CN114660309A - Autonomous evidence obtaining detection method and system for real-time monitoring supervision area - Google Patents
Autonomous evidence obtaining detection method and system for real-time monitoring supervision area Download PDFInfo
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Abstract
The invention relates to the technical field of Internet of things, in particular to an autonomous evidence obtaining detection method and system for a real-time monitoring supervision area. According to the method and the system, the monitoring sensors are installed in each target supervision area, the abnormal condition of the detected index parameters is obtained in real time, after the abnormal condition is judged, the detection center is reminded at the first time, the transportation equipment carrying the sampling equipment is automatically dispatched according to the acquisition type, the abnormal position is sampled, the detection center which returns to the air is automatically detected, the evidence is solidified in real time, and effective guarantee is provided for citizen action and order rectification. The invention is suitable for large-scale area management, the equipment scheduling is comprehensive and intelligent, no human intervention is needed during the evidence obtaining detection period, the data index can be monitored in real time, the area condition can be dynamically mastered, various equipment can be autonomously allocated, no manual scheme is needed to be made, the sampling route can be autonomously planned, unmanned cruising inspection can be carried out, the evidence can be rapidly obtained and solidified, and the evidence can be prevented from being lost.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to an autonomous evidence obtaining detection method and system for a real-time monitoring and supervision area.
Background
With the increase of the awareness of ecological environment protection and the enhancement of law enforcement, the measures for protecting the ecological environment are also continuously strengthened. In order to avoid the damage of the ecological environment, a monitoring organ such as public security or a monitoring hospital monitors and supervises the damage degree of the ecological environment at the first time.
When the supervision areas are inspected in the fields of public welfare litigation, public security food and drug rings, environmental protection supervision and the like, after clues are found, various devices are manually operated to sample and detect. The manual operation has the following disadvantages: 1. manual monitoring is not effective; 2. part of clues are easy to lose along with the ecological environment; 3. the manual formulation of the sampling detection scheme is tedious in process and long in operation time.
The reasons for the above-mentioned manual operation defects include: 1. the traditional manual operation method cannot monitor the change of key parameters of a supervision area in real time; 2. the thread of ecological environment damage is easy to lose; 3. the sampling detection scheme is manually formulated, the equipment scheduling time is long, and the round trip is long.
Disclosure of Invention
The invention provides an autonomous evidence obtaining detection method and system for a real-time monitoring supervision area, aiming at solving the problems of poor effectiveness, easy clue extinguishment, time and labor consumption of manual operation during the inspection of the supervision area.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
in a first aspect, in an embodiment provided by the present invention, an autonomous forensics detection method facing a real-time monitoring supervision area is provided, the method including the following steps:
step one, setting a target supervision area
Recording a target supervision area based on a GIS map, and acquiring geographic coordinate information of the target supervision area;
step two, configuring monitoring equipment
Selecting a supervision point and assembling a monitoring sensor in a target supervision area;
step three, returning the acquired data in real time
Transmitting the data of the monitoring sensor back to the central system in real time;
step four, judging the abnormity of the collected data
Judging whether the acquired data is abnormal or not according to a preset acquired data index standard;
step five, triggering evidence obtaining task
After receiving the abnormal alarm of the acquired data, immediately triggering the operation of a evidence obtaining task;
step six, acquiring an abnormal position;
acquiring a forensics sampling geographic position, and sending the forensics position;
step seven, planning evidence obtaining route
According to the geographical coordinates of the evidence-taking and sampling geographical position, planning an autonomous cruising route of the transportation equipment, and identifying road condition information in the route according to a map;
step eight, selecting transport equipment
Judging whether the flight equipment needs to be used or not according to the road condition information, if so, executing a forensics task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
step nine, automatic matching sampling equipment
According to the monitoring equipment, automatically matching sampling equipment, and loading the sampling equipment onto the transportation equipment through a manipulator;
step ten, automatically collecting samples
According to route navigation, the transportation equipment loads the sampling equipment to autonomously cruise to a sampling place, and the mechanical arm automatically samples the evidence obtaining point by using the sampling equipment and automatically collects a sample;
step eleven, automatically detecting the sample
And (4) according to the content of the collected sample, autonomously selecting detection equipment, detecting the sample, automatically returning a detection result, and solidifying the evidence in real time.
As a further aspect of the present invention, the entering a target supervision area based on a GIS map and acquiring geographic coordinate information of the target supervision area includes: and setting a target supervision area on the GIS map through drawing operation to obtain a target supervision area map.
As a further scheme of the present invention, in the second step, when monitoring equipment is configured, the monitoring equipment includes a water quality collecting sensor, a soil collecting sensor, a gas collecting sensor and a noise collecting sensor, and the monitoring equipment is configured to preliminarily monitor the abnormal conditions of the index parameters of water quality, soil, gas and noise.
As a further scheme of the present invention, in the sixth step, before obtaining the evidence-taking sampling geographic position, according to the position information of the front-end acquisition sensor, in combination with the enterprise directory geographic information, when the front-end sensor finds an abnormality, the enterprise geographic position information is selected according to the distance relative to the abnormality, and the sampling geographic position is determined.
As a further aspect of the present invention, in the seventh step, when the autonomous cruising route of the transportation device is planned, the method includes:
acquiring the determined sampling geographic position information;
acquiring a navigation route from a detection center to a sampling position based on a GIS map according to the sampling geographic position information;
and selecting the optimal route according to the route distance, the predicted time and the weight of the travel road condition.
As a further scheme of the present invention, in step eight, when the transportation device is selected, after the transportation device of the unmanned aerial vehicle or the unmanned vehicle is selected, the method further includes sending the route navigation information to the transportation device terminal.
As a further scheme of the invention, in the step eight, when the transportation device selects, according to the navigation route, in combination with map information, it is determined whether a road condition needing to fly exists in the route, if so, the unmanned aerial vehicle is selected to execute a flight task, and if not, the unmanned aerial vehicle is selected to perform sampling evidence collection.
As a further scheme of the invention, after the sampling equipment is automatically matched, the system further comprises a return flight detection center, wherein after sampling is finished, the unmanned aerial vehicle or the unmanned aerial vehicle automatically returns the return flight detection center according to the navigation information.
In a second aspect, in another embodiment provided by the present invention, an autonomous evidence obtaining detection system facing a real-time monitoring supervision area is provided, including:
the area setting module is used for recording a target supervision area based on a GIS map and acquiring geographic coordinate information of the target supervision area;
the monitoring equipment configuration module is used for selecting a monitoring point and equipping a monitoring sensor in a target monitoring area;
the acquisition and analysis module is used for transmitting data of the monitoring sensor back to the central system in real time, judging whether the acquired data is abnormal according to a preset acquired data index standard, and immediately triggering evidence obtaining task operation after receiving an alarm of the abnormal acquired data;
the abnormal position acquisition module is used for acquiring a forensics sampling geographic position and sending the forensics position;
the evidence obtaining planning module is used for planning an autonomous cruising route of the transportation equipment according to the geographic coordinates of the evidence obtaining sampling geographic position, identifying road condition information in the route according to a map, judging whether the flight equipment needs to be used or not according to the road condition information, and if so, executing an evidence obtaining task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
and the sampling detection module is used for automatically collecting samples according to route navigation, autonomously selecting detection equipment according to the content of the collected samples, detecting the samples, automatically returning detection results and solidifying evidences in real time.
As a further scheme of the present invention, the system further includes an abnormal location determining module, configured to select geographical location information of the enterprise according to location information of the front-end acquisition sensor, in combination with geographical information of the enterprise directory, and when the front-end sensor finds an abnormality, according to a distance from the abnormality, determine a sampling geographical location.
In a third aspect, in yet another embodiment provided by the present invention, a computer device is provided, which includes a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the autonomous forensics detection method for monitoring a surveillance area in real time when loading and executing the computer program.
In a fourth aspect, in a further embodiment provided by the present invention, a storage medium is provided, which stores a computer program that is loaded by a processor and executed to implement the steps of the autonomous forensics detection method for monitoring a surveillance area in real time.
The technical scheme provided by the invention has the following beneficial effects:
according to the autonomous evidence obtaining detection method and system for the real-time monitoring and supervision areas, the monitoring sensors are installed in the target supervision areas, the abnormal conditions of the detected index parameters are obtained in real time, after the abnormal conditions are judged, the detection center is reminded in the first time, the transportation equipment carrying the sampling equipment is automatically dispatched according to the acquisition type, the abnormal positions are sampled, the detection center returns to the air to perform automatic detection, evidences are solidified in real time, and effective guarantee is provided for citizen action and responsibility adjustment.
The autonomous evidence obtaining detection method and system for monitoring and supervising the area in real time are suitable for large-scale area management, comprehensive and intelligent equipment scheduling is achieved, manual intervention is not needed during evidence obtaining detection, data indexes can be monitored in real time, area conditions can be dynamically mastered, various equipment can be autonomously allocated, a scheme does not need to be made manually, a sampling route is autonomously planned, unmanned cruising inspection is carried out, evidence obtaining is rapidly carried out and solidification is prevented from being lost.
These and other aspects of the invention are apparent from and will be elucidated with reference to the embodiments described hereinafter. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
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. In the drawings:
fig. 1 is a flowchart of an autonomous forensics detection method for monitoring a surveillance area in real time according to an embodiment of the present invention.
Fig. 2 is a flowchart of planning a cruising route in an autonomous evidence obtaining detection method for a real-time monitoring and supervision area according to an embodiment of the present invention.
Fig. 3 is a flowchart of autonomous forensics detection in an autonomous forensics detection method for a real-time monitoring and supervision area according to an embodiment of the present invention.
Fig. 4 is a system block diagram of an autonomous forensic detection system for monitoring a surveillance area in real time according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further 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.
The technical solutions in the exemplary embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the exemplary embodiments of the present invention, and it is apparent that the described exemplary embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The existing manual operation has the following disadvantages: manual monitoring is not effective; part of clues are easy to lose along with the ecological environment; the process of manually formulating the sampling detection scheme is complicated, and the operation time is long. The traditional manual operation method cannot monitor the change of key parameters of a supervision area in real time; the thread of ecological environment damage is easy to lose; the sampling detection scheme is manually formulated, the equipment scheduling time is long, and the round trip is long.
Aiming at the problems, the invention provides the autonomous evidence obtaining detection method and the autonomous evidence obtaining detection system for the real-time monitoring and supervision area.
In some embodiments, the autonomous evidence obtaining detection method for the real-time monitoring and supervision area may be applied to an autonomous evidence obtaining detection device for the real-time monitoring and supervision area, where the autonomous evidence obtaining detection device for the real-time monitoring and supervision area may be a device with display and processing functions, such as a PC, a portable computer, and a mobile terminal, but is not limited thereto.
Specifically, the embodiments of the present application will be further explained below with reference to the drawings.
Fig. 1 is a schematic flowchart of a first embodiment of an autonomous evidence obtaining detection method for a real-time monitoring and supervision area according to the present application. In an embodiment of the present application, referring to fig. 1 and fig. 2, the method for detecting autonomous forensics for a real-time monitoring supervision area includes the following steps S10 to S110:
step S10, setting a target supervision area: and recording a target supervision area based on the GIS map, and acquiring geographic coordinate information of the target supervision area.
In an embodiment of the application, the entering of the target supervision area based on the GIS map and the obtaining of the geographic coordinate information of the target supervision area include: and setting a target supervision area on the GIS map through drawing operation to obtain a target supervision area map.
For example, environment modification is performed on a certain lake, and a lake coverage area is drawn on a GIS map.
Step S20, configuring the monitoring device: in the target monitoring area, a monitoring point is selected and monitoring sensors are equipped.
In the embodiment of this application, when the configuration monitoring facilities, monitoring facilities includes quality of water collection sensor, soil collection sensor, gaseous collection sensor and noise collection sensor, monitoring facilities is used for the index parameter abnormal conditions of preliminary monitoring quality of water, soil, gas and noise.
Step S30, returning collected data in real time: transmitting the data of the monitoring sensor back to the central system in real time;
step S40, judging the abnormity of the collected data: judging whether the acquired data is abnormal or not according to a preset acquired data index standard;
step S50, triggering a forensics task: after receiving the abnormal alarm of the acquired data, immediately triggering the operation of a evidence obtaining task;
step S60, obtaining abnormal positions, namely obtaining the forensics sampling geographic positions and sending the forensics positions;
in the embodiment of the application, before the forensics sampling geographic position is obtained, according to the position information of the front-end acquisition sensor and in combination with the enterprise directory geographic information (such as a chemical plant, a farm and the like), when the front-end sensor finds an abnormality, the enterprise geographic position information is selected according to the distance relative to the abnormality, and the sampling geographic position is determined.
Step S70, planning a evidence obtaining route: according to the evidence obtaining and sampling geographic coordinates of the geographic position, an autonomous cruising route of the transportation equipment is planned, and road condition information in the route is identified according to a map;
in an embodiment of the present application, when planning an autonomous cruising route of a transportation device, the method includes the following steps:
step S701, obtaining the determined sampling geographic position information;
step S702, acquiring a navigation route from a detection center to a sampling position based on a GIS map according to the sampling geographic position information;
and step S703, selecting the optimal route according to the route distance, the predicted time and the weight of the journey and road condition.
Step S80, the transportation device selects: judging whether the flight equipment needs to be used or not according to the road condition information, if so, executing a forensics task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
in the embodiment of the application, when the transportation equipment is selected, after the transportation equipment of the unmanned aerial vehicle or the unmanned vehicle is selected, the route navigation information is sent to the transportation equipment terminal.
In the embodiment of the application, when the transportation equipment is selected, whether road conditions such as rivers, mountain stream and the like needing to fly exist in the route or not is judged by combining map information according to the navigation route, if yes, the unmanned aerial vehicle is selected to execute a flight task, and if not, the unmanned aerial vehicle is selected to perform sampling evidence collection.
Step S90, automatically matching the sampling device: according to the monitoring equipment, automatically matching sampling equipment, and loading the sampling equipment onto the transportation equipment through a mechanical arm;
in the embodiment of this application, after automatic matching sampling equipment, still include the detection center that navigates back, wherein, after the sample was accomplished, unmanned aerial vehicle or unmanned car navigated back the detection center according to navigation information, automatically.
Step S100, automatically collecting samples: according to route navigation, the transportation equipment loads the sampling equipment to automatically cruise to a sampling place, and the mechanical arm automatically samples the evidence-taking point by using the sampling equipment and automatically collects samples;
step S110, automatic detection of a sample: and (4) according to the content of the collected sample, autonomously selecting detection equipment, detecting the sample, automatically returning a detection result, and solidifying the evidence in real time.
In the inspection of public welfare litigation business, if the industrial wastewater discharged into a river by a factory is found to be stolen at night, the ecological environment of the river is polluted, and the river basin is a centralized industrial area and cannot locate a target factory, the invention can be used under the condition.
Exemplarily, install water quality monitoring sensor at each mill's drain, acquire water quality parameter variation in real time, receive the back when the water receives the pollution, the very first time reminds the center to according to gathering the type, automatic dispatch carries on water quality sampling equipment's unmanned aerial vehicle, take a sample to the drain, and the detection center of returning a journey carries out automated inspection, real-time solidification evidence, for mentioning public welfare litigation, the order is rectified and is provided the effective guarantee.
It should be understood that although the above steps are described in a certain order, these steps are not necessarily performed in the order described. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, some steps of the present embodiment may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or in turns with other steps or at least a part of the steps or stages in other steps.
Referring to fig. 3, the autonomous evidence obtaining detection method and system for a real-time monitoring and supervision area perform autonomous evidence obtaining and detection processes of equipment as follows:
1. inputting supervision area map
Recording a target supervision area based on a GIS map, and acquiring geographic coordinate information of the target supervision area;
2. each monitoring channel is provided with monitoring equipment (for example, water quality, soil, gas and noise acquisition sensor)
In the supervision area, a supervision point is selected and a monitoring sensor is arranged, and the abnormal conditions of various index parameters (such as the situations that rivers are polluted and harmful substances in water are increased) are mainly monitored preliminarily;
3. real-time return of collected data
Transmitting the data of the monitoring sensor back to the central system in real time;
4. anomaly of collected data
According to a preset acquired data index standard, carrying out abnormity judgment on the acquired data;
5. triggering evidence obtaining task
After receiving an alarm of abnormal collected data, immediately triggering a evidence obtaining task function;
6. sending a location for evidence collection
Acquiring a forensics sampling geographic position, namely an abnormal position;
7. planning evidence-obtaining route
And according to the geographic coordinates, intelligently planning an autonomous cruising route of the equipment, and identifying road condition information in the route according to a map.
8. Video recording whether flying is needed
Judging whether the flight equipment needs to be used or not according to the road condition information;
9. unmanned aerial vehicle/unmanned vehicle execution evidence obtaining task
Intelligently selecting transportation equipment and sending route navigation information to a transportation terminal;
10. automatic matching sampling device
According to the monitoring equipment, automatically matching the sampling equipment (for example, if the monitoring equipment is an oxygen content sensor in water, matching a water body sampler);
11. manipulator loads sampling device on unmanned aerial vehicle/vehicle
Automatically loading the sampling device to the transport device by a manipulator;
12. to the sampling site
According to the route navigation, the transportation equipment loads the sampling equipment to autonomously cruise to a sampling place;
13. automatic sample collection of manipulator
The mechanical arm automatically samples the evidence obtaining point by using sampling equipment;
14. return detection center
After sampling is finished, the unmanned aerial vehicle/vehicle automatically returns to the detection center according to the navigation information;
15. automatically detecting according to the sample
According to the content of the collected sample, selecting detection equipment autonomously (for example, selecting water quality detector equipment if the water quality is detected);
16. returning the detection result
And automatically returning a detection result and solidifying the evidence in real time.
The autonomous evidence obtaining detection method and system for the real-time monitoring and supervision area are suitable for large-scale area management, comprehensive and intelligent equipment scheduling is achieved, manual intervention is not needed during evidence obtaining detection, data indexes can be monitored in real time, area conditions can be dynamically mastered, various equipment can be autonomously allocated, manual scheme making is not needed, sampling routes are autonomously planned, unmanned cruise inspection is conducted, evidence obtaining and solidification are rapidly conducted, and evidence loss is prevented.
Referring to fig. 4, an embodiment of the present invention provides an autonomous forensics detection system facing a real-time monitoring supervision area, and the system includes.
The region setting module 100 is configured to enter a target supervision region based on a GIS map and acquire geographic coordinate information of the target supervision region;
a monitoring device configuration module 200, configured to select a supervision point and equip a monitoring sensor in a target supervision area;
the acquisition and analysis module 300 is used for transmitting data of the monitoring sensor back to the central system in real time, judging whether the acquired data is abnormal according to a preset acquired data index standard, and triggering evidence obtaining task operation immediately after receiving an alarm of the abnormal acquired data;
an abnormal position acquisition module 400, configured to acquire a forensics sampling geographic position and send the forensics position;
the evidence obtaining planning module 500 is used for planning an autonomous cruising route of the transportation equipment according to the geographic coordinates of the evidence obtaining sampling geographic position, identifying road condition information in the route according to a map, judging whether the flight equipment needs to be used or not according to the road condition information, and if so, executing an evidence obtaining task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
and the sampling detection module 600 is used for automatically collecting samples according to route navigation, autonomously selecting detection equipment according to the content of the collected samples, detecting the samples, automatically returning detection results and solidifying evidences in real time.
The abnormal position determining module 700 is configured to select geographical position information of the enterprise according to the position information of the front-end acquisition sensor in combination with geographical information of the enterprise directory when the front-end sensor finds an abnormality, and determine a sampling geographical position according to a distance from the abnormality.
According to the autonomous evidence obtaining detection system for the real-time monitoring and supervision areas, the monitoring sensors are installed in the target supervision areas, the abnormal condition of the detected index parameters is obtained in real time, after the abnormality is judged, the detection center is reminded in the first time, the transportation equipment carrying the sampling equipment is automatically dispatched according to the acquisition type, the position where the abnormality occurs is sampled, the detection center returns to the air to perform automatic detection, evidences are solidified in real time, and effective guarantee is provided for citizen law enforcement and law enforcement.
The autonomous evidence obtaining detection method and system for monitoring and supervising the area in real time are suitable for large-scale area management, comprehensive and intelligent equipment scheduling is achieved, manual intervention is not needed during evidence obtaining detection, data indexes can be monitored in real time, area conditions can be dynamically mastered, various equipment can be autonomously allocated, a scheme does not need to be made manually, a sampling route is autonomously planned, unmanned cruising inspection is carried out, evidence obtaining is rapidly carried out and solidification is prevented from being lost.
It should be noted that, the autonomous evidence obtaining detection system for the real-time monitoring and supervision area is executed according to the autonomous evidence obtaining detection method for the real-time monitoring and supervision area as described in the foregoing embodiments, and therefore, the steps of the autonomous evidence obtaining detection method for the real-time monitoring and supervision area are not described in detail in this embodiment.
In one embodiment, there is further provided in an embodiment of the present invention a computer device, including at least one processor, and a memory communicatively connected to the at least one processor, the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the steps of the autonomous forensics detection method for a real-time monitoring surveillance area:
1. inputting supervision area map
Recording a target supervision area based on a GIS map, and acquiring geographic coordinate information of the target supervision area;
2. each supervision key channel configuration monitoring equipment
In the supervision area, selecting supervision points and equipping monitoring sensors, mainly preliminarily monitoring abnormal conditions of various index parameters;
3. real-time return of collected data
Transmitting the data of the monitoring sensor back to the central system in real time;
4. anomaly of collected data
According to a preset acquired data index standard, carrying out abnormity judgment on the acquired data;
5. triggering evidence obtaining task
After receiving an acquired data abnormity alarm, immediately triggering a forensics task function;
6. sending a location for evidence collection
Acquiring a forensics sampling geographic position, namely an abnormal position;
7. planning evidence-obtaining route
And according to the geographic coordinates, intelligently planning an autonomous cruising route of the equipment, and identifying road condition information in the route according to a map.
8. Video recording whether flying is needed
Judging whether the flight equipment needs to be used or not according to the road condition information;
9. unmanned aerial vehicle/unmanned vehicle execution evidence obtaining task
Intelligently selecting transportation equipment, and sending route navigation information to a transportation terminal;
10. automatic matching sampling device
Automatically matching sampling equipment according to the monitoring equipment;
11. manipulator loads sampling device on unmanned aerial vehicle/vehicle
Automatically loading the sampling device to the transport device by a manipulator;
12. to the sampling site
According to the route navigation, the transportation equipment loads the sampling equipment to autonomously cruise to a sampling place;
13. manipulator automatic sample collection
The mechanical arm automatically samples the evidence obtaining point by using sampling equipment;
14. return detection center
After sampling is finished, the unmanned aerial vehicle/vehicle automatically returns to the detection center according to the navigation information;
15. automatically detecting according to the sample
Selecting detection equipment autonomously according to the content of the collected sample;
16. returning the detection result
And automatically returning a detection result, and solidifying the evidence in real time.
In an embodiment of the present invention, there is further provided a storage medium having a computer program stored thereon, which when executed by a processor, performs the steps in the above-mentioned method embodiments:
1. inputting supervision area map
Recording a target supervision area based on a GIS map, and acquiring geographic coordinate information of the target supervision area;
2. each supervision key channel configuration monitoring equipment
In the supervision area, selecting supervision points and equipping monitoring sensors, mainly preliminarily monitoring abnormal conditions of various index parameters;
3. real-time return of collected data
Transmitting the data of the monitoring sensor back to the central system in real time;
4. anomaly of collected data
According to a preset acquired data index standard, carrying out abnormity judgment on the acquired data;
5. triggering evidence obtaining task
After receiving an acquired data abnormity alarm, immediately triggering a forensics task function;
6. sending a location for evidence collection
Acquiring a forensics sampling geographic position, namely an abnormal position;
7. planning evidence-obtaining route
And according to the geographic coordinates, intelligently planning an autonomous cruising route of the equipment, and identifying road condition information in the route according to a map.
8. Video recording whether flight is required
Judging whether the flight equipment needs to be used or not according to the road condition information;
9. unmanned aerial vehicle/unmanned vehicle execution evidence obtaining task
Intelligently selecting transportation equipment and sending route navigation information to a transportation terminal;
10. automatic matching sampling device
Automatically matching sampling equipment according to the monitoring equipment;
11. manipulator loads sampling device on unmanned aerial vehicle/vehicle
Automatically loading the sampling device to the transport device by a manipulator;
12. to the sampling site
According to the route navigation, the transportation equipment loads the sampling equipment to autonomously cruise to a sampling place;
13. automatic sample collection of manipulator
The mechanical arm automatically samples the evidence-taking point by using sampling equipment;
14. return detection center
After sampling is finished, the unmanned aerial vehicle/vehicle automatically returns to the detection center according to the navigation information;
15. automatically detecting according to the sample
Selecting detection equipment autonomously according to the content of the collected sample;
16. returning the detection result
And automatically returning a detection result and solidifying the evidence in real time.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description, and do not represent the advantages and disadvantages of the embodiments.
The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
In summary, according to the autonomous evidence obtaining detection method and system for real-time monitoring and supervision areas provided by the invention, the monitoring sensors are installed in the target supervision areas, the abnormal condition of the detected index parameters is obtained in real time, after the abnormality is judged, the detection center is reminded at the first time, the transportation equipment carrying the sampling equipment is automatically dispatched according to the acquisition type, the position where the abnormality occurs is sampled, and the detection center returning to the air is automatically detected, so that evidence is solidified in real time, and effective guarantee is provided for commendable lition and adjustment. The autonomous evidence obtaining detection method and system for monitoring and supervising the area in real time are suitable for large-scale area management, comprehensive and intelligent equipment scheduling is achieved, manual intervention is not needed during evidence obtaining detection, data indexes can be monitored in real time, area conditions can be dynamically mastered, various equipment can be autonomously allocated, a scheme does not need to be made manually, a sampling route is autonomously planned, unmanned cruising inspection is carried out, evidence obtaining is rapidly carried out and solidification is prevented from being lost.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. An autonomous evidence obtaining detection method for a real-time monitoring and supervision area is characterized by comprising the following steps:
step one, setting a target supervision area
Recording a target supervision area based on a GIS map, and acquiring geographic coordinate information of the target supervision area;
step two, configuring monitoring equipment
Selecting a supervision point and assembling a monitoring sensor in a target supervision area;
step three, returning the collected data in real time
Transmitting the data of the monitoring sensor back to the central system in real time;
step four, judging the abnormity of the collected data
Judging whether the acquired data is abnormal or not according to a preset acquired data index standard;
step five, triggering evidence obtaining task
After receiving an alarm of abnormal collected data, immediately triggering evidence obtaining task operation;
step six, acquiring an abnormal position;
acquiring a forensics sampling geographic position, and sending the forensics sampling position;
step seven, planning evidence obtaining route
According to the geographical coordinates of the evidence-taking and sampling geographical position, planning an autonomous cruising route of the transportation equipment, and identifying road condition information in the route according to a map;
step eight, selecting transport equipment
Judging whether the flight equipment needs to be used or not according to the road condition information, if so, executing a forensics task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
step nine, automatic matching sampling equipment
According to the monitoring equipment, automatically matching sampling equipment, and loading the sampling equipment onto the transportation equipment through a manipulator;
step ten, automatically collecting samples
According to route navigation, the transportation equipment loads the sampling equipment to autonomously cruise to a sampling place, and the mechanical arm automatically samples the evidence obtaining point by using the sampling equipment and automatically collects a sample;
step eleven, automatically detecting the sample
And (4) according to the content of the collected sample, autonomously selecting detection equipment, detecting the sample, automatically returning a detection result, and solidifying the evidence in real time.
2. The autonomous evidence obtaining detection method for real-time monitoring and supervision area as recited in claim 1, wherein the entering of the target supervision area based on the GIS map to obtain geographic coordinate information of the target supervision area comprises: and setting a target supervision area on the GIS map through drawing operation to obtain a target supervision area map.
3. The autonomous evidence-obtaining detection method for real-time monitoring and supervision areas as claimed in claim 1, wherein in the second step, when the monitoring device is configured, the monitoring device comprises a water quality collecting sensor, a soil collecting sensor, a gas collecting sensor and a noise collecting sensor, and the monitoring device is used for preliminarily monitoring the abnormal conditions of the index parameters of water quality, soil, gas and noise.
4. The autonomous evidence collection detection method for monitoring and supervising an area in real time as claimed in claim 1, wherein in step six, before obtaining the evidence collection and sampling geographic location, according to the location information of the front-end collection sensor, in combination with the business directory geographic information, when the front-end sensor finds an anomaly, the business geographic location information is selected according to the distance relative to the anomaly, and the sampling geographic location is determined.
5. The autonomous evidence obtaining detection method for real-time monitoring and supervision area as claimed in claim 1, wherein in the seventh step, when the autonomous cruising route of the transportation device is planned, the method comprises:
acquiring the determined sampling geographic position information;
acquiring a navigation route from a detection center to a sampling position based on a GIS map according to the sampling geographic position information;
and selecting an optimal route according to the route distance, the predicted time and the weight of the travel road condition.
6. The autonomous evidence-obtaining detection method for real-time monitoring and supervision areas according to claim 1, wherein in step eight, during the transportation equipment selection, after the transportation equipment of the unmanned aerial vehicle or the unmanned vehicle is selected, the method further comprises sending the route navigation information to the transportation equipment terminal.
7. The autonomous evidence obtaining detection method for the real-time monitoring and supervision area as claimed in claim 6, wherein in step eight, when the transportation device selects, according to the navigation route, and in combination with map information, it is determined whether a road condition that needs to fly exists in the route, if so, the unmanned aerial vehicle is selected to execute a flight task, and if not, the unmanned aerial vehicle is selected to perform sampling evidence obtaining.
8. The autonomous evidence-obtaining detection method for real-time monitoring and supervision area according to claim 1, characterized in that after the automatic matching of the sampling device, a return detection center is further included, wherein after the sampling is completed, the unmanned aerial vehicle or the unmanned vehicle automatically returns to the return detection center according to the navigation information.
9. The utility model provides an autonomous evidence obtaining detection system towards real-time supervision area which characterized in that includes:
the region setting module is used for recording a target supervision region based on a GIS map and acquiring geographic coordinate information of the target supervision region;
the monitoring equipment configuration module is used for selecting a monitoring point and preparing a monitoring sensor in a target monitoring area;
the acquisition and analysis module is used for transmitting data of the monitoring sensor back to the central system in real time, judging whether the acquired data is abnormal according to a preset acquired data index standard, and immediately triggering evidence obtaining task operation after receiving an alarm of the abnormal acquired data;
the abnormal position acquisition module is used for acquiring a forensics sampling geographic position and sending the forensics position;
the evidence obtaining planning module is used for planning an autonomous cruising route of the transportation equipment according to the geographic coordinates of the evidence obtaining sampling geographic position, identifying road condition information in the route according to a map, judging whether the flight equipment needs to be used or not according to the road condition information, and if so, executing an evidence obtaining task by using the flight equipment; if not, using the unmanned vehicle to execute the evidence obtaining task;
and the sampling detection module is used for automatically collecting samples according to route navigation, autonomously selecting detection equipment according to the content of the collected samples, detecting the samples, automatically returning detection results and solidifying evidences in real time.
10. The autonomous evidence-taking detection system for real-time monitoring and supervision areas according to claim 9, further comprising an anomaly location determination module for determining a sampling geographic location by selecting the geographic location information of the enterprise according to the distance to the anomaly when the front-end sensor finds the anomaly, in combination with the geographic information of the enterprise directory.
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