A method, system, device and storage medium for measuring carbon emission content

Abstract

The present application discloses a method, system, device and storage medium for measuring carbon emission content, which relates to the field of information technology and is applied to a central controller at a construction site. The central controller is used for data processing. The method includes: obtaining a set of monitoring points and a set of monitoring time points, monitoring the carbon emission content of the ith monitoring point at the jth monitoring time point, using the ith monitoring point, the jth monitoring time point and the obtained carbon emission content monitoring value as sample data to train a carbon emission prediction model, monitoring the carbon emission content of the ith monitoring point at the j+1th time point, and predicting using the carbon emission prediction model, comparing the carbon emission content monitoring value of the ith monitoring point at the j+1th monitoring time point with the carbon emission content prediction value, and controlling the mobile monitoring vehicle to go to the next monitoring point if the difference is lower than a threshold. This method can reduce the number of carbon emission content monitoring devices.

Description

Technical Field

[0001] The present application relates to the field of information technology, and in particular to a method, system, device and storage medium for measuring carbon emission content. Background Art

[0002] Carbon emissions refer to the process by which gases such as carbon dioxide produced by human activities enter the atmosphere. As the severity of global climate change becomes increasingly prominent, measuring and monitoring carbon emissions has become an important issue.

[0003] At present, the carbon emissions of construction sites are measured by equipment monitoring. The existing equipment can only achieve fixed-point monitoring, that is, the monitoring equipment is fixed in one place for monitoring. In the actual monitoring process, due to the large monitoring demand, a large number of monitoring equipment are required. Summary of the invention

[0004] The present application provides a carbon emission content measurement method, system, device and storage medium, which can reduce the number of carbon emission content monitoring devices.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for measuring carbon emission content, which is applied to a central controller at a construction site, the central controller being used for data processing, and the method comprises:

[0007] Acquire a monitoring point set and a monitoring time point set, wherein the monitoring point set includes a plurality of monitoring points, and the monitoring time point set includes a plurality of monitoring time points;

[0008] Controlling the mobile monitoring vehicle to arrive at the i-th monitoring point in the set of monitoring points, and monitoring the m-th carbon emission content monitoring value at the j-th monitoring time point in the set of monitoring time points, wherein i, j and m are positive integers;

[0009] Using the i-th monitoring point, the j-th monitoring time point, and the m-th carbon emission content monitoring value, the t-1-th round carbon emission content prediction model of the i-th monitoring point is trained to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, where t is an integer greater than or equal to 2;

[0010] Controlling the mobile monitoring vehicle to monitor the i-th monitoring point at the j+1-th monitoring time point to obtain the m+1-th carbon emission content monitoring value;

[0011] Inputting the j+1th monitoring time point and the i-th monitoring point into the t-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction value of the i-th monitoring point;

[0012] Comparing the predicted value of the carbon emission content in the tth round of the i-th monitoring point with the m+1-th carbon emission content monitoring value;

[0013] If the difference between the predicted value of the t-th round carbon emission content at the i-th monitoring point and the m+1-th carbon emission content monitoring value is lower than a threshold, the mobile monitoring vehicle is controlled to go to the i+1-th monitoring point for monitoring.

[0014] In some possible implementations, the method further includes:

[0015] If the difference between the t-round carbon emission content prediction value of the i-th monitoring point and the m+1-th carbon emission content monitoring value is greater than or equal to a threshold, the t-round carbon emission content prediction model of the i-th monitoring point is trained using the j+1-th monitoring time point, the i-th monitoring point and the m+1-th carbon emission content monitoring value to obtain the t+1-round carbon emission content prediction model of the i-th monitoring point.

[0016] In some possible implementations, the method further includes:

[0017] Control the mobile monitoring vehicle to go to the i-th monitoring point, monitor at the j+k-th time point, and obtain the m+k-th carbon emission content monitoring value, where k is an integer greater than or equal to 2;

[0018] Comparing the predicted value of the carbon emission content in the t+kth round of the i-th monitoring point with the m+k-th carbon emission content monitoring value;

[0019] If the difference between the predicted value of the carbon emission content in the t+kth round at the i-th monitoring point and the monitored value of the carbon emission content in the m+kth round is lower than a threshold, the mobile monitoring vehicle is controlled to go to the i+1-th monitoring point.

[0020] In some possible implementations, obtaining a set of monitoring points and a set of monitoring time points includes:

[0021] Obtaining a construction plan for the construction site, the construction plan including construction areas and a construction schedule for each of the construction areas;

[0022] A monitoring point set and a monitoring time point set are obtained according to the construction plan.

[0023] In some possible implementations, the construction area includes a large equipment area, a material processing area, a construction site edge area, and a living area.

[0024] In some possible implementations, controlling the mobile monitoring vehicle to go to the (i+1)th monitoring point for monitoring includes:

[0025] Generate an optimal moving path according to the i-th monitoring point and the i+1-th monitoring point;

[0026] Control the mobile monitoring vehicle to reach the (i+1)th monitoring point according to the optimal moving path.

[0027] In some possible implementations, the mobile monitoring vehicle stores and charges through a storage device, a balancing structure is provided inside the vehicle body, at least three first wheels and at least three second wheels are arranged opposite to each other on both sides of the vehicle body, the at least three first wheels and the at least three first wheels are respectively arranged circumferentially around the axis of the vehicle body, the first wheel is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three first wheels can rotate around their own axes and revolve around the axis of the vehicle body; the second wheel is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three second wheels can rotate around their own axes and revolve around the axis of the vehicle body.

[0028] In a second aspect, the present application provides a carbon emission content measurement system, the system comprising:

[0029] An acquisition module, used to acquire a monitoring point set and a monitoring time point set, wherein the monitoring point set includes a plurality of monitoring points, and the monitoring time point set includes a plurality of monitoring time points;

[0030] A training module, used to control the mobile monitoring vehicle to arrive at the i-th monitoring point in the monitoring point set, monitor the m-th carbon emission content monitoring value at the j-th monitoring time point in the monitoring time point set, wherein i, j and m are positive integers; use the i-th monitoring point, the j-th monitoring time point and the m-th carbon emission content monitoring value to train the t-1-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, wherein t is an integer greater than or equal to 2; control the mobile monitoring vehicle to monitor the i-th monitoring point at the j+1-th monitoring time point to obtain the m+1-th carbon emission content monitoring value;

[0031] A prediction module, used for inputting the j+1th monitoring time point and the i-th monitoring point into the t-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction value of the i-th monitoring point;

[0032] A comparison module, used for comparing the t-th round carbon emission content prediction value of the ith monitoring point with the m+1-th carbon emission content monitoring value;

[0033] The control module is used to control the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring if the difference between the predicted value of the tth round of carbon emission content at the i-th monitoring point and the m+1th carbon emission content monitoring value is lower than a threshold value.

[0034] In some possible implementations, the control module is also used to train the t-round carbon emission content prediction model of the i-th monitoring point using the j+1-th monitoring time point, the i-th monitoring point and the m+1-th carbon emission content monitoring value if the difference between the t-round carbon emission content prediction value of the i-th monitoring point and the m+1-th carbon emission content monitoring value is greater than or equal to a threshold, so as to obtain the t+1-round carbon emission content prediction model of the i-th monitoring point.

[0035] In some possible implementations, the control module is also used to control the mobile monitoring vehicle to go to the i-th monitoring point, monitor at the j+k-th time point, and obtain the m+k-th carbon emission content monitoring value, where k is an integer greater than or equal to 2; compare the t+k-th round carbon emission content prediction value of the i-th monitoring point and the m+k-th carbon emission content monitoring value; if the difference between the t+k-th round carbon emission content prediction value of the i-th monitoring point and the m+k-th carbon emission content monitoring value is lower than a threshold, control the mobile monitoring vehicle to go to the i+1-th monitoring point.

[0036] In some possible implementations, the acquisition module is specifically used to acquire a construction plan of the construction site, wherein the construction plan includes construction areas and a construction schedule for each of the construction areas; and obtain a monitoring point set and a monitoring time point set according to the construction plan.

[0037] In some possible implementations, the construction area includes a large equipment area, a material processing area, a construction site edge area, and a living area.

[0038] In some possible implementations, the control module is specifically used to generate an optimal moving path according to the i-th monitoring point and the i+1-th monitoring point; and control the mobile monitoring vehicle to reach the i+1-th monitoring point according to the optimal moving path.

[0039] In some possible implementations, the mobile monitoring vehicle stores and charges through a storage device, a balancing structure is provided inside the vehicle body, at least three first wheels and at least three second wheels are arranged opposite to each other on both sides of the vehicle body, the at least three first wheels and the at least three first wheels are respectively arranged circumferentially around the axis of the vehicle body, the first wheel is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three first wheels can rotate around their own axes and revolve around the axis of the vehicle body; the second wheel is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three second wheels can rotate around their own axes and revolve around the axis of the vehicle body.

[0040] In a third aspect, the present application provides a computing device, including a memory and a processor;

[0041] One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the computing device executes the method as described in any one of the first aspects.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method as described in any one of the first aspects.

[0043] It can be seen from the above technical solution that the present application has at least the following beneficial effects:

[0044] In this application, the carbon emission content of the ith monitoring point is monitored at the jth monitoring time point, the ith monitoring point, the jth monitoring time point and the obtained carbon emission content monitoring value are used as sample data to train the carbon emission prediction model, the carbon emission content of the ith monitoring point is monitored at the j+1th time point, and the carbon emission prediction model is used to make predictions, and the carbon emission content monitoring value of the ith monitoring point at the j+1th monitoring time point is compared with the carbon emission content prediction value. If the difference is lower than the threshold, the mobile monitoring vehicle is controlled to go to the next monitoring point. It can be seen that this method can reduce the carbon emission content monitoring equipment at the construction site and use limited monitoring equipment to obtain the carbon emission content of more areas.

[0045] It should be understood that the description of technical features, technical solutions, beneficial effects or similar language in this application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it is understood that the description of features or beneficial effects means that specific technical features, technical solutions or beneficial effects are included in at least one embodiment. Therefore, the description of technical features, technical solutions or beneficial effects in this specification does not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions and beneficial effects described in the present embodiment can also be combined in any appropriate manner. Those skilled in the art will understand that the embodiment can be realized without one or more specific technical features, technical solutions or beneficial effects of a specific embodiment. In other embodiments, additional technical features and beneficial effects can also be identified in a specific embodiment that does not embody all embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flow chart of a method for measuring carbon emission content provided in an embodiment of the present application;

[0047] Figure 2 A structural schematic diagram of a mobile monitoring vehicle provided in an embodiment of the present application;

[0048] Figure 3 A front view of a mobile monitoring vehicle provided in an embodiment of the present application;

[0049] Figure 4 A top view of a mobile monitoring vehicle provided in an embodiment of the present application;

[0050] Figure 5 A schematic diagram of the internal structure of a mobile monitoring vehicle provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of a mobile monitoring vehicle climbing over an obstacle provided in an embodiment of the present application

[0052] Figure 7 A schematic diagram of the structure of a storage device provided in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of a carbon emission content measurement system provided in an embodiment of the present application;

[0054] Fig. 9 A schematic diagram of a computing device provided in an embodiment of the present application.

[0055] The text labels shown in the figure represent:

[0056] 201. Carbon-containing pollutant detection device; 202. Nitrogen, sulfur oxides and other pollutant detection device; 203. Double-sided hatch cover; 204. Visual camera; 205-1. First wheel; 205-2. Second wheel; 206. Wind force and direction parameter detection device; 207. Magnetic charger; 208. GPS module; 209. Microcomputer; 210. Motor transmission system; 211. Retractable cabin cover; 212. Obstacle; 701. Auxiliary positioning rail; 702. Opening and closing hatch; 703. Charging pile; 704. Parking point; 801. Acquisition module; 802. Training module; 803. Prediction module; 804. Comparison module; 805. Control module; 900. Computing device; 901. Bus; 902. Processor; 903. Communication interface; 904. Memory. DETAILED DESCRIPTION

[0057] The terms "first", "second", "third", etc. in the specification of this application and the accompanying drawings are used to distinguish different objects rather than to limit a specific order.

[0058] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0059] In order to make the description of the following embodiments clear and concise, a brief introduction to the related technology is first given:

[0060] Carbon emissions is a general term or abbreviation for greenhouse gas emissions. The most important component of greenhouse gases is carbon dioxide (CO2), so people simply understand "carbon emissions" as "carbon dioxide emissions". The increase in greenhouse gas content has a serious impact on climate change, and measuring and monitoring carbon emissions has become an important issue.

[0061] Carbon emission monitoring refers to the process of obtaining information on the status of carbon sources and sinks and their changing trends, such as greenhouse gas emission intensity, concentration in the environment, ecosystem carbon sinks, and impacts on ecosystems, through comprehensive observation, numerical simulation, statistical analysis and other means, so as to serve the research and management of climate change.

[0062] Currently, fixed-point monitoring is often used to monitor the carbon emission content at construction sites. Due to the large area of ​​the construction site, there are many areas that need to be monitored and the working conditions are complex, which leads to the need for a large number of monitoring equipment at the construction site.

[0063] In view of this, the present application provides a method for measuring carbon emission content, the method comprising:

[0064] Obtain a monitoring point set and a monitoring time point set, the monitoring point set includes multiple monitoring points, and the monitoring time point set includes multiple monitoring time points; control the mobile monitoring vehicle to arrive at the ith monitoring point in the monitoring set, and monitor the mth carbon emission content monitoring value at the jth monitoring time point in the monitoring time point, wherein i, j, and m are positive integers; use the ith monitoring point, the jth monitoring time point, and the mth carbon emission content monitoring value to train the t-1th round carbon emission content prediction model of the ith monitoring point, and obtain the tth round carbon emission content prediction model of the ith monitoring point, wherein t is an integer greater than or equal to 2; Control the mobile monitoring vehicle to monitor the ith monitoring point at the j+1th monitoring time point to obtain the m+1th carbon emission content monitoring value; input the j+1th monitoring time point and the ith monitoring point into the tth round carbon emission content prediction model of the ith monitoring point to obtain the tth round carbon emission content prediction value of the ith monitoring point; compare the tth round carbon emission content prediction value of the ith monitoring point with the m+1th carbon emission content monitoring value; if the difference between the tth round carbon emission content prediction value and the m+1th carbon emission content monitoring value of the ith monitoring point is lower than a threshold value, control the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring.

[0065] In this application, the carbon emission content of the ith monitoring point is monitored at the jth monitoring time point, the ith monitoring point, the jth monitoring time point and the obtained carbon emission content monitoring value are used as sample data to train the carbon emission prediction model, the carbon emission content of the ith monitoring point is monitored at the j+1th time point, and the carbon emission prediction model is used to make predictions, and the carbon emission content monitoring value of the ith monitoring point at the j+1th monitoring time point is compared with the carbon emission content prediction value. If the difference is lower than the threshold, the mobile monitoring vehicle is controlled to go to the next monitoring point. It can be seen that this method can reduce the carbon emission content monitoring equipment at the construction site and use limited monitoring equipment to obtain the carbon emission content of more areas.

[0066] In order to make the technical solution provided by the embodiment of the present application clearer and easier to understand, a method for measuring carbon emission content provided by the embodiment of the present application is introduced below in conjunction with the accompanying drawings. Figure 1 A flow chart of a method for measuring carbon emission content provided in an embodiment of the present application. The method comprises:

[0067] S101. Obtain a set of monitoring points and a set of monitoring time points.

[0068] The monitoring point set includes a plurality of monitoring points arranged in sequence, and the monitoring time point set includes a plurality of monitoring time points arranged in sequence.

[0069] The following specifically describes how to obtain multiple monitoring points and multiple monitoring time points.

[0070] In some embodiments, a construction plan for the construction site is first obtained. The construction site may be a manufacturing plant, a processing plant, etc., wherein the construction plan includes construction areas and the construction schedule for each construction area. Then, the locations and times that need to be monitored, i.e., monitoring points and monitoring time points, are determined according to the construction plan.

[0071] The value format of the monitoring time point can be MM-DD hh:mm, where "MM" represents the two-digit month, from 01 to 12, "DD" represents the two-digit date, from 01 to 31, "hh" represents the hour in the 24-hour system, from 00 to 23, and "mm" represents the minute, from 00 to 59; it can also be MM-DD hh:mm:ss, where "ss" represents the second, from 00 to 59. It should be noted that the monitoring time point includes at least the characteristics of month, date, and hours, which can better reflect the impact of the monitoring time point on the carbon emission content and make the carbon emission prediction model more accurate. For example, for some industrial equipment, it will only work and generate carbon emissions during a specific period of time on a specific date (for example, a few days of a month, or a working day). Therefore, the characteristics of month, date, hours, etc. are reflected in the detection time point, and the accuracy of the trained model can be further improved through more refined influencing factors.

[0072] The value of the monitoring time point can be a time point within a continuous period of time. For example, the monitoring time point set can be 00:00 to 23:00 every hour on 06-01, 00:00 to 23:00 every hour on 06-02, 00:00 to 23:00 every hour on 06-03... 00:00 to 23:00 every hour on 06-06, and 00:00 to 23:00 every hour on 06-07. It can also be a time point within a discontinuous period of time. The time format and time frequency selection of the specific monitoring time point can be adjusted according to the actual situation, and this application does not limit it.

[0073] In some embodiments, the construction site is divided into regions according to function, and the construction area includes a large equipment area, a material processing area, a construction site edge area, and a living area, wherein the large equipment area, the material processing area, and the living area are areas with higher carbon emission content, and the construction site edge area is an area with lower carbon emission content. The areas with higher and lower carbon emission content are selected to form a contrast, which is conducive to the prediction of subsequent carbon emission content. In actual operation, different construction site conditions can be used to divide the construction site into regions as needed with reference to the level of carbon emission content. One or more monitoring points are selected in each area to form a set of monitoring points. The embodiment of the present application takes the selection of one monitoring point in each area as an example. For example, a large equipment area is set with a monitoring point, a material processing area is set with a monitoring point, a construction site edge area is set with a monitoring point, and a living area is set with a monitoring point, and the four monitoring points are arranged in sequence.

[0074] S102. Control the mobile monitoring vehicle to arrive at the i-th monitoring point in the monitoring point set, and monitor the m-th carbon emission content monitoring value at the j-th monitoring time point in the monitoring time point set, where i, j and m are positive integers.

[0075] In some embodiments, the mobile monitoring vehicle stores and charges through a storage device. The mobile monitoring vehicle is first introduced below. The mobile monitoring vehicle is a mobile device for monitoring carbon emission content. The embodiment of the present application provides a mobile monitoring vehicle. In order to make the technical solution of the present application clearer and easier to understand, the following is combined with Figures 2 to 5 The mobile monitoring vehicle provided by this application is introduced, such as Figure 2 A schematic diagram of the structure of a mobile monitoring vehicle provided in an embodiment of the present application is shown in FIG. Figure 3 A front view of a mobile monitoring vehicle provided in an embodiment of the present application, Figure 4 A top view of a mobile monitoring vehicle provided in an embodiment of the present application, Figure 5 A schematic diagram of the internal structure of a mobile monitoring vehicle provided in an embodiment of the present application.

[0076] like Figures 2 to 5As shown, the mobile monitoring vehicle includes a vehicle body, a balancing structure is provided inside the vehicle body, at least three first wheels 205-1 and at least three second wheels 205-2 are arranged opposite to each other on both sides of the vehicle body, the at least three first wheels 205-1 and the at least three first wheels 205-1 are arranged circumferentially around the axis of the vehicle body, respectively, the first wheel 205-1 is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relatively around the axis of the vehicle body, so that the at least three first wheels 205-1 can rotate around their own axes and revolve around the axis of the vehicle body; the second wheel 205-2 is connected to the vehicle body through a first bracket, the first bracket and the vehicle body can rotate relatively around the axis of the vehicle body, so that the at least three second wheels 205-2 can rotate around their own axes and revolve around the axis of the vehicle body;

[0077] At least two of the first wheels 205-1 and two of the second wheels 205-2 form a running wheel, and the running wheel includes two front wheels and two rear wheels. The running wheels drive the vehicle body to move. When the front wheel of the running wheel encounters an obstacle 212 such as a stone, a step, etc., the front wheel cannot rotate relative to the axis of the wheel. Since the four wheels rotate relative to the axis of the vehicle body, the third first wheel 205-1 and the second wheel 205-2 roll down and serve as the front wheels of the running wheels. The original front wheels become rear wheels. At this time, the rear wheels are still blocked by obstacles and cannot rotate. The fourth first wheel 205-1 and the second wheel 205-2 rotate down and become front wheels. In this way, the four first wheels 205-1 and the second wheels 205-2 alternately form running wheels, so that the vehicle body can climb over obstacles. Since there is a balancing structure in the vehicle body, such as a gyroscope, the vehicle body always maintains an upward posture during the entire process of climbing over obstacles to prevent the gas detection device from tipping over. The embodiment of the present application is introduced by taking the first wheel climbing over an obstacle as an example. Figure 6 As shown, Figure 6 A schematic diagram of a mobile monitoring vehicle climbing over an obstacle provided in an embodiment of the present application, wherein the four first wheels 205-1 are arranged in a square around the axis of the vehicle body. When the mobile monitoring vehicle encounters an obstacle 212, the mobile monitoring vehicle climbs over the obstacle by relying on two running wheels. Even if the mobile monitoring vehicle falls over, the other two wheels can still be relied on to keep moving, while the vehicle body is facing upwards.

[0078] The vehicle body also includes a gas detection device disposed inside the vehicle body. The gas detected in the embodiment of the present application includes carbon-containing pollutants and sulfide pollutants. In actual operation, the gas detected can be selected as needed. The gas detection device includes a carbon-containing pollutant detection device 201 and a nitrogen, sulfur oxide and other pollutant detection device 202. The carbon-containing pollutant detection device 201 is used to detect the content of the gas required for carbon emission monitoring, and the nitrogen, sulfur oxide and other pollutant detection device 202 is used to detect the content of nitrogen, sulfur oxide and other pollutants.

[0079] The vehicle body also includes a plurality of wind force and direction parameter detection devices 206 disposed at both ends of the vehicle body, such as Figure 4 As shown, the typhoon force and direction parameter detection device 206 is used to detect wind force and direction parameters;

[0080] A visual camera 204 and a magnetic charger 207 are respectively disposed at the front or rear end of the vehicle body. The visual camera 204 is used to provide the microcomputer with the real-time road conditions of the mobile monitoring vehicle. The magnetic charger 207 has a magnetic effect and is used to charge the mobile monitoring vehicle.

[0081] The vehicle body also includes a double-sided hatch cover 203, such as Figure 3 As shown, the left double-sided hatch cover 203 is in a closed state, and the right double-sided hatch cover 203 is in an open state. When the double-sided hatch cover 203 is in a closed state, the wind force and direction parameter detection device 206 is in a standby state. When the double-sided hatch cover 203 is in an open state, the wind force and direction parameter detection device 206 detects the wind force and direction. The vehicle body also includes a retractable cabin cover 211 on the top, and the retractable cabin cover 211 is used to protect the internal gas detection device.

[0082] The vehicle body also includes a GPS module 208, a microcomputer 209 and a motor transmission system 210. The GPS module 208 is used to provide the location information of the monitoring point where the mobile monitoring vehicle is located; the microcomputer 209 has an automatic driving function and a data processing and transmission function. For example, when the wind force detected by the wind force and wind direction parameter detection device 206 exceeds the preset threshold, the microcomputer 209 generates a prompt message to prompt the user that the wind force is large and the monitoring data is inaccurate at this time; the motor transmission system 210 is used to provide power for the mobile monitoring vehicle. When the mobile monitoring vehicle turns, the electric transmission system provides differential power to the left and right wheels to achieve device steering. Specifically, the automatic driving function includes completing the obstacle avoidance function through the location information provided by the GPS module 208, the real-time road conditions provided by the visual camera 204, and the optimal moving path provided by the central controller; the data processing and transmission function includes the microcomputer 209 screening, calculating and integrating the gas data obtained by the gas detection device, and uploading it to the central controller by radio.

[0083] After the mobile monitoring vehicle arrives at the designated monitoring point, the double-sided hatch 203 is opened for detection, and multiple data are collected for adjustment. The microcomputer 209 transmits the measured data to the computer for data processing and uploads it to the central controller.

[0084] The following describes the storage device in conjunction with the accompanying drawings. Figure 7 A structural schematic diagram of a storage device provided in an embodiment of the present application, as shown in the figure, the storage device includes a device body and a plurality of parking points 704 arranged inside the device body, the parking points 704 are points in the storage device for parking a mobile monitoring vehicle, and a plurality of auxiliary positioning rails 701 are provided at the lower end of the parking points 704, the auxiliary positioning rails 701 include a first rail and a second rail arranged adjacent to each other, the distance between the first rail and the second rail is adapted to the distance between the first wheel and the second wheel of the mobile monitoring vehicle, and the auxiliary positioning rails 701 are used for auxiliary positioning when the mobile monitoring vehicle enters the storage device; the interior of the device body also includes a charging pile 703, the charging pile 703 includes a charging head with a magnetic suction effect, which is used to charge the mobile monitoring vehicle; the device body also includes an opening and closing hatch 702 arranged on the top of the device body, and the opening and closing hatch 702 can be extended and opened and closed along an arc direction.

[0085] When it is necessary to detect the carbon emission content, the central controller issues a command to the mobile monitoring vehicle, the opening and closing hatch 702 opens automatically, the mobile monitoring vehicle leaves the parking point 704 in the storage device, and arrives at the monitoring point for detection according to the specified optimal moving path; when the mobile monitoring vehicle completes the gas detection task, it returns to the storage device according to the specified optimal moving path, the opening and closing hatch 702 opens automatically, and the mobile monitoring vehicle drives into the storage device cabin with the assistance of the auxiliary positioning guide rail 701, and approaches the magnetic charging head of the charging pile 703. Under the action of magnetic force, the magnetic charging head contacts the battery contacts on the magnetic charger 207 of the mobile monitoring vehicle to start charging the mobile monitoring vehicle. The storage device cabin setting of the mobile monitoring vehicle is convenient for unified transportation of multiple mobile monitoring vehicles. For example, when the construction site does not need to use mobile monitoring vehicles for carbon emission content monitoring due to changes in the construction plan or the use of a carbon emission content prediction model to obtain carbon emission content, multiple mobile monitoring vehicles can be allowed to enter the storage device and be uniformly transported to other sites where carbon emission content monitoring is required.

[0086] The central controller controls the mobile monitoring vehicle to arrive at the i-th monitoring point among the multiple monitoring points, and monitors the m-th carbon emission content monitoring value at the j-th monitoring time point among the multiple monitoring time points. For the convenience of understanding, the carbon emission content monitoring value can be recorded as C i,j,m , where i, j and m are positive integers.

[0087] For example, i is 1, the mobile monitoring vehicle arrives at the first monitoring point, such as the monitoring point in the large equipment area; j is 1, the mobile monitoring vehicle starts monitoring at the first time point, such as 06-01 8:00; m is 1, that is, the mobile monitoring vehicle arrives at the monitoring point in the large equipment area, starts monitoring at 06-01 8:00, and obtains the first carbon emission content monitoring value of 20.

[0088] S103. Using the i-th monitoring point, the j-th monitoring time point and the m-th carbon emission content monitoring value, train the t-1-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, where t is an integer greater than or equal to 2.

[0089] The carbon emission prediction model refers to a neural network model used to predict carbon emission content. In this application, each monitoring point is set with a neural network model to predict the carbon emission content of the monitoring point, thereby reducing the use of monitoring equipment. The neural network model of each monitoring point can be the same or different neural network models can be selected. This application does not limit the neural network model. Taking a neural network model provided in this application as an example, the input layer of the neural network model x 1 ，x 2, among which, x 1 is the monitoring point ，x 2 is the monitoring time, and in actual operation, it can also include the wind speed and direction of the monitoring point. The neuron nodes of the input layer can be adjusted according to the factors that actually affect the carbon emission content; the hidden layer uses the following formula:

[0090]

[0091] Each neuron has its own weight and bias ,in, Refers to the l The hth neuron in the layer and the l-1 The weights between neurons in the gth layer, Refers to the l The bias term of the hth neuron in the layer, Input data to the model, is the error term, p is the total number of neurons, and y is the model output data; the output layer can be an identity function, that is, directly output the weighted sum result. This ensures that the carbon emission prediction model directly outputs the predicted value of carbon emission content without the need for additional nonlinear transformation.

[0092] In order to measure the difference between the carbon emission content prediction value and the carbon emission content monitoring value of the neural network model, so as to optimize the prediction ability of the neural network model, the embodiment of the present application adopts the following loss function:

[0093]

[0094] in, is the loss value, is the predicted value of carbon emission content, is the carbon emission content monitoring value, N is the number of sample data.

[0095] For example, taking the first monitoring point in the large equipment area as an example, the first time point is 06-01 8:00, and the carbon emission content monitoring value is 20. The above data is used as sample data, where (1, 06-01 8:00) is used as the model input data and 20 is used as the model output data. The carbon emission prediction model is trained to obtain the next round of neural network training model after training.

[0096] S104. Control the mobile monitoring vehicle to monitor the ith monitoring point at the j+1th monitoring time point to obtain the m+1th carbon emission content monitoring value.

[0097] The j+1th monitoring time point is the next monitoring time point. The mobile monitoring vehicle is still at the ith monitoring point without changing its position, and continues to monitor to obtain the carbon emission content monitoring value at the next monitoring time point.

[0098] For example, still taking the first monitoring point in the large equipment area as an example, the mobile monitoring vehicle is controlled to monitor at 9:00 to obtain the second carbon emission content monitoring value of 21.

[0099] S105. Input the j+1th monitoring time point and the ith monitoring point into the tth round carbon emission content prediction model of the ith monitoring point to obtain the tth round carbon emission content prediction value of the ith monitoring point.

[0100] The j+1th monitoring time point and the i-th monitoring point are input into the t-th round carbon emission content prediction model obtained by training in S103 to obtain the m+1th carbon emission content monitoring value.

[0101] S106. Compare the predicted value of the carbon emission content in the tth round of the ith monitoring point with the monitored value of the carbon emission content in the m+1th round.

[0102] The m+1th carbon emission content monitoring value is the carbon emission content monitoring value at the ith monitoring point and the j+1th monitoring time point; the tth round carbon emission content prediction value at the ith monitoring point is the carbon emission content prediction value at the ith monitoring point and the j+1th monitoring time point; the above two values ​​are compared.

[0103] S107: If the difference between the predicted value of the carbon emission content in the tth round at the i-th monitoring point and the monitored value of the carbon emission content in the m+1th round is lower than a threshold, control the mobile monitoring vehicle to go to the i+1-th monitoring point for monitoring.

[0104] The threshold refers to the value set by the system, and the size of the threshold can be selected as needed. If the difference between the predicted value of carbon emission content and the monitored value of carbon emission content is small, it means that the carbon emission prediction model has been trained and the predicted value of the carbon emission prediction model can be used as the carbon emission content of the monitoring point. There is no need to use a mobile monitoring vehicle for monitoring. The mobile monitoring vehicle can be controlled to go to the next monitoring point, which can reduce the number of mobile monitoring vehicles.

[0105] For example, the threshold value is set to 1, the monitoring point is the large equipment area, the monitoring time point is the 501st monitoring time point, and the 500th round of carbon emission prediction model is obtained after 500 trainings. The carbon emission content predicted value predicted by the 500th round of carbon emission content prediction model is a, and the actual monitoring value at the 501st monitoring time point is b. The difference between a and b is less than 1. Therefore, the 500th round of carbon emission content prediction model is used to obtain the carbon emission content in the large equipment area, without the need for actual monitoring by a mobile monitoring vehicle.

[0106] In some embodiments, an optimal moving path is generated according to the i-th monitoring point and the i+1-th monitoring point; and the mobile monitoring vehicle is controlled to reach the i+1-th monitoring point according to the optimal moving path.

[0107] The optimal moving path refers to the optimal moving path of the mobile monitoring vehicle between two monitoring points. This application provides a method for calculating the optimal moving path using a genetic algorithm, which can be selected as needed in actual operation. The optimal moving path algorithm is introduced below:

[0108] Step 1: Abstract the construction site into a grid-like graph structure, where nodes represent locations and edges represent the paths of the mobile monitoring vehicle from one location to another. Define the starting and target locations of the mobile monitoring vehicle and all monitoring points.

[0109] Step 2, represent each possible movement path according to the sequence coding method;

[0110] Step 3, setting a fitness function to evaluate the quality of each candidate path. The fitness function can be the inverse or opposite of the total travel distance of the path. The lower the distance, the higher the fitness;

[0111] Step 4, iteratively perform selection, crossover, and mutation operations, and continuously update the population until the preset termination conditions are met, such as reaching the maximum number of iterations or finding a sufficiently satisfactory optimal moving path;

[0112] Step 5: The individual with the highest fitness, i.e., the optimal moving path encoding, needs to be decoded back to the actual driving path of the mobile monitoring vehicle and used as the final monitoring path.

[0113] After obtaining the optimal moving path of the two monitoring points using the above algorithm, the car is controlled to move to the next monitoring point along the optimal moving path.

[0114] In some embodiments, if the difference between the t-round carbon emission content prediction value and the m+1-th carbon emission content monitoring value at the i-th monitoring point is greater than or equal to a threshold, that is, if the t-round carbon emission content prediction value and the m+1-th carbon emission content monitoring value at the i-th monitoring point differ greatly, the t-round carbon emission content prediction model of the i-th monitoring point is trained using the j+1-th monitoring time point, the i-th monitoring point and the m+1-th carbon emission content monitoring value to obtain the t+1-round carbon emission content prediction model of the i-th monitoring point, so that the predicted value of the carbon emission content prediction model is more accurate.

[0115] At j+1 monitoring time points, the carbon emission content of the monitoring point is monitored and predicted at the same time, and the monitoring value and the predicted value at the same time and place are compared. If there is a large difference, the time, place and monitoring value are used as sample data to continue training the carbon emission prediction model. If there is a small difference, the carbon emission prediction model is considered to be mature in training, and the predicted value of the carbon emission prediction model is used as the carbon emission content of the monitoring point to control the mobile monitoring vehicle to go to the next monitoring point. This can reduce the number of monitoring equipment.

[0116] Taking the four monitoring points set in this application as an example, at least two mobile monitoring vehicles are required for actual monitoring in this application. One is placed at the edge of the construction site, and the other one monitors the other three monitoring points in turn. After the carbon emission prediction model is trained to maturity, the mobile monitoring vehicle no longer needs to monitor. At this time, the required number of monitoring equipment is zero, and multiple mobile monitoring vehicles can be placed in a storage device, waiting for the next monitoring task.

[0117] In some embodiments, the mobile monitoring vehicle is controlled to go to the i-th monitoring point, monitor at the j+k-th time point, and obtain the m+k-th carbon emission content monitoring value, where k is an integer greater than or equal to 2; the t+k-th round carbon emission content prediction value and the m+k-th carbon emission content monitoring value of the i-th monitoring point are compared; if the difference between the t+k-th round carbon emission content prediction value and the m+k-th carbon emission content monitoring value of the i-th monitoring point is lower than a threshold value, the mobile monitoring vehicle is controlled to go to the i+1-th monitoring point.

[0118] After the carbon emission prediction model of the monitoring point is trained to maturity, the mobile monitoring vehicle is controlled to return to the monitoring point for monitoring at intervals of j+k time points. The interval can be set according to actual needs, for example, every one month, in order to prevent the predicted value of the carbon emission prediction model from becoming inaccurate. When the monitoring vehicle is controlled to return to the monitoring point for monitoring, the specific number of monitoring times can also be set according to actual needs, in order to collect as much data as possible to confirm that the prediction of the carbon emission prediction model is accurate. If the predicted value of the carbon emission content is close to the actual monitored value after multiple monitorings, the mobile monitoring vehicle is controlled to go to other monitoring points;

[0119] In some embodiments, if the difference between the predicted value of the carbon emission content in the t+kth round and the monitored value of the carbon emission content in the m+kth round at the ith monitoring point is higher than a threshold, the prediction model of the carbon emission content in the t+k-1th round at the ith monitoring point is trained using the ith monitoring point, the t+kth monitoring time point, and the monitored value of the carbon emission content in the m+kth round to obtain the prediction model of the carbon emission content in the t+kth round at the ith monitoring point, where t is an integer greater than or equal to 2; the mobile monitoring vehicle is controlled to monitor the ith monitoring point at the j+k+1th monitoring time point to obtain To the m+k+1th carbon emission content monitoring value; input the j+k+1th monitoring time point and the ith monitoring point into the t+kth round carbon emission content prediction model of the ith monitoring point to obtain the t+kth round carbon emission content prediction value of the ith monitoring point; compare the t+kth round carbon emission content prediction value of the ith monitoring point with the m+k+1th carbon emission content monitoring value; if the difference between the t+kth round carbon emission content prediction value and the m+k+1th carbon emission content monitoring value of the ith monitoring point is lower than the threshold, control the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring.

[0120] If after multiple monitorings, the predicted value of the carbon emission prediction model differs greatly from the monitored value of the mobile monitoring vehicle, the mobile monitoring vehicle is used to obtain more sample data, and the carbon emission prediction model is corrected to improve the accuracy of the carbon emission content prediction model, until the carbon emission prediction value of the carbon emission prediction model is close to the actual monitored value, and then the mobile monitoring vehicle is controlled to go to other monitoring points.

[0121] In some embodiments, a spatial model based on the Manufacturing Execution System (MES) is constructed to display the data collected in real time by mobile monitoring vehicles in a visual way such as maps, charts, and dashboards. At the same time, decision support tools are provided to build an open carbon emission data platform to promote data sharing and collaboration among different fields.

[0122] Combination of the above Figures 1 to 7A method for measuring carbon emission content provided in an embodiment of the present application is introduced in detail. The following will introduce the device and equipment provided in the embodiment of the present application in conjunction with the accompanying drawings.

[0123] like Figure 8 As shown, this figure is a schematic diagram of a carbon emission content measurement system provided in an embodiment of the present application, and the system includes:

[0124] An acquisition module 801 is used to acquire a monitoring point set and a monitoring time point set, wherein the monitoring point set includes a plurality of monitoring points, and the monitoring time point set includes a plurality of monitoring time points;

[0125] The training module 802 is used to control the mobile monitoring vehicle to arrive at the i-th monitoring point in the monitoring point set, and monitor the m-th carbon emission content monitoring value at the j-th monitoring time point in the monitoring time point set, wherein i, j and m are positive integers; using the i-th monitoring point, the j-th monitoring time point and the m-th carbon emission content monitoring value, the t-1-th round carbon emission content prediction model of the i-th monitoring point is trained to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, wherein t is an integer greater than or equal to 2; the mobile monitoring vehicle is controlled to monitor the i-th monitoring point at the j+1-th monitoring time point to obtain the m+1-th carbon emission content monitoring value;

[0126] The prediction module 803 is used to input the j+1th monitoring time point and the i-th monitoring point into the t-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction value of the i-th monitoring point;

[0127] A comparison module 804 is used to compare the t-th round carbon emission content prediction value of the ith monitoring point with the m+1-th carbon emission content monitoring value;

[0128] The control module 805 is used to control the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring if the difference between the predicted value of the tth round carbon emission content at the i-th monitoring point and the m+1th carbon emission content monitoring value is lower than a threshold.

[0129] In some embodiments, the control module 805 is also used to train the t-round carbon emission content prediction model of the i-th monitoring point using the j+1-th monitoring time point, the i-th monitoring point and the m+1-th carbon emission content monitoring value if the difference between the t-round carbon emission content prediction value of the i-th monitoring point and the m+1-th carbon emission content monitoring value is greater than or equal to a threshold, so as to obtain the t+1-round carbon emission content prediction model of the i-th monitoring point.

[0130] In some embodiments, the control module 805 is also used to control the mobile monitoring vehicle to go to the i-th monitoring point, monitor at the j+k-th time point, and obtain the m+k-th carbon emission content monitoring value, where k is an integer greater than or equal to 2; compare the t+k-th round carbon emission content prediction value of the i-th monitoring point and the m+k-th carbon emission content monitoring value; if the difference between the t+k-th round carbon emission content prediction value of the i-th monitoring point and the m+k-th carbon emission content monitoring value is lower than a threshold, control the mobile monitoring vehicle to go to the i+1-th monitoring point.

[0131] In some embodiments, the acquisition module 801 is specifically used to acquire a construction plan of a construction site, wherein the construction plan includes construction areas and a construction schedule for each construction area; and obtain a set of monitoring points and a set of monitoring time points according to the construction plan.

[0132] In some embodiments, the construction area includes a large equipment area, a material processing area, a construction site edge area, and a living area.

[0133] In some embodiments, the control module 805 is specifically used to generate an optimal moving path according to the i-th monitoring point and the i+1-th monitoring point; and control the mobile monitoring vehicle to reach the i+1-th monitoring point according to the optimal moving path.

[0134] In some embodiments, a balancing structure is provided inside the vehicle body, and at least three first wheels 205-1 and at least three second wheels 205-2 are arranged on both sides of the vehicle body opposite to each other. The at least three first wheels 205-1 and the at least three first wheels 205-1 are respectively arranged circumferentially around the axis of the vehicle body, and the first wheel 205-1 is connected to the vehicle body through a first bracket, and the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three first wheels 205-1 can rotate around their own axes and revolve around the axis of the vehicle body at the same time; the second wheel 205-2 is connected to the vehicle body through a first bracket, and the first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three second wheels 205-2 can rotate around their own axes and revolve around the axis of the vehicle body at the same time.

[0135] The carbon emission content measurement system according to the embodiment of the present application may correspond to the method described in the embodiment of the present application, and the above-mentioned other operations and / or functions of each module / unit of the carbon emission content measurement system are respectively to achieve Figure 1 For the sake of brevity, the corresponding process of the method in the illustrated embodiment will not be repeated here.

[0136] The present application also provides a computing device, Fig. 9 A schematic diagram of a computing device provided in an embodiment of the present application, such as Fig. 9 As shown, computing device 900 includes bus 901, processor 902, communication interface 903 and memory 904. Processor 902, memory 904 and communication interface 903 communicate with each other via bus 901.

[0137] The bus 901 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 9 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0138] The processor 902 may be any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0139] The communication interface 903 is used for external communication. For example, the communication interface 903 can be used to communicate with the microcomputer of the mobile monitoring vehicle, and send information such as movement instructions and optimal movement path to the microcomputer of the mobile monitoring vehicle.

[0140] The memory 904 may include a volatile memory, such as a random access memory (RAM). The memory 904 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0141] The memory 904 stores executable codes, and the processor 902 executes the executable codes to perform the aforementioned carbon emission content measurement method.

[0142] Specifically, in implementing Figure 8 In the case of the embodiment shown, and Figure 8When each module or unit of the carbon emission content measurement system described in the embodiment is implemented by software, the execution Figure 8 The software or program code required for the functions of each module / unit in the memory 904 may be partially or completely stored in the memory 904. The processor 902 executes the program code corresponding to each unit stored in the memory 904 to perform the aforementioned carbon emission content measurement method.

[0143] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by a computing device or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute the above-mentioned carbon emission content measurement method applied to the carbon emission content measurement system.

[0144] The embodiment of the present application further provides a computer program product, which includes one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the process or function described in the embodiment of the present application is generated in whole or in part.

[0145] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer or data center to another website, computer or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0146] When the computer program product is executed by a computer, the computer executes any of the aforementioned methods for measuring carbon emission content. The computer program product may be a software installation package, and when any of the aforementioned methods for measuring carbon emission content is required, the computer program product may be downloaded and executed on a computer.

[0147] The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0148] The above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application.

Claims

1. A carbon emission content measurement system, characterized in that: The system comprises: An acquisition module, used to acquire a monitoring point set and a monitoring time point set, wherein the monitoring point set includes a plurality of monitoring points, and the monitoring time point set includes a plurality of monitoring time points; A training module, used to control the mobile monitoring vehicle to arrive at the i-th monitoring point in the monitoring point set, monitor the m-th carbon emission content monitoring value at the j-th monitoring time point in the monitoring time point set, wherein i, j and m are positive integers; use the i-th monitoring point, the j-th monitoring time point and the m-th carbon emission content monitoring value to train the t-1-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, wherein t is an integer greater than or equal to 2; control the mobile monitoring vehicle to monitor the i-th monitoring point at the j+1-th monitoring time point to obtain the m+1-th carbon emission content monitoring value; A prediction module, used for inputting the j+1th monitoring time point and the i-th monitoring point into the t-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction value of the i-th monitoring point; A comparison module, used for comparing the t-th round carbon emission content prediction value of the ith monitoring point with the m+1-th carbon emission content monitoring value; A control module, for controlling the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring if the difference between the predicted value of the t-th round carbon emission content of the i-th monitoring point and the m+1th carbon emission content monitoring value is lower than a threshold value; and for training the t-th round carbon emission content prediction model of the i-th monitoring point using the j+1th monitoring time point, the i-th monitoring point and the m+1th carbon emission content monitoring value to obtain the t+1th round carbon emission content prediction model of the i-th monitoring point if the difference between the predicted value of the t-th round carbon emission content of the i-th monitoring point and the m+1th carbon emission content monitoring value is greater than or equal to a threshold value. Among them, the mobile monitoring vehicle includes a body body, and a balancing structure is arranged inside the body body. During the entire process of climbing over obstacles, the body body can always maintain an upward posture to prevent the gas detection device from tipping over. The body body also includes a gas detection device arranged inside the body body, and several wind force and direction parameter detection devices arranged at both ends of the body body. A visual camera and a magnetic charger are respectively arranged at the front end or the rear end of the body body. The body body also includes a double-sided cabin cover and a retractable cabin cover on the top. The body body also includes a GPS module, a microcomputer and a motor transmission system.

2. The system according to claim 1, characterized in that The mobile monitoring vehicle stores and charges via a storage device. At least three first wheels (205-1) and at least three second wheels (205-2) are arranged on opposite sides of the vehicle body. The at least three first wheels (205-1) and the at least three first wheels (205-1) are arranged circumferentially around the axis of the vehicle body, respectively. The first wheel (205-1) is connected to the vehicle body via a first bracket. The first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three first wheels (205-1) can rotate around their own axes and can also revolve around the axis of the vehicle body; the second wheel (205-2) is connected to the vehicle body via a first bracket. The first bracket and the vehicle body can rotate relative to each other around the axis of the vehicle body, so that the at least three second wheels (205-2) can rotate around their own axes and can also revolve around the axis of the vehicle body.

3. A method for measuring carbon emission content using the carbon emission content measurement system according to claim 1 or 2, characterized in that: A central controller applied to a construction site, the central controller is used for data processing, and the method comprises: Acquire a monitoring point set and a monitoring time point set, wherein the monitoring point set includes a plurality of monitoring points, and the monitoring time point set includes a plurality of monitoring time points; Controlling the mobile monitoring vehicle to arrive at the i-th monitoring point in the set of monitoring points, and monitoring the m-th carbon emission content monitoring value at the j-th monitoring time point in the set of monitoring time points, wherein i, j and m are positive integers; Using the i-th monitoring point, the j-th monitoring time point, and the m-th carbon emission content monitoring value, the t-1-th round carbon emission content prediction model of the i-th monitoring point is trained to obtain the t-th round carbon emission content prediction model of the i-th monitoring point, where t is an integer greater than or equal to 2; Controlling the mobile monitoring vehicle to monitor the i-th monitoring point at the j+1-th monitoring time point to obtain the m+1-th carbon emission content monitoring value; Inputting the j+1th monitoring time point and the i-th monitoring point into the t-th round carbon emission content prediction model of the i-th monitoring point to obtain the t-th round carbon emission content prediction value of the i-th monitoring point; Comparing the predicted value of the carbon emission content in the tth round of the i-th monitoring point with the m+1-th carbon emission content monitoring value; If the difference between the predicted value of the t-round carbon emission content at the i-th monitoring point and the m+1-th carbon emission content monitoring value is lower than a threshold, control the mobile monitoring vehicle to go to the i+1-th monitoring point for monitoring; if the difference between the predicted value of the t-round carbon emission content at the i-th monitoring point and the m+1-th carbon emission content monitoring value is greater than or equal to a threshold, use the j+1-th monitoring time point, the i-th monitoring point and the m+1-th carbon emission content monitoring value to train the t-round carbon emission content prediction model for the i-th monitoring point to obtain the t+1-round carbon emission content prediction model for the i-th monitoring point.

4. The method according to claim 3, characterized in that The obtaining of the monitoring point set and the monitoring time point set comprises: Obtaining a construction plan for the construction site, the construction plan including construction areas and a construction schedule for each of the construction areas; A monitoring point set and a monitoring time point set are obtained according to the construction plan.

5. The method according to claim 4, characterized in that The construction area includes the large equipment area, material processing area, construction site edge area and living area.

6. The method according to claim 3, characterized in that The controlling the mobile monitoring vehicle to go to the i+1th monitoring point for monitoring comprises: Generate an optimal moving path according to the i-th monitoring point and the i+1-th monitoring point; Control the mobile monitoring vehicle to reach the (i+1)th monitoring point according to the optimal moving path.

7. A computing device, characterized in that including memory and processor; One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the computing device executes the method as claimed in any one of claims 3 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method according to any one of claims 3 to 6.

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