Residue soil handling capacity monitoring method based on trajectory data of residue soil truck

Abstract

The invention discloses a muck handling capacity monitoring method based on trajectory data of muck trucks, which comprises the following steps: matching the trajectory data of each muck truck with point location information of a management point location to obtain a detail table of vehicle access point locations, adding an auxiliary counting column used for marking the point position change condition of the muck vehicle in and out of the vehicle point position detail table to obtain a first auxiliary table; the first auxiliary table is divided into a vehicle entering point location detail table and a vehicle leaving point location detail table corresponding to each muck vehicle, and the vehicle entering point location detail table and the vehicle leaving point location detail table are spliced into a vehicle operation detail table; the in-out frequency of each muck vehicle at the management point location is counted according to the vehicle operation detail table, the muck amount transported by the muck vehicles at the management point location is calculated so as to monitor the working condition of the current management point location, only the track data of the muck vehicles are analyzed, and the transportation condition of the muck vehicles among the management point locations is quickly mastered, so that the management point location is more accurate. And supervision on each management point location is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of slag operation monitoring, and in particular to a slag processing amount monitoring method based on trajectory data of a slag truck. Background Art

[0002] Driven by the dual forces of social economy and rapid expansion of urban space, the output of construction waste has exploded, and the accompanying problems of random stacking and dumping of construction waste are becoming increasingly serious. Although special garbage disposal sites are playing a core role, due to limited processing scale, technical limitations, and the lack of monitoring and early warning mechanisms, excessive discharge of slag and frequent overload operations at disposal sites have led to environmental pollution, safety hazards, and even illegal operations. As a key carrier for the transportation of construction waste, the driving trajectory of slag trucks contains rich information, which not only affects transportation efficiency and route planning, but also directly affects the operation management and environmental safety of construction sites and disposal sites. However, due to the scattered and large number of sites, the traditional management model relies on manual monitoring and extensive estimation, and it is difficult to accurately grasp the actual loading and unloading of each slag truck. In view of this, integrating cutting-edge information technology, deeply analyzing the entire link of slag flow, and realizing intelligent early warning of excessive discharge and disposal of slag have become urgent issues to improve the level of intelligent urban management and environmental protection efficiency. However, current early warning technology is too complicated. How to quickly process data and manage and monitor construction sites and disposal sites is an urgent problem that needs to be solved. Summary of the invention

[0003] The purpose of the present invention is to provide a method for monitoring the amount of slag processing based on the trajectory data of slag trucks, by analyzing only the trajectory data of the slag trucks and by quickly grasping the transportation conditions of each slag truck between each management point, supervision of each management point is achieved.

[0004] To achieve the above objectives, this application adopts the following scheme: A method for monitoring the amount of slag processed based on trajectory data of a slag truck comprises the following steps: S1. Obtain the trajectory data of each muck truck in the monitoring area and the corresponding maximum single-trip transportation volume of the vehicle during the monitoring period; the point information of the management point and the corresponding muck control volume; S2, matching the trajectory data of each muck truck with the point information of the management point, obtaining the point information of each trajectory point of each muck truck and storing it in the vehicle entry and exit point details table, the vehicle entry and exit point details table includes the time of each trajectory point of each vehicle and the point information of its location; S3. Adding an auxiliary count column for marking the position change of the muck truck to the vehicle entry and exit point details table to obtain a first auxiliary table; S4. Divide the first auxiliary table into a vehicle entry point details table and a vehicle exit point details table corresponding to each muck truck according to each muck truck and the auxiliary count column, and splice the vehicle entry point details table and the vehicle exit point details table of each muck truck to obtain a vehicle operation details table; S5. Count the entry and exit frequency of each muck truck at the management point according to the vehicle operation details table of each vehicle, and calculate the amount of muck transported by the muck truck at the management point according to the entry and exit frequency of each muck truck and the corresponding maximum single-trip transportation volume of the vehicle; S6. Determine whether the amount of slag transported by the slag truck at the management point exceeds the corresponding slag control amount. If so, issue an early warning to the current management point.

[0005] In some specific implementation schemes, the trajectory data of each muck truck includes the license plate number, the longitude and latitude of each trajectory point and the time, and the point information of the management point includes the point name and point type of the management point, and the longitude and latitude range of the regional geographic fence. The specific process of step S2 is: S21, sorting the trajectory data of each muck truck in chronological order, and matching them with the longitude and latitude range of the regional geofence, determining the point name of each trajectory point, and if the trajectory data cannot match the longitude and latitude range of the regional geofence, marking the point name of the trajectory point as a null value; S22, establish a vehicle entry and exit point details table, the fields of the vehicle entry and exit point details table include license plate, time and area, and store the license plate number, time and point name corresponding to each trajectory point as a field value of a data in the license plate, time and area fields of the vehicle entry and exit point details table respectively; S23, sequentially traverse the vehicle entry and exit point details table to see if the point names corresponding to the time-continuous track points are consistent. If not, record the inconsistent track points as drift points; S24. Correct the area field value in the vehicle entry and exit point details table, obtain the point name corresponding to the trajectory point at the adjacent time before and after the drift point, compare whether the point names before and after the drift point are consistent, and if they are consistent, correct the point name of the drift point to the corresponding point name when they are consistent.

[0006] In some specific implementation schemes, the fields of the first auxiliary table include the license plate number of the muck truck, the time of the track point, the point information, and the auxiliary count column; wherein the auxiliary count column is used to mark the point change of the muck truck as follows: Traverse the names of the two points in the area field in turn to determine whether the point names corresponding to the two track points have changed. If changed, add one to the field value of the auxiliary count column corresponding to the changed track point to mark the change in the point of the muck truck.

[0007] In some specific implementation schemes, the fields of the vehicle entry point details table of each muck truck include the license plate number, entry time, region, and auxiliary count column; the fields of the vehicle departure point details table of each muck truck include the license plate number, departure time, region, and auxiliary count column. The specific process of step S4 is: S41, grouping the vehicle operation details table according to the license plate number to obtain a grouping table for each muck truck; S42, obtaining the first and last data of the grouping table of each muck truck, storing the first data in the vehicle entry point details table corresponding to the muck truck, and storing the last data in the vehicle exit point details table corresponding to the muck truck; S43. Merge the same fields and concatenate the different fields of the vehicle entry point details table and the vehicle departure point details table of each dump truck, and add the residence time field to obtain the vehicle operation details table corresponding to each dump truck, wherein the residence time field value is the difference between the departure time field value and the entry time field value of each data in the vehicle operation details table.

[0008] In some specific implementation schemes, the specific process of step S5 is: For each muck truck's vehicle operation details table, traverse each area field value of each muck truck's vehicle operation details table, that is, each data whose point name is not empty, and determine whether the residence time of each data is greater than a preset time. If not, delete the data from the vehicle operation details table, and obtain an updated vehicle operation details table after traversal; According to the updated vehicle operation details table, the amount of data contained in each management point is counted according to the point name corresponding to the area field value as the frequency of the muck truck entering and exiting the management point, and the transportation volume of the muck truck at the management point is obtained according to the product of the vehicle single-trip maximum transportation volume of the muck truck and the frequency of the muck truck entering and exiting the management point; The total amount of transportation of all muck trucks corresponding to each management point is counted to obtain the amount of muck transported by muck trucks at each management point.

[0009] In some specific implementation schemes, the specific process of step S6 is: Obtain the construction certificate of each management point, calculate the historical amount of slag accumulated from the project start time specified in the construction certificate, calculate the difference between the total amount of slag specified in the construction certificate and the historical amount of slag, and obtain the slag control amount corresponding to the management point; Determine whether the amount of slag transported by slag trucks at the management point exceeds the corresponding slag control amount. If so, issue an over-volume warning for the current management point.

[0010] In some specific embodiments, the steps are further included: S51, for the vehicle operation details table, traverse each area field value of the vehicle operation details table of each muck truck, that is, each data whose point name is not empty; S52, judging whether the residence time of each piece of data is greater than a preset time, if so, marking the piece of data as a corresponding operation type according to the point type corresponding to the point name of the piece of data, when the point type corresponding to the point name is a construction site, marking the piece of data as a loading operation, when the point type corresponding to the point name is a disposal site, marking the piece of data as a dumping operation; S53, saving the data marked with loading operation and dumping operation into the vehicle statistics list.

[0011] In some specific implementation schemes, before saving to the vehicle statistics list, the steps of: S521, marking the operation type of the data with empty point name in the vehicle operation details table as transportation, deleting the data with a stay time less than a preset time from the vehicle operation details table, and obtaining a vehicle operation details table; S522. Traverse the vehicle operation details table to determine whether there is data of continuous loading operations or dumping operations before and after the data of operation type transportation. If so, merge the continuous loading operation data and mark them as one loading operation, and merge the continuous dumping operation data and mark them as one dumping operation.

[0012] In some specific implementation schemes, the vehicle statistics list is counted according to the marked operation type, and a continuous loading operation and a dumping operation are regarded as a set of operation data; The number of groups of operation data included in the vehicle statistics list is counted, and the total amount of slag transported by each slag truck in the monitoring area is obtained according to the product of the vehicle single-trip maximum transportation volume of the slag truck and the number of groups of operation data.

[0013] In some specific implementation schemes, the total amount of slag transported by all slag trucks in the monitoring area is calculated to obtain the total transportation volume in the detection area; Obtain the construction certificate of each management point, calculate the historical amount of slag accumulated from the project start time specified in the construction certificate, calculate the difference between the total amount of slag specified in the construction certificate and the historical amount of slag, and obtain the slag control amount corresponding to each management point; According to the type of management points, the total amount of waste soil discharged from all construction sites and the total amount of waste soil disposed of at all disposal sites are counted respectively; Determine whether the total transport volume exceeds the total amount of slag discharge. If so, issue an over-discharge warning in the monitoring area; Determine whether the total transportation volume exceeds the total amount of slag disposal. If so, issue an over-consumption warning in the monitoring area.

[0014] The present invention has the beneficial effects: The present invention realizes real-time monitoring and intelligent analysis of the slag removal process by integrating GPS positioning trajectory data of slag trucks, electronic geographic fence data of construction sites and disposal sites, government-approved construction site emission certificates and disposal site disposal certificates, etc., so as to timely and effectively count the construction site slag emission and disposal site disposal, providing a basis for the supervision of construction sites and disposal sites. The present invention uses Python's dataframe highly abstract functions and methods to complete complex data cleaning, conversion, merging, grouping, filtering and other processing processes in the slag truck trajectory at one time, without the need to manually write loop logic, reducing the error probability, improving code readability and maintainability, and accelerating data processing speed, helping regulators to quickly grasp situations such as over-discharge of slag and over-operation of disposal sites, and take management measures in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a method for monitoring the amount of slag processed based on trajectory data of a slag truck provided in an embodiment of the present invention; Figure 2 A schematic diagram of a trajectory point correction method provided by an embodiment of the present invention; Figure 3 A flowchart of a specific method for obtaining a vehicle operation details table provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] The relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0018] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0019] Additionally, descriptions of well-known structures, functions, and configurations may be omitted for clarity and conciseness.One of ordinary skill in the art will recognize that various changes and modifications may be made to the examples described herein without departing from the spirit and scope of the present disclosure.

[0020] Technologies, methods, and apparatus known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the authorization specification.

[0021] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0022] Example 1 like Figure 1 As shown, this embodiment provides a method for monitoring the amount of slag processing based on the trajectory data of a slag truck, which specifically includes the following steps: S1. Obtain the trajectory data of each muck truck in the monitoring area and the corresponding maximum single-trip transportation volume of the vehicle during the monitoring period; the point information of the management point and the corresponding muck control volume; It should be noted that the management points in this application include construction sites and disposal sites. For construction sites, the slag control volume is the emission volume of the construction site, and the slag control volume of the disposal site is the slag disposal volume. The slag control volume is related to the historical emission (disposal) volume of the construction site (disposal site) and its corresponding construction certificate (construction site emission certificate and disposal site disposal certificate). Specifically, the process of obtaining the vehicle GPS trajectory data within the monitoring period of the monitoring area and the preliminary processing in step S1 is as follows: S11, obtain the real-time trajectory data of each muck truck in the monitoring area, including the license plate number, longitude and latitude, time and other information. Each trajectory data of each muck truck is recorded as Zi (s, lat i ,lon i , t i ), where s represents the license plate number, lat i Indicates latitude, lon i Indicates longitude, t i Indicates time; S12. Obtain the maximum single-trip transport volume information of each dump truck, that is, the emission standard type of each dump truck, such as National V vehicle, National VI vehicle, new energy vehicle, etc. This type of information is mainly used to quantify the vehicle full load standard. For example, the amount of dump when a National V vehicle is fully loaded is 20 cubic meters, and when a new energy vehicle is fully loaded, it is 15 cubic meters, etc.

[0023] S13, the point information of the management point, mainly including the point name, point type, longitude and latitude, regional geographic fence information, etc. of the management point (construction site and disposal site). The data of each point is recorded as Gd (name, type ， lat, lon, geometry); S14. The construction certificate information of the management point (construction site emission certificate and disposal site disposal certificate information) mainly includes the name of the construction site (disposal site), emission certificate id, start and end time of the slag emission (disposal) cycle, emission (disposal) limit, etc., recorded as (name, id, start_time, end_time, threshold); threshold is a specific value, such as 10,000 cubic meters.

[0024] S2, matching the trajectory data of each muck truck with the point information of the management point, obtaining the point information of each trajectory point of each muck truck and storing it in the vehicle entry and exit point details table, the vehicle entry and exit point details table includes the time of each trajectory point of each vehicle and the point information of its location; In order to avoid the drift of the track data of the muck truck and the repeated occurrence in a certain management point area, the following operations need to be performed when matching the track point data of the muck truck with the management point: the track data of each muck truck includes the license plate number, the longitude and latitude of each track point and the time, and the point information of the management point includes the point name and point type of the management point, and the longitude and latitude range of the regional geographic fence, such as Figure 2 As shown, the specific process of step S2 is: S21, sorting the trajectory data of each muck truck in chronological order, and matching them with the longitude and latitude range of the regional geofence, determining the point name of each trajectory point, and if the trajectory data cannot match the longitude and latitude range of the regional geofence, marking the point name of the trajectory point as a null value; S22, establish a vehicle entry and exit point details table, the fields of the vehicle entry and exit point details table include license plate, time and area, and store the license plate number, time and point name corresponding to each trajectory point as a field value of a data in the license plate, time and area fields of the vehicle entry and exit point details table respectively; S23, sequentially traverse the vehicle entry and exit point details table to see if the point names corresponding to the time-continuous track points are consistent. If not, record the inconsistent track points as drift points; S24. Correct the area field value in the vehicle entry and exit point details table, obtain the point name corresponding to the trajectory point at the adjacent time before and after the drift point, compare whether the point names before and after the drift point are consistent, and if they are consistent, correct the point name of the drift point to the corresponding point name when they are consistent.

[0025] For each acquired trajectory data, the trajectory data of each muck truck is sorted in chronological order, and the longitude and latitude in each trajectory data are matched with the longitude and latitude range of the regional geographic fence of the management point, so as to determine the area of ​​the management point where each trajectory point is located, that is, to determine whether the muck truck trajectory point is within the geometry range of the point, and obtain the matching result of each trajectory data. The data format of the matching result is recorded as (s, lat i ,lon i , t i ,name i ), s is a certain muck truck (indicated by the license plate number), (lat i ,lon i ) is the real-time track position of the muck truck, i.e., longitude and latitude, t i is the real time of the muck truck, name i Indicates the point name (construction site or disposal site name) where the current trajectory is located, and stores it in the data result set R, and replaces the s and t in the matching results of each trajectory data i ,name i As field values, they are filled into the license plate, time, and area fields of the vehicle entry and exit point details table, as shown in Table 1. If the current track is not at the construction site or disposal site, it means that the vehicle is on the road or in other areas. At this time, name i Is empty.

[0026] Due to the drift of the vehicle trajectory, the position of the vehicle s will change continuously in continuous time, such as t i-1 Located at construction site A, i Area name i Empty, t i+1 Then we return to construction site A. Considering that the trajectory transmission frequency of the muck truck is relatively frequent (e.g., once every 30 seconds), we can assume that the vehicle is at t i Point name i If there is an offset, it can be initially corrected to A according to the timing changes before and after the position. The corrected vehicle entry and exit point details are shown in Table 2.

[0027] Table 1 Details of vehicle entry and exit points After the first round of data cleaning, for a vehicle s within the monitoring period (such as 12 hours), the continuity of the change of the area where it is located over time increases, which may be (construction site A, ..., construction site A, null, ..., null, disposal site B, ..., disposal site B, null, ..., null, construction site A, ..., construction site A, null, ...), that is, a truckload of construction waste leaves construction site A and arrives at disposal site B after a period of time, and then leaves disposal site B and returns to construction site A after a period of time.

[0028] Table 2 Corrected vehicle entry and exit point details S3. Adding an auxiliary count column for marking the position change of the muck truck to the vehicle entry and exit point details table to obtain a first auxiliary table; In order to obtain the entry and exit of vehicles at different points, an auxiliary count column is added to the modified vehicle entry and exit point details table in Table 2 to obtain Table 3, the purpose of which is to mark the vehicles at different points according to time. Among them, the fields of the first auxiliary table include the license plate number of the muck truck, the time of the track point, the point information and the auxiliary count column; among them, the marking method of the auxiliary count column for marking the point changes of the muck truck is: Traverse the names of the two points in the area field in turn to determine whether the point names corresponding to the two track points have changed. If changed, add one to the field value of the auxiliary count column corresponding to the changed track point to mark the change in the point of the muck truck.

[0029] In order to reduce the probability of errors, improve code readability and maintainability, and reduce the use of loop query logic, the frequency of point changes can be used with the help of the dataframe framework of the Python language to briefly obtain the vehicle entry and exit status as shown in Table 3. If the vehicle point changes, the corresponding auxiliary column count increases by 1. The vehicle experiences (A, A, A, null, B, B, A..) points, and the corresponding auxiliary count column is (0, 0, 0, 1, 2, 2, 3…).

[0030] Table 3 The first auxiliary table S4. Divide the first auxiliary table into a vehicle entry point details table and a vehicle exit point details table corresponding to each muck truck according to each muck truck and the auxiliary count column, and splice the vehicle entry point details table and the vehicle exit point details table of each muck truck to obtain a vehicle operation details table; Specifically, the fields of the vehicle entry point details table of each muck truck include the license plate number, entry time, region, and auxiliary count columns; the fields of the vehicle departure point details table of each muck truck include the license plate number, departure time, region, and auxiliary count columns, such as Figure 3 As shown, the specific process of step S4 is: S41, grouping the vehicle operation details table according to the license plate number to obtain a grouping table for each muck truck; S42, obtaining the first and last data of the grouping table of each muck truck, storing the first data in the vehicle entry point details table corresponding to the muck truck, and storing the last data in the vehicle exit point details table corresponding to the muck truck; S43. Merge the same fields and concatenate the different fields of the vehicle entry point details table and the vehicle departure point details table of each dump truck, and add the residence time field to obtain the vehicle operation details table corresponding to each dump truck, wherein the residence time field value is the difference between the departure time field value and the entry time field value of each data in the vehicle operation details table.

[0031] Similarly, for the convenience of statistics, this embodiment uses the groupby method in the dataframe to group by the columns 'license plate number' and 'auxiliary count column', and calls the first method to obtain the first row of data for each group, thereby obtaining the data record each time the vehicle enters a new location, as shown in Table 4. At the same time, the last method is called to obtain the last row of data for each group, thereby obtaining the data record each time the vehicle leaves a location, as shown in Table 5.

[0032] Table 4 Vehicle entry point details Table 5 Vehicle departure point details The grouped entry point area table and exit point area table are spliced ​​according to the 'license plate number' and 'auxiliary count column' to obtain a detailed record of each vehicle entering and exiting each point, as shown in Table 6 below, where the stay time = exit time - entry time. It can be understood that the auxiliary count column in Table 6 is the statistics of entering and exiting the area once.

[0033] Table 6 Details of vehicle entry and exit points S5. Count the entry and exit frequency of each muck truck at the management point according to the vehicle operation details table of each vehicle, and calculate the amount of muck transported by the muck truck at the management point according to the entry and exit frequency of each muck truck and the corresponding maximum single-trip transportation volume of the vehicle; With the above Table 6, statistics can be collected for each management point. The residence time threshold can be used to determine whether the vehicle is operating in the area. If the residence time is less than the preset time (for example, 2 minutes), it is considered that the vehicle temporarily enters and exits the area, and the record can be filtered out. The specific process is: For each muck truck's vehicle operation details table, traverse each area field value of each muck truck's vehicle operation details table, that is, each data whose point name is not empty, and determine whether the residence time of each data is greater than a preset time. If not, delete the data from the vehicle operation details table, and obtain an updated vehicle operation details table after traversal; According to the updated vehicle operation details table, the amount of data contained in each management point is counted according to the point name corresponding to the area field value as the frequency of the muck truck entering and exiting the management point, and the transportation volume of the muck truck at the management point is obtained according to the product of the vehicle single-trip maximum transportation volume of the muck truck and the frequency of the muck truck entering and exiting the management point; The total amount of transportation of all muck trucks corresponding to each management point is counted to obtain the amount of muck transported by muck trucks at each management point.

[0034] S6. Determine whether the amount of slag transported by the slag truck at the management point exceeds the corresponding slag control amount. If so, issue an early warning to the current management point.

[0035] Specifically, the specific process of step S6 is: Obtain the construction certificate of each management point, calculate the historical amount of slag accumulated from the project start time specified in the construction certificate, calculate the difference between the total amount of slag specified in the construction certificate and the historical amount of slag, and obtain the slag control amount corresponding to the management point; Determine whether the amount of slag transported by slag trucks at the management point exceeds the corresponding slag control amount. If so, issue an over-volume warning for the current management point.

[0036] Based on the travel details of the vehicle at each point during the study period, the frequency of its appearance at each point is counted according to the auxiliary count series, that is, the number of trips the vehicle enters and exits the point, and then the vehicle's maximum single-trip transportation volume is obtained based on the vehicle's emission standard information (National V, National VI, new energy, etc.), and the vehicle's slag transportation volume at the point can be obtained = maximum single-trip transportation volume * frequency; the transportation volume of different vehicles is accumulated, and finally the current slag transportation volume of each point (construction site, disposal site) is obtained.

[0037] Starting from the project start time specified in the construction site emission certificate (disposal site certificate), the historical slag volume of each construction site (disposal site) is calculated cumulatively to determine whether the current historical cumulative slag volume exceeds the slag emission (disposal) specified in the certificate. If so, an alarm message is given.

[0038] In this embodiment, the amount of slag soil at each management point can be counted separately to monitor the situation at each management point, or the amount of waste soil at the entire monitoring area can be monitored as a whole. Based on Tables 1 to 6 above, the specific process of the overall early warning method for the monitoring area is as follows: S51, for the vehicle operation details table, traverse each area field value of the vehicle operation details table of each muck truck, that is, each data whose point name is not empty; S52, judging whether the residence time of each piece of data is greater than a preset time, if so, marking the piece of data as a corresponding operation type according to the point type corresponding to the point name of the piece of data, when the point type corresponding to the point name is a construction site, marking the piece of data as a loading operation, when the point type corresponding to the point name is a disposal site, marking the piece of data as a dumping operation; S53, saving the data marked with loading operation and dumping operation into the vehicle statistics list.

[0039] In order to avoid vehicles from being repeatedly counted due to some special circumstances (such as repeatedly entering and leaving a certain type of area, since the muck truck is generally a continuous operation process of loading muck from the construction site and then transporting it to the corresponding disposal site for dumping, and each muck truck generally operates in a fixed order of construction site A-road null-disposal site B-road null during the monitoring period, the vehicle operation details table can be screened again according to the above characteristics to avoid the problem of repeated statistics. Therefore, the screening step is also included before saving to the vehicle statistics list: S521, marking the operation type of the data with empty point name in the vehicle operation details table as transportation, deleting the data with a stay time less than the preset time from the vehicle operation details table, and obtaining a vehicle operation details table, as shown in Table 7; Table 7 Vehicle operation details S522. Traverse the vehicle operation details table to determine whether there is data of continuous loading operations or dumping operations before and after the data of operation type transportation. If so, merge the continuous loading operation data and mark them as one loading operation, and merge the continuous dumping operation data and mark them as one dumping operation.

[0040] It can be understood that a complete operation process includes a loading operation and a dumping operation. Therefore, the continuous loading operation and dumping operation can be regarded as a group of operation processes. In this way, when counting the amount of slag in the monitoring area, the total amount of slag in the monitoring section of the monitoring area can be counted through the operation process of the slag truck. The specific process is: The vehicle statistics list is counted according to the marked operation type, and a continuous loading operation and a dumping operation are regarded as a group of operation data; the number of groups of operation data contained in the vehicle statistics list is counted, and the total amount of slag transported by each slag truck in the monitoring area is obtained according to the product of the vehicle's single-trip maximum transportation volume and the number of groups of operation data.

[0041] The total amount of slag transported by all slag trucks in the monitoring area is calculated to obtain the total transportation volume in the detection area; Obtain the construction certificate of each management point, calculate the historical amount of slag accumulated from the project start time specified in the construction certificate, calculate the difference between the total amount of slag specified in the construction certificate and the historical amount of slag, and obtain the slag control amount corresponding to each management point; According to the type of management points, the total amount of waste soil discharged from all construction sites and the total amount of waste soil disposed of at all disposal sites are counted respectively; Determine whether the total transport volume exceeds the total amount of slag discharge. If so, issue an over-discharge warning in the monitoring area; Determine whether the total transportation volume exceeds the total amount of slag disposal. If so, issue an over-consumption warning in the monitoring area.

[0042] Therefore, if you want to quickly understand the construction status of slag in the monitoring area, you can directly use the above method to quickly determine it. If over-discharge or over-consumption occurs, you can use the specific process of steps S5-S6 to check each management point in turn.

[0043] It is understandable that this application only uses the GPS data of slag trucks, relevant certificate information of construction sites and disposal sites, and geographic fence data to achieve rapid real-time monitoring and accurate prediction of point slag processing capacity, and promptly issue overload warning signals to provide decision-making support for managers and ensure that related operations are carried out within the framework of safety and environmental protection.

[0044] Use Python's dataframe's highly abstract functions and methods to complete complex data cleaning, conversion, merging, grouping, filtering and other processing tasks in the muck truck trajectory at one time, without manually writing loop logic, reducing the error probability and improving code readability and maintainability.

[0045] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. According to the technical essence of the present invention, within the spirit and principles of the present invention, any simple modification, equivalent replacement and improvement made to the above embodiment still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for monitoring the amount of slag processed based on trajectory data of slag trucks, characterized in that: The specific steps include: S1. Obtain the trajectory data of each muck truck in the monitoring area and the corresponding maximum single-trip transportation volume of the vehicle during the monitoring period; the point information of the management point and the corresponding muck control volume; S2, matching the trajectory data of each muck truck with the point information of the management point, obtaining the point information of each trajectory point of each muck truck and storing it in the vehicle entry and exit point details table, the vehicle entry and exit point details table includes the time of each trajectory point of each vehicle and the point information of its location; S3. Adding an auxiliary count column for marking the position change of the muck truck to the vehicle entry and exit point details table to obtain a first auxiliary table; S4. Divide the first auxiliary table into a vehicle entry point details table and a vehicle exit point details table corresponding to each muck truck according to each muck truck and the auxiliary count column, and splice the vehicle entry point details table and the vehicle exit point details table of each muck truck to obtain a vehicle operation details table; S5. Count the entry and exit frequency of each muck truck at the management point according to the vehicle operation details table of each vehicle, and calculate the amount of muck transported by the muck truck at the management point according to the entry and exit frequency of each muck truck and the corresponding maximum single-trip transportation volume of the vehicle; S6. Determine whether the amount of slag transported by the slag truck at the management point exceeds the corresponding slag control amount. If so, issue an early warning to the current management point.

2. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 1, characterized in that: The trajectory data of each muck truck includes the license plate number, the longitude and latitude of each trajectory point and the time. The point information of the management point includes the point name and point type of the management point, and the longitude and latitude range of the regional geographic fence. The specific process of step S2 is: S21, sorting the trajectory data of each muck truck in chronological order, and matching them with the longitude and latitude range of the regional geofence, determining the point name of each trajectory point, and if the trajectory data cannot match the longitude and latitude range of the regional geofence, marking the point name of the trajectory point as a null value; S22, establish a vehicle entry and exit point details table, the fields of the vehicle entry and exit point details table include license plate, time and area, and store the license plate number, time and point name corresponding to each trajectory point as a field value of a data in the license plate, time and area fields of the vehicle entry and exit point details table respectively; S23, sequentially traverse the vehicle entry and exit point details table to see if the point names corresponding to the time-continuous track points are consistent. If not, record the inconsistent track points as drift points; S24. Correct the area field value in the vehicle entry and exit point details table, obtain the point name corresponding to the trajectory point at the adjacent time before and after the drift point, compare whether the point names before and after the drift point are consistent, and if they are consistent, correct the point name of the drift point to the corresponding point name when they are consistent.

3. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 2, characterized in that: The fields of the first auxiliary table include the license plate number of the muck truck, the time of the track point, the point information and the auxiliary count column; wherein the auxiliary count column is used to mark the point change of the muck truck as follows: Traverse the names of the two points in the area field in turn to determine whether the point names corresponding to the two track points have changed. If changed, add one to the field value of the auxiliary count column corresponding to the changed track point to mark the change in the point of the muck truck.

4. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 3 is characterized in that: The fields of the vehicle entry point details table of each muck truck include the license plate number, entry time, region and auxiliary count column; the fields of the vehicle departure point details table of each muck truck include the license plate number, departure time, region and auxiliary count column. The specific process of step S4 is: S41, grouping the vehicle operation details table according to the license plate number to obtain a grouping table for each muck truck; S42, obtaining the first and last data of the grouping table of each muck truck, storing the first data in the vehicle entry point details table corresponding to the muck truck, and storing the last data in the vehicle exit point details table corresponding to the muck truck; S43. Merge the same fields and concatenate the different fields of the vehicle entry point details table and the vehicle departure point details table of each dump truck, and add the residence time field to obtain the vehicle operation details table corresponding to each dump truck, wherein the residence time field value is the difference between the departure time field value and the entry time field value of each data in the vehicle operation details table.

5. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 3 is characterized in that: The specific process of step S5 is: For each muck truck's vehicle operation details table, traverse each area field value of each muck truck's vehicle operation details table, that is, each data whose point name is not empty, and determine whether the residence time of each data is greater than a preset time. If not, delete the data from the vehicle operation details table, and obtain an updated vehicle operation details table after traversal; According to the updated vehicle operation details table, the amount of data contained in each management point is counted according to the point name corresponding to the area field value as the frequency of the muck truck entering and exiting the management point, and the transportation volume of the muck truck at the management point is obtained according to the product of the vehicle single-trip maximum transportation volume of the muck truck and the frequency of the muck truck entering and exiting the management point; The total amount of transportation of all muck trucks corresponding to each management point is counted to obtain the amount of muck transported by muck trucks at each management point.

6. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 5, characterized in that: The specific process of step S6 is: Obtain the construction certificate of each management point, calculate the historical slag volume cumulatively starting from the project start time specified in the construction certificate, calculate the difference between the total slag volume specified in the construction certificate and the historical slag volume, and obtain the slag control volume corresponding to the management point; Determine whether the amount of slag transported by slag trucks at the management point exceeds the corresponding slag control amount. If so, issue an over-volume warning for the current management point.

7. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 3 is characterized in that: Also includes the steps: S51, for the vehicle operation details table, traverse each area field value of the vehicle operation details table of each muck truck, that is, each data whose point name is not empty; S52, judging whether the residence time of each piece of data is greater than a preset time, if so, marking the piece of data as a corresponding operation type according to the point type corresponding to the point name of the piece of data, when the point type corresponding to the point name is a construction site, marking the piece of data as a loading operation, when the point type corresponding to the point name is a disposal site, marking the piece of data as a dumping operation; S53, saving the data marked with loading operation and dumping operation into the vehicle statistics list.

8. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 7, characterized in that: Before saving to the vehicle statistics list, the following steps are also included: S521, marking the operation type of the data with empty point name in the vehicle operation details table as transportation, deleting the data with a stay time less than a preset time from the vehicle operation details table, and obtaining a vehicle operation details table; S522. Traverse the vehicle operation details table to determine whether there is data of continuous loading operations or dumping operations before and after the data of operation type transportation. If so, merge the continuous loading operation data and mark them as one loading operation, and merge the continuous dumping operation data and mark them as one dumping operation.

9. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 7, characterized in that: The vehicle statistics list is counted according to the marked operation type, and a continuous loading operation and a dumping operation are regarded as a set of operation data; The number of groups of operation data included in the vehicle statistics list is counted, and the total amount of slag transported by each slag truck in the monitoring area is obtained according to the product of the vehicle single-trip maximum transportation volume of the slag truck and the number of groups of operation data.

10. The method for monitoring the amount of slag processed based on the trajectory data of slag trucks according to claim 9, characterized in that: The total amount of slag transported by all slag trucks in the monitoring area is calculated to obtain the total transportation volume in the detection area; Obtain the construction certificate of each management point, calculate the historical amount of slag accumulated from the project start time specified in the construction certificate, calculate the difference between the total amount of slag specified in the construction certificate and the historical amount of slag, and obtain the slag control amount corresponding to each management point; According to the type of management points, the total amount of waste soil discharged from all construction sites and the total amount of waste soil disposed of at all disposal sites are counted respectively; Determine whether the total transport volume exceeds the total amount of slag discharge. If so, issue an over-discharge warning in the monitoring area; Determine whether the total transportation volume exceeds the total amount of slag disposal. If so, issue an over-consumption warning in the monitoring area.

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