A multi-ticket concurrent job monitoring method, device and medium

Abstract

The present application relates to a kind of multi-ticket concurrent operation monitoring method, equipment and medium.The method comprises: obtaining multiple effective electronic operation licenses, each electronic operation license includes the space range of corresponding operation area and operation constraint information;According to each space range, determine the space intersection area and corresponding electronic operation license set;Obtain observation data of space intersection area, and respectively based on the operation constraint information of each electronic operation license, carry out compliance check;Each check result is respectively written into corresponding independent evidence chain.The present application can avoid the confusion of different electronic operation license check basis and result when operation area overlaps, improve the accuracy and traceability of multi-ticket concurrent operation monitoring.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology in industrial sites, and more specifically, to a method, device, and medium for monitoring multiple concurrent operations. Background Technology

[0002] As industrial production sites become increasingly digitalized and intelligent, various operations, such as hot work, hoisting, maintenance, and confined space work, are gradually being applied for, approved, and managed through electronic work permits. In shipbuilding, petrochemical, metallurgical, and construction scenarios, multiple operations often occur concurrently within the same timeframe, and the work areas for different operations may be adjacent to or partially overlap. Therefore, effectively monitoring multiple concurrent operations has become a crucial aspect of industrial site safety management.

[0003] In existing technologies, monitoring tasks can typically be established for each electronic work permit, and on-site inspections or remote monitoring can be conducted on the corresponding work based on the work area, personnel, work type, or other permit conditions recorded in the electronic work permit. On-site monitoring personnel, fixed monitoring equipment, or mobile inspection equipment can collect images, videos, environmental parameters, or personnel information within the work area, and then determine whether the on-site work is compliant according to the management requirements of the corresponding electronic work permit, and generate corresponding monitoring records.

[0004] However, when multiple electronic work permits are in effect at the same time and the corresponding work areas overlap, the existing monitoring methods usually still process them separately as a single electronic work permit. This makes it difficult to accurately determine the multiple electronic work permits corresponding to the same site area, which can easily lead to confusion between the verification basis and verification results of different electronic work permits, affecting the accuracy of monitoring multiple concurrent work permits. Summary of the Invention

[0005] Therefore, it is necessary to address the above-mentioned problems by providing a method, device, and medium for monitoring concurrent operations with multiple electronic work permits. This invention aims to solve the problem that when the work areas corresponding to multiple electronic work permits overlap, the verification criteria and verification results corresponding to different electronic work permits are easily confused, leading to low accuracy in monitoring concurrent operations with multiple permits.

[0006] In a first aspect, the present invention provides a method for monitoring concurrent multi-license operations, the method comprising: acquiring multiple electronic work permits in effect; wherein each electronic work permit includes at least the spatial range of a corresponding work area and work constraint information; determining a spatial intersection zone and a set of electronic work permits corresponding to the spatial intersection zone based on the spatial ranges corresponding to the multiple electronic work permits; the spatial intersection zone characterizing an area jointly covered by at least two electronic work permits in the set of electronic work permits; acquiring observation data for the spatial intersection zone; independently performing compliance verification on the observation data for each electronic work permit in the set of electronic work permits based on the work constraint information corresponding to the electronic work permit, obtaining a verification result corresponding to the electronic work permit; and writing the verification results corresponding to each electronic work permit into a corresponding independent evidence chain.

[0007] Optionally, the spatial range includes two-dimensional polygonal fences; determining the spatial intersection area and the set of electronic work permits corresponding to the spatial intersection area based on the spatial ranges corresponding to the multiple electronic work permits includes: performing spatial Boolean operations on the two-dimensional polygonal fences corresponding to the multiple electronic work permits to obtain spatial operation results; determining the corresponding spatial intersection area based on the spatial operation results when any two two-dimensional polygonal fences intersect, or when one two-dimensional polygonal fence is contained within another two-dimensional polygonal fence; in the determined spatial intersection area, for the common intersection formed by three or more two-dimensional polygonal fences, determining the common intersection area as a multi-permit spatial intersection area, and removing the common intersection area from the pairwise spatial intersection areas corresponding to the multi-permit spatial intersection area; determining the set of electronic work permits corresponding to each spatial intersection area based on the spatial intersection area.

[0008] In the above implementation process, by reading the vertex coordinates of the two-dimensional polygon fences, calculating the boundary intersections, and determining the internal and external relationships of the vertices, the intersection areas and inclusion relationships can be formed according to the actual boundaries of each two-dimensional polygon fence, avoiding the judgment of spatial overlap based solely on the name of the work area or a rough location; by separately determining the common intersection of three or more two-dimensional polygon fences as a multi-ticket spatial intersection area, and removing the common intersection from the corresponding pairwise spatial intersection areas, different spatial intersection areas can correspond to mutually unique physical areas, avoiding the duplicate counting or duplicate allocation of monitoring resources for the same area; by determining the set of electronic work permits based on the two-dimensional polygon fences that form each spatial intersection area, the spatial intersection area can be accurately matched with the electronic work permits that actually cover the spatial intersection area, providing a clear spatial range and permit range for subsequent ticket-by-ticket verification.

[0009] Optionally, acquiring observation data for the spatial intersection area includes: acquiring the operational risk level of each electronic work permit in the set of electronic work permits corresponding to the spatial intersection area; determining the monitoring density coefficient of the spatial intersection area based on the operational risk level of each electronic work permit; determining the patrol point distribution density and / or the dwell time of each patrol point in the spatial intersection area based on the monitoring density coefficient; and acquiring observation data of the spatial intersection area based on the patrol point distribution density and / or the dwell time.

[0010] In the above implementation process, by obtaining the operational risk level of each electronic work permit corresponding to the spatial intersection area and determining the monitoring density coefficient based on each operational risk level, the allocation of monitoring resources can be matched with the operational risk corresponding to the spatial intersection area. By calculating the distribution density of patrol points, the number of patrol points, and the duration of stay based on the monitoring density coefficient, the number of observation positions can be increased or the continuous observation time can be extended when the monitoring density coefficient is large, thereby increasing the possibility of abnormal operational behaviors and environmental anomalies being collected. When the monitoring density coefficient is small, unnecessary occupation of observation resources can be reduced, so that limited monitoring resources can be prioritized for spatial intersection areas with high monitoring needs.

[0011] In a second aspect, the present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing program instructions, and the processor executing the steps in the method described above when running the program instructions.

[0012] Thirdly, embodiments of the present invention provide a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer program instructions, which, when executed by a processor, perform the steps of the method described in any of the preceding claims.

[0013] In this invention, by determining the spatial overlap area based on the spatial range corresponding to multiple active electronic work permits, and identifying the set of electronic work permits that commonly cover the spatial overlap area, it is possible to clearly identify which electronic work permits currently constrain the same site area. By acquiring observation data for the spatial overlap area and independently performing compliance verification on the same observation data based on the work constraint information corresponding to each electronic work permit, it is possible to avoid the merging of the permit conditions of different electronic work permits, which would lead to the misuse of verification basis. This ensures that each verification result accurately reflects whether the site status meets the requirements of the corresponding electronic work permit. By writing the verification results corresponding to each electronic work permit into their respective independent evidence chains, the observation data, verification basis, and verification results can be associated and stored with the corresponding electronic work permits, avoiding the overlap or confusion of monitoring records for multiple concurrent operations. This allows for the accurate reconstruction of the monitoring process and anomaly judgment basis for each electronic work permit. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0015] Figure 1 This is a flowchart of a multi-ticket concurrent operation monitoring method provided in one embodiment of the present invention; Figure 2 This is a schematic diagram of an electronic device provided in another embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will now be described with reference to the accompanying drawings. For example, the flowcharts and block diagrams in the drawings illustrate the architecture, functions, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, program segment, or part of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions. In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0017] The multi-permit concurrent operation monitoring method provided by this invention can be applied to industrial sites where multiple operations are carried out simultaneously. Industrial sites may include shipbuilding and repair sites, metallurgical sites, petrochemical sites, construction sites, or other work sites that require safety management through work permits.

[0018] Concurrent operations with multiple permits refer to operations that are simultaneously implemented within the same time period. The work areas corresponding to multiple electronic work permits can be independent of each other, or they can partially or completely overlap. The work content, personnel, or requirements corresponding to multiple electronic work permits can be the same or different.

[0019] The multi-ticket concurrent operation monitoring method provided by this invention can be executed by a field monitoring server, edge computing device, work permit management platform, cloud server, monitoring robot, or other devices with data processing capabilities. The device executing the method can communicate with the work permit management platform, field data acquisition device, and data storage device.

[0020] Please see Figure 1 , Figure 1 A flowchart of a multi-ticket concurrent job monitoring method provided for embodiments of the present invention; the method may include the following steps: Step S101: Obtain multiple electronic work permits that are in effect; wherein each electronic work permit includes at least the spatial range of the corresponding work area and work constraint information; Step S102: Based on the spatial ranges corresponding to the multiple electronic work permits, determine the spatial intersection area and the set of electronic work permits corresponding to the spatial intersection area; the spatial intersection area represents the area jointly covered by at least two electronic work permits in the set of electronic work permits; Step S103: Obtain observation data for the spatial intersection area; Step S104: For each electronic work permit in the set of electronic work permits, based on the work constraint information corresponding to the electronic work permit, independently perform compliance verification on the observation data to obtain the verification result corresponding to the electronic work permit; Step S105: Write the verification results corresponding to each of the electronic work permits into the corresponding independent evidence chains.

[0021] The following sections provide detailed explanations of each step.

[0022] In step S101, multiple electronic work permits in effect can be obtained. Electronic work permits can be generated by the work permit management platform after a work application has been approved, or they can be generated by other business systems and synchronized to the work permit management platform. Each electronic work permit can have a corresponding permit identifier, which may include a numerical number, a character number, a combination of numbers and characters, or other information that can distinguish different electronic work permits.

[0023] An "effective" status can indicate that the electronic work permit has been approved and allows the corresponding work to be carried out. An "effective" status can also indicate that the current time is within the validity period of the electronic work permit and that the permit has not been revoked, closed, or suspended.

[0024] Multiple valid electronic work permits can be obtained by calling the data interface provided by the work permit management platform, by subscribing to the permit status messages sent by the work permit management platform, or by querying the permit database according to a preset period and filtering according to the status field and the validity period of the permit.

[0025] The scope of access can be all valid electronic work permits within the preset monitoring range. The preset monitoring range can be set according to the on-site management area, the monitoring area corresponding to the monitoring equipment, or the safety management range.

[0026] Each electronic work permit may include at least the spatial scope of the corresponding work area and work constraint information. The spatial scope can represent the work area corresponding to the work permitted by the electronic work permit, and can be composed of data that can represent the boundary or coverage of the work area. The work constraint information can represent the restrictions or permitting conditions imposed by the electronic work permit on the on-site work, and can be generated by the work permit management platform during the electronic work permit approval process, or can be configured by safety management personnel according to the work content and work environment.

[0027] Multiple obtained electronic work permits can be stored in a set of valid permits. The set of valid permits can be stored using a list, index table, database record set, or other data structures, and can be indexed by the permit identifier to associate and store the spatial range and work constraint information corresponding to the electronic work permit.

[0028] For example, a welding work permit and a cutting work permit can coexist on an industrial site. When both the welding and cutting work permits have been approved and are within their valid validity period, they can be designated as effective electronic work permits.

[0029] In step S102, spatial overlap areas and the set of electronic work permits corresponding to the spatial overlap areas can be determined based on the spatial ranges corresponding to multiple electronic work permits. A spatial overlap area can represent an area jointly covered by the spatial ranges corresponding to at least two electronic work permits. Joint coverage can mean that the two spatial ranges partially overlap, or that one spatial range is entirely located within another spatial range.

[0030] After obtaining the spatial scope corresponding to each electronic work permit, the spatial scopes can be compared under a unified on-site coordinate reference, and the common coverage area can be determined based on the overlap relationship between the spatial scopes. When at least two spatial scopes have a common coverage area, the common coverage area can be identified as a spatial intersection area, and a corresponding spatial intersection area identifier can be assigned to the spatial intersection area, while the area boundary corresponding to the spatial intersection area is recorded.

[0031] An electronic work permit set represents a collection of electronic work permits that collectively cover the same spatial intersection area. Based on the spatial boundaries that form the intersection area, the permit identifiers corresponding to each spatial boundary can be queried, and the corresponding electronic work permits can be grouped into an electronic work permit set. Each spatial intersection area can correspond to one electronic work permit set; different spatial intersection areas can have the same or different electronic work permit sets.

[0032] For example, electronic work permit A corresponds to work area A, and electronic work permit B corresponds to work area B. When work area A and work area B overlap, the overlapping area can be defined as a spatial intersection area, and electronic work permits A and B can be combined into a set of electronic work permits corresponding to the spatial intersection area.

[0033] Spatial intersection zone identifiers, the corresponding spatial extent of spatial intersection zones, and the set of electronic work permits can be stored together to determine which electronic work permits are applicable to the observation data acquired for spatial intersection zones.

[0034] In step S103, observation data can be acquired for the spatial intersection area. The observation data can represent data that reflects the on-site conditions within the spatial intersection area, and the on-site conditions can include the status of the workers, the status of the equipment, the status of the work behavior, or the status of the work environment.

[0035] For example, observation data can be collected by on-site data acquisition equipment. On-site data acquisition equipment may include image acquisition equipment, video acquisition equipment, sound acquisition equipment, temperature acquisition equipment, gas detection equipment, personnel identification equipment, or other equipment capable of collecting on-site operational status. On-site data acquisition equipment can be fixedly installed at the work site or mounted on monitoring robots, drones, mobile inspection terminals, or other mobile devices.

[0036] For example, a data acquisition device whose monitoring range can cover the spatial intersection area can be selected based on the spatial extent of the intersection area, and a data acquisition command can be sent to the data acquisition device. Alternatively, the monitoring robot can be controlled to move to a position where it can observe the spatial intersection area, and the data acquisition device carried by the monitoring robot can collect on-site data.

[0037] Observational data may include at least one of the following: image data, video data, audio data, temperature data, gas concentration data, personnel identification data, equipment operation data, or other data related to the on-site operational status. Observational data can be associated with spatial intersection zone identifiers, data acquisition time, and data source identifiers to establish a correspondence between observational data and spatial intersection zones.

[0038] For example, when welding and cutting operations are carried out simultaneously in a spatial intersection area, video data that reflects the operating status of personnel, tools, flames, arc light, or equipment in the spatial intersection area can be acquired and used as the observation data corresponding to the spatial intersection area.

[0039] In step S104, compliance verification can be performed independently on the observation data for each electronic work permit in the electronic work permit set, based on the work constraint information of the corresponding electronic work permit.

[0040] Independent compliance verification means that for different electronic work permits in the electronic work permit set, the corresponding work constraint information of each electronic work permit is read separately, and the observation data is judged based on the corresponding work constraint information. Different electronic work permits can share the observation data obtained for spatially overlapping areas, but different electronic work permits do not share work constraint information and verification results.

[0041] In practice, the set of electronic work permits can be traversed. For the current electronic work permit, the corresponding work constraint information can be read, and the site conditions reflected by the observation data can be determined according to the permit conditions recorded in the work constraint information to see if they meet the requirements of the current electronic work permit.

[0042] Verification results can include compliance results, abnormal results, or indeterminate results. They can also include verification time, verification basis, abnormal content, or other information that describes the verification process. Different verification results can be obtained when the same observation data is verified based on the work constraint information corresponding to different electronic work permits.

[0043] For example, the spatial intersection area corresponds to electronic work permit A and electronic work permit B. A compliance check can be performed on the observation data based on the work constraint information corresponding to electronic work permit A, yielding the check result for electronic work permit A; conversely, a second compliance check can be performed on the same observation data based on the work constraint information corresponding to electronic work permit B, yielding the check result for electronic work permit B.

[0044] When the site conditions reflected by the observation data meet the licensing conditions of Electronic Work Permit A but not Electronic Work Permit B, the verification result corresponding to Electronic Work Permit A can be a compliant result, and the verification result corresponding to Electronic Work Permit B can be an abnormal result.

[0045] In step S105, the verification results corresponding to each electronic work permit can be written into their respective independent evidence chains. An independent evidence chain can represent a set of monitoring records maintained separately for each individual electronic work permit. Each electronic work permit can correspond to one independent evidence chain. Independent evidence chains can be stored in a database, a distributed storage system, a log storage system, or other data storage devices capable of storing monitoring records.

[0046] In some cases, an independent chain of evidence corresponding to an electronic work permit can be determined based on the permit identifier, and the verification result corresponding to the electronic work permit can be written into the corresponding independent chain of evidence. The evidence record written into the independent chain of evidence may include the permit identifier, spatial intersection zone identifier, observation data identifier, data acquisition time, verification time, and verification result. It may also include the storage address or data summary of the observation data, so as to query the corresponding observation data based on the evidence record.

[0047] The same observation data can be cited by multiple independent chains of evidence, and each independent chain of evidence can store different verification results obtained based on the same observation data.

[0048] For example, when a spatial intersection area corresponds to electronic work permit A and electronic work permit B, the verification result corresponding to electronic work permit A can be written into the independent evidence chain corresponding to electronic work permit A, and the verification result corresponding to electronic work permit B can be written into the independent evidence chain corresponding to electronic work permit B. The verification result corresponding to electronic work permit A will not replace or cover the verification result corresponding to electronic work permit B.

[0049] In this embodiment, by determining the spatial intersection zone based on the spatial range corresponding to multiple active electronic work permits, and identifying the set of electronic work permits that commonly cover the spatial intersection zone, it is possible to clarify which electronic work permits currently constrain the same site area. By acquiring observation data for the spatial intersection zone and independently performing compliance verification on the same observation data based on the work constraint information corresponding to each electronic work permit, it is possible to avoid the merging of the permit conditions of different electronic work permits, which would lead to the misuse of verification basis. This ensures that each verification result can accurately reflect whether the site status meets the requirements of the corresponding electronic work permit. By writing the verification results corresponding to each electronic work permit into their respective independent evidence chains, the observation data, verification basis, and verification results can be associated and stored with the corresponding electronic work permits, avoiding the overlap or confusion of monitoring records for multiple concurrent operations. This allows for the accurate reconstruction of the monitoring process and anomaly judgment basis for each electronic work permit.

[0050] Optionally, in some embodiments, the spatial extent includes a two-dimensional polygonal fence.

[0051] The step S102, which involves determining the spatial intersection area and the set of electronic work permits corresponding to the spatial intersection area based on the spatial ranges corresponding to the multiple electronic work permits, may include steps S1021 to S1024. Steps S1021 to S1024 are used to convert the common coverage relationship between the aforementioned spatial ranges into a spatial operation relationship between two-dimensional polygon fences, and to perform deduplication processing on the common coverage area of ​​multiple permits. The two-dimensional polygon fence can represent a closed area formed by multiple two-dimensional coordinate points in a preset connection order. The two-dimensional coordinate points can be represented by industrial site planar coordinates, geographic coordinates, or electronic map coordinates.

[0052] Step S1021: Perform spatial Boolean operations on the two-dimensional polygonal fences corresponding to the multiple electronic work permits to obtain spatial operation results.

[0053] Specifically, the vertex coordinate sequence of each 2D polygon fence can be read, and the vertex coordinates in different coordinate systems can be transformed to a unified coordinate system. For any two 2D polygon fences, the circumscribed rectangles of the two 2D polygon fences can be compared first. If the circumscribed rectangles do not overlap, it can be determined that the two 2D polygon fences do not intersect. If the circumscribed rectangles overlap, the intersection points between the boundary segments of the two 2D polygon fences can be further calculated, and the intersection polygon of the two 2D polygon fences can be generated by combining the inside-out relationship of each vertex with respect to the other 2D polygon fence. The inside-out relationship of a vertex with respect to the other 2D polygon fence can be determined by ray casting, the number of turns method, or other methods of judging points within the polygon. For the inclusion relationship, when the 2D polygon fence is a simple polygon, it can be determined whether all vertices of one 2D polygon fence are located within the other 2D polygon fence, and the inclusion relationship can be determined by combining whether the boundaries of the two 2D polygon fences intersect. The spatial operation results can include the intersection relationship between 2D polygon fences, the inclusion relationship, the vertex coordinate sequence of the intersection region, the area of ​​the intersection region, and the electronic work permit identifiers that participated in forming the intersection region.

[0054] Step S1022: Based on the spatial calculation result, determine the corresponding spatial intersection area when any two two-dimensional polygon fences intersect, or when one two-dimensional polygon fence is contained within another two-dimensional polygon fence.

[0055] Specifically, spatial relationship identifiers and intersection area data can be read from the spatial calculation results. When the spatial relationship identifier indicates that two two-dimensional polygonal fences intersect, and the area of ​​the intersection area is greater than a preset area threshold, the vertex coordinate sequence corresponding to the intersection area can be determined as the boundary of the spatial intersection area. When the spatial relationship identifier indicates that one two-dimensional polygonal fence is contained within another two-dimensional polygonal fence, the area covered by the contained two-dimensional polygonal fence can be determined as the spatial intersection area. The preset area threshold can be zero, or it can be set to a value greater than zero based on positioning error, map drawing error, or on-site management accuracy, to avoid forming spatial intersection areas with no practical monitoring significance due to boundary point contact or minor geometric errors. When two two-dimensional polygonal fences only share a boundary line or boundary point, but do not have a common coverage area with area, the shared boundary line or shared boundary point may not be determined as a spatial intersection area.

[0056] Step S1023: In the determined spatial intersection area, for the common intersection formed by three or more of the two-dimensional polygon fences, the common intersection is determined as a multi-vote spatial intersection area, and the common intersection is removed from the pairwise spatial intersection areas corresponding to the multi-vote spatial intersection area.

[0057] Specifically, a multi-vote spatial intersection area can represent an area covered by three or more two-dimensional polygonal fences. Based on the spatial calculation results, it can be determined whether there exists a common intersection formed by three or more two-dimensional polygonal fences within the identified spatial intersection area.

[0058] For example, for three two-dimensional polygon fences A, B, and C, we can determine the pairwise spatial intersections formed by two-dimensional polygon fences A and B, the pairwise spatial intersections formed by two-dimensional polygon fences A and C, and the pairwise spatial intersections formed by two-dimensional polygon fences B and C. We can also determine the common intersection formed by the three two-dimensional polygon fences.

[0059] The common intersection can be defined separately as the multi-vote spatial intersection area, and the common intersection can be removed from each pairwise spatial intersection area corresponding to the multi-vote spatial intersection area. For example, the common intersection formed by three two-dimensional polygon fences can be represented as A∩B∩C, and the pairwise spatial intersection areas after removing the common intersection can be represented as (A∩B)-(A∩B∩C), (A∩C)-(A∩B∩C), and (B∩C)-(A∩B∩C), respectively.

[0060] By removing common intersections from pairwise spatial intersections, we can avoid the same physical area being both divided into multiple spatial intersections and repeatedly retained in multiple pairwise spatial intersections.

[0061] For four or more two-dimensional polygon fences, the common intersections corresponding to different vote counts can be determined sequentially according to the number of two-dimensional polygon fences that jointly cover the same area, from most to least. The already determined common intersections of high vote counts are then removed from the spatial intersections of low vote counts that contain the corresponding common intersections, so that the physical areas corresponding to each spatial intersection do not overlap.

[0062] Step S1024: Determine the set of electronic work permits corresponding to each of the spatial intersection zones based on the spatial intersection zones.

[0063] Specifically, based on the two-dimensional polygonal fence identifiers forming the spatial intersection area, the corresponding electronic work permit identifiers for each two-dimensional polygonal fence can be queried, and the retrieved electronic work permits can be combined into a corresponding electronic work permit set. For a spatial intersection area formed by two two-dimensional polygonal fences with multiple common intersections removed, the electronic work permit set can include the electronic work permits corresponding to each of the two two-dimensional polygonal fences; for a spatial intersection area with multiple common intersections, the electronic work permit set can include the electronic work permits corresponding to all two-dimensional polygonal fences that form a common intersection. The spatial intersection area identifier, spatial intersection area boundary, spatial intersection area area, and electronic work permit set can be stored as a linked record for subsequent observation and verification of the spatial intersection area.

[0064] In this embodiment, by reading the vertex coordinates of the two-dimensional polygon fence, calculating the boundary intersections, and determining the internal and external relationships of the vertices, the intersection areas and inclusion relationships can be formed according to the actual boundaries of each two-dimensional polygon fence, avoiding the judgment of spatial overlap based solely on the name of the work area or a rough location. By separately determining the common intersection of three or more two-dimensional polygon fences as a multi-ticket spatial intersection area, and removing the common intersection from the corresponding pairwise spatial intersection areas, different spatial intersection areas can correspond to non-overlapping physical areas, avoiding the duplicate counting or allocation of monitoring resources for the same area. By determining the set of electronic work permits based on the two-dimensional polygon fences that form each spatial intersection area, the spatial intersection area can be accurately matched with the electronic work permits that actually cover the spatial intersection area, providing a clear spatial range and permit range for subsequent ticket-by-ticket verification.

[0065] Optionally, in some embodiments, the step of acquiring observation data for the spatial intersection zone, i.e., step S103, may include steps S103A1 and S103A2. Steps S103A1 and S103A2 are used to filter observation data from a large range of candidate observation data where the monitored object is located within the spatial intersection zone. Candidate observation data may represent field observation data that has not yet been filtered according to the spatial intersection zone, and the monitored object may represent personnel, equipment, tools, heat sources, flames, or other field objects that need to be monitored. Step S103A1: Obtain candidate observation data containing spatial location information of the monitored object.

[0066] Specifically, the spatial location information of the monitored object can be in the form of two-dimensional coordinates, three-dimensional coordinates, map grid markers, or other data formats that can characterize the spatial location of the monitored object. For operators or equipment carrying positioning tags, the coordinates output by the positioning tags can be read as the spatial location information of the monitored object. For monitored objects in images or videos, the pixel position of the monitored object in the image can be identified, and the pixel position can be converted into on-site coordinates according to the installation position of the image acquisition equipment, the shooting direction, and the intrinsic and extrinsic parameters.

[0067] When the ground surface is approximately planar, coordinate transformation can be achieved through homography transformation: ; in, This indicates the pixel coordinates of the monitored object in the image. This represents the two-dimensional coordinates of the monitored object in the on-site coordinate system. This represents the homography matrix determined based on the calibration results of the image acquisition equipment. This represents the scale factor. After calculating the right-hand vector, the first and second components of the right-hand vector can be divided by the third component to obtain the two-dimensional coordinates of the monitored object in the field coordinate system. .

[0068] For image acquisition devices with depth information, the three-dimensional coordinates of the monitored object in the field coordinate system can be determined based on pixel coordinates, depth values, and the intrinsic and extrinsic parameters of the image acquisition device. Candidate observation data can include the observation content of the monitored object and its spatial location information. For example, it can include the identification information and spatial location information of the workers, or it can include the temperature and spatial location information of the heat source.

[0069] Step S103A2: Based on the spatial location information, determine the observation data corresponding to the spatial intersection zone from the candidate observation data; wherein, the observation data corresponding to the spatial intersection zone are candidate observation data in which the spatial location of the corresponding monitoring object is located within the spatial intersection zone.

[0070] Specifically, the spatial location information of the monitored object and the boundary of the spatial intersection area can be placed in the same coordinate system, and the method of determining whether the spatial location of the monitored object is within the spatial intersection area can be used. When using the ray method, a ray can be emitted from the spatial location of the monitored object along a preset direction, and the number of intersection points between the ray and the boundary of the spatial intersection area can be counted; when the number of intersection points is odd, it can be determined that the spatial location of the monitored object is within the spatial intersection area, and when the number of intersection points is even, it can be determined that the spatial location of the monitored object is outside the spatial intersection area.

[0071] When the monitored object is located on the boundary of a spatial intersection zone, candidate observation data can be included in the spatial intersection zone according to preset boundary processing rules, or a boundary buffer zone can be set based on the positioning error. The positioning error is... At that time, the spatial intersection area can be extended outward by a distance. The matching region is obtained, and when the spatial location of the monitored object is within the matching region, the corresponding candidate observation data is determined as the observation data of the spatial intersection area.

[0072] When a single image frame contains multiple monitored objects, the spatial location of each monitored object can be determined one by one, and only the image area, identity information, or behavioral information corresponding to the monitored object whose spatial location is located within the spatial intersection area can be retained.

[0073] In this embodiment, the spatial location of each monitored object is determined by means of positioning tag output, image coordinate transformation or depth positioning, and the spatial location of the monitored object is judged by the execution point of the spatial intersection zone boundary within the region. This can accurately filter the observation data located within the spatial intersection zone from the large range of field data obtained by the data acquisition equipment, and avoid mistaking personnel, equipment or work activities outside the spatial intersection zone as monitored objects within the spatial intersection zone. Since the subsequent compliance verification is only performed on the observation data that matches the spatial intersection zone, the interference of irrelevant field data on the verification results can be reduced, so that the verification object is consistent with the actual work object within the spatial intersection zone.

[0074] Optionally, in some embodiments, the job constraint information includes spatial constraint information, identity constraint information, and process constraint information.

[0075] For each electronic work permit in the set of electronic work permits, based on the work constraint information corresponding to that electronic work permit, a compliance check is independently performed on the observation data to obtain a check result corresponding to that electronic work permit. That is, step S104 may include steps S1041 and S1042. Steps S1041 and S1042 are used to check the observation data from at least one aspect: work space, participating personnel, and actual work process. Step S1041: For each of the electronic work permits, perform at least one of the following verifications: perform spatial verification on the observation data based on the spatial constraint information determined by the spatial range corresponding to the electronic work permit, and obtain a spatial verification result; perform identity verification on the observation data based on the identity constraint information including the list of authorized personnel corresponding to the electronic work permit, and obtain an identity verification result; perform process verification on the observation data based on the process constraint information including the work process type corresponding to the electronic work permit, and obtain a process verification result.

[0076] Specifically, spatial constraint information can represent the spatial conditions specified in the electronic work permit for the work location or monitoring location, and can be generated based on the spatial range corresponding to the electronic work permit. The spatial location corresponding to the monitored object can be obtained from the observation data, and the spatial location corresponding to the monitored object can be compared with the spatial constraint information. When the spatial location corresponding to the monitored object meets the spatial constraint information, the spatial verification result can be compliant; when the spatial location corresponding to the monitored object does not meet the spatial constraint information, the spatial verification result can be abnormal.

[0077] Identity constraint information represents the restrictions imposed by the electronic work permit on the identity of personnel participating in the operation. It may include a list of authorized personnel for the corresponding electronic work permit. The authorized personnel list records the identifiers of personnel permitted to participate in the corresponding operation. These identifiers may include personnel numbers, ID card numbers, location tag numbers, facial recognition data, or other information that can identify a person. The personnel identifiers corresponding to the monitored objects can be obtained from observation data and matched against the authorized personnel list. If a personnel identifier is in the authorized personnel list, the identity verification result can be considered compliant; if the personnel identifier is not in the authorized personnel list, the identity verification result can be considered abnormal.

[0078] Process constraint information represents the restrictions imposed by the electronic work permit on on-site work processes, and may include the work process type corresponding to the electronic work permit. Work process types may include welding, gas cutting, grinding, hoisting, or other on-site work process types. The actual on-site work process type can be identified based on the work tools, work actions, flame patterns, arc light characteristics, or sound spectrum characteristics in the observation data, and then compared with the work process type recorded in the corresponding electronic work permit. When the actual work process type matches the work process type recorded in the electronic work permit, the process verification result can be considered compliant; when the actual work process type does not match the work process type recorded in the electronic work permit, the process verification result can be considered abnormal.

[0079] Step S1042: Based on the verification result corresponding to at least one of the performed verifications, obtain the verification result corresponding to the electronic work permit.

[0080] Specifically, when performing only one verification, the verification result corresponding to that one verification can be determined as the verification result corresponding to the electronic work permit. When performing multiple verifications, if all verification results are compliant, the verification result corresponding to the electronic work permit can be determined as compliant; if at least one verification result is abnormal, the verification result corresponding to the electronic work permit can be determined as abnormal, and the abnormal verification item can be recorded. Spatial verification results, identity verification results, and process verification results can also be saved separately, so that the verification result corresponding to the electronic work permit includes multiple verification sub-results.

[0081] In this embodiment, by performing at least one of spatial verification, identity verification, and process verification for each electronic work permit, it can be determined whether the location of the monitored object conforms to the spatial constraints of the corresponding electronic work permit, whether the personnel involved in the operation are authorized personnel of the corresponding electronic work permit, and whether the actual on-site operation process is consistent with the operation process type recorded in the corresponding electronic work permit. Since each verification uses the operation constraint information corresponding to the current electronic work permit itself, it can avoid the mixing of operation areas, authorized personnel, and operation processes between different electronic work permits. By retaining the verification results and abnormal verification items, the verification results can not only reflect whether the on-site operation is compliant, but also clarify the source of the abnormality, providing a specific basis for subsequent abnormal handling.

[0082] Optionally, in some embodiments, the step of performing spatial verification on the observation data based on the spatial constraint information determined by the spatial range corresponding to the electronic work permit, and obtaining the spatial verification result, may include the following steps. These steps are used to determine the monitored spatial range based on the currently valid fence version of the electronic work permit, and to determine the spatial compliance status of the monitored object relative to the current electronic work permit.

[0083] Based on the current fence version of the electronic work permit and the corresponding spatial constraint information, the corresponding monitored space range is determined.

[0084] Specifically, the current fence version can represent the currently valid spatial range version of the electronic work permit. The fence version record corresponding to the electronic work permit can be queried based on the permit identifier, and the fence version marked as the currently effective version in the fence version record is determined as the current fence version; if no currently effective version mark is set, the fence version with the most recent effective time and status as effective can be determined as the current fence version.

[0085] Spatial constraint information can include the spatial boundary corresponding to the current fence version, or the spatial expansion or contraction distance set according to security management requirements. When no spatial adjustment parameters are configured, the monitored space range can be the same as the spatial range corresponding to the current fence version; configuring the spatial expansion distance... At this time, an outward buffering operation can be performed on the current fence boundary to obtain the monitored space range; the space contraction distance can be configured. At that time, an inward buffering operation can be performed on the current fence boundary to obtain the range of the monitored space.

[0086] Determine the spatial location of the monitoring object corresponding to the observation data.

[0087] Specifically, the location determination method can be selected based on the data source of the observation data. When the observation data includes location tag data, the on-site coordinates output by the location tag can be read directly; when the observation data includes images or videos, the pixel position of the monitored object in the image can be identified, and the pixel position can be converted into on-site coordinates according to the calibration parameters of the image acquisition device; when the observation data is collected by sensors mounted on the monitoring robot, the position of the monitored object can be converted to the on-site coordinate system according to the pose of the monitoring robot, the installation pose of the sensor relative to the monitoring robot, and the sensor ranging results. When multiple positioning results exist simultaneously, the positioning result can be selected according to the positioning reliability, or a weighted average method can be used to fuse multiple positioning results.

[0088] Based on the spatial location and the range of the monitoring space, it is determined whether the monitored object is located within the range of the monitoring space, and the spatial verification result is obtained.

[0089] Specifically, the spatial location of the monitored object and the boundary of the monitored space can be placed in the same coordinate system, and the method of determining whether the monitored object is within the monitored space can be used. When considering positioning errors, the position error area of ​​the monitored object can be constructed based on the error radius output by the positioning device; when the entire position error area is within the monitored space, the spatial verification result can be determined as compliant; when the entire position error area is outside the monitored space, the spatial verification result can be determined as abnormal; when the position error area intersects with the boundary of the monitored space, the spatial verification result can be determined as indeterminate, triggering a second observation or manual confirmation.

[0090] If the monitored object is located within the spatial intersection zone but outside the monitoring space, the spatial verification result is determined as an abnormal spatial verification result to indicate that the monitored object is an abnormal monitoring object relative to the electronic work permit.

[0091] Specifically, it can be first determined whether the spatial location of the monitored object is within a spatial intersection zone, and then whether the spatial location of the monitored object is within the monitored space range corresponding to the current electronic work permit. When the monitored object is located within the spatial intersection zone but outside the current monitored space range, the abnormal space verification result can be written to the current electronic work permit identifier, the monitored object identifier, the monitored object's spatial location, and the monitored space range identifier to clarify which electronic work permit the abnormal monitored object is spatially abnormal relative to. For example, if the spatial intersection zone corresponds to both electronic work permit A and electronic work permit B, and the monitored object is located within the spatial intersection zone but outside the monitored space range corresponding to electronic work permit A, the monitored object can be identified as an abnormal monitored object relative to electronic work permit A; for electronic work permit B, an independent spatial verification can be performed based on the monitored space range corresponding to electronic work permit B.

[0092] In this embodiment, by selecting the currently valid fence version from the fence version record and combining it with the spatial expansion distance or spatial contraction distance to determine the monitoring space range, the influence of historical fence versions or expired space ranges on the verification results can be avoided. By determining the spatial location of the monitored object based on the source of observation data using methods such as positioning tag reading, image coordinate transformation, or pose transformation, an executable location basis can be provided for comparing the monitored object with the monitoring space range. By determining whether the monitored object is located within the corresponding monitoring space range for each electronic work permit, it is possible to avoid misjudging the space requirements of the current electronic work permit because the monitored object is located within the permitted area of ​​other electronic work permits, so that the spatial anomaly judgment can be accurately matched to the specific electronic work permit.

[0093] Optionally, in some embodiments, the step of acquiring observation data for the spatial intersection area, i.e., step S103, may further include steps S103B1 to S103B4. Steps S103B1 to S103B4 are used to determine the monitoring density coefficient of the spatial intersection area based on the operational risk level of each electronic work permit corresponding to the spatial intersection area, and to configure the patrol point distribution density and / or the dwell time of each patrol point according to the monitoring density coefficient. Step S103B1: Obtain the operational risk level of each electronic work permit in the set of electronic work permits corresponding to the spatial intersection area.

[0094] Specifically, the job risk level represents the degree of risk associated with the job corresponding to the electronic job permit. It can be determined by the job permit management platform based on the job type, work environment, and hazard information, or it can be configured by safety management personnel during the electronic job permit approval process. Job risk levels can include high-risk, medium-risk, and low-risk levels, or they can be classified as special-grade, level one, level two, and level three. Based on the permit identifier in the electronic job permit set, the job risk level field corresponding to each electronic job permit in the permit database can be queried, forming a set of job risk levels for spatially overlapping areas.

[0095] Step S103B2: Determine the monitoring density coefficient of the spatial intersection area based on the operational risk level of each of the electronic work permits.

[0096] Specifically, the monitoring density coefficient represents the level of monitoring resources required in the spatial intersection area. A pre-established correspondence between operational risk levels and monitoring density coefficients can be established, and the corresponding monitoring density coefficient can be queried based on the operational risk level of each electronic work permit for the spatial intersection area. Alternatively, the operational risk level of each electronic work permit can be converted into corresponding risk parameters, and the monitoring density coefficient can be determined using the maximum value, weighted sum, weighted average, or other methods that reflect the operational risk level. A higher monitoring density coefficient indicates that a denser network of patrol points and / or a longer patrol dwell time is required in the spatial intersection area.

[0097] Step S103B3: Based on the monitoring density coefficient, determine the distribution density of patrol points and / or the dwell time of each patrol point in the spatial intersection area.

[0098] Specifically, the distribution density of basic patrol points can be preset. and basic stay duration The distribution density of target patrol points is determined according to the following formula. Duration of stay at the target : ; ; in, Indicates the monitoring density coefficient. Indicates the distribution density of basic patrol points. Indicates the distribution density of target patrol points. Indicates the basic stay duration. Indicates the duration of stay at the target.

[0099] Patrol point distribution density can be represented by the number of patrol points per unit area, or by the target spacing between adjacent patrol points. The area of ​​the spatial intersection zone is... The number of patrol points can be determined using the following formula. : ; in, Represents the area of ​​the spatial intersection region. Indicates the number of patrol points within the spatial intersection zone. This indicates the rounding up operation.

[0100] Patrol points can be generated within spatial intersection areas using grid sampling, uniform sampling, Poisson disk sampling, or path sampling combined with obstacle distribution. When the monitoring density coefficient increases, the number of patrol points can be increased, the distance between adjacent patrol points can be decreased, and / or the dwell time at each patrol point can be increased; conversely, when the monitoring density coefficient decreases, the number of patrol points can be decreased, the distance between adjacent patrol points can be increased, and / or the dwell time at each patrol point can be shortened. Alternatively, the patrol point distribution density can be adjusted solely based on the monitoring density coefficient, or only the dwell time at each patrol point can be adjusted.

[0101] Step S103B4: Based on the patrol point distribution density and / or the dwell time, obtain the observation data of the spatial intersection area.

[0102] Specifically, patrol routes can be planned based on the generated patrol points and the current location of the monitoring robot, avoiding obstacles and prohibited areas. The monitoring robot can move to each patrol point according to the patrol route and, upon arrival, control its onboard data acquisition equipment to collect observation data for the corresponding dwell time. During the dwell time, the data acquisition equipment can continuously collect observation data or collect data according to a preset sampling period. Observation data collected from multiple patrol points can be associated with patrol point identifiers, collection time, and spatial intersection zone identifiers, and merged into observation data corresponding to the spatial intersection zone in chronological order of collection time.

[0103] In this embodiment, by obtaining the operational risk level of each electronic work permit corresponding to the spatial intersection area and determining the monitoring density coefficient based on each operational risk level, the monitoring resource allocation can be matched with the operational risk corresponding to the spatial intersection area. By calculating the patrol point distribution density, number of patrol points and dwell time based on the monitoring density coefficient, the number of observation positions or the duration of continuous observation can be increased when the monitoring density coefficient is large, thereby increasing the possibility of abnormal operational behavior and environmental anomalies being collected. When the monitoring density coefficient is small, unnecessary observation resource occupation can be reduced, so that limited monitoring resources can be prioritized for spatial intersection areas with high monitoring needs.

[0104] Optionally, in some embodiments, determining the monitoring density coefficient of the spatial intersection area based on the operational risk level of each of the electronic work permits, i.e., step S103B2, may include steps B21 and B22. Steps B21 and B22 are used to quantify the operational risk level into a risk level score, and combine the highest risk level score and the number of electronic work permits to determine the monitoring density coefficient. Step B21: Determine the corresponding risk level score based on the operational risk level of each electronic work permit.

[0105] Specifically, the risk level score can represent the score obtained after numerically processing the risk level of an operation. The mapping relationship between operation risk levels and risk level scores can be pre-stored. For example, Level 1, Level 2, and Level 3 can correspond to 1.00, 0.85, 0.55, and 0.25, respectively. The operation risk level corresponding to each electronic work permit can be read, and the corresponding risk level score for each operation risk level can be determined based on the mapping relationship.

[0106] Step B22: Determine the monitoring density coefficient based on the highest risk level score in the risk level score and the number of electronic work permits in the electronic work permit set; wherein the monitoring density coefficient increases with the increase of the highest risk level score and with the increase of the number of electronic work permits in the electronic work permit set.

[0107] Specifically, the risk level scores corresponding to each electronic work permit can be compared, and the highest risk level score can be determined from among them; the number of electronic work permits in the set of electronic work permits can also be counted. The monitoring density coefficient can be determined according to the following formula: ; in, Indicates the monitoring density coefficient. This represents the highest risk level score in the set of electronic work permits. This indicates the number of electronic work permits in the set of electronic work permits. This indicates the preset superposition bonus coefficient.

[0108] For example, a spatial intersection zone corresponds to one Level 1 electronic work permit and one Level 2 electronic work permit. The risk level score corresponding to the Level 1 electronic work permit can be 0.85, and the risk level score corresponding to the Level 2 electronic work permit can be 0.55. With a preset cumulative bonus coefficient of 0.15, the monitoring density coefficient can be: ; Other calculation methods that allow the monitoring density coefficient to increase with the highest risk level score and the number of electronic work permits can also be used; this embodiment does not specifically limit this method.

[0109] In this embodiment, by converting different job risk levels into risk level scores that can be uniformly compared and calculated, the inability of textual levels to directly participate in the calculation of monitoring resources can be avoided; by determining the basic level of the monitoring density coefficient based on the highest risk level score, the average weakening of high-risk jobs due to the existence of other low-risk jobs can be avoided; by increasing the monitoring density coefficient according to the number of electronic work permits, the mutual influence and risk coupling of jobs brought about by the increase in the number of concurrent jobs in the same area can be further reflected, so that the monitoring density coefficient can simultaneously reflect the highest risk of a single job and the superimposed risk generated by the concurrent occurrence of multiple jobs.

[0110] Optionally, in some embodiments, patrol points within the spatial intersection area can be generated based on the monitoring density coefficient. The spacing between the patrol points can decrease as the monitoring density coefficient increases, and / or the dwell time of the patrol points can increase as the monitoring density coefficient increases.

[0111] Specifically, candidate patrol points can be generated within the spatial intersection area according to a preset sampling method based on the area boundary. The preset sampling method can include regular grid sampling, uniform random sampling, Poisson disk sampling, or non-uniform sampling based on risk hotspots. The target spacing between patrol points can be determined based on the monitoring density coefficient. (Base target spacing) At that time, target spacing It can satisfy: ; in, Indicates the basic target spacing. This indicates the target spacing determined based on the monitoring density coefficient.

[0112] As the surveillance density coefficient increases, the target spacing decreases, allowing for the generation of more patrol points per unit area. The dwell time of patrol points can also be determined based on the surveillance density coefficient. The base dwell time is... At that time, the duration of the target stay It can satisfy: ; in, Indicates the basic stay duration. Indicates the duration of stay at the target.

[0113] Therefore, increasing the monitoring density coefficient can reduce the distance between patrol points and increase the dwell time at each patrol point.

[0114] In this embodiment, by generating patrol points in the spatial intersection area based on the monitoring density coefficient, the number and spatial distribution of patrol points can be matched with the operational risks of the spatial intersection area; by decreasing the spacing between patrol points as the monitoring density coefficient increases, the number of observation positions in the high-risk spatial intersection area can be increased; by increasing the dwell time of patrol points as the monitoring density coefficient increases, the continuous observation time in the high-risk spatial intersection area can be extended, thereby increasing the possibility of timely collection of abnormal operational behaviors or environmental anomalies.

[0115] Optionally, in some embodiments, the transition cost between patrol points can be determined based on the drivability cost map of the legged robot, and the access order of each patrol point can be determined based on the transition cost to generate a patrol topology.

[0116] A accessibility cost map is a map that quantifies the difficulty of a legged robot traversing different locations on-site. The accessibility cost map can be a 2D grid map, a 3D voxel map, or other data structures capable of representing traversable areas on-site. Each grid or spatial location in the accessibility cost map corresponds to a accessibility cost value. The accessibility cost value can be determined based on at least one of the following: ground slope, ground undulation, obstacle distance, passage width, ground adhesion conditions, step height, or prohibited areas. A higher accessibility cost value indicates a higher difficulty or risk for the legged robot traversing the corresponding location.

[0117] For any two patrol points, candidate paths connecting the two patrol points can be determined in the drivability cost graph. The transition cost between the two patrol points is then determined based on at least one of the following: the drivability cost at each location traversed by the candidate path, the length of the candidate path, and the number of turns. The transition cost between the two patrol points can satisfy the following: ; in, Indicates patrol point To the patrol point The transition costs Indicates patrol point To the patrol point Candidate path length, This represents the set of locations traversed by the candidate path. Indicates the position in the candidate path The corresponding value of passage, This represents the turning cost of the candidate path. and This indicates the corresponding weight.

[0118] First, the shortest path algorithm can be used to determine the minimum transition cost between any two patrol points. Then, each patrol point is used as a topology node, and the minimum transition cost is used as the weight of the topology edge. The visiting order of each patrol point is then determined using algorithms for solving the traveling salesman problem, greedy sorting, heuristic search, or other multi-node path sorting algorithms. The data structure formed by the patrol points, the connections between them, the transition costs, and the visiting order can be called the patrol topology. Based on the visiting order recorded in the patrol topology and the traversable paths between adjacent patrol points, a patrol path for the legged robot to execute can be generated.

[0119] In this embodiment, by using the drivability cost map to quantify the impact of different field areas on the passage of the legged robot, the transition cost between patrol points can reflect not only the geometric distance, but also the actual passage difficulty such as ground slope, obstacles and passage conditions. By determining the access order of patrol points based on the transition cost, the situation where the legged robot passes through high-cost areas or repeatedly detours can be reduced, making the generated patrol topology more consistent with the actual passage conditions on site.

[0120] Optionally, in some embodiments, if any patrol point is located in an impassable area, the patrol point can be removed from the patrol topology and an alternative patrol point can be generated in an impassable area adjacent to the patrol point.

[0121] Impassable areas can refer to areas that legged robots cannot safely enter or are not allowed to enter. These can include areas occupied by fixed obstacles, temporarily closed areas, areas exceeding the maximum stride height of the legged robot, areas exceeding the maximum allowable slope, or areas where the cost of passage is greater than a preset passage threshold.

[0122] The location of patrol points can be matched with the drivability cost graph. When the location of a patrol point is marked as impassable, or when the drivability cost corresponding to the location of a patrol point is greater than a preset drivability threshold, the patrol point can be identified as an invalid patrol point, and the invalid patrol point and the topological edges connected to the invalid patrol point can be deleted from the patrol topology.

[0123] A passable location can be searched within a preset search radius, centered on an invalid patrol point. Alternative patrol points can be determined based on the distance between candidate passable locations and invalid patrol points, the passable cost of the candidate passable location, and the coverage of the original monitoring area by the candidate passable location. The replacement cost of a candidate passable location can satisfy the following: ; in, Indicates the passable location of the candidate. The cost of substitution This indicates the distance between a candidate passable location and an invalid patrol point. Indicates the passable location of the candidate. The corresponding value of passage, Indicates the passable location of the candidate. Regarding the coverage ratio of the original guardianship area, and This indicates the corresponding weight.

[0124] The candidate passable location with the lowest alternative cost can be identified as the alternative patrol point and added to the patrol topology. Then, the transition cost and access order between the alternative patrol point and its adjacent patrol points are re-determined. If there is no passable path between the alternative patrol point and at least one adjacent patrol point, the candidate passable location with the second lowest alternative cost can be selected until the selected candidate passable location can be connected to at least one patrol point in the patrol topology.

[0125] In this embodiment, by removing the corresponding patrol point when it is located in an impassable area, the legged robot can be prevented from entering the obstacle area or high-risk passage area according to the original patrol topology. By generating alternative patrol points in the passable area adjacent to the original patrol point and comprehensively considering the position offset, passage cost and monitoring coverage, the alternative patrol points can be selected. This can ensure that the legged robot can pass while maintaining the monitoring range corresponding to the original patrol point as much as possible, and reduce the impact of patrol point failure on the monitoring integrity of the spatial intersection area.

[0126] Optionally, in some embodiments, the method may further include steps S201 to S204. Steps S201 to S204 are used to respond to electronic work permit related events, update the currently effective electronic work permit and corresponding information, and dynamically adjust the spatial intersection area and monitoring resources accordingly. Step S201: In response to the creation event, revocation event, spatial scope change event, work risk level change event, or status change event of the electronic work permit, update the set of electronic work permits in effect and / or the information corresponding to the electronic work permit.

[0127] Specifically, users can subscribe to license events published by the work permit management platform via the message bus, or query the platform at preset intervals and identify license changes based on the results of two consecutive queries. Creation events indicate the creation and activation of a new electronic work permit; revocation events indicate the revocation, closure, or termination of an electronic work permit; spatial scope change events indicate adjustments to the spatial scope corresponding to an electronic work permit; work risk level change events indicate an increase or decrease in the work risk level corresponding to an electronic work permit; and status change events indicate a change in the electronic work permit's status between pending activation, activated, suspended, resumed, or closed. Upon detecting a creation event, the newly created and activated electronic work permit can be added to the set of activated electronic work permits; upon detecting a revocation event, the corresponding electronic work permit can be removed; upon detecting a spatial scope change event or a work risk level change event, the spatial scope or work risk level of the corresponding electronic work permit can be updated; and upon detecting a status change event, the status can be used to determine whether the corresponding electronic work permit should be added to or removed from the set of activated electronic work permits.

[0128] Step S202: Based on the updated and active electronic work permits, redetermine the spatial intersection zone and the set of electronic work permits corresponding to the spatial intersection zone.

[0129] Specifically, for newly added, removed, or spatially altered electronic work permits (EMPs), other valid EMPs whose spatial extent may overlap with the corresponding EMP can be queried, and the affected spatial overlap areas can be recalculated; alternatively, the spatial overlap areas corresponding to all valid EMPs can be recalculated. When a new EMP is added, it can create a new spatial overlap area or increase the number of EMPs corresponding to an existing spatial overlap area; when an EMP is removed, the spatial overlap area associated with the removed EMP may disappear, or the set of EMPs corresponding to the spatial overlap area may change; when the spatial extent of an EMP changes, the regional boundaries of the spatial overlap area and the corresponding set of EMPs can be redefined.

[0130] Step S203: Based on the operational risk level of each electronic work permit in the set of electronic work permits corresponding to the redefined spatial intersection area, redetermine the monitoring density coefficient of the spatial intersection area.

[0131] Specifically, the current work risk level corresponding to each electronic work permit in the newly determined set of electronic work permits can be read, and the monitoring density coefficient can be recalculated according to the aforementioned method for determining the monitoring density coefficient. When the method for determining the monitoring density coefficient considers the number of electronic work permits, the monitoring density coefficient can change with the number of electronic work permits when the number of electronic work permits in the set changes; similarly, when the work risk level corresponding to an electronic work permit changes, the monitoring density coefficient can change with the risk parameters corresponding to that work risk level, the highest risk level score, or other risk calculation results.

[0132] Step S204: Based on the redefined monitoring density coefficient, adjust the distribution density of patrol points and / or the dwell time of each patrol point in the spatial intersection area.

[0133] Specifically, the newly determined monitoring density coefficient can be compared with the original monitoring density coefficient. If the newly determined monitoring density coefficient increases, the number of patrol points can be increased, the distance between adjacent patrol points can be decreased, and / or the dwell time at each patrol point can be increased; if the newly determined monitoring density coefficient decreases, the number of patrol points can be reduced, the distance between adjacent patrol points can be increased, and / or the dwell time at each patrol point can be shortened. After adjusting the patrol points, the patrol path of the monitoring robot can be replanned, and the new patrol points, dwell time, and path information can be sent to the monitoring robot.

[0134] For example, if a high-risk electronic work permit is revoked, the highest risk level score or the number of electronic work permits corresponding to the original spatial intersection area can be reduced, which can correspondingly reduce the density of patrol points in the corresponding spatial intersection area or shorten the dwell time at each patrol point; if a high-risk electronic work permit becomes effective, it can form a new spatial intersection area or increase the number of electronic work permits corresponding to the original spatial intersection area, which can correspondingly increase the density of patrol points in the corresponding spatial intersection area or increase the dwell time at each patrol point.

[0135] In this embodiment, by subscribing to license events or comparing periodic query results, the creation, revocation, spatial range change, operation risk level change, and status change of electronic work permits can be identified in a timely manner, and the currently valid electronic work permits and corresponding information can be updated. By recalculating the spatial intersection area only for electronic work permits affected by changes, unnecessary duplication of calculations can be reduced while ensuring timely updates of spatial relationships. By redetermining the monitoring density coefficient based on the updated number of electronic work permits and operation risk levels, and adjusting the distribution density and / or dwell time of patrol points accordingly, monitoring resources can be synchronized with the number of on-site operations, spatial relationships, and risk levels, avoiding situations where high-risk areas are under-monitored or areas where operations have ended are still being monitored repeatedly after changes in on-site operations in the static patrol plan.

[0136] Optionally, in some embodiments, during the execution of steps S201 to S204, multiple electronic work permit-related events may be received consecutively within a short period. If a spatial intersection zone calculation and patrol planning are performed for each received event, it may result in redundant calculations and frequent changes in the patrol planning. Therefore, if multiple electronic work permit-related events are received within a preset anti-shake time window, the multiple events can be merged, and a replanning can be performed after the preset anti-shake time window ends.

[0137] The preset debouncing time window represents the time range from the receipt of the first electronic work permit-related event to the period during which replanning is paused and subsequent related events are collected. The preset debouncing time window can be set based on the frequency of electronic work permit-related events, the system's allowable response latency, and the computational resources required for replanning. For example, the preset debouncing time window can be set to several seconds to tens of seconds, and can also be adjusted according to the frequency of on-site event updates.

[0138] Upon receiving the first event, a preset stabilization time window can be initiated, and the first event can be written to the event set to be processed. If new events continue to be received within the preset stabilization time window, the new events can be added to the event set to be processed without immediately performing replanning.

[0139] Merging multiple events can include grouping events according to electronic work permit identifiers and determining the final state of the merged event based on the event type. For example, if the same electronic work permit experiences both a creation event and a cancellation event within a preset anti-shake time window, the corresponding electronic work permit can be excluded from the effective permit set based on the final cancellation state; if the same electronic work permit experiences multiple consecutive spatial range change events, the spatial range with the latest event time can be retained; if the same electronic work permit experiences multiple consecutive work risk level change events, the work risk level with the latest event time can be retained; if the same electronic work permit experiences both a pause event and a resumption event within a preset anti-shake time window, the final state at the end of the preset anti-shake time window can be used to determine whether the corresponding electronic work permit is in an effective state.

[0140] After the preset anti-shake time window ends, the active electronic work permits and their corresponding information can be updated all at once based on the merged electronic work permit related events, and a replanning can be performed. The replanning may include at least one of the following: redetermining spatial intersection zones, redetermining the set of electronic work permits corresponding to the spatial intersection zones, redetermining the monitoring density coefficient, and adjusting the patrol point distribution density and / or the dwell time of each patrol point.

[0141] In this embodiment, by suspending replanning within a preset anti-shake time window and collecting continuously arriving electronic work permit-related events, repeated spatial calculations and patrol replanning can be avoided for continuous changes in electronic work permits within a short period of time. By merging multiple electronic work permit-related events according to electronic work permit identifier, event type, and event time, the monitoring scheme can be updated based on the final state of each electronic work permit at the end of the preset anti-shake time window. By performing a replanning once after the preset anti-shake time window ends, the monitoring scheme can be kept consistent with the actual on-site state while reducing redundant calculations and frequent changes in patrol instructions.

[0142] Based on the same inventive concept, the present invention also provides an electronic device, which includes a memory and a processor. The memory stores program instructions, and when the processor reads and runs the program instructions, it executes the steps in any of the above implementation methods.

[0143] The electronic device can be a variety of digital computers, such as laptops, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframes, etc. The electronic device can also be a variety of mobile devices, such as cellular phones, smartphones, wearable devices, and other similar computing devices.

[0144] Figure 2An exemplary structural diagram of the electronic device is disclosed. The electronic device includes one or more processors 1101, a memory 1102, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected via different buses 1105 and can be mounted on a common motherboard or otherwise installed as needed. The electronic device may further include an input device 1103 and an output device 1104. The processor 1101, memory 1102, input device 1103, and output device 1104 can be connected via bus 1105 or other means; the diagram shows an example of connection via bus 1105.

[0145] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing computer program instructions, which, when read and executed by a processor, perform the steps in any of the above implementations.

[0146] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring concurrent multi-ticket operations, characterized in that, The method includes: Obtain multiple electronic work permits that are in effect; wherein each electronic work permit includes at least the spatial range of the corresponding work area and work constraint information; Based on the spatial ranges corresponding to the multiple electronic work permits, a spatial intersection zone and a set of electronic work permits corresponding to the spatial intersection zone are determined; the spatial intersection zone represents the area jointly covered by at least two electronic work permits from the set of electronic work permits; For the aforementioned spatial intersection area, acquire observation data; For each electronic work permit in the set of electronic work permits, based on the work constraint information corresponding to the electronic work permit, compliance verification is performed independently on the observation data to obtain the verification result corresponding to the electronic work permit; The verification results corresponding to each of the aforementioned electronic work permits are written into their respective independent evidence chains.

2. The method according to claim 1, characterized in that, The spatial range includes a two-dimensional polygonal fence; The step of determining the spatial intersection zone and the set of electronic work permits corresponding to the spatial intersection zone based on the spatial ranges corresponding to the multiple electronic work permits includes: Perform spatial Boolean operations on the two-dimensional polygonal fences corresponding to the multiple electronic work permits to obtain spatial operation results; Based on the spatial calculation results, in the case where any two two-dimensional polygon fences intersect, or where one two-dimensional polygon fence is contained within another two-dimensional polygon fence, the corresponding spatial intersection area is determined; In the determined spatial intersection area, for the common intersection formed by three or more of the two-dimensional polygon fences, the common intersection is determined as a multi-vote spatial intersection area, and the common intersection is removed from the pairwise spatial intersection areas corresponding to the multi-vote spatial intersection area. Based on the spatial intersection zones, determine the set of electronic work permits corresponding to each of the spatial intersection zones.

3. The method according to claim 1, characterized in that, The acquisition of observation data for the spatial intersection region includes: Acquire candidate observation data containing spatial location information of the monitored object; Based on the spatial location information, observation data corresponding to the spatial intersection zone is determined from the candidate observation data; wherein, the observation data corresponding to the spatial intersection zone are candidate observation data in which the spatial location of the corresponding monitoring object is located within the spatial intersection zone.

4. The method according to claim 1, characterized in that, The operational constraint information includes spatial constraint information, identity constraint information, and process constraint information; For each electronic work permit in the set of electronic work permits, based on the work constraint information corresponding to that electronic work permit, a compliance check is independently performed on the observation data to obtain a check result corresponding to that electronic work permit, including: For each of the aforementioned electronic work permits, at least one of the following verifications is performed: spatial verification is performed on the observation data based on spatial constraint information determined by the spatial range corresponding to the electronic work permit, to obtain a spatial verification result; identity verification is performed on the observation data based on identity constraint information including the list of authorized personnel corresponding to the electronic work permit, to obtain an identity verification result; process verification is performed on the observation data based on process constraint information including the work process type corresponding to the electronic work permit, to obtain a process verification result. Based on the verification result corresponding to at least one of the performed verifications, the verification result corresponding to the electronic work permit is obtained.

5. The method according to claim 4, characterized in that, The spatial verification of the observation data, based on the spatial constraint information determined by the spatial range corresponding to the electronic work permit, yields the spatial verification result, including: Based on the current fence version of the electronic work permit and the corresponding spatial constraint information, determine the corresponding monitored space range; Determine the spatial location of the monitoring object corresponding to the observation data; Based on the spatial location and the monitoring space range, determine whether the monitored object is located within the monitoring space range, and obtain the spatial verification result; If the monitored object is located within the spatial intersection zone but outside the monitoring space, the spatial verification result is determined as an abnormal spatial verification result to indicate that the monitored object is an abnormal monitoring object relative to the electronic work permit.

6. The method according to claim 1, characterized in that, The acquisition of observation data for the spatial intersection region includes: Obtain the operational risk level of each electronic work permit in the set of electronic work permits corresponding to the spatial intersection area; Based on the operational risk level of each of the aforementioned electronic work permits, the monitoring density coefficient of the spatial intersection area is determined; Based on the monitoring density coefficient, determine the distribution density of patrol points and / or the dwell time of each patrol point within the spatial intersection zone; Based on the patrol point distribution density and / or the dwell time, obtain the observation data of the spatial intersection area.

7. The method according to claim 6, characterized in that, The determination of the monitoring density coefficient for the spatial intersection zone based on the operational risk level of each of the aforementioned electronic work permits includes: Based on the operational risk level of each electronic work permit, the corresponding risk level score is determined; The monitoring density coefficient is determined based on the highest risk level score in the risk level assessment and the number of electronic work permits in the electronic work permit set. The monitoring density coefficient increases with the increase of the highest risk level score and with the increase of the number of electronic work permits in the electronic work permit set.

8. The method according to claim 6 or 7, characterized in that, The method further includes: In response to the creation, revocation, spatial scope change, work risk level change, or status change events of electronic work permits, update the set of electronic work permits in effect and / or the information corresponding to the electronic work permits; Based on the updated and effective electronic work permits, the spatial intersection zones and the set of electronic work permits corresponding to the spatial intersection zones are redefined; Based on the operational risk level of each electronic work permit in the set of electronic work permits corresponding to the redefined spatial intersection zone, the monitoring density coefficient of the spatial intersection zone is redefined. Based on the redefined monitoring density coefficient, the distribution density of patrol points and / or the dwell time of each patrol point in the spatial intersection zone are adjusted.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing program instructions, and the processor executing the steps of the method according to any one of claims 1-8 when running the program instructions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, perform the steps of the method according to any one of claims 1-8.

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