CN115938009A - Intelligent electronic patrol positioning method and system - Google Patents
Intelligent electronic patrol positioning method and system Download PDFInfo
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- CN115938009A CN115938009A CN202310209145.1A CN202310209145A CN115938009A CN 115938009 A CN115938009 A CN 115938009A CN 202310209145 A CN202310209145 A CN 202310209145A CN 115938009 A CN115938009 A CN 115938009A
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Abstract
The invention provides an intelligent electronic inspection positioning method, which comprises the steps of obtaining a target area containing important levels; the target area is represented by a three-dimensional coordinate set; determining a limiting track according to the target area, and determining a speed function of the inspection tour according to the importance level; receiving a polling requirement input by a user, and determining the type and the number of the polling devices according to the polling requirement; and acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report. The invention also provides an intelligent electronic inspection positioning system. The invention determines a limit track according to a target area input by a manager, installs a preset number of polling devices with the same motion condition in the limit track, and carries out omnibearing timing polling on a worker; in addition, the work flow of the inspection device can be changed easily, the regularity is weak, evasive response is difficult to be made by workers, and the inspection comprehensiveness is greatly improved.
Description
Technical Field
The invention relates to the technical field of regional inspection, in particular to an intelligent electronic inspection positioning method and system.
Background
Along with the improvement of productivity, production activities are more and more, and these production activities all have the link of patrolling and examining, and the security of production activities is guaranteed in the purpose, prevents that the staff from appearing the operation of violating the rules and regulations.
The conventional inspection mode mostly depends on manual periodic inspection, and inspection personnel perform regular inspection, and as the inspection work is repeated and tedious, many inspection personnel can be idle in working and are difficult to find detailed problems. How to ensure the comprehensiveness and the fatigue degree of the routing inspection work is the technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The invention aims to provide an intelligent electronic inspection positioning method and system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
an intelligent electronic inspection positioning method, comprising:
acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
determining a limiting track according to the target area, and determining a speed function of the inspection tour according to the importance level;
receiving a polling requirement input by a user, and determining the type and the number of the polling devices according to the polling requirement;
and acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
As a further scheme of the invention: the step of acquiring the target area containing the importance level comprises the following steps:
receiving boundary information input by a user, and building a global scene containing a preset scale according to the boundary information;
receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
determining an observation point in the observation area, and acquiring an actual scene of a target area at the observation point;
identifying the actual scene according to the recorded facility database, and correcting the universe scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
and displaying the corrected global scene containing the target areas, and receiving confirmation information sent by the user and the importance level of each target area.
As a further scheme of the invention: the step of determining a limiting track according to the target area and determining a speed function of the inspector according to the importance level comprises the following steps:
reading an observation area of a target area, and acquiring the height span of the observation area;
selecting a trajectory plane in the height span;
projecting the target area on the trajectory plane to obtain an area distribution map;
determining a limiting track based on the region distribution map;
determining sampling points in the limiting track according to a preset sampling frequency, inquiring the important level of a corresponding nearest target area at the sampling points, and determining the movement speed according to the important level;
counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed.
As a further scheme of the invention: the method comprises the following steps of receiving a polling requirement input by a user, and determining the type and the number of polling devices according to the polling requirement, wherein the steps comprise:
inquiring definition requirements of all target areas, and determining the type of the inspection tour according to the definition requirements;
and receiving a polling period input by a user, and determining the number of polling devices according to the polling period.
As a further scheme of the invention: the method comprises the following steps of acquiring a patrol image fed back by a patrol detector in real time, identifying the patrol image, and generating a patrol report, wherein the steps comprise:
acquiring a patrol image containing a position tag fed back by a patrol device in real time; the position is a distance relative to the starting point of the limiting track;
inquiring a target area corresponding to the inspection image according to the position, and storing the target area in a database corresponding to the target area; wherein the image storage sequence in the database is determined by the image acquisition time;
identifying different databases based on preset threads, and determining risk characteristics and probabilities of different target areas according to identification results;
and (4) counting all risk characteristics and probabilities thereof to obtain a routing inspection report.
As a further scheme of the invention: the steps of identifying different databases based on preset threads and determining risk characteristics and probabilities of different target areas according to identification results comprise:
sequentially identifying the patrol inspection images in a preset time period range in the database based on a preset neural network model, and acquiring equipment information and personnel information;
inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
counting the abnormal degree, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
and inputting the abnormal curve and the derivative curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof.
The technical scheme of the invention also provides an intelligent electronic inspection positioning system, which comprises:
the target area acquisition module is used for acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
the path setting module is used for determining a limiting track according to the target area and determining a speed function of the inspection tour according to the importance level;
the system comprises a polling device selection module, a polling device selection module and a polling device selection module, wherein the polling device selection module is used for receiving polling requirements input by a user and determining the types and the number of polling devices according to the polling requirements;
and the report generation module is used for acquiring the patrol inspection image fed back by the patrol inspection device in real time, identifying the patrol inspection image and generating a patrol inspection report.
As a further scheme of the invention: the target area acquisition module includes:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
the observation region determining unit is used for receiving a target region selected by a user based on the global scene and determining an observation region of the target region;
an actual scene obtaining unit, configured to determine an observation point in the observation region, and obtain an actual scene of a target region at the observation point;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance levels of the target areas.
As a further scheme of the invention: the path setting module includes:
the span acquisition unit is used for reading an observation area of the target area and acquiring the height span of the observation area;
the trajectory surface selecting unit is used for selecting a trajectory surface in the height span;
the distribution diagram determining unit is used for projecting the target area on the track surface to obtain an area distribution diagram;
the track determining unit is used for determining a limiting track based on the region distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to a preset sampling frequency, inquiring the importance levels of the corresponding nearest target areas at the sampling points, and determining the movement speed according to the importance levels;
the speed counting unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed.
As a further scheme of the invention: the patrol inspection device selection module comprises:
the type selection unit is used for inquiring the definition requirements of all target areas and determining the type of the inspection tour according to the definition requirements;
and the quantity selection unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of determining a limit track according to a target area input by a manager, installing a preset number of polling devices with the same motion condition in the limit track, and performing omnibearing timing polling on workers; in addition, the work flow of the inspection device can be changed easily, the regularity is weak, evasive response is difficult to be made by workers, and the inspection comprehensiveness is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a flow chart diagram of an intelligent electronic inspection positioning method.
Fig. 2 is a first sub-flow block diagram of the intelligent electronic patrol positioning method.
Fig. 3 is a second sub-flow block diagram of the intelligent electronic patrol locating method.
Fig. 4 is a third sub-flow block diagram of the intelligent electronic patrol positioning method.
Fig. 5 is a fourth sub-flow block diagram of the intelligent electronic patrol locating method.
Fig. 6 is a block diagram of the structure of the intelligent electronic patrol positioning system.
Detailed description of the preferred embodiments
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 is a flow chart of an intelligent electronic inspection positioning method, in an embodiment of the present invention, the intelligent electronic inspection positioning method includes:
step S100: acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
the target area is an area needing to be inspected, and the area needing to be inspected is predetermined by workers in a workshop or a working area; the area to be inspected is a range, which is a three-dimensional range defined by three-dimensional coordinates pointing to points on the boundary of the three-dimensional range.
Step S200: determining a limiting track according to the target area, and determining a speed function of the inspection tour according to the importance level;
after the target area is determined, a limiting track can be determined according to the position of the target area, and the limiting track is used for limiting the patrol detector; in a hardware architecture, the limit track can be a rail on which the polling device moves; and when the polling device moves on the track and moves to different target areas, determining the movement speed of the polling device according to the corresponding importance level, wherein the higher the importance level is, the lower the speed of the polling device is.
Step S300: receiving a polling requirement input by a user, and determining the type and the number of the polling devices according to the polling requirement;
the inspection requirements are input by a user, the user determines how many times to inspect once and how much definition is needed for each target area at least according to the actual conditions of the working area, and the how many times to inspect once represents how many inspection devices are placed, and the motion process of each inspection device is the same; the required resolution determines the type of inspector.
Step S400: acquiring a patrol inspection image fed back by a patrol inspection device in real time, identifying the patrol inspection image and generating a patrol inspection report;
the method comprises the steps of obtaining patrol data fed back by a patrol device in real time, wherein the patrol data are image data, identifying the image data to obtain analysis results of each target area, counting the analysis results of each target area, and obtaining a whole patrol report.
Fig. 2 is a first sub-flow block diagram of the intelligent electronic inspection positioning method, where the step of acquiring a target area containing an importance level includes:
step S101: receiving boundary information input by a user, and building a global scene containing a preset scale according to the boundary information;
boundary information is input by a user, and a global scene corresponding to the whole work area to be analyzed can be determined according to the boundary information; typically, the global scene is a cube.
Step S102: receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
after the global scene is built, a user inputs selection information, a target area is determined according to the selection information, the target area can be a three-dimensional curved surface or a plane, and an observation area of the target area can be determined according to a sight rule in the global scene.
Step S103: determining an observation point in the observation area, and acquiring an actual scene of a target area at the observation point;
determining an observation point in the observation area, and acquiring an actual scene of a target area at the observation point; in general, an actual image of a target area is photographed at each observation point as an actual scene.
Step S104: identifying the actual scene according to the recorded facility database, and correcting the universe scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
the actual scene is identified in a comparison mode, and because facilities in a working area are limited, the identification process of the comparison mode is very simple and is easy to complete; according to the identification result, which facilities are arranged at each position in the global scene can be inquired, and then the global scene is adjusted to obtain the global scene which is more in line with the reality.
Step S105: displaying the corrected global scene containing the target areas, and receiving confirmation information sent by a user and the importance level of each target area;
displaying the corrected global scene containing the target area, judging by the user, and if the user thinks that no problem exists, sending confirmation information and the importance level of the confirmation information; the importance levels are used to characterize the importance of the respective target areas.
Fig. 3 is a second sub-flow block diagram of the intelligent electronic inspection positioning method, where the step of determining a limiting trajectory according to the target area and determining a speed function of the inspector according to the importance level includes:
step S201: reading an observation area of a target area, and acquiring the height span of the observation area;
reading observation areas of all target areas, and acquiring the height span of the observation areas;
step S202: selecting a trajectory plane in the height span;
comparing all the height spans to determine a detection height, namely the track surface; the types of the track surfaces are various, and only one track surface is selected at random.
Step S203: projecting the target area on the trajectory surface to obtain an area distribution map;
the target area is a three-dimensional area, and a regional distribution map can be obtained by projecting the three-dimensional area.
Step S204: determining a limit trajectory based on the region distribution map;
and determining a limiting track in the region distribution map, wherein the requirement of the limiting track is that the inspection device can acquire information of all target regions in the movement process of the limiting track.
Step S205: determining sampling points in the limiting track according to a preset sampling frequency, inquiring the important level of a corresponding nearest target area at the sampling points, and determining the movement speed according to the important level;
and segmenting the limiting track to obtain sampling points, inquiring the nearest target area at each sampling point, and determining the current movement speed according to the importance level of the target area.
Step S206: counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed;
counting all the movement speeds to obtain a speed function; it should be noted that the independent variable of the speed function is not time, but a distance from the starting point of the limit trajectory.
Fig. 4 is a third sub-flow block diagram of the intelligent electronic routing inspection positioning method, where the step of receiving a routing inspection requirement input by a user and determining the types and the number of the routing inspection devices according to the routing inspection requirement includes:
step S301: inquiring definition requirements of all target areas, and determining the type of the inspection tour according to the definition requirements;
step S302: and receiving a polling period input by a user, and determining the number of polling devices according to the polling period.
The determination of the type and number of the inspectors is not difficult, the type being determined by the cleanliness requirements and the number being determined by the inspection cycle.
Fig. 5 is a fourth sub-flow block diagram of the intelligent electronic inspection positioning method, where the steps of acquiring an inspection image fed back by an inspection device in real time, identifying the inspection image, and generating an inspection report include:
step S401: acquiring a patrol image containing a position tag fed back by a patrol detector in real time; the position is a distance relative to the starting point of the limiting track;
and establishing a connecting channel between the inspection device and the inspection device, and acquiring an inspection image based on the connecting channel.
Step S402: inquiring a target area corresponding to the inspection image according to the position, and storing the target area in a database corresponding to the target area; wherein the image storage sequence in the database is determined by the image acquisition time;
the position of the inspection device corresponds to a target area, and the target area is inquired according to the position and is the target area corresponding to the inspection image; each target area is provided with a database belonging to the target area, and the inspection image is stored in the corresponding database; the elements in the database are ordered by time.
Step S403: identifying different databases based on preset threads, and determining risk characteristics and probabilities of different target areas according to identification results;
the databases of different target areas are identified, so that the risk characteristics of each target area and the probability of the risk characteristics can be obtained.
Step S404: counting all risk characteristics and probabilities thereof to obtain a routing inspection report;
and (4) counting the risk characteristics of all target areas and the probability of the risk characteristics to appear, and generating a patrol report.
As a preferred embodiment of the technical solution of the present invention, the step of identifying different databases based on preset threads and determining risk characteristics and probabilities of different target areas according to the identification result includes:
sequentially identifying the inspection images in the preset time period range in the database based on a preset neural network model to obtain equipment information and personnel information;
the inspection image belongs to an image in a global scene, the type of the inspection image is limited, and equipment information and personnel information can be obtained only by training a neural network model according to a pre-collected sample and identifying the inspection image based on the neural network model when a new inspection image is received; the equipment information comprises equipment types and the levels and the number of workers required by the equipment; the person information includes the level and number of persons already present in the current target area.
Inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
inquiring personnel requirements according to the equipment information, verifying whether the personnel information has problems according to the personnel requirements, and determining the abnormal degree of each inspection image; for example, in the case where two technicians are required, only one technician is required, and a certain degree of abnormality exists; if there is no technician, the degree of abnormality is high.
Counting the abnormal degree, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
and counting the abnormal degrees of the routing inspection images at different time to obtain an abnormal curve, and performing multiple derivation on the abnormal curve to obtain the derivative curves of different orders.
Inputting the abnormal curve and the derivative curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof;
the abnormal curve and the derivative curve thereof have a mapping relation with the risk characteristics and the probability thereof, the mapping relation is autonomously determined by the working personnel according to the samples and the actual conditions, and the method is not repeated.
Wherein the risk profile includes at least one of the types:
risk profile: the shortage of equipment management personnel; probability: 80 percent.
It is worth mentioning that under the framework of the technical scheme of the invention, other recognition algorithms can be introduced to further determine different risk characteristics and occurrence probability of the equipment.
Example 2
Fig. 6 is a block diagram of a structure of an intelligent electronic inspection positioning system, in an embodiment of the present invention, an intelligent electronic inspection positioning system includes:
a target area obtaining module 11, configured to obtain a target area containing an importance level; the target area is represented by a three-dimensional coordinate set;
the path setting module 12 is configured to determine a limiting trajectory according to the target area, and determine a speed function of the inspector according to the importance level;
the inspection device selecting module 13 is used for receiving inspection requirements input by a user and determining the types and the number of the inspection devices according to the inspection requirements;
and the report generation module 14 is used for acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
The target area acquisition module 11 includes:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
the observation region determining unit is used for receiving a target region selected by a user based on the global scene and determining an observation region of the target region;
an actual scene obtaining unit, configured to determine an observation point in the observation region, and obtain an actual scene of a target region at the observation point;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance levels of the target areas.
The path setting module 12 includes:
the span acquisition unit is used for reading an observation area of the target area and acquiring the height span of the observation area;
the trajectory surface selecting unit is used for selecting a trajectory surface in the height span;
the distribution diagram determining unit is used for projecting the target area on the track surface to obtain an area distribution diagram;
the track determining unit is used for determining a limiting track based on the region distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to a preset sampling frequency, inquiring the importance levels of the corresponding nearest target areas at the sampling points, and determining the movement speed according to the importance levels;
the speed counting unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed.
The inspector selecting module 13 includes:
the type selection unit is used for inquiring the definition requirements of all target areas and determining the type of the inspection tour according to the definition requirements;
and the quantity selection unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. An intelligent electronic inspection positioning method is characterized by comprising the following steps:
acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
determining a limiting track according to the target area, and determining a speed function of the inspection tour according to the importance level;
receiving a polling requirement input by a user, and determining the type and the number of the polling devices according to the polling requirement;
and acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
2. The intelligent electronic inspection positioning method according to claim 1, wherein the step of obtaining target areas containing importance levels includes:
receiving boundary information input by a user, and building a global scene containing a preset scale according to the boundary information;
receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
determining an observation point in the observation area, and acquiring an actual scene of a target area at the observation point;
identifying the actual scene according to the recorded facility database, and correcting the universe scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
and displaying the corrected global scene containing the target areas, and receiving confirmation information sent by the user and the importance level of each target area.
3. The intelligent electronic inspection positioning method according to claim 1, wherein the determining a limit trajectory based on the target area and a speed function for the inspector based on the importance level includes:
reading an observation area of a target area, and acquiring the height span of the observation area;
selecting a trajectory plane in the height span;
projecting the target area on the trajectory surface to obtain an area distribution map;
determining a limit trajectory based on the region distribution map;
determining sampling points in the limiting track according to a preset sampling frequency, inquiring the importance levels of the nearest target areas corresponding to the sampling points, and determining the movement speed according to the importance levels;
counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed.
4. The intelligent electronic inspection positioning method according to claim 1, wherein the step of receiving inspection requirements input by a user and determining the types and the number of the inspectors according to the inspection requirements comprises:
inquiring definition requirements of all target areas, and determining the type of the inspection tour according to the definition requirements;
and receiving a polling period input by a user, and determining the number of polling devices according to the polling period.
5. The intelligent electronic inspection positioning method according to claim 1, wherein the step of obtaining the inspection image fed back by the inspection device in real time, identifying the inspection image, and generating the inspection report includes:
acquiring a patrol image containing a position tag fed back by a patrol device in real time; the position is a distance relative to the starting point of the limiting track;
inquiring a target area corresponding to the inspection image according to the position, and storing the target area in a database corresponding to the target area; wherein the image storage sequence in the database is determined by the image acquisition time;
identifying different databases based on a preset thread, and determining risk characteristics and probabilities of different target areas according to identification results;
and (4) counting all risk characteristics and probabilities thereof to obtain a routing inspection report.
6. The intelligent electronic inspection positioning method according to claim 5, wherein the steps of identifying different databases based on preset threads and determining risk characteristics and probabilities of different target areas according to the identification result include:
sequentially identifying the inspection images in the preset time period range in the database based on a preset neural network model to obtain equipment information and personnel information;
inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
counting the abnormal degree, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
and inputting the abnormal curve and the derivative curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof.
7. The utility model provides an intelligence electron location system that patrols and examines which characterized in that, the system includes:
the target area acquisition module is used for acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
the path setting module is used for determining a limiting track according to the target area and determining a speed function of the inspection tour according to the importance level;
the system comprises a polling device selection module, a polling device selection module and a polling device selection module, wherein the polling device selection module is used for receiving polling requirements input by a user and determining the types and the number of polling devices according to the polling requirements;
and the report generation module is used for acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
8. The intelligent electronic inspection positioning system according to claim 7, wherein the target area acquisition module includes:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
the observation region determining unit is used for receiving a target region selected by a user based on the global scene and determining an observation region of the target region;
an actual scene obtaining unit, configured to determine an observation point in the observation region, and obtain an actual scene of a target region at the observation point;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to an identification result; in the correction process of the global scene, adjusting a target area in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance levels of the target areas.
9. The intelligent electronic inspection positioning system according to claim 7, wherein the routing module includes:
the span acquisition unit is used for reading an observation area of the target area and acquiring the height span of the observation area;
the trajectory surface selecting unit is used for selecting a trajectory surface in the height span;
the distribution diagram determining unit is used for projecting the target area on the track surface to obtain an area distribution diagram;
the track determining unit is used for determining a limiting track based on the region distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to a preset sampling frequency, inquiring the importance levels of the nearest target areas corresponding to the sampling points, and determining the movement speed according to the importance levels;
the speed counting unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limiting track, and the dependent variable is the speed.
10. The intelligent electronic inspection positioning system according to claim 7, wherein the inspector selection module includes:
the type selection unit is used for inquiring the definition requirements of all target areas and determining the type of the inspection tour according to the definition requirements;
and the quantity selection unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
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| CN117314129A (en) * | 2023-11-29 | 2023-12-29 | 北京爱可生信息技术股份有限公司 | Park safety inspection system based on Internet of things |
| CN117314129B (en) * | 2023-11-29 | 2024-02-02 | 北京爱可生信息技术股份有限公司 | Park safety inspection system based on Internet of things |
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