vehicle information, and compare each first weight value with the first preset weight threshold of the corresponding first vehicle to determine which first vehicles' first weight values exceed the corresponding first preset weight threshold, and determine the first vehicles whose corresponding first weight values exceed the corresponding first preset weight threshold, that is, the overloaded first vehicles, as the first target vehicles.

[0050] Step 103: Send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station to prompt the staff at the first over-limit detection station to detect the first target vehicle when it travels from the processing unit to the first over-limit detection station.

[0051] In the embodiment of the present application, after the RPA robot obtains the first target vehicle, it can send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station to prompt the staff at the first over-limit detection station to conduct an inbound inspection on the first target vehicle when it travels from the processing unit to the first over-limit detection station. Among them, when prompting the staff at the first over-limit detection station, it can be prompted by displaying the vehicle identification of the first target vehicle on the display screen of the local terminal device where the second system is located, such as a local computer screen. Moreover, the vehicle identification of the first target vehicle can be highlighted, or other methods can also be used for prompting, and the present application does not limit this.

[0052] In the embodiment of the present application, the first vehicle information may further include the weighing time corresponding to the first weight value. This weighing time is the time when the first vehicle is weighed at the processing unit. The RPA robot can also send the weighing time of the first target vehicle and the vehicle identification of the first target vehicle to the second system at the same time, so that the staff at the first over-limit detection station can estimate the time when the first target vehicle travels to the first over-limit detection station, and thus prepare for the detection of the first target vehicle in advance.

[0053] In the embodiment of the present application, in addition to displaying the vehicle identification of the first target vehicle on the display screen of the local terminal device to prompt the staff at the first over-limit detection station, other display screens, such as LED screens, can also be set at the first over-limit detection station. The RPA robot can also send the vehicle identification of the first target vehicle to the screen management system of this display screen to control this display screen to display the vehicle identification of the first target vehicle through the screen management system, so that when the first target vehicle travels to the first over-limit detection station, it can be prompted to conduct an inbound inspection.

[0054] It can be understood that after the processing unit enters the first vehicle information into the corresponding first system, the first vehicle information can be displayed on the local terminal device where the first system is located, such as a local computer. Thus, the staff of the processing unit can determine whether each first vehicle is overloaded based on the first vehicle information, so as to avoid the situation of overloaded departure of each first vehicle. However, in actual applications, there may still be a situation where a certain first vehicle departs from the processing unit with overloading due to negligence of the staff of the processing unit or other reasons. The over-limit detection method combining RPA and AI provided by the embodiments of the present application can determine the first target vehicle with overloading departing from the processing unit, and send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station, so as to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels to the first over-limit detection station. Thus, the situation of overloaded vehicle driving is avoided, and further problems such as road surface damage, bridge fracture, and shortened service life of the road caused by overloading are avoided, the occurrence of traffic accidents is reduced, and the vehicle does not need to reduce the driving speed due to overloading, ensuring that the vehicle travels at a normal speed, thereby improving the road transportation capacity and vehicle transportation efficiency.

[0055] The over-limit detection method combining RPA and AI provided by the embodiments of the present application obtains the first vehicle information in the first system corresponding to the processing unit through the RPA robot. The first vehicle information includes the vehicle identification and the first weight value of at least one first vehicle departing from the processing unit. Based on the natural language processing NLP technology, the first vehicle information is parsed to obtain the first target vehicle among at least one first vehicle whose corresponding first weight value exceeds the first preset weight threshold, realizing the combination of RPA and AI technologies to accurately determine the first target vehicle with overloading among the first vehicles departing from the processing unit. Furthermore, by sending the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station, the staff of the first over-limit detection station can pre-determine the first target vehicle to be detected when the first target vehicle departs from the processing unit, and detect the first target vehicle when the first target vehicle travels to the first over-limit detection station, and there is no need to detect all passing vehicles, thereby improving the detection efficiency and reducing the labor cost.

[0056] The following combines Figure 2 , and further illustrates the over-limit detection method combining RPA and AI provided by the embodiments of the present application. Figure 2 is a flowchart of the over-limit detection method combining RPA and AI according to the second embodiment of the present application. As Figure 2 shown, the method includes:

[0057] Step 201: Obtain the first vehicle information in the first system corresponding to the processing unit; the first vehicle information includes the vehicle identification, the first weight value, and the weighing time of at least one first vehicle sent from the processing unit.

[0058] Among them, the weighing time of the first vehicle is the time when the processing unit weighs the first vehicle.

[0059] Step 202: Based on the natural language processing (NLP) technology, parse the first vehicle information to obtain at least one first target vehicle among the at least one first vehicle, where the corresponding first weight value of the first target vehicle exceeds the first preset weight threshold.

[0060] Step 203: Send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station.

[0061] Among them, for the specific implementation process and principle of steps 201 - 203, reference can be made to the description of the above embodiments, and details will not be elaborated here.

[0062] By using an RPA robot to obtain the first vehicle information in the first system corresponding to the processing unit, where the first vehicle information includes the vehicle identification, the first weight value, and the weighing time of at least one first vehicle sent from the processing unit, and based on the natural language processing (NLP) technology, parsing the first vehicle information to obtain at least one first target vehicle among the at least one first vehicle, where the corresponding first weight value of the first target vehicle exceeds the first preset weight threshold, it realizes the accurate determination of the first overloaded target vehicle among the first vehicles sent from the processing unit by combining RPA and AI technologies. Furthermore, by sending the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station, the staff of the first over-limit detection station can pre-determine the first target vehicle to be detected when the first target vehicle is sent from the processing unit, and detect the first target vehicle when the first target vehicle travels to the first over-limit detection station, without the need to detect all passing vehicles, thus improving the detection efficiency and reducing the labor cost.

[0063] Step 204: Obtain the second vehicle information in the second system corresponding to the first over-limit detection station; the second vehicle information includes the vehicle identification, the passing time, and the second weight value of at least one first vehicle.

[0064] Among them, the passing time of the first vehicle refers to the time when the first vehicle is weighed at the first over-limit detection station.

[0065] Among them, when the first vehicle carries the products of the processing unit, the second weight value may include the total weight value of the products and the first vehicle; when the first vehicle carries the raw materials of the processing unit, the second weight value may include the total weight value of the raw materials and the first vehicle.

[0066] It can be understood that an over-limit detection system can be set on the road surface of the first over-limit detection station. When each first vehicle passes through this road surface, the over-limit detection system can weigh each first vehicle to obtain the second weight value, so as to realize the non-stop weighing of each first vehicle. And after the over-limit detection system weighs each first vehicle, it can record the vehicle identification, passing time and second weight value of each first vehicle into the second system, so that the RPA robot can obtain the vehicle identification, passing time and second weight value of each first vehicle from the second system in real time.

[0067] Step 205: Compare the weighing time corresponding to at least one first vehicle with the passing time, and compare the corresponding first weight value with the second weight value, so as to obtain a second target vehicle that meets the preset conditions among at least one first vehicle.

[0068] Among them, the preset conditions may include at least one of the following conditions: the first difference between the passing time and the weighing time is greater than the preset time threshold; the second difference between the second weight value and the first weight value is greater than the second preset weight threshold. Among them, the preset time threshold can be set as needed. For example, it can be set as the time required for the first vehicle to normally drive from the processing unit to the first over-limit detection station. The second preset weight threshold can be set arbitrarily as needed. For example, it can be set as 2 tons, 3 tons, etc.

[0069] In the embodiment of the present application, the RPA robot can compare the weighing time corresponding to each first vehicle with the passing time, and compare the first weight value corresponding to each first vehicle with the second weight value, so as to obtain a second target vehicle that meets the preset conditions from each first vehicle, and determine the second target vehicle as a violation vehicle.

[0070] Step 206: Display and / or broadcast the vehicle identification and passing time of the second target vehicle to prompt the staff of the first over-limit detection station to detect the second target vehicle.

[0071] In an embodiment of the present application, the RPA robot can send the vehicle identification and passing time of the second target vehicle to the second system, and display them through the display screen of the local terminal device where the second system is located, such as the local computer screen. Moreover, the vehicle identification and passing time of the second target vehicle can be highlighted in different colors. Alternatively, the RPA robot can send the vehicle identification and passing time of the second target vehicle to the LED screen set at the first over-limit detection station for display through the LED screen. Moreover, when the number of second target vehicles is multiple, the screen scrolling method can be used for display. Alternatively, the vehicle identification and passing time of the second target vehicle can also be displayed in other ways, and the present application does not limit this.

[0072] In an embodiment of the present application, the vehicle identification and passing time of the second target vehicle can also be only broadcasted, or, while displaying the vehicle identification and passing time of the second target vehicle, the vehicle identification and passing time of the second target vehicle can be broadcasted to ensure that the staff of the first over-limit detection station can know the violation situation of the second target vehicle.

[0073] In addition, in an embodiment of the present application, by displaying and / or broadcasting the vehicle identification and passing time of the second target vehicle, the staff of the first over-limit detection station can be prompted to conduct an in-station inspection on the second target vehicle, thereby avoiding the personal safety problems existing in the vehicle stop inspection by the staff of the first over-limit detection station in some situations with complex weather, dense vehicles, and high vehicle speeds.

[0074] Reference Figure 3 As shown, the first over-limit detection station can be set downstream of the processing unit. The RPA robot can obtain the first vehicle information from the first system corresponding to the processing unit and synchronize the first vehicle information to the second system corresponding to the first over-limit detection station. After determining the first target vehicle, the vehicle identification of the first target vehicle can be sent to the second system corresponding to the first over-limit detection station to prompt the staff of the first over-limit detection station to conduct an inspection on the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station. Moreover, after determining the second target vehicle, the vehicle identification and passing time of the second target vehicle can be sent to the second system to display the vehicle identification and passing time of the second target vehicle through the display screen of the terminal device where the second system is located.

[0075] In this way, data interconnection between the first system corresponding to the processing unit and the second system corresponding to the first over-limit detection station can be achieved. Compared with the resource-consuming method of establishing a system, opening up the underlying data interface of the system, and realizing data synchronization between the processing unit and the first over-limit detection station, this application can easily realize data synchronization between the processing unit and the first over-limit detection station through non-intrusive RPA technology, thereby reducing the economic cost and time cost of data synchronization.

[0076] The over-limit detection method combining RPA and AI provided in the embodiment of the present application can accurately obtain the second target vehicle that meets the preset conditions in the at least one first vehicle by comparing the weighing time and the passing time of at least one first vehicle corresponding to the RPA robot, and comparing the corresponding first weight value with the second weight value, and then prompt the staff of the first over-limit detection station to inspect the second target vehicle by displaying and / or broadcasting the vehicle identification and passing time of the second target vehicle, so as to avoid the first vehicle traveling from the processing unit to the first over-limit detection station from unloading midway, ensure the safe and orderly driving of the vehicle, and avoid damage to the interests of the processing unit.

[0077] Combine the following Figure 4 In view of the above situation, the over-limit detection method combining RPA and AI provided in the embodiment of the present application is further explained.

[0078] Figure 4 is a flow chart of an over-limit detection method combining RPA and AI according to the third embodiment of the present application, such as Figure 4 As shown, the method may also include:

[0079] Step 401, obtaining third vehicle information in a third system corresponding to a second overload detection station; wherein the third vehicle information includes a vehicle identification, a transit time, and a third weight value of at least one second vehicle traveling from the second overload detection station to a processing unit.

[0080] The second vehicle may refer to a vehicle carrying goods of the processing unit and traveling from the second overload detection station to the processing unit. If the second vehicle carries products of the processing unit, the third weight value may include the total weight of the products and the second vehicle; if the second vehicle carries raw materials of the processing unit, the third weight value may include the total weight of the raw materials and the second vehicle.

[0081] The transit time of the second vehicle refers to the time when the second vehicle is weighed at the second overload inspection station.

[0082] It is understandable that an overload detection system can be set up on the road surface of the second overload detection station. When each second vehicle passes through the road surface, the overload detection system can weigh each second vehicle to obtain the third weight value, thereby realizing the non-stop weighing of each second vehicle. In addition, after the overload detection system weighs each second vehicle, the vehicle identification, station passing time and third weight value of each second vehicle can be entered into the third system, so that the RPA robot can obtain the vehicle identification, station passing time and third weight value of each second vehicle from the third system in real time.

[0083] Step 402, sending the third vehicle information to the first system corresponding to the processing unit.

[0084] In the examples of this application, reference is made to Figure 3 , the second over-limit detection station can be set up upstream of the processing unit, and the RPA robot can obtain the third vehicle information in the third system corresponding to the second over-limit detection station, and synchronize the third vehicle information to the first system corresponding to the processing unit, thereby realizing the data interconnection and intercommunication between the third system corresponding to the second over-limit detection station and the first system corresponding to the processing unit. Compared with the resource-consuming method of establishing a system, opening up the underlying data interface of the system, and realizing data synchronization between the second over-limit detection station and the processing unit, the present application can easily realize data synchronization between the second over-limit detection station and the processing unit through non-invasive RPA technology, thereby reducing the economic cost and time cost of data synchronization.

[0085] Among them, the preset time range can be set as needed, for example, it can be set to the time required for the second vehicle to normally travel from the second overload inspection station to the processing unit.

[0086] In an embodiment of the present application, the third vehicle information obtained by the RPA robot from the third system may include the vehicle identification, the stop-over time and the third weight value of the second vehicle traveling from the second overload detection station to the processing unit within a time period. After the RPA robot obtains the third vehicle information in the third system corresponding to the second overload detection station, it can parse the third vehicle information based on the natural language processing NLP technology, for example, it can extract the stop-over time of each second vehicle included in the third vehicle information, and determine whether the stop-over time of each second vehicle is within the preset time range according to the difference between the stop-over time of each second vehicle and the current time, and determine the second vehicle whose corresponding stop-over time is within the preset time range as the third target vehicle. The third target vehicle is the second vehicle on the road between the second overload detection station and the processing unit at the current position. Furthermore, the RPA robot can display and / or broadcast the vehicle identification and the third weight value of the third target vehicle to prompt the staff of the processing unit to weigh the third target vehicle when the third target vehicle travels from the second overload detection station to the processing unit.

[0087] Among them, when the difference between the passing time of the second vehicle and the current time is less than the preset time range, it can be determined that the passing time of the second vehicle is within the preset time range; when the difference between the passing time of the second vehicle and the current time is not less than the preset time range, it can be determined that the passing time of the second vehicle is not within the preset time range.

[0088] That is, after step 401, it may further include:

[0089] Based on natural language processing NLP technology, parse the third vehicle information to obtain at least one third target vehicle among the second vehicles, whose corresponding passing time is within the preset time range;

[0090] Display and / or broadcast the vehicle identification and the third weight value of the third target vehicle to prompt the staff of the processing unit to weigh the third target vehicle when the third target vehicle travels from the second over-limit detection station to the processing unit.

[0091] Among them, the way of displaying the vehicle identification and the third weight value of the third target vehicle can refer to the way of displaying the vehicle identification and the passing time of the second target vehicle, which will not be elaborated here.

[0092] In the embodiment of the present application, after the processing unit weighs the third target vehicle to obtain the fourth weight value, the vehicle identification and the fourth weight value of the third target vehicle can be entered into the corresponding first system. The RPA robot can obtain the fourth weight value of the third target vehicle in the first system corresponding to the processing unit, and determine the third difference between the third weight value and the fourth weight value of the third target vehicle, and determine the third target vehicle with the corresponding third difference exceeding the third preset weight threshold as the fourth target vehicle, and then display and / or broadcast the vehicle identification of the fourth target vehicle to prompt the staff of the processing unit to detect the fourth target vehicle.

[0093] Among them, when the second vehicle is carrying the products of the processing unit, the fourth weight value may include the total weight value of the products and the second vehicle; when the second vehicle is carrying the raw materials of the processing unit, the fourth weight value may include the total weight value of the raw materials and the second vehicle.

[0094] The third preset weight threshold can be set arbitrarily according to needs, such as it can be set to 2 tons, 3 tons, etc.

[0095] Among them, the way of displaying the vehicle identification of the fourth target vehicle can refer to the way of displaying the vehicle identification and the passing time of the second target vehicle, which will not be elaborated here.

[0096] Obtain the fourth weight value of the third target vehicle in the first system corresponding to the processing unit through the RPA robot, and determine the third difference between the third weight value and the fourth weight value of the third target vehicle, which can accurately determine the load deviation of the third target vehicle when driving from the second over-limit detection station to the processing unit. Furthermore, by identifying the third target vehicle whose corresponding third difference exceeds the third preset weight threshold as the fourth target vehicle, and displaying and / or broadcasting the vehicle identification of the fourth target vehicle, it can prompt the staff of the processing unit to detect the fourth target vehicle, avoid the mid-way unloading behavior of the second vehicle driving from the second over-limit detection station to the processing unit, ensure the safe and orderly driving of the vehicle, and avoid the damage of the interests of the processing unit.

[0097] To implement the above embodiments, the present application also proposes an over-limit detection device combining RPA and AI. Figure 5 It is a schematic structural diagram of an over-limit detection device combining RPA and AI according to the fourth embodiment of the present application.

[0098] As Figure 5 shown, the over-limit detection device 500 combining RPA and AI, which is applied to the RPA robot, includes: a first acquisition module 501, a second acquisition module 502, and a first sending module 503.

[0099] Among them, the first acquisition module 501 is used to acquire the first vehicle information in the first system corresponding to the processing unit; the first vehicle information includes the vehicle identification and the first weight value of at least one first vehicle sent from the processing unit;

[0100] The second acquisition module 502 is used to parse the first vehicle information based on the natural language processing NLP technology to obtain the first target vehicle among the first vehicles whose corresponding first weight value exceeds the first preset weight threshold;

[0101] The first sending module 503 is used to send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle drives from the processing unit to the first over-limit detection station.

[0102] It should be noted that the over-limit detection device combining RPA and AI in the embodiments of the present application can execute the over-limit detection method combining RPA and AI provided in the above embodiments. Among them, the over-limit detection device combining RPA and AI can be implemented by the RPA robot. For example, the over-limit detection device combining RPA and AI can be the RPA robot, or the over-limit detection device can be configured in the RPA robot. The present application does not limit this.

[0103] Among them, the RPA robot can be configured in an electronic device, which can include but is not limited to a terminal device, a server, etc. This embodiment does not specifically limit the electronic device. In this application embodiment, the over-limit detection device is taken as an example of the RPA robot installed in the terminal device for illustration.

[0104] In an embodiment of the present application, the first vehicle information further includes the weighing time of at least one first vehicle; the over-limit detection device 500 combining RPA and AI further includes:

[0105] A third acquisition module, configured to acquire second vehicle information in a second system corresponding to a first over-limit detection station; the second vehicle information includes the vehicle identifier, passing time, and second weight value of at least one first vehicle;

[0106] A comparison module, configured to compare the weighing time corresponding to at least one first vehicle with the passing time, and compare the corresponding first weight value with the second weight value, so as to obtain a second target vehicle among at least one first vehicle that meets a preset condition;

[0107] A first prompt module, configured to display and / or broadcast the vehicle identifier and passing time of the second target vehicle, so as to prompt the staff of the first over-limit detection station to detect the second target vehicle;

[0108] Among them, the preset condition includes at least one of the following conditions: the first difference between the passing time and the weighing time is greater than a preset time threshold; the second difference between the second weight value and the first weight value is greater than a second preset weight threshold.

[0109] In an embodiment of the present application, the above-mentioned over-limit detection device 500 combining RPA and AI further includes:

[0110] A second sending module, configured to send the vehicle identifier of the first target vehicle to a screen management system, so as to display the vehicle identifier of the first target vehicle through a display screen corresponding to the screen management system.

[0111] In an embodiment of the present application, the above-mentioned over-limit detection device 500 combining RPA and AI further includes:

[0112] A fourth acquisition module, configured to acquire third vehicle information in a third system corresponding to a second over-limit detection station; among them, the third vehicle information includes the vehicle identifier, passing time, and third weight value of at least one second vehicle traveling from the second over-limit detection station to a processing unit;

[0113] A third sending module, configured to send the third vehicle information to a first system corresponding to a processing unit.

[0114] In an embodiment of the present application, the above-mentioned over-limit detection device 500 combining RPA and AI further includes:

[0115] An analysis module, configured to analyze the third vehicle information based on natural language processing (NLP) technology to obtain at least one third target vehicle among the second vehicles, where the corresponding passing time is within a preset time range.

[0116] A second prompt module, configured to display and / or broadcast the vehicle identification and the third weight value of the third target vehicle to prompt the staff of the processing unit to weigh the third target vehicle when the third target vehicle travels from the second over-limit detection station to the processing unit.

[0117] In an embodiment of the present application, the above-mentioned over-limit detection device 500 combining RPA and AI further includes:

[0118] A fifth acquisition module, configured to acquire the fourth weight value of the third target vehicle in the first system corresponding to the processing unit.

[0119] A first determination module, configured to determine the third difference between the third weight value and the fourth weight value of the third target vehicle.

[0120] A second determination module, configured to determine the third target vehicle with the corresponding third difference exceeding the third preset weight threshold as the fourth target vehicle.

[0121] A third prompt module, configured to display and / or broadcast the vehicle identification of the fourth target vehicle to prompt the staff of the processing unit to detect the fourth target vehicle.

[0122] It should be noted that the foregoing explanation of the embodiment of the over-limit detection method combining RPA and AI is also applicable to the over-limit detection device combining RPA and AI in this embodiment. Details not disclosed in the embodiment of the over-limit detection device combining RPA and AI of the present application will not be elaborated here.

[0123] In summary, the over-limit detection device combining RPA and AI according to the embodiments of the present application obtains the first vehicle information in the first system corresponding to the processing unit through the RPA robot. The first vehicle information includes the vehicle identifier of the first vehicle sent from the processing unit and the first weight value. Based on the natural language processing NLP technology, the first vehicle information is parsed to obtain the first target vehicle in the first vehicle whose corresponding first weight value exceeds the first preset weight threshold, realizing the accurate determination of the first target vehicle overloaded in the first vehicle sent from the processing unit by combining RPA and AI technologies. Furthermore, by sending the vehicle identifier of the first target vehicle to the second system corresponding to the first over-limit detection station, the staff of the first over-limit detection station can pre-determine the first target vehicle to be detected when the first target vehicle is sent from the processing unit, and detect the first target vehicle when the first target vehicle travels to the first over-limit detection station, without detecting all passing vehicles, thus improving the detection efficiency and reducing the labor cost.

[0124] To implement the above embodiments, the embodiments of the present application also propose an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the over-limit detection method combining RPA and AI as described in any of the foregoing method embodiments.

[0125] To implement the above embodiments, the embodiments of the present application also propose a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the over-limit detection method combining RPA and AI as described in any of the foregoing method embodiments.

[0126] To implement the above embodiments, the embodiments of the present application also propose a computer program product. When the instruction processor in the computer program product executes, it implements the over-limit detection method combining RPA and AI as described in any of the foregoing method embodiments.

[0127] Figure 6 The block diagram of an exemplary electronic device suitable for implementing the embodiments of the present application is shown. Figure 6 The shown electronic device 12 is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.

[0128] As Figure 6 shown, the electronic device 12 is presented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the memory 28 and the processing unit 16).

[0129] Bus 18 represents one or more of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, an Accelerated Graphics Port, a processor, or a local bus using any of the various bus architectures. By way of example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnection (PCI) bus.

[0130] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and nonvolatile media, removable and non-removable media.

[0131] Memory 28 can include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and / or cache memory 32. Electronic device 12 can further include other removable / non-removable, volatile / nonvolatile computer system storage media. By way of example only, storage system 34 can be used for reading and writing on non-removable, nonvolatile magnetic media ( Figure 6 not shown, typically referred to as a "hard disk drive"). Although Figure 6 not shown in, a disk drive for reading and writing on a removable nonvolatile disk (such as a "floppy disk") and an optical disk drive for reading and writing on a removable nonvolatile optical disk (such as Compact Disc Read Only Memory (CD-ROM), Digital Video Disc Read Only Memory (DVD-ROM), or other optical media) can be provided. In these cases, each drive can be connected to bus 18 through one or more data media interfaces. Memory 28 can include at least one program product having a set (such as at least one) of program modules that are configured to perform the functions of the embodiments of the present application.

[0132] A program / utilities 40 having a set (at least one) of program modules 42 can be stored, for example, in a memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules 42 generally execute the functions and / or methods in the embodiments described in the present application.

[0133] The electronic device 12 can also communicate with one or more external devices 14 (such as a keyboard, a pointing device, a display 24, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 12, and / or communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through an input / output (I / O) interface 22. Moreover, the electronic device 12 can also communicate with one or more networks (such as a Local Area Network (LAN), a Wide Area Network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As Figure 6 shown, the network adapter 20 communicates with other modules of the electronic device 12 through a bus 18. It should be understood that although Figure 6 not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0134] The processing unit 16 executes various functional applications and data processing by running programs stored in the memory 28, such as implementing the methods mentioned in the foregoing embodiments.

[0135] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0136] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features indicated. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0137] Any process or method description represented in a flowchart or described otherwise herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0138] The logic and / or steps represented in a flowchart or described otherwise herein, for example, may be considered as a sequenced list of executable instructions for implementing a logical function and may be specifically implemented in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other appropriate processing as necessary, and then storing it in a computer memory.

[0139] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following techniques known in the art or a combination thereof can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0140] Those of ordinary skill in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0141] In addition, each functional unit in the various embodiments of the present application can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0142] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An overload detection method combining robotic process automation (RPA) and artificial intelligence (AI), characterized in that, applied to an RPA robot, the method includes: Obtaining first vehicle information in a first system corresponding to a processing unit; the first vehicle information includes vehicle identifiers and first weight values of at least one first vehicle sent from the processing unit, where the processing unit refers to a unit capable of processing raw materials into products, and the first system is the system used by the processing unit; Based on natural language processing (NLP) technology, parsing the first vehicle information to obtain at least one first target vehicle among the at least one first vehicle, where the corresponding first weight value exceeds a first preset weight threshold; Sending the vehicle identifier of the first target vehicle to a second system corresponding to a first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station; The first vehicle information further includes the weighing time of at least one of the first vehicles; after obtaining the first vehicle information in the first system corresponding to the processing unit, it further includes: Obtaining second vehicle information in a second system corresponding to the first over-limit detection station; the second vehicle information includes vehicle identifiers, passing times, and second weight values of at least one of the first vehicles, and the second weight value is detected by an over-limit detection system arranged on the road surface of the first over-limit detection station; Comparing the weighing time corresponding to at least one of the first vehicles with the passing time, and comparing the corresponding first weight value with the second weight value to obtain at least one second target vehicle among the at least one first vehicles that meets a preset condition, and determining the second target vehicle as a violation vehicle; Displaying and / or broadcasting the vehicle identifier and passing time of the second target vehicle to prompt the staff of the first over-limit detection station to detect the second target vehicle; Wherein, the preset condition includes at least one of the following conditions: a first difference between the passing time and the weighing time is greater than a preset time threshold; a second difference between the second weight value and the first weight value is greater than a second preset weight threshold.

2. The method according to claim 1, characterized in that, after parsing the first vehicle information based on natural language processing (NLP) technology to obtain at least one first target vehicle among the at least one first vehicle, where the corresponding first weight value exceeds a first preset weight threshold, it further includes: Sending the vehicle identifier of the first target vehicle to a screen management system to display the vehicle identifier of the first target vehicle through a display screen corresponding to the screen management system.

3. The method according to any one of claims 1-2, characterized in that, the method further includes: Obtaining third vehicle information in a third system corresponding to a second over-limit detection station; wherein, the third vehicle information includes vehicle identifiers, passing times, and third weight values of at least one second vehicle traveling from the second over-limit detection station to the processing unit; Send the third vehicle information to the first system corresponding to the processing unit.

4. The method according to claim 3, wherein, after obtaining the third vehicle information in the third system corresponding to the second over-limit detection station, it further includes: Based on natural language processing NLP technology, parse the third vehicle information to obtain at least one third target vehicle among the second vehicles, whose corresponding passing time is within a preset time range; Display and / or broadcast the vehicle identification and the third weight value of the third target vehicle to prompt the staff of the processing unit to weigh the third target vehicle when the third target vehicle travels from the second over-limit detection station to the processing unit.

5. The method according to claim 4, wherein, the method further includes: Obtain the fourth weight value of the third target vehicle in the first system corresponding to the processing unit; Determine the third difference between the third weight value and the fourth weight value of the third target vehicle; Determine the third target vehicle whose corresponding third difference exceeds the third preset weight threshold as the fourth target vehicle; Display and / or broadcast the vehicle identification of the fourth target vehicle to prompt the staff of the processing unit to detect the fourth target vehicle.

6. An overloading detection device combining robotic process automation RPA and artificial intelligence AI, wherein, Applied to an RPA robot, the device includes: A first acquisition module, configured to acquire first vehicle information in the first system corresponding to the processing unit; the first vehicle information includes the vehicle identification and the first weight value of at least one first vehicle sent from the processing unit, the processing unit refers to a unit that can process raw materials into products, and the first system is the system used by the processing unit; A second acquisition module, configured to parse the first vehicle information based on natural language processing NLP technology to obtain a first target vehicle among the first vehicles whose corresponding first weight value exceeds the first preset weight threshold; A first sending module, configured to send the vehicle identification of the first target vehicle to the second system corresponding to the first over-limit detection station to prompt the staff of the first over-limit detection station to detect the first target vehicle when the first target vehicle travels from the processing unit to the first over-limit detection station; The first vehicle information further includes the weighing time of at least one of the first vehicles; the device further includes: A third acquisition module, configured to acquire second vehicle information in the second system corresponding to the first over-limit detection station; the second vehicle information includes the vehicle identification, passing time, and second weight value of at least one of the first vehicles, and the second weight value is detected by an over-limit detection system arranged on the road surface of the first over-limit detection station. A comparison module, configured to compare the weighing time corresponding to at least one of the first vehicles with the passing time, and compare the corresponding first weight value with the second weight value, so as to obtain at least one second target vehicle among the first vehicles that meets a preset condition, and determine the second target vehicle as a violation vehicle; A first prompting module, configured to display and / or broadcast the vehicle identification and passing time of the second target vehicle, so as to prompt the staff of the first over-limit detection station to detect the second target vehicle; Wherein, the preset condition includes at least one of the following conditions: a first difference between the passing time and the weighing time is greater than a preset time threshold; a second difference between the second weight value and the first weight value is greater than a second preset weight threshold.

7. The device according to claim 6, wherein, further comprising: A second sending module, configured to send the vehicle identification of the first target vehicle to the screen management system, so as to display the vehicle identification of the first target vehicle through a display screen corresponding to the screen management system.

8. The device according to any one of claims 6-7, wherein, the device further comprises: A fourth obtaining module, configured to obtain third vehicle information in a third system corresponding to a second over-limit detection station; wherein, the third vehicle information includes vehicle identifications, passing times, and third weight values of at least one second vehicle traveling from the second over-limit detection station to the processing unit; A third sending module, configured to send the third vehicle information to the first system corresponding to the processing unit.

9. The device according to claim 8, wherein, further comprising: An analysis module, configured to analyze the third vehicle information based on natural language processing (NLP) technology, so as to obtain at least one third target vehicle among the second vehicles whose corresponding passing time is within a preset time range; A second prompting module, configured to display and / or broadcast the vehicle identification and third weight value of the third target vehicle, so as to prompt the staff of the processing unit to weigh the third target vehicle when the third target vehicle travels from the second over-limit detection station to the processing unit.

10. The device according to claim 9, wherein, the device further comprises: A fifth obtaining module, configured to obtain a fourth weight value of the third target vehicle in the first system corresponding to the processing unit; A first determining module, configured to determine a third difference between the third weight value and the fourth weight value of the third target vehicle; A second determining module, configured to determine a third target vehicle whose corresponding third difference exceeds a third preset weight threshold as a fourth target vehicle; A third prompting module, configured to display and / or broadcast the vehicle identification of the fourth target vehicle, so as to prompt the staff of the processing unit to detect the fourth target vehicle.

11. An electronic device, wherein, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method described in any one of claims 1-5 is implemented.

12. A computer-readable storage medium, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the method described in any one of claims 1-5 is implemented.

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