CN117079203A - Road construction monitoring method, system and storage medium - Google Patents
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Abstract
The application provides a road construction monitoring method, a system and a storage medium, wherein the method comprises the following steps: each region is separated by a preset time period to acquire a plurality of personnel position data corresponding to the primary region; obtaining personnel position data of an area, obtaining a maximum density value of personnel in the area according to the personnel position data, judging whether the maximum density value exceeds a preset density value of the area, if so, obtaining an area value corresponding to the personnel position data, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of a road construction site corresponding to the area value, and obtaining abnormal site information representing the road construction condition according to the abnormal image information; if the current time does not exceed the preset ending time, acquiring the current time, judging whether the current time reaches the preset ending time, and if the current time does not reach the preset ending time, continuing to wait for acquiring the personnel position data; and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation. The application can reduce the input cost of road monitoring.
Description
Technical Field
The present application relates to the field of construction monitoring technologies, and in particular, to a road construction monitoring method, system, and storage medium.
Background
Municipal construction is a building of various public practices and industries, such as road construction, sponsored by municipal government according to the general deployment of municipal planning, with the aim of facilitating the citizens' production and living environments. However, the site situation of municipal construction directly relates to whether municipal construction can be normally checked and accepted, and in order to ensure that municipal construction can be safely carried out according to preset procedures and periods, monitoring personnel, such as project managers, are required to be equipped for the existing engineering construction to check the construction site. Monitoring personnel need to arrive at construction sites in different areas of the city every day, the construction progress of each construction site, personnel safety problems and other site conditions are recorded, relevant information of the actual progress condition is compared with relevant information of relevant corresponding reference progress conditions, the current construction progress condition is determined, and the recorded relevant information representing the safety problems is analyzed to determine the safety condition of the current construction site.
At present, the road construction sites are inspected by manual means, and although the accuracy of site condition recording can be ensured, the distances involved between the road construction sites in different areas are far, the vigor of the prisoner is limited, and one prisoner can hardly consider the inspection work of a plurality of road construction sites in time and comprehensively. Therefore, in order to better and fully and timely acquire the site conditions of road construction, it is necessary to reduce the number of each supervisor taking into account the site conditions of road construction, so that less monitoring cost is generated in a short-term construction period, however, as the construction time increases, the monitoring cost needs to be continuously supported, and thus the investment cost is increased when the road construction monitoring work is performed manually.
Disclosure of Invention
In order to reduce the input cost of road monitoring, the embodiment of the application provides a road construction monitoring method, a system and a storage medium.
In a first aspect, the present embodiment provides a road construction monitoring method, including:
each region is separated by a preset time period to acquire a plurality of personnel position data corresponding to the region once;
obtaining the maximum density value of the personnel in the area according to the personnel position data every time the personnel position data of the area is obtained, judging whether the maximum density value exceeds the preset density value of the area,
if the abnormal image information exceeds the abnormal image information, acquiring an area value corresponding to the personnel position data, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of a road construction site corresponding to the area value, and acquiring abnormal site information representing the road construction condition according to the abnormal image information;
if the current time does not exceed the preset ending time, acquiring the current time, judging whether the current time reaches the preset ending time, and if the current time does not reach the preset ending time, continuing waiting for acquiring the personnel position data;
and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation.
In some of these embodiments, obtaining a maximum density value for personnel in the area from the personnel location data comprises:
sequentially taking each piece of personnel position data as reference position data, and acquiring distance data sets between the reference position data and other pieces of personnel position data, wherein each distance data set comprises a plurality of distance values;
and sequentially counting the qualified number of which the distance value in each distance data group is not greater than a preset distance value, and determining the maximum qualified data in all qualified data as the maximum density value of the personnel in the area, wherein each distance data group corresponds to one qualified data.
In some embodiments, the maximum density value corresponds to a target sub-region, the target sub-region is a closed graph formed by positions of each person in the distance data set corresponding to the maximum density value, and obtaining the abnormal site information representing the road construction condition according to the abnormal graph information includes:
acquiring target area image information of a target subarea corresponding to the maximum density value from the abnormal image information;
acquiring facial expressions of each person in the target area image information, judging whether at least a preset number of facial expressions representing a panic state exist in all the facial expressions, if so, generating safety information representing that safety problems exist on site, and acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal site information comprises the safety information and the actual progress information;
If not, acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal field information comprises the actual progress information.
In some of these embodiments, the method further comprises:
acquiring actual times of each area for acquiring safety information contained in abnormal field information in a historical time period, sequentially judging whether each actual time exceeds preset times, and if not, continuously acquiring a plurality of personnel position data corresponding to the area once in every preset time period by the area;
if the number of the difference times between the actual times and the preset times is exceeded, obtaining a problem area value corresponding to the actual times, adjusting a preset time period corresponding to the problem area value according to the difference times to obtain a new preset time period, and updating the new preset time period to the preset time period corresponding to the problem area value.
In some embodiments, adjusting the preset time period corresponding to the problem area value according to the difference number includes:
obtaining a grade value corresponding to the preset time period according to a preset grade table;
acquiring a ratio value between the difference times and the preset times, and acquiring an adjustment grade value corresponding to the ratio value according to a preset ratio value adjustment table;
And correspondingly adjusting the grade value according to the adjustment grade value to obtain a new grade value, and obtaining a new preset time period according to the new grade value and the grade table.
In some of these embodiments, the method further comprises:
judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring the to-be-processed area values corresponding to the abnormal acquisition instructions generated at the same time, sequencing the preset time periods corresponding to the to-be-processed area values in sequence from small to large to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
In some embodiments, obtaining the field progress information corresponding to the area and representing the road construction condition includes:
and acquiring an area value corresponding to the personnel position data, generating a corresponding progress acquisition instruction according to the area value to obtain normal image information of a road construction site corresponding to the area value, and obtaining site progress information representing the road construction condition according to the normal image information, wherein the site progress information comprises actual progress information.
In a second aspect, the present embodiment provides a road construction monitoring system, the system including a position acquisition module, a security diagnosis module, an abnormality monitoring module, and a daily monitoring module; wherein,
The position acquisition module is used for acquiring a plurality of pieces of personnel position data corresponding to the areas once at preset time intervals in each area;
the safety diagnosis module is used for obtaining the maximum density value of the personnel in the area according to the personnel position data every time the personnel position data of the area is obtained, and judging whether the maximum density value exceeds the preset density value of the area;
the abnormal monitoring module is used for acquiring an area value corresponding to the personnel position data if the maximum density value exceeds the preset density value of the area, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of a road construction site corresponding to the area value, and obtaining abnormal site information representing the road construction condition according to the abnormal image information;
the daily monitoring module is used for acquiring current time if the maximum density value does not exceed the preset density value of the area, judging whether the current time reaches the preset ending time, and if not, continuing waiting for acquiring personnel position data; and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation.
In some of these embodiments, the system further comprises a ranking module; wherein,
the sequencing module is used for judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring a region value to be processed corresponding to the abnormal acquisition instructions generated at the same time, sequencing the preset time periods corresponding to the region value to be processed in sequence from small to large to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
In a third aspect, an embodiment of the present application provides a storage medium having stored thereon a computer program executable on a processor, the computer program implementing a road construction monitoring method according to the first aspect when executed by the processor.
By adopting the method, each interval is separated by a preset section to acquire a plurality of personnel position data corresponding to the area once, after the personnel position data of one area is acquired, the maximum density value of the personnel in the area is calculated according to the acquired personnel position data, and the maximum density value is compared with the preset density value corresponding to the area. If the maximum density value exceeds the corresponding preset density value, indicating that the area possibly has a safety problem, further acquiring an area value corresponding to the personnel position data, generating a corresponding abnormal acquisition instruction based on the area value, acquiring abnormal image information of a road construction site corresponding to the area value by using an unmanned aerial vehicle according to the abnormal acquisition instruction, and acquiring abnormal site information representing the road construction condition according to the abnormal image information, thereby further accurately determining whether the area has the safety problem or not, and simultaneously acquiring the progress of the area.
If the maximum density value does not exceed the corresponding preset density value, indicating that the area has no safety problem, continuously acquiring the current time, judging whether the current time reaches the preset ending time, and if the current time does not reach the preset ending time, continuously waiting for acquiring the personnel position data in order to reduce unnecessary shooting of the unmanned aerial vehicle, and generating no corresponding instruction to trigger the unmanned aerial vehicle to move. And if the preset ending time is reached, the unmanned aerial vehicle is used for acquiring the on-site progress information corresponding to the area and representing the road construction condition. The road construction monitoring work can be completed only by using corresponding equipment, the progress and safety monitoring is realized, and the input cost of road monitoring is reduced.
Drawings
Fig. 1 is a block diagram of a road construction monitoring method according to the present embodiment.
Fig. 2 is a block diagram of maximum density values of persons in an area obtained from person location data according to an embodiment of the present application.
Fig. 3 is a block diagram of obtaining abnormal site information characterizing road construction conditions according to abnormal graphic information provided by an embodiment of the present application.
Fig. 4 is a block diagram of a preset time period corresponding to the problem area value adjusted according to the number of difference values according to an embodiment of the present application.
Fig. 5 is a framework diagram of a road construction monitoring system according to the present embodiment.
Detailed Description
The present application will be described and illustrated with reference to the accompanying drawings and examples for a clearer understanding of the objects, technical solutions and advantages of the present application. However, it will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. It will be apparent to those having ordinary skill in the art that various changes can be made to the disclosed embodiments of the application and that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Thus, the present application is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the scope of the application as claimed.
Embodiments of the application are described in further detail below with reference to the drawings.
Fig. 1 is a block diagram of a road construction monitoring method according to the present embodiment. As shown in fig. 1, a road construction monitoring method includes the steps of:
step S100, each area is separated by a preset time period to acquire a plurality of pieces of personnel position data corresponding to the area.
Each road construction work undertaken by a company corresponds to an area, and in order to facilitate management of all road construction works, the company may arrange for a project manager to be responsible for several areas. In this embodiment, a plurality of areas in charge of a certain project manager are taken as an example for explanation. Each of the plurality of areas is configured to schedule the corresponding staff and the number of staff according to the work that the area is actually required to perform. The person position data may be obtained by using GPS positioning technology or RFID positioning technology, and the manner in which the person position data is obtained is not further limited here. The present embodiment will be described in detail by taking an RFID positioning technology as an example.
The above personnel position data is a position coordinate in the world coordinate system. An RFID reader-writer is arranged on certain core equipment of each area, and the core equipment can move correspondingly along with the road construction progress, so that the RFID reader-writer can effectively identify RFID identifications worn by each worker in the area in real time, and the RFID reader-writer can read the personnel position data of each worker in the area. Each area corresponds to a respective working time and a preset time period, and the working time corresponding to each area can be determined according to the actual geographic position or working habit of the area, and the working time is not further limited. The working time of each area is the reference time for acquiring the personnel position data of the area, the reference time is taken as the starting time, and the road construction monitoring system acquires the personnel position data about the area, which is acquired last time, from the RFID reader-writer every preset time interval, so that a plurality of personnel position data corresponding to the area are acquired every preset time interval. Thus, by using the RFID reader/writer installed in each area, a plurality of pieces of personnel position information data corresponding to each area can be obtained once every predetermined period of time.
Each area corresponds to an initial preset time period, and the initial preset time period corresponding to each area is inversely related to the construction difficulty identified by the area. The specific time of each initial preset time period is not further limited in this embodiment.
Step S200, each time personnel position data of an area is obtained, a maximum density value of personnel in the area is obtained according to the personnel position data, and whether the maximum density value exceeds a preset density value of the area is judged.
Fig. 2 is a block diagram of maximum density values of persons in an area obtained from person location data according to an embodiment of the present application. As shown in fig. 2, obtaining the maximum density value of the person in the area from the person position data includes the steps of:
step S201, sequentially taking each piece of personnel position data as reference position data, and acquiring distance data values between the reference position data and other pieces of personnel position data, wherein each distance data set comprises a plurality of distance values.
Step S202, sequentially counting qualified data with a distance value not larger than a preset distance value in each distance data set, and determining the maximum qualified data in all the qualified data as the maximum density value of personnel in the area, wherein each distance data set corresponds to one qualified data.
When the road construction monitoring system acquires the personnel position data, all the personnel position data corresponding to a certain area are acquired at the same time, and the received personnel position data are subjected to subsequent processing. All the personnel position data corresponding to a certain area are acquired to form a personnel position data set, and each personnel position data set only comprises all the personnel position data in the area. For a personnel position data set, firstly taking certain personnel position data in the personnel position data set as reference position data, and then importing any personnel position data in the reference position data and other personnel position data into a distance formula between two points to obtain a distance value between the reference position data and the personnel position data. And similarly, sequentially replacing the personnel position data in the other personnel position data, substituting the personnel position data into a distance formula between two points, and obtaining a distance data set after the personnel position data except the reference position data in the personnel position data set are substituted into the distance formula between the two points, wherein the distance data set comprises all distance values belonging to the same reference position data.
After a distance data set is obtained, continuing to use the other personnel position data in the personnel position data set as reference position data, and obtaining a new distance data set by the same method. Thus, all distance data sets in the area are obtained after each of the personnel position data sets is used as reference position data once. The number of sets of distance data sets corresponding to an area is the same as the number of workers in the area.
The preset distance value is used for distinguishing whether the two workers belong to an aggregation state or not. The preset distance value may be determined according to practical situations, and is generally between 0.45 and 1.2 meters, and in this embodiment, the preset distance value is preferably determined to be 0.8 meters. For the same area, subtracting a preset distance value corresponding to the area from each distance value in a distance data set in the area to obtain a corresponding distance difference value, and recording the number of which the distance difference value does not belong to a positive number as qualified data. In this way, each distance data set in the area can obtain qualified data corresponding to the distance data set by adopting the method, and each distance data set corresponds to one qualified data. And selecting the maximum qualified data with the largest value from all the qualified data in the same area, wherein the maximum qualified data is the maximum density value of the personnel in the area. Similarly, the maximum density value of the personnel in each area can be obtained by adopting the method.
The preset density value is used for distinguishing whether concentrated aggregation exists in the area. One zone corresponds to a preset density value that is positively correlated to the total number of workers in the zone. The preset density value is generally 60% -90% of the total number of workers in the area, and in consideration of the large area of each area, some workers in the road construction process must arrange corresponding workers for treatment. The present embodiment preferably determines the preset density value for each zone to be 75% of the total number of workers in that zone. If an integer cannot be obtained by multiplying the total number of workers in the area by 75%, the final corresponding preset density value of the area is determined by following the rounding principle. Subtracting the preset density value corresponding to each region from the maximum density value corresponding to each region in sequence to obtain a corresponding density difference value, and judging whether the maximum density value of the region exceeds the preset density value of the region according to the sign of the density difference value, so as to judge whether the concentrated aggregation condition of the workers exists in the region.
And step S300, if the abnormal image information exceeds the abnormal image information, acquiring an area value corresponding to the personnel position data, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of the road construction site corresponding to the area value, and acquiring abnormal site information representing the road construction condition according to the abnormal image information.
Each area corresponds to a uniquely determined area value, and when the road construction monitoring system acquires all the personnel position data corresponding to a certain area, the road construction monitoring system acquires the preset value corresponding to the area together, so that each area value corresponds to one personnel position data set. If the sign of the density difference is positive, the maximum density value of the area exceeds the preset density value corresponding to the area. The situation that people are concentrated and gathered is generally caused when the safety problem occurs, so that the situation that the concentrated and gathered situation exists in the area is indicated, the construction site of the area possibly has abnormality, and the road construction monitoring system can obtain the area value corresponding to the personnel position data according to the personnel position data of the area with the abnormality.
And generating an abnormal acquisition instruction for triggering the unmanned aerial vehicle to be in a working state according to the region value corresponding to the maximum density value when the maximum density value is determined to exceed the corresponding preset density value, wherein the abnormal acquisition instruction corresponds to the region value one by one, so that the road monitoring system knows which regions use the unmanned aerial vehicle for on-site inspection, and the follow-up tracing of abnormal conditions on a construction site is facilitated. After an abnormal acquisition instruction is generated, the abnormal acquisition instruction is sent to the unmanned aerial vehicle, and meanwhile, the last acquired personnel position data corresponding to the abnormal acquisition instruction is sent to the unmanned aerial vehicle, so that the unmanned aerial vehicle automatically generates a corresponding path plan according to the position of the unmanned aerial vehicle and the received personnel position data, and the unmanned aerial vehicle reaches a position area corresponding to the personnel position data according to the generated path plan, so that the area is photographed and automatically sent to a road construction monitoring system, and the road construction monitoring system receives abnormal image information of a road construction site corresponding to an area value. The abnormal image information represents a picture taken by the unmanned aerial vehicle corresponding to the region value from the upper air.
Fig. 3 is a block diagram of obtaining abnormal site information characterizing road construction conditions according to abnormal graphic information provided by an embodiment of the present application. As shown in fig. 3, obtaining abnormal site information characterizing road construction conditions from abnormal graphic information includes the steps of:
step S301, acquiring target area image information of a target sub-area corresponding to the maximum density value from the abnormal image information.
Step S302, obtaining facial expressions of each person in the image information of the target area, and judging whether at least a preset number of facial expressions representing the panic state exist in all the facial expressions.
Step S303, if yes, generating safety information representing that safety problems exist in the scene, and acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal scene information comprises the safety information and the actual progress information.
Step S304, if not, acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal field information comprises the actual progress information.
The maximum density value of each area corresponds to one reference position data, the reference position data is taken as the center, the personnel position data with the distance between the reference position data and the reference position data not larger than the preset distance value corresponding to the reference position data are all auxiliary personnel position data, the minimum closed graph which can contain all the auxiliary personnel position data and the reference position data in the area is the target subarea corresponding to the maximum density value, and the positions corresponding to all the auxiliary personnel position data and the positions corresponding to the reference position data in the area are not outside the target subarea. Since both the reference position data and the auxiliary personnel position data are coordinate values in the world coordinate system, the coordinates of the target subarea corresponding to the outer border of the target subarea can be obtained.
The obtained abnormal image information also has image coordinates in a world coordinate system corresponding to the image, and the corresponding relation between the target sub-region coordinates and the image coordinates, namely the image distance value of the target sub-region corresponding to the target sub-region coordinates and the abnormal image information representing the image side edge is obtained by comparing the target sub-region coordinates with the image coordinates one by one according to coordinate values in the horizontal direction. And then cutting the abnormal image information according to the image distance value to obtain the target area image information of the sub-area corresponding to the maximum density value. The target area image information is also essentially an image.
After obtaining the image information of the target area, the road construction monitoring system can use a facial recognition algorithm or an expression recognition algorithm to obtain the facial expression of each person in the image information of the target area. The face recognition algorithm is adopted to determine the position and the direction of the face by detecting the face area of the person and extracting key characteristic points, and thus the characteristic points comprise eyes, a nose, a mouth and the like, and the head expression of the person can be judged according to the position of the characteristic points on the image. The expression recognition algorithm can be realized by training a deep learning model, and the model can detect the face of a person and predict the expression of the person in the image information of the input target area. Typically, expression recognition models require a large amount of input information and corresponding output information to train and optimize.
After obtaining the facial expression of each person in the image information of the target area, counting the number of the terrorists of the facial expressions representing the terrorist state in all the facial expressions in the image information of the target area, comparing the terrorist data with the preset number, and if the number of the terrorists is not smaller than the preset number, indicating that the safety problem exists in the area; if the number of panics is less than the preset number, it is indicated that there is no security problem in the area.
If the safety problem exists in the area, the corresponding image information identification software is used for carrying out image identification on the image information of the target area, and the identified image is subjected to corresponding text conversion to obtain the safety information describing the safety problem existing on the scene represented by the image information of the target area, wherein the safety information is a text.
In addition, the road construction corresponding to each area adopts BIM technology in advance to generate the whole construction process simulation operation and the corresponding preset schedule corresponding to each area. And acquiring an actual engineering stage from the abnormal image information. The time corresponding to the abnormal image information can be obtained when the personnel position data are acquired each time, so that the theoretical engineering stage in which the time is supposed to be is matched from the preset schedule according to the time, and the actual schedule information corresponding to the abnormal image information is obtained by comparing whether the theoretical engineering stage is identical with the actual engineering stage. If the theoretical engineering stage is the same as the actual engineering stage, the actual progress information represents normal construction; if the theoretical engineering stage is advanced from the actual engineering stage, the actual progress information characterizes the delayed construction; if the theoretical engineering stage lags the actual engineering stage, the actual progress information characterizes the advanced construction. Since there is a safety problem in the area, abnormal scene information obtained from abnormal image information acquired by the unmanned aerial vehicle includes safety information and actual progress information.
If no safety problem exists in the area, acquiring actual progress information corresponding to the abnormal image information from the preset progress table only by means of the preset progress table and time corresponding to the abnormal image information, namely, acquiring the abnormal field information from the abnormal image information acquired by the unmanned aerial vehicle, wherein the abnormal field information only comprises the actual progress information. Under the condition that the safety problem possibly exists in the area is judged through the personnel position data, the unmanned aerial vehicle is dispatched to take a corresponding field photograph, and the road construction monitoring system performs image processing to further determine whether the safety problem exists in the area, so that the safety problem can be accurately obtained according to the safety condition of the accurate field of the image, and when the safety problem is determined to exist, the safety problem can be accurately obtained through abnormal image information, the number of times that a project manager patrols the area is reduced, the labor detection cost is reduced, and compared with the continuous expenditure labor cost along with the project, the input cost of road monitoring is reduced. In addition, the actual construction stage of the area at the current time can be obtained through the image, and thus the actual construction stage is compared with the theoretical construction stage, and the progress condition of the current construction of the area can be obtained. And when the safety problem is checked, the construction progress of the area is known incidentally, and the unmanned aerial vehicle does not need to be additionally dispatched to monitor the construction progress, so that the cost brought by the flight of the unmanned aerial vehicle is reduced.
In addition, the present embodiment further includes: acquiring actual times of each area for acquiring safety information contained in abnormal field information in a historical time period, sequentially judging whether each actual time exceeds preset times, and if not, continuously acquiring a plurality of personnel position data corresponding to each area every preset time period; if the number of the difference between the actual times and the preset times is exceeded, acquiring a problem area value corresponding to the actual times, adjusting a preset time period corresponding to the problem area value according to the difference times to obtain a new preset time period, and updating the new preset time period into the preset time period corresponding to the problem area value.
The above-described historical time period characterizes the time period from the start time of construction of the area to the end time of the present time. Every time the personnel position data of the area is acquired, the actual number of times of receiving the abnormal site information containing the safety information of the area is acquired. And comparing the actual times with preset times, and if the actual times are not greater than the preset times, continuously acquiring a plurality of personnel position data corresponding to the area according to the current preset time by the area. The preset times are used for distinguishing whether the area has excessive safety problems or not, and can be set according to engineering standards.
If the actual times are greater than the preset times, the fact that the area has too many safety problems is indicated, the actual times are required to be subtracted by the preset times to obtain difference times, the frequency of acquiring personnel position data of the area is adjusted according to the difference times, so that construction safety problems of the area can be known in time according to the positions of the personnel, the area is marked as a problem area, and an area value corresponding to the problem area is a problem area value. Updating the adjusted preset time period to a preset time period corresponding to the problem area value, and subsequently, acquiring the frequency of the personnel position data according to the adjusted preset time period. Fig. 4 is a block diagram of a preset time period corresponding to the problem area value adjusted according to the number of difference values according to an embodiment of the present application. As shown in fig. 4, the adjustment of the preset time period corresponding to the problem area according to the difference number includes the following steps:
step S305, obtaining a grade value corresponding to a preset time period according to a preset grade table.
Step S306, a ratio value between the difference times and the preset times is obtained, and an adjustment grade value corresponding to the ratio value is obtained according to a preset ratio value adjustment table.
Step S307, the grade value is correspondingly adjusted according to the adjustment grade value to obtain a new grade value, and a new preset time period is obtained according to the new grade value and the grade table.
The preset level table represents a preset time period corresponding to each level value, and the preset proportion value adjustment table represents the numerical value of the level value change corresponding to different proportion values, and can be determined according to industry rules. Substituting the preset time period into a preset grade table to obtain a grade value corresponding to the preset time period. Dividing the difference times by the preset times to obtain a ratio value between the two times, and substituting the obtained ratio value into a preset ratio value adjustment table to obtain an adjustment grade value corresponding to the ratio value. After the grade value is adjusted to the grade value representation, a new grade value can be obtained, and then the new grade value is substituted into a preset grade table, so that a new preset time period corresponding to the new grade value can be obtained.
In addition, the present embodiment further includes: judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring the to-be-processed area values corresponding to the abnormal acquisition instructions generated at the same time, sequencing the to-be-processed area values according to preset time periods corresponding to the to-be-processed area values from small to large in sequence to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
If the road construction monitoring system can simultaneously acquire the personnel position data of at least two areas after the preset time period is adjusted, and the maximum density value of the personnel position data in the at least two areas exceeds the preset density value of the area, the condition that at least two abnormal acquisition instructions are generated at the same moment is indicated; otherwise, it indicates that at least two exception fetch instructions are not generated at the same time. If at least two abnormal acquisition instructions are not generated at the same time, the unmanned aerial vehicle continues to execute work according to the sequence of receiving the abnormal acquisition instructions. If at least two abnormal acquisition instructions are generated at the same moment, the to-be-processed area value corresponding to each abnormal acquisition instruction and the preset time period corresponding to each to-be-processed area value can be acquired, the preset time period corresponding to each to-be-processed area value is sequenced from small to large, so that sequencing information about the preset time period from small to large is obtained, and the unmanned aerial vehicle sequentially reaches the area corresponding to the to-be-processed area value according to the sequence of the preset time period from small to large to perform shooting work, so that corresponding image information is obtained. After all, the number of times that the safety problem occurs in the area corresponding to the small preset time period is more, so that the unmanned aerial vehicle is preferentially arranged to go to the area with the more times that the safety problem occurs for shooting, whether the safety problem exists in the area with high probability of occurrence of the safety problem is preferentially checked, and the area with the real safety problem is found out in blocks under the preferential capability.
Step S400, if not, the current time is obtained, whether the current time reaches the preset ending time is judged, and if not, the acquisition of the personnel position data is continued.
If the sign of the density difference is not positive, the maximum density value of the area does not exceed the preset density value corresponding to the area, and the area is not concentrated and gathered at the moment, so that the area is considered to be in normal road construction work. The road construction is a long-period work, the construction progress of the road is not required to be acquired in real time, and the unmanned aerial vehicle is used for acquiring on-site images in each area every day. The preset ending time characterizes the time that the unmanned aerial vehicle obtains the field image in each area every day, and the preset ending time is preferably set as the off-duty time in the embodiment, so that the current workload of each area can be conveniently known. If the maximum density value does not exceed the preset density value of the area and the current time does not reach the preset ending time, the area is indicated to work normally, unmanned aerial vehicle work is not required to be sent out, and the next time of acquiring personnel position data is only required to be waited.
And S500, if the road construction situation is reached, acquiring the field progress information representing the road construction situation corresponding to the region.
If the maximum density value does not exceed the preset density value of the area and the current time reaches the preset ending time, the unmanned aerial vehicle needs to be dispatched to acquire the work result of each area in the day, namely the field progress information corresponding to the area and representing the road construction condition is acquired. The method for obtaining the on-site progress information corresponding to the region and representing the road construction condition comprises the following steps: the method comprises the steps of obtaining an area value corresponding to personnel position data, generating a corresponding progress obtaining instruction according to the area value to obtain normal image information of a road construction site corresponding to the area value, and obtaining site progress information representing road construction conditions according to the normal image information, wherein the site progress information comprises actual progress information.
The road construction monitoring system sequentially generates corresponding progress acquisition instructions according to the sequence of the off-duty time corresponding to each area, so that the unmanned aerial vehicle can acquire corresponding normal image information according to the progress acquisition instructions, and the road construction monitoring system analyzes and processes the on-site progress information to obtain on-site progress information of each actual progress information representing road construction conditions, wherein the on-site progress information comprises the actual progress information. And the unmanned aerial vehicle equipment is used for completing the check of the road construction progress in each area, so that the investment cost of road monitoring is reduced. The process of analyzing and processing the on-site progress information by the road construction monitoring system is the same as the principle of analyzing the abnormal image information, and will not be described here again.
Fig. 5 is a framework diagram of a road construction monitoring system according to the present embodiment. As shown in fig. 5, a road construction monitoring system includes a position acquisition module, a security diagnosis module, an abnormality monitoring module, a daily monitoring module, and a ranking module.
The position acquisition module is used for acquiring a plurality of personnel position data corresponding to the primary region at preset time intervals in each region. And the safety diagnosis module is used for obtaining the personnel position data of one area, obtaining the maximum density value of personnel in the area according to the personnel position data, and judging whether the maximum density value exceeds the preset density value of the area. The abnormal monitoring module is used for acquiring the area value corresponding to the personnel position data if the maximum density value exceeds the preset density value of the area, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of the road construction site corresponding to the area value, and obtaining abnormal site information representing the road construction condition according to the abnormal image information. The daily monitoring module is used for acquiring the current time if the maximum density value does not exceed the preset density value of the area, judging whether the current time reaches the preset ending time, and if not, continuing to wait for acquiring the personnel position data; and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation. The sequencing module is used for judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring the to-be-processed area values corresponding to the abnormal acquisition instructions generated at the same time, sequencing the to-be-processed area values according to preset time periods corresponding to the to-be-processed area values from small to large in sequence to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
The other functions executed by the position acquisition module, the security diagnosis module, the abnormality monitoring module, the daily monitoring module and the sequencing module and the technical details of the functions are the same as or similar to the corresponding features in the road construction monitoring method described above, so that the details are not repeated here.
Embodiments of the present application provide a computer readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the relevant content of the method embodiments described above.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein.
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations are intended to be comprehended within the scope of the present application.
Claims (10)
1. A method of road construction monitoring, the method comprising:
each region is separated by a preset time period to acquire a plurality of personnel position data corresponding to the region once;
obtaining the maximum density value of the personnel in the area according to the personnel position data every time the personnel position data of the area is obtained, judging whether the maximum density value exceeds the preset density value of the area,
if the abnormal image information exceeds the abnormal image information, acquiring an area value corresponding to the personnel position data, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of a road construction site corresponding to the area value, and acquiring abnormal site information representing the road construction condition according to the abnormal image information;
if the current time does not exceed the preset ending time, acquiring the current time, judging whether the current time reaches the preset ending time, and if the current time does not reach the preset ending time, continuing waiting for acquiring the personnel position data;
and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation.
2. The method of claim 1, wherein obtaining a maximum density value for personnel in the area from the personnel location data comprises:
Sequentially taking each piece of personnel position data as reference position data, and acquiring distance data sets between the reference position data and other pieces of personnel position data, wherein each distance data set comprises a plurality of distance values;
and sequentially counting the qualified number of which the distance value in each distance data group is not greater than a preset distance value, and determining the maximum qualified data in all qualified data as the maximum density value of the personnel in the area, wherein each distance data group corresponds to one qualified data.
3. The method according to claim 2, wherein the maximum density value corresponds to a target sub-area, the target sub-area is a closed figure formed by positions of each person in the distance data set corresponding to the maximum density value, and obtaining the abnormal site information representing the road construction condition according to the abnormal figure information comprises:
acquiring target area image information of a target subarea corresponding to the maximum density value from the abnormal image information;
acquiring facial expressions of each person in the target area image information, judging whether at least a preset number of facial expressions representing a panic state exist in all the facial expressions, if so, generating safety information representing that safety problems exist on site, and acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal site information comprises the safety information and the actual progress information;
If not, acquiring actual progress information corresponding to the abnormal image information from a preset progress table, wherein the abnormal field information comprises the actual progress information.
4. A method according to claim 3, characterized in that the method further comprises:
acquiring actual times of each area for acquiring safety information contained in abnormal field information in a historical time period, sequentially judging whether each actual time exceeds preset times, and if not, continuously acquiring a plurality of personnel position data corresponding to the area once in every preset time period by the area;
if the number of the difference times between the actual times and the preset times is exceeded, obtaining a problem area value corresponding to the actual times, adjusting a preset time period corresponding to the problem area value according to the difference times to obtain a new preset time period, and updating the new preset time period to the preset time period corresponding to the problem area value.
5. The method of claim 4, wherein adjusting the preset time period corresponding to the problem area value according to the number of differences comprises:
obtaining a grade value corresponding to the preset time period according to a preset grade table;
Acquiring a ratio value between the difference times and the preset times, and acquiring an adjustment grade value corresponding to the ratio value according to a preset ratio value adjustment table;
and correspondingly adjusting the grade value according to the adjustment grade value to obtain a new grade value, and obtaining a new preset time period according to the new grade value and the grade table.
6. The method according to claim 4, wherein the method further comprises:
judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring the to-be-processed area values corresponding to the abnormal acquisition instructions generated at the same time, sequencing the preset time periods corresponding to the to-be-processed area values in sequence from small to large to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
7. The method of claim 1, wherein obtaining field progress information corresponding to the region and characterizing a road construction condition comprises:
and acquiring an area value corresponding to the personnel position data, generating a corresponding progress acquisition instruction according to the area value to obtain normal image information of a road construction site corresponding to the area value, and obtaining site progress information representing the road construction condition according to the normal image information, wherein the site progress information comprises actual progress information.
8. A road construction monitoring system, the system comprising: the system comprises a position acquisition module, a safety diagnosis module, an abnormality monitoring module and a daily monitoring module; wherein,
the position acquisition module is used for acquiring a plurality of pieces of personnel position data corresponding to the areas once at preset time intervals in each area;
the safety diagnosis module is used for obtaining the maximum density value of the personnel in the area according to the personnel position data every time the personnel position data of the area is obtained, and judging whether the maximum density value exceeds the preset density value of the area;
the abnormal monitoring module is used for acquiring an area value corresponding to the personnel position data if the maximum density value exceeds the preset density value of the area, generating a corresponding abnormal acquisition instruction based on the area value to obtain abnormal image information of a road construction site corresponding to the area value, and obtaining abnormal site information representing the road construction condition according to the abnormal image information;
the daily monitoring module is used for acquiring current time if the maximum density value does not exceed the preset density value of the area, judging whether the current time reaches the preset ending time, and if not, continuing waiting for acquiring personnel position data; and if the road construction situation arrives, acquiring the field progress information corresponding to the region and representing the road construction situation.
9. The system of claim 8, further comprising a ranking module; wherein,
the sequencing module is used for judging whether at least two abnormal acquisition instructions are generated at the same time or not, if yes, acquiring a region value to be processed corresponding to the abnormal acquisition instructions generated at the same time, sequencing the preset time periods corresponding to the region value to be processed in sequence from small to large to obtain sequencing information, and sequentially obtaining corresponding image information according to the sequencing information.
10. A computer-readable storage medium, on which a computer program is stored which can be run on a processor, characterized in that the computer program, when executed by the processor, implements a road construction monitoring method as claimed in any one of claims 1 to 7.
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| CN118052414B (en) * | 2024-04-09 | 2024-06-14 | 中建安装集团有限公司 | Electromechanical construction data management system and method based on modularization |
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