A park unmanned inspection safety monitoring system based on intelligent property

Abstract

The application belongs to the field of park unmanned inspection safety monitoring, and specifically discloses a park unmanned inspection safety monitoring system based on intelligent property, which comprises the following steps: acquiring a UAV inspection path by counting each missing space and each intersection space in a park, and discovering safety hazards in hidden spaces in the park in a timely manner; acquiring a redundant material heat conductivity index in each key space and an overlapping area of the redundant material heat conductivity index and an illumination area, evaluating a cumulative spontaneous combustion effect index between the redundant material heat conductivity index and a meteorological environment, combining a pollution rate of the redundant material in each key space, analyzing a safety coefficient of the redundant material in each key space, and helping to discover spontaneous combustion risks and environmental pollution problems in a timely manner; analyzing priority weight values of each passage path to which each key space belongs, determining a UAV inspection optimized path, and further optimizing the inspection optimized path by extracting historical inspection data, so that the UAV inspection path is more in line with actual requirements of the park.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of park unmanned inspection safety monitoring, and relates to a park unmanned inspection safety monitoring system based on intelligent property. BACKGROUND

[0002] With the progress of science and technology and the development of society, unmanned inspection safety monitoring methods have been widely used in various fields. In park management, unmanned inspection safety monitoring not only can timely detect abnormal conditions and prevent safety accidents, but also can remotely monitor and manage various equipment in the park to ensure the normal operation of the equipment, thereby ensuring the safety of the park. At the same time, by using advanced technical means, automated and intelligent inspection and management in the park can be realized, greatly improving the management efficiency. Therefore, unmanned inspection safety monitoring in the park has important significance in improving safety, improving intelligent level and promoting sustainable development.

[0003] Although the existing park unmanned inspection safety monitoring content can meet most of the safety management requirements, there are still some deficiencies: on the one hand, the existing inspection content is mostly based on fixed monitoring cameras or relies on unmanned aerial vehicles to inspect the overall space of the park. The field of view of the fixed monitoring camera is limited, it is difficult to achieve full coverage, and blind spots are easily formed. Moreover, the unmanned aerial vehicle can only inspect the surface space and cannot fully monitor the area blocked by the construction object, which may cause some key spaces to be missed, affecting the effect of safety management.

[0004] On the other hand, when monitoring the safety state of the park, the existing method often focuses on analyzing the safe operation of the application facilities and lacks in environmental analysis. It does not consider the safety hazards caused by redundant objects affected by the meteorological environment. This limited monitoring method may not be able to timely detect and handle some potential safety hazards, such as spontaneous combustion of flammable materials in high-temperature environments, thereby causing the preventive measures to be inadequate. In addition, the accumulation of redundant objects in the missed space for a long time causes environmental pollution, which is contrary to the concept of sustainable development. SUMMARY

[0005] In view of this, in order to solve the problems raised in the background art, a park unmanned inspection safety monitoring system based on intelligent property is proposed.

[0006] The purpose of the present application can be achieved by the following technical solutions: the present application provides a park unmanned inspection safety monitoring system based on intelligent property, which comprises: a missed space positioning module in the park, which is used to obtain the positions of each fixed camera in the park, extract the picture collection space of the corresponding position, splice it into a fixed monitoring space model, obtain the complete space model of the park, and locate each missed space accordingly.

[0007] a cross-space confirmation module for locating the occlusion space in the picture collection space range corresponding to each fixed camera position, and recording it as each cross-space.

[0008] a patrol path confirmation module for obtaining the positions of each missing space and each cross-space, collectively referring to the spaces corresponding to each position as each patrol space, and further connecting each patrol space as a UAV patrol path, determining each key space on the UAV patrol path, and numbering it as 1, 2,..., i,..., a, and further obtaining a UAV patrol optimization path.

[0009] a safety analysis module for obtaining the regular images of each key space on the UAV patrol optimization path, and collecting video images of each patrol space by a UAV, and comparing and analyzing the facility safety index of each key space on the UAV patrol optimization path.

[0010] a patrol effect evaluation module for comparing the facility safety index of each key space with the preset facility safety index critical value, thereby determining the patrol efficiency of each key space, and obtaining a UAV simplest patrol path.

[0011] For example, the specific confirmation method of each missing space is to extract a mobile patrol space model composed of UAV regular patrol path collected video, integrate it with a fixed monitoring space model, obtain a daily monitoring space model, further compare it with a park complete space model, obtain the area position of each non-overlapping space, which is the area position of each missing space, and extract the area volume of each missing space.

[0012] For example, the specific confirmation method of each cross-space is to obtain each non-overlapping space region by comparing the mobile patrol space model with the park complete space model, record it as each cut space region, and extract the volume of each cut space region.

[0013] Extract the construction object contour volume of each cut space region from the park complete space model, extract the volume proportion of it in the corresponding cut space region, and if the volume proportion is less than the preset volume proportion limit value, extract the cut space region.

[0014] Compare the fixed monitoring space model with the cut space region, if the cut space region is not in the fixed monitoring space model, record the cut space region as a cross-space, and in this way obtain each cross-space.

[0015] For example, the specific connection method of the UAV patrol path is to identify whether the corresponding position of each patrol space is a building boundary position, when the corresponding position of a certain patrol space is a building boundary position, set the position influence weight of the building falling object risk factor of the patrol space to 1, otherwise set it to 0.

[0016] identifying whether the application facility exists in the corresponding position of the inspection space, if the application facility exists in the corresponding position of the inspection space, adding 1 to the position influence weight of the facility damage factor of the inspection space, otherwise adding 0.

[0017] identifying the position influence weight of each influence factor to which each inspection space belongs, and superimposing to obtain the comprehensive influence weight of the corresponding position of each inspection space, denoted as G k , k is the number of the inspection space, k = 1, 2, …, v.

[0018] extracting the missing volume V k analyzing the inspection demand rate of the corresponding position of each inspection space V' represents a unit space volume, and then comparing the inspection demand rate of the corresponding position of each inspection space with the preset inspection demand rate reference value, screening each inspection space whose inspection demand rate is greater than or equal to the preset inspection demand rate reference value, denoted as each key space, and connecting the positions to obtain the UAV inspection path.

[0019] Illustratively, the acquisition step of the UAV inspection optimization path is: locating the center position points of each key space on the UAV inspection path from the complete space model of the park, and extracting each passable layout path between the center position points of each key space and the center position points of its adjacent key space, denoted as each passable path of each key space.

[0020] acquiring the number of construction objects Dig and the construction object avoidance complexity of each passable path of each key space analyzing the priority weight of each passable path of each key space wherein C0 is a constant greater than 2, g is the number of the passable path, g = 1, 2, …, c, and r is the number of the construction object, r = 1, 2, …, d.

[0021] comparing and screening the passable path with the maximum priority weight of each key space, taking it as the optimization path of each key space, and then connecting the optimization paths of each key space to obtain the UAV inspection optimization path.

[0022] Illustratively, the acquisition method of the construction object avoidance complexity of each passable path of each key space is: acquiring the contour volume and shape of each construction object, and acquiring the travel state path requirement width and maximum climbing height of the UAV, and according to this, screening each lateral passable space point position of the contour shape of each construction object, and acquiring the position height.

[0023] The lateral bypass space points of each construction object profile shape are pruned to obtain the remaining lateral bypass space points of each construction object profile shape, and the bypass position of the UAV is obtained. Then, the distance between the bypass position of the UAV and the remaining lateral bypass space points of each construction object profile shape is obtained, and the minimum distance is selected as the bypass distance Lr of each construction object profile.

[0024] The construction object avoidance complexity of each key space is analyzed wherein V r 建 represents the volume of the rth construction object profile, represents the unit profile volume of the construction object, represents the unit bypass distance, J1 and J2 represent the set avoidance importance influence factors corresponding to the construction object profile volume and the bypass distance, respectively, and the construction object avoidance complexity of each key space on each passing path is obtained.

[0025] For example, the facility safety index of each key space on the UAV inspection optimization path is analyzed, and the process is as follows: the regular reference value of each damage degree evaluation index of each application facility is obtained, the video image of each key space on the UAV inspection optimization path is compared with the regular image, and then the actual detection value of each damage degree evaluation index of each application facility in each key space is extracted. The deviation value of each damage degree evaluation index of each application facility in each key space is analyzed, and the maximum deviation value is selected as the damage value of each application facility in each key space, and the application facility damage factor η i of each key space is obtained by accumulation.

[0026] The redundant area in each key space is obtained, the types and areas of the redundancies in each key space are obtained, and then the safety factor δ i of the redundancies in each key space is evaluated.

[0027] The facility safety index of each key space on the UAV inspection optimization path is analyzed wherein β1 and β2 represent the set evaluation proportions corresponding to the application facility damage factor and the redundancy safety factor, respectively.

[0028] For example, the safety factor of the redundancies in each key space is evaluated, which includes: obtaining the pollution rate ε i and the thermal conductivity index γ i of the redundancies in each key space.

[0029] The light area in each key space is extracted, and its area is obtained. The area of the light area is compared with the area of the redundancy area in each key space to obtain the overlapping area S i of the redundancies and the light area in each key space.光 .

[0030] Extract the coverage area of the combustion-supporting material region in each key space, and compare the overlap between the combustion-supporting material region and the redundant material region to obtain the overlap area between the redundant material and the combustion-supporting material in each key space, and then determine the combustion-supporting material influence factor τ in each key space i , evaluate the cumulative spontaneous combustion effect index between the redundant material and the meteorological environment in each key space wherein is the unit overlap area of the redundant material and the light region in the key space.

[0031] The safety factor of the redundant material in each key space is obtained by the evaluation formula , e is the natural constant.

[0032] Illustratively, the determination of the inspection efficiency of each key space corresponds to the content comprising: extracting the facility safety index of each key space belonging to each historical inspection process, comparing it with the preset facility safety index critical value, extracting each key space whose facility safety index belonging to each historical inspection process is less than the preset facility safety index critical value, and recording it as each minor space belonging to each historical inspection process.

[0033] Extract each key space whose facility safety index belonging to each historical inspection process is greater than or equal to the preset facility safety index critical value, and record it as each important space belonging to each historical inspection process.

[0034] Statistically, the number of times each key space is a minor space and the number of times it is an important space are Y i 次 and Y i 重 , respectively, determine the inspection efficiency of each key space Y0 represents the number of key spaces on the optimized path of the unmanned aerial vehicle inspection.

[0035] Compared with the prior art, the beneficial effects of the present application are as follows: (1) The present application obtains the unmanned aerial vehicle inspection path by counting each missed space and each intersection space in the park, which can timely discover the safety hazards of hidden spaces in the park and take corresponding measures to handle them, avoiding the occurrence of safety accidents. At the same time, the flexibility and maneuverability of the unmanned aerial vehicle inspection process are improved.

[0036] (2)The present application can timely discover and warn the possible spontaneous combustion risk by acquiring the redundant heat conductivity index in each key space and the overlapping area with the illumination area, evaluating the cumulative spontaneous combustion effect index between the redundant heat conductivity index and the meteorological environment, so as to take preventive measures to avoid the occurrence of fire and other safety accidents. In combination with the pollution rate of the redundant materials in each key space, the safety factor of the redundant materials in each key space is analyzed, which is helpful to timely discover and handle the environmental pollution problem, protect the environmental quality of the park, and promote the sustainable development of the park.

[0037] (3)The present application can determine the unmanned aerial vehicle inspection optimization path by analyzing the priority weight of each passing path of each key space, and further optimize the unmanned aerial vehicle inspection optimization path by extracting historical inspection data and analyzing the inspection efficiency of each key space, so as to obtain the simplest unmanned aerial vehicle inspection path, so that the unmanned aerial vehicle inspection path can be dynamically adjusted and optimized according to the actual situation, more in line with the actual inspection demand of the park, and unnecessary inspection process is avoided, thereby improving the inspection efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0039] Figure 1 It is a schematic diagram of the system module of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0041] Please refer to Figure 1 As shown in the figure, the present application provides a park unmanned inspection safety monitoring system based on intelligent property, which comprises: a missing space positioning module in the park, a cross space confirmation module, an inspection path confirmation module, a safety analysis module, an inspection effect evaluation module and a database. The missing space positioning module in the park is connected with the cross space confirmation module, the cross space confirmation module is connected with the inspection path confirmation module, the inspection path confirmation module is connected with the safety analysis module, the safety analysis module is connected with the inspection effect evaluation module, the safety analysis module is connected with the inspection effect evaluation module, and the database is connected with the safety analysis module and the inspection effect evaluation module.

[0042] The missing space positioning module in the park is used to obtain the positions of each fixed camera in the park, extract the picture collection space corresponding to the positions, splice the fixed monitoring space model according to the picture collection space, obtain the complete space model of the park, and position each missing space.

[0043] In a preferred embodiment, the specific confirmation method of each missing space is as follows: a mobile inspection space model composed of the video collected by the regular patrol path of the unmanned aerial vehicle is extracted, integrated with the fixed monitoring space model to obtain a daily monitoring space model, and further compared with the complete space model of the park to obtain the position of each non-overlapping space, that is, the position of each missing space, and the volume of each missing space is extracted.

[0044] Specifically, the missing space represents a space region that is not collected by the regular patrol video of the unmanned aerial vehicle and the fixed camera.

[0045] The intersection space confirmation module is used to position the occlusion space in the picture collection space range corresponding to the position of each fixed camera, and record it as each intersection space. The intersection space represents a space region in the mobile inspection space model that is not collected by the regular patrol video of the unmanned aerial vehicle due to the existence of the occlusion.

[0046] In a preferred embodiment, the specific confirmation method of each intersection space is as follows: each non-overlapping space region is obtained by comparing the mobile inspection space model with the complete space model of the park, recorded as each divided space region, and the volume of each divided space region is extracted.

[0047] The contour volume of the construction object to which each divided space region belongs is extracted from the complete space model of the park, and the ratio between the contour volume and the volume of the corresponding divided space region is taken as the volume proportion of the contour volume in the corresponding divided space region. If the volume proportion is less than a preset volume proportion limit value, the divided space region is extracted.

[0048] The fixed monitoring space model is compared with the divided space region. If the divided space region is not in the fixed monitoring space model, the divided space region is recorded as an intersection space, and each intersection space is obtained in this way.

[0049] The inspection path confirmation module is used to obtain the positions of each missing space and each intersection space, and each position corresponding space is collectively referred to as each inspection space. Then, each inspection space is connected as a patrol path of the unmanned aerial vehicle, each key space on the patrol path of the unmanned aerial vehicle is determined, numbered as 1, 2,... i,... a, and then the optimized patrol path of the unmanned aerial vehicle is obtained.

[0050] In a preferred embodiment, the specific connection mode of the UAV inspection path is as follows: the positions of each building and each inspection space are located from the complete space model of the park, the distances between each inspection space position and each building position are compared, the building position closest to each inspection space position is screened out, the closest distance of the building position closest to each inspection space position is counted, and it is compared with the set boundary distance influence value. If the closest distance of the building position closest to each inspection space position is less than the set boundary distance influence value, it indicates that the corresponding position of the inspection space is a building boundary position. Accordingly, whether the corresponding position of each inspection space is a building boundary position is counted. When the corresponding position of each inspection space is a building boundary position, the position influence weight of the building falling object risk factor of the inspection space is set to 1, otherwise it is set to 0.

[0051] The layout positions of each application facility are extracted from the complete space model of the park, which are compared with the corresponding positions of each inspection space to obtain the number of application facilities in each inspection space. If the number of application facilities in a certain inspection space is greater than 0, it indicates that there is an application facility in the corresponding position of the inspection space. Accordingly, whether there is an application facility in the corresponding position of each inspection space is identified, and then for the inspection space with an application facility, the position influence weight of the facility damage factor is added by 1, otherwise it is added by 0.

[0052] Based on the preset position influence weight analysis mode of each influence factor, the position influence weight of each influence factor corresponding to the position of each inspection space is identified, and the comprehensive influence weight of the corresponding position of each inspection space is obtained by superposition, denoted as G k , k is the number of inspection space, k = 1, 2,..., v. Wherein each influence factor includes building falling object risk factor, facility damage factor, human flow activity factor, etc.

[0053] For example, for a certain inspection space, if the position influence weight of the building falling object risk factor is set to 1, the position influence weight of the facility damage factor is 0, and the position influence weight of the human flow activity factor is 1, then the comprehensive influence weight of the corresponding position of the inspection space is G = 1 + 0 + 1.

[0054] The missing volume V k of each inspection space is extracted, the inspection demand rate of the corresponding position of each inspection space is analyzed V' represents the unit space volume, and then the inspection demand rate of the corresponding position of each inspection space is compared with the preset inspection demand rate reference value. The inspection spaces with an inspection demand rate greater than or equal to the preset inspection demand rate reference value are screened out, denoted as each key space, and the positions of the key spaces are connected to obtain the UAV inspection path.

[0055] The extracting the missing volume belonging to each inspection space specifically includes: comparing each inspection space with each intersection space, if a certain inspection space can match a certain intersection space, then extracting the construction outline volume V0 of the inspection space from the construction outline volume of each split space region, and extracting the region volume V of the inspection space from each split space region volume, and taking the region volume of the missing space as the missing volume belonging to the inspection space; otherwise, the inspection space is a missing space, and the region volume of the missing space is obtained from the region volume of each missing space, that is, the missing volume belonging to the inspection space, so as to obtain the missing volume belonging to each inspection space. 空 , and further taking as the missing volume belonging to the inspection space; otherwise, the inspection space is a missing space, and the region volume of the missing space is obtained from the region volume of each missing space, that is, the missing volume belonging to the inspection space, so as to obtain the missing volume belonging to each inspection space.

[0056] The unmanned aerial vehicle inspection path can be obtained by counting the missing spaces and the intersection spaces in the park, so that the safety hazards of hidden spaces in the park can be found in time, and corresponding measures can be taken for processing, so that safety accidents can be avoided. Meanwhile, the flexibility and maneuverability of the unmanned aerial vehicle inspection process are improved.

[0057] In another preferred embodiment, the obtaining step of the unmanned aerial vehicle inspection optimization path is: locating the key space center position points on the unmanned aerial vehicle inspection path from the park complete space model, and extracting each passable layout path between each key space center position point and its adjacent key space center position point, which is recorded as each passable path belonging to each key space.

[0058] The number of constructions D on each passable path belonging to each key space is obtained ig and the construction avoidance complexity The priority weight of each passable path belonging to each key space is analyzed Wherein C0 is a constant greater than 2, i is the number of key spaces, i=1, 2,..., a, g is the number of passable paths, g=1, 2,..., c, and r is the number of constructions, r=1, 2,..., d. The constructions include entertainment area facilities, flower garden trees and the like in the park.

[0059] The number of constructions on each passable path belonging to each key space is the preset storage data in the park complete space model.

[0060] The priority weights of each passable path belonging to each key space are compared with each other, and the passable path with the maximum priority weight belonging to each key space is screened out as the optimization path of each key space, and then the optimization paths of each key space are connected to obtain the unmanned aerial vehicle inspection optimization path.

[0061] In another preferred embodiment, the construction object profile shape of each construction object is obtained by extracting the profile volume and shape of each construction object from the complete space model of the park, and obtaining the path requirement width and maximum climbing height of the UAV, and then screening the lateral passable space point positions of the profile shape of each construction object, and obtaining the position height thereof. The path requirement width and maximum climbing height of the UAV are preset structural design parameters of the UAV.

[0062] It should be noted that the specific content of the lateral passable space point positions of the profile shape of each construction object includes: taking the path requirement width of the UAV as the safe distance for passing, and proportionally enlarging the profile shape of each construction object by the safe distance for passing to obtain the passable space profile of each construction object, and then uniformly arranging the edge point positions on the passable space profile of each construction object, which are recorded as the edge point positions of the profile shape of each construction object.

[0063] The edge point positions of the profile shape of each construction object are located in the complete space model of the park, and if there is another construction object at a certain edge point position of the profile shape of a certain construction object, the edge point position of the profile shape of the construction object is removed, and the remaining edge point positions of the profile shape of each construction object are counted to obtain the lateral passable space point positions of the profile shape of each construction object, and then the height of each lateral passable space point position of the profile shape of the corresponding construction object is extracted on the passable space profile of each construction object.

[0064] The position height of each construction object is compared with the maximum climbing height of the UAV, and the lateral passable space point positions of the profile shape of each construction object whose position height exceeds the maximum climbing height of the UAV are removed to obtain the remaining lateral passable space point positions of the profile shape of each construction object, the intersection positions between the passable space profile of each construction object and the optimized path of the UAV are extracted in the complete space model of the park, which are recorded as the UAV passing positions of the profile of each construction object, and then the distance between each UAV passing position of the profile of each construction object and the remaining lateral passable space point positions of the profile shape of each construction object is obtained, and the minimum distance is screened out as the passing distance Lr of the profile of each construction object.

[0065] The construction object profile shape of each construction object is obtained by analyzing the construction object profile shape of each construction object Vr = Vr / V r 建 Vr represents the profile volume of the rth construction object, Vr represents the profile volume of the rth construction object, The unit represents the distance of the round, J1 and J2 represent the influence factor of the set avoidance importance degree of the construction object contour volume and the round distance respectively, and then the positions of the construction objects are obtained from the complete space model of the park, which are matched with the positions of the corresponding traffic paths of the corresponding key spaces, and the avoidance complexity of the construction objects on the corresponding traffic paths of the corresponding key spaces is obtained

[0066] The safety analysis module is used to obtain the regular image of each key space on the unmanned aerial vehicle inspection optimization path from the database, and collect the video image of each inspection space by the unmanned aerial vehicle, and compare and analyze the facility safety index of each key space on the unmanned aerial vehicle inspection optimization path.

[0067] In a preferred embodiment, the process of analyzing the facility safety index of each key space on the unmanned aerial vehicle inspection optimization path is as follows: obtaining the regular reference value of each damage degree evaluation index of each application facility from the database, comparing the video image of each key space on the unmanned aerial vehicle inspection optimization path with the regular image, and then extracting the actual detection value of each damage degree evaluation index of each application facility in each key space, comparing it with the regular reference value of the corresponding damage degree evaluation index of the corresponding application facility, obtaining the deviation value of each damage degree evaluation index of each application facility in each key space, screening out the maximum deviation value, which is recorded as the damage value of each application facility in each key space, and accumulating to obtain the application facility damage factor η of each key space i .

[0068] Specifically, the application facilities include poles, street lamps, signs, fire fighting facilities, etc., and the damage degree evaluation indexes of the application facilities include the pole body inclination angle and cable integrity of the poles, the position offset degree and text integrity of the signs, and the rust area and effective date of the fire fighting facilities.

[0069] Comparing the video image of each key space with various redundant image stored in the database, the redundant area in each key space is obtained, and the type and area of the redundant in each key space are obtained, and then the safety coefficient δ of the redundant in each key space is evaluated i . Wherein, the redundant types include the falling detonator, smoke agent, scattered fireworks and firecrackers in the corner, and plastic paper scraps and other floating objects.

[0070] Analyzing the facility safety index of each key space on the unmanned aerial vehicle inspection optimization path Wherein, β1 and β2 represent the set evaluation proportion of the application facility damage factor and the redundant object safety coefficient respectively.

[0071] In another preferred embodiment, the safety factor of the redundant object in each key space is evaluated, including: obtaining the pollution rate and thermal conductivity index of various redundant objects from the database, comparing the pollution rate and thermal conductivity index of various redundant objects with the types of redundant objects in each key space, obtaining the pollution rate epsilon of the redundant object in each key space i and the thermal conductivity index gamma i .

[0072] The light simulation is performed in each key space to obtain the light area and the area of the light area at each sunshine time point in each key space, the area of the light area at each sunshine time point in each key space is compared with each other, the light area corresponding to the maximum value of the area of the light area at the sunshine time point in each key space is screened out, which is recorded as the light area in each key space, and the area of the light area is compared with the area of the redundant object area in each key space to obtain the overlapping area S of the redundant object and the light area in each key space i .

[0073] The combustion-supporting object area coverage S in each key space is extracted i 助 The combustion-supporting object area and the redundant object area are compared to obtain the overlapping area S between the redundant object and the combustion-supporting object in each key space i 叠 , and the combustion-supporting object influence factor in each key space is determined wherein are the unit coverage area of the key space, the unit overlapping area between the redundant object and the combustion-supporting object, respectively, and the cumulative spontaneous combustion effect index between the redundant object and the meteorological environment in each key space is evaluated wherein S0 光 is the unit overlapping area between the redundant object and the light area in the key space.

[0074] The safety factor of the redundant object in each key space is obtained from the evaluation formula , and e is a natural constant.

[0075] The combustion-supporting object area coverage in each key space is the preset storage data in the complete space model of the park.

[0076] The present application can discover and warn the possible spontaneous combustion risk in time by obtaining the thermal conductivity index of the redundant object in each key space and the overlapping area between the redundant object and the light area, so as to take preventive measures to avoid the occurrence of fire and other safety accidents. In combination with the pollution rate of the redundant object in each key space, the safety factor of the redundant object in each key space is analyzed, which is helpful to discover and handle the environmental pollution problem in time, protect the environmental quality of the park, and promote the sustainable development of the park.

[0077] The inspection effect evaluation module is configured to compare the facility safety index of each key space with a preset facility safety index threshold, and determine the inspection efficiency of each key space according to the comparison, and obtain the simplest inspection path of the unmanned aerial vehicle.

[0078] In a preferred embodiment, the determination of the inspection efficiency of each key space comprises the following steps: extracting the facility safety index of each key space in each historical inspection record stored in the database, comparing the facility safety index with the preset facility safety index threshold, and extracting each key space with a facility safety index less than the preset facility safety index threshold as a minor space in each historical inspection process.

[0079] Extracting each key space with a facility safety index greater than or equal to the preset facility safety index threshold as an important space in each historical inspection process.

[0080] Counting the number of times each key space is a minor space and the number of times each key space is an important space, and recording them as Y i 次 , Y i 重 , and determining the inspection efficiency of each key space Y0 represents the number of key spaces on the optimized inspection path of the unmanned aerial vehicle.

[0081] Comparing the inspection efficiency of each key space with a preset inspection efficiency threshold, eliminating each key space with an inspection efficiency lower than the preset inspection efficiency threshold, obtaining each remaining key space, and connecting the remaining key spaces to obtain the simplest inspection path of the unmanned aerial vehicle.

[0082] The application determines the optimized inspection path of the unmanned aerial vehicle by analyzing the priority weight of each passage of each key space, and further optimizes the optimized inspection path of the unmanned aerial vehicle by extracting historical inspection data and analyzing the inspection efficiency of each key space, to obtain the simplest inspection path of the unmanned aerial vehicle, so that the inspection path of the unmanned aerial vehicle can be dynamically adjusted and optimized according to the actual situation, and more in line with the actual inspection needs of the park, avoiding unnecessary inspection process, thereby improving the inspection efficiency.

[0083] The database is configured to store the regular image of each key space on the optimized inspection path of the unmanned aerial vehicle, the regular reference value of each damage degree evaluation index of each application facility, various redundant images, the pollution rate and thermal conductivity index of various redundancies, and store each historical inspection record. The above contents are only examples and descriptions of the concept of the application, and those skilled in the art can make various modifications or supplements to the described specific embodiments or use similar ways to replace them, as long as they do not deviate from the concept of the application or exceed the scope defined by the application, and they should belong to the protection scope of the application.

Claims

1. A park unmanned inspection safety monitoring system based on intelligent property, characterized in that, The system comprises: an omitted space positioning module in the park, configured to obtain positions of fixed cameras in the park, extract picture collection spaces corresponding to the positions, splice the picture collection spaces into a fixed monitoring space model, obtain a complete space model of the park, and position each omitted space according to the complete space model; a cross space confirmation module, configured to position an occlusion space in a picture collection space range corresponding to each fixed camera position, and record the occlusion space as each cross space; The inspection path confirmation module is configured to acquire positions of the missed spaces and the intersection spaces, collectively refer to spaces corresponding to the positions as inspection spaces, connect the inspection spaces as a UAV inspection path, determine key spaces on the UAV inspection path, and number the key spaces as , and further obtain a UAV inspection optimization path. Specifically, the UAV inspection optimization path is obtained by positioning a center position of a key space, extracting a passable path adjacent to the center, acquiring a number of construction objects on the path and a complexity of avoiding the path, calculating a priority weight value of each passable path, screening a path with a maximum weight value, and connecting the path. a safety analysis module, configured to obtain regular images of each key space on an unmanned aerial vehicle (UAV) inspection optimization path, collect video images of each inspection space by the UAV, and compare and analyze facility safety indexes of the key spaces on the UAV inspection optimization path, specifically including: obtaining a regular reference value of a facility damage evaluation index, comparing actual values obtained from images, calculating a maximum deviation value after a deviation value is calculated, and obtaining an application facility damage factor by accumulating the maximum deviation value; obtaining a type and an area of a redundant object in the key space to evaluate a safety coefficient of the redundant object; and calculating the facility safety index according to a set proportion; an inspection effect evaluation module, configured to compare the facility safety index of each key space with a preset facility safety index threshold value, determine an inspection efficiency of each key space according to the comparison, and obtain a simplest UAV inspection path.

2. The park unmanned inspection safety monitoring system based on intelligent property according to claim 1, characterized in that: The specific confirmation manner of each omitted space is as follows: a mobile inspection space model composed of videos collected by the UAV on a regular patrol path is integrated with the fixed monitoring space model to obtain a daily monitoring space model, and the daily monitoring space model is further compared with the complete space model of the park to obtain a region position of each non-overlapping space, that is, a region position of each omitted space, and a region volume of each omitted space is extracted.

3. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 2, characterized in that: The specific confirmation manner of each cross space is as follows: each non-overlapping space region is obtained by comparing the mobile inspection space model with the complete space model of the park, recorded as each divided space region, and a volume of each divided space region is extracted; a volume proportion of a construction object contour volume of each divided space region in the corresponding divided space region is extracted, and if the volume proportion is less than a preset volume proportion limit value, the divided space region is extracted; the fixed monitoring space model is compared with the divided space region, if the divided space region is not in the fixed monitoring space model, the divided space region is recorded as a cross space, and each cross space is obtained in this way.

4. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 1, characterized in that: The specific connection manner of the UAV inspection path is as follows: whether a position corresponding to each inspection space is a building boundary position is identified, when the position corresponding to a certain inspection space is the building boundary position, a position influence weight of a building falling object risk factor of the inspection space is set to 1, otherwise, the position influence weight is set to 0; whether the position corresponding to the inspection space exists an application facility is identified, if the position corresponding to the inspection space exists the application facility, a position influence weight of a facility damage factor of the inspection space is added by 1, otherwise, the position influence weight is added by 0; identify the position influence weight of each influencing factor to which the corresponding position of each inspection space belongs, superimpose to obtain the comprehensive influence weight of the corresponding position of each inspection space, denoted as , is the number of the inspection space, ; extracting each missing volume belonging to each inspection space , analyzing the inspection demand rate of the corresponding position of each inspection space , representing the unit space volume, and then comparing the inspection demand rate of the corresponding position of each inspection space with the preset inspection demand rate reference value, screening out each key space whose inspection demand rate is greater than or equal to the preset inspection demand rate reference value, and connecting the positions of the key spaces to obtain the UAV inspection path.

5. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 3, characterized in that: the obtaining steps of the UAV inspection optimization path are as follows: center position points of each key space on the UAV inspection path are positioned from the complete space model of the park, and each passable layout path between the center position point of each key space and a center position point of an adjacent key space is extracted, recorded as each passable path of each key space. obtaining the number of construction objects on each passage path belonging to each key space and the complexity of each construction object analyzing the priority weight of each passage path belonging to each key space wherein is a set constant greater than 2, is the number of passage paths, , is the number of construction objects, ; The passage with the maximum priority weight value of each key space is screened out as the optimized path of each key space, and the optimized paths of the key spaces are connected to obtain the optimized path of the UAV inspection.

6. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 5, characterized in that: The method for obtaining the complexity of each construction object on each passage of each key space is as follows: The contour volume and shape of each construction object are obtained, and the path requirement width and maximum climbing height of the UAV are obtained, based on which the lateral passable space point positions of the contour shape of each construction object are screened out, and the position height is obtained; The lateral circumventing space point positions exceeding the maximum climbing height of the unmanned aerial vehicle are removed from the positions of the contour shape of each construction object, to obtain each remaining lateral circumventing space point position of the contour shape of each construction object, to obtain the circumventing position of the unmanned aerial vehicle relative to the contour of each construction object, and to further obtain the distance between the circumventing position of the unmanned aerial vehicle and each remaining lateral circumventing space point position of the contour shape of each construction object, and to screen out the minimum distance as the circumventing distance of the contour of each construction object ; Analysis yields the complexity of circumvention for each building. ,in Indicates the first The outline and volume of the building. Indicates the unit outline volume of the building. Indicates the unit detour distance. The factors representing the importance of avoidance for the building outline volume and the detour distance are respectively used to summarize the avoidance complexity of each building on each passageway in each key space.

7. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 4, characterized in that: The facility safety index of each key space on the optimized path of the UAV inspection is analyzed, and the process is as follows: The routine reference values of each damage degree evaluation index of each application facility are obtained, the video images of each key space on the optimized inspection path of the unmanned aerial vehicle are compared with the routine images, and then the actual detection values of each damage degree evaluation index of each application facility in each key space are extracted, the deviation values of each damage degree evaluation index of each application facility in each key space are analyzed, the maximum deviation value is screened out and recorded as the damage value of each application facility in each key space, and the application facility damage factors of each key space are obtained by accumulation ; Obtaining the redundant area in each key space, obtaining the type and area of the redundancies in each key space, and then evaluating the safety factor of the redundancies in each key space ; Analyzing facility safety indexes of each key space on the optimal path of unmanned aerial vehicle inspection , wherein respectively represent the set evaluation proportion corresponding to the facility damage factor and the redundant object safety coefficient.

8. The smart property based park unmanned inspection safety monitoring system according to claim 7, characterized in that: The safety coefficient of the redundancy in each key space is evaluated, and the content includes: Obtaining contamination rates of redundancies in each critical space and thermal conductivity index ; extracting the light area in each key space, obtaining the area, comparing the area with the redundant area in each key space, and obtaining the overlapping area of the redundant and the light area in each key space ; The area of the combustion-supporting region in each key space is extracted, the combustion-supporting region is compared with the redundant region in overlap, the overlap area between the redundant and the combustion-supporting in each key space is obtained, and then the combustion-supporting influence factor in each key space is determined , the cumulative spontaneous combustion effect index between the redundant and the meteorological environment in each key space is evaluated , wherein is the unit overlap area of the redundant and the light region in the key space The safety factor of each key space is obtained from the evaluation formula where e is the natural constant.

9. The unmanned inspection and safety monitoring system for a park based on a smart property according to claim 1, characterized in that: The corresponding content of the determination of the inspection efficiency of each key space includes: The facility safety index of each key space in each historical inspection process is extracted, and is compared with the preset facility safety index critical value, each key space with a facility safety index less than the preset facility safety index critical value in each historical inspection process is extracted, and is recorded as each minor space in each historical inspection process; Each key space with a facility safety index greater than or equal to the preset facility safety index critical value in each historical inspection process is extracted, and is recorded as each important space in each historical inspection process; The number of times each key space is counted as a secondary space and as an important space is counted respectively, and denoted as The inspection efficiency of each key space is determined , The number of key spaces on the optimal path of the unmanned aerial vehicle inspection is represented.

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