CN112511541A - Intelligent park emergency early warning management system based on cloud computing - Google Patents
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Abstract
The invention discloses a cloud computing-based intelligent park emergency early warning management system, relates to the technical field of safety early warning, and solves the technical problem that the prior art cannot accurately judge the danger of strangers in an intelligent park; the invention is provided with the acquisition and analysis module, which is beneficial to improving the linkage processing capacity of events and avoiding the immobilization of event processing modes; the invention is provided with the early warning scheduling module, which is beneficial to improving the processing efficiency and the processing capacity of events; the acquisition and analysis module supports video butt joint of different manufacturers, and converts different video stream protocols into standard protocols inside the acquisition and analysis module by adopting a dynamic link library mode; the acquisition and analysis module supports the loading of the model, and is beneficial to improving the application range and the working capacity of the system.
Description
Technical Field
The invention belongs to the field of safety early warning, relates to a cloud computing technology, and particularly relates to a smart park emergency early warning management system based on cloud computing.
Background
The emergency management means that a series of necessary measures are taken by establishing a necessary emergency mechanism in the processes of pre-prevention, incident response, disposal and good post-management of emergent public events by governments and other public institutions, so that the safety of the lives and properties of the public is guaranteed, and the relevant activities of harmonious and healthy development of the society are promoted.
The invention patent with publication number CN107393248A discloses a safety emergency early warning management system for a scientific and technological park; the system comprises a safety early warning terminal, a mobile terminal and a monitoring terminal, wherein the safety early warning terminal is in signal connection with the mobile terminal, and the safety early warning terminal is in signal connection with the monitoring terminal; the monitoring terminals are distributed at each corner of the scientific and technological park, and safety dead corners cannot exist; and all the personnel entering the park are equipped with the mobile terminal.
According to the scheme, the fire disaster can be monitored, the control valve is opened through the controller, water is automatically sprayed, people can accurately know the position of the people and the relative position of a fire disaster occurrence point through the navigation module and the display module of the mobile terminal, people can conveniently plan a reasonable escape route, and the life safety of people is guaranteed; at that time, the above scheme only sets early warning measures for fire, and can not protect people in all directions; therefore, the above solution still needs further improvement.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides a cloud computing-based intelligent park emergency early warning management system.
The purpose of the invention can be realized by the following technical scheme: a smart park emergency early warning management system based on cloud computing comprises a cloud platform, an early warning scheduling module, a data storage module, a registration and login module, an acquisition and analysis module and a safety protection module;
the cloud platform is respectively in communication connection with the early warning scheduling module, the data storage module, the registration and login module, the acquisition and analysis module and the safety protection module;
the registration login module is used for a user to perform registration login through the intelligent terminal and sending registration login information to the data storage module for storage;
the data storage module stores a white list data table and a key precaution list data table; the white list data table is the registered personnel, and the key precaution list is the preset person who is forbidden to pass through;
the acquisition and analysis module is in communication connection with the high-definition camera, supports the high-definition cameras of different video stream protocols, and converts the different video stream protocols into standard protocols inside the acquisition and analysis module in a dynamic link library mode.
Preferably, the acquisition and analysis module is used for acquiring a video image of a visitor through a high-definition camera and analyzing the video image, and includes:
acquiring the number i, i-1, 2, … …, n of the high-definition camera; acquiring a monitoring video of a monitoring area through a high-definition camera, and sending the monitoring video to a collection analysis module; the monitoring area is a target monitoring area of the high-definition camera;
the acquisition analysis module receives the monitoring video and then performs video primary analysis on the monitoring video; the video initial analysis is to identify the character information in the monitoring video; after the character information is identified in the monitoring video, generating an image analysis signal, and carrying out image analysis on the monitoring video by a collecting and analyzing module;
when the visitor is marked as a stranger, extracting the stranger number in the monitoring video, and marking the stranger number as N; determining a threat level and a high-definition camera position according to the stranger number N; wherein N is a non-0 natural number;
when the threat level is a third level, sending a slight threat signal and the position of the high-definition camera to an early warning scheduling module through the cloud platform; when the threat level is a second level, sending a medium threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform; when the threat level is a first level, sending a serious threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform;
sending the early warning signal sending records to a data storage module through a cloud platform for storage, wherein the early warning signals comprise a slight threat signal, a medium threat signal and a serious threat signal.
Preferably, the determining of the threat level specifically includes:
when the number of strangers N is 1, acquiring the number of occurrences of the strangers in the high-definition camera, and marking the number of occurrences as CC; when the occurrence frequency CC meets the condition that CC is less than L3, judging that the stranger threat level is a third level; when the occurrence frequency CC meets that L3 is not more than CC, judging that the stranger threat level is a second level; wherein L3 is a preset occurrence threshold, and L3 is greater than 0;
when the number N of strangers is larger than 1, acquiring the number of times of the contact of the strangers in the high-definition camera, and marking the number of times of the contact as PC; the meeting face means that at least two of strangers appear in one monitoring image at the same time; when the number of times of face collision PC is less than PC < L4, judging that the threat level of the stranger is a second level; when the number of times of face collision PC meets the condition that L4 is not more than PC, judging that the threat level of the stranger is a first level; wherein L4 is a preset number threshold of times of surface contact, and L4 is greater than 0;
sending the position of the high-definition camera to an early warning scheduling module through the cloud platform;
sending the threat level to a data storage module through a cloud platform for storage; the threat levels include a first level, a second level, and a third level.
Preferably, the image analysis specifically includes:
decomposing the monitoring video into monitoring images frame by frame, and carrying out image preprocessing on the monitoring images; the image preprocessing comprises image segmentation, image correction, image enhancement and gray scale transformation;
extracting a facial image of the visitor through the monitoring image after image preprocessing, and marking the facial image of the visitor as an image to be verified;
matching the image to be verified with the face image in the white list data table to obtain a white list matching degree, and marking the white list matching degree as BPD; when the white list matching degree BPD meets the condition that L1 is less than BPD, judging that the image to be verified is successfully matched, and generating an admission signal through a cloud platform; when the white list matching degree BPD is more than 0 and less than or equal to L1, matching the image to be verified with the key precaution list data table to obtain the matching degree, and marking the precaution list matching degree as FPD; when the matching degree FPD of the precaution list meets L2< FPD, judging that the image to be verified is successfully matched, and sending a precaution early warning signal to an early warning scheduling module through the cloud platform; when the matching degree FPD of the precaution list is more than 0 and less than or equal to L2, marking the visiting person as a stranger and generating an entrance forbidding signal; wherein L1 is a preset white list matching threshold, and L2 is a preset precautionary list matching threshold.
Preferably, the early warning scheduling module receives the early warning signal and schedules the staff, including:
when the early warning scheduling module receives the high-definition camera position, marking the high-definition camera position as a target position, acquiring workers in a circle with the target position as the center of the circle and R1 as the radius, acquiring the distance between the workers and the target position, and marking the distance as a working distance; wherein R1 presets a radius threshold;
when the early warning scheduling module receives a slight threat signal, K1 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a medium threat signal, K2 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a serious threat signal, K3 workers with the shortest working distance are dispatched to reach the target position; wherein K1, K2 and K3 are preset people number threshold values, and K1 is more than 0 and less than 1.5 multiplied by K1 and less than or equal to K2 and more than 2 multiplied by K2 and less than or equal to K3;
and sending the dispatching records of the workers to a data storage module for storage through the cloud platform.
Preferably, the registering and logging specifically includes:
the user is connected with the registration login module through the intelligent terminal; the intelligent terminal comprises an intelligent mobile phone, a tablet personal computer and a notebook computer, and is in wireless connection with the registration login module;
the user sends the registration information to the registration login module through the intelligent terminal; the registration information comprises a name, a mobile phone number authenticated by a real name, a face image acquired in real time and a visiting affair;
acquiring a white list data table and a key precaution list data table from a data storage module through a cloud platform; analyzing and matching the registration information with the white list data table, and sending a registration completion signal to the intelligent terminal of the user through the registration login module when the matching is successful; when the matching is unsuccessful, the registration information is analyzed and matched with the key precaution list data table, and when the matching is successful, a passing prohibition signal is sent to the intelligent terminal of the user through the registration login module; when the matching is unsuccessful, generating a registration signal and sending the registration signal to a registration login module;
the registration login module registers according to the registration information, sends a registration success signal to the intelligent terminal of the specific personnel after the registration is completed, and meanwhile adds the registration information to the white list data table;
and sending the registration information, the registration completion signal sending record, the prohibition of the signal sending record and the registration success signal sending record to the data storage module for storage through the cloud platform.
Preferably, the early warning scheduling module provides early warning information for the user after receiving the early warning signal, and the method includes:
the method comprises the steps that the mobile phone number of a registered user is obtained through a data storage module, the mobile phone number is located, and when the position of the mobile phone number is located in a monitoring area, the mobile phone number is marked as a target mobile phone number;
acquiring a linear distance between a target mobile phone number and a target position, and marking the linear distance as ZJ;
when the straight-line distance ZJ is smaller than or equal to a preset safety distance threshold value, planning an avoiding route for a user; the avoidance route takes the target mobile phone number as a starting point and a safety exit of the monitoring area as a key point, and the shortest distance between the avoidance route and the target position is not less than a preset shortest distance threshold value;
and sending the avoiding route to a target mobile phone number, and enabling the user to be far away from the target position according to the avoiding route.
Preferably, the collection and analysis module supports loading of a model including a neural network model that is capable of identifying a face wearing a mask.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with a collecting and analyzing module, which is used for collecting the video image of the visitor through a high-definition camera and analyzing the video image; acquiring a serial number i of a high-definition camera, acquiring a monitoring video of a monitoring area through the high-definition camera, and sending the monitoring video to a collection analysis module; the acquisition analysis module receives the monitoring video and then performs video primary analysis on the monitoring video; after the character information is identified in the monitoring video, generating an image analysis signal, and carrying out image analysis on the monitoring video by a collecting and analyzing module; when the visitor is marked as a stranger, extracting the stranger number in the monitoring video, and marking the stranger number as N; determining a threat level and a high-definition camera position according to the stranger number N; when the threat level is a third level, sending a slight threat signal and the position of the high-definition camera to an early warning scheduling module through a processor; when the threat level is a second level, sending a medium threat signal and the position of the high-definition camera to the early warning scheduling module through the processor; when the threat level is a first level, sending a serious threat signal and the position of a high-definition camera to an early warning scheduling module through a processor; the early warning scheduling module dispatches workers to a target position for processing according to the early warning signal; the acquisition and analysis module extracts a facial image through the high-definition camera, compares the facial image with a data table in the data storage module for analysis, and generates a corresponding early warning signal according to an analysis result, so that the linked processing capacity of an event is improved, and the immobilization of an event processing mode is avoided;
2. the invention is provided with an early warning scheduling module which receives an early warning signal to schedule workers; when the early warning scheduling module receives the high-definition camera position, marking the high-definition camera position as a target position, acquiring workers in a circle with the target position as the center of the circle and R1 as the radius, acquiring the distance between the workers and the target position, and marking the distance as a working distance; when the early warning scheduling module receives a slight threat signal, K1 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a medium threat signal, K2 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a serious threat signal, K3 workers with the shortest working distance are dispatched to reach the target position; the early warning scheduling module flexibly adjusts the number of dispatched workers according to different early warning signals, and is beneficial to improving the processing efficiency and the processing capacity of events;
3. the acquisition and analysis module supports video butt joint of different manufacturers, and converts different video stream protocols into standard protocols inside the acquisition and analysis module by adopting a dynamic link library mode.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described 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.
Referring to fig. 1, two embodiments of the present invention are provided.
The first embodiment is as follows:
a smart park emergency early warning management system based on cloud computing comprises a cloud platform, an early warning scheduling module, a data storage module, a registration and login module, an acquisition and analysis module and a safety protection module;
the cloud platform is respectively in communication connection with the early warning scheduling module, the data storage module, the registration and login module, the acquisition and analysis module and the safety protection module;
the registration login module is used for performing registration login by a user through the intelligent terminal and sending registration login information to the data storage module for storage;
the data storage module stores a white list data table and a key precaution list data table; the white list data table is the registered personnel, and the key precaution list is the preset person who is forbidden to pass;
the acquisition and analysis module is in communication connection with the high-definition camera, supports the high-definition cameras with different video stream protocols, and converts the different video stream protocols into standard protocols inside the acquisition and analysis module in a dynamic link library mode.
Further, the acquisition and analysis module is used for acquiring the video image of the visitor through the high-definition camera and analyzing the video image, and comprises:
acquiring the number i, i-1, 2, … …, n of the high-definition camera; acquiring a monitoring video of a monitoring area through a high-definition camera, and sending the monitoring video to a collection analysis module; the monitoring area is a target monitoring area of the high-definition camera;
the acquisition analysis module receives the monitoring video and then performs video primary analysis on the monitoring video; the video initial analysis means identifying character information in a monitoring video; after the character information is identified in the monitoring video, generating an image analysis signal, and carrying out image analysis on the monitoring video by a collecting and analyzing module;
when the visitor is marked as a stranger, extracting the stranger number in the monitoring video, and marking the stranger number as N; determining a threat level and a high-definition camera position according to the stranger number N; wherein N is a non-0 natural number;
when the threat level is a third level, sending a slight threat signal and the position of the high-definition camera to an early warning scheduling module through the cloud platform; when the threat level is a second level, sending a medium threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform; when the threat level is a first level, sending a serious threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform;
sending the early warning signal sending records to a data storage module through a cloud platform for storage, wherein the early warning signals comprise a slight threat signal, a medium threat signal and a serious threat signal.
Further, the determining of the threat level specifically includes:
when the number of strangers N is 1, acquiring the number of occurrences of the strangers in the high-definition camera, and marking the number of occurrences as CC; when the occurrence frequency CC meets the condition that CC is less than L3, judging that the stranger threat level is a third level; when the occurrence frequency CC meets that L3 is not more than CC, judging that the stranger threat level is a second level; wherein L3 is a preset occurrence threshold, and L3 is greater than 0;
when the number N of strangers is larger than 1, acquiring the number of times of the contact of the strangers in the high-definition camera, and marking the number of times of the contact as PC; the meeting face means that at least two of strangers simultaneously appear in one monitoring image; when the number of times of face collision PC is less than PC < L4, judging that the threat level of the stranger is a second level; when the number of times of face collision PC meets the condition that L4 is not more than PC, judging that the threat level of the stranger is a first level; wherein L4 is a preset number threshold of times of surface contact, and L4 is greater than 0;
sending the position of the high-definition camera to an early warning scheduling module through the cloud platform;
sending the threat level to a data storage module through a cloud platform for storage; the threat levels include a first level, a second level, and a third level.
Further, the image analysis specifically includes:
decomposing the monitoring video into monitoring images frame by frame, and carrying out image preprocessing on the monitoring images; the image preprocessing comprises image segmentation, image correction, image enhancement and gray scale transformation;
extracting a facial image of the visitor through the monitoring image after image preprocessing, and marking the facial image of the visitor as an image to be verified;
matching the image to be verified with the face image in the white list data table to obtain a white list matching degree, and marking the white list matching degree as BPD; when the white list matching degree BPD meets the condition that L1 is less than BPD, judging that the image to be verified is successfully matched, and generating an admission signal through a cloud platform; when the white list matching degree BPD is more than 0 and less than or equal to L1, matching the image to be verified with the key precaution list data table to obtain the matching degree, and marking the precaution list matching degree as FPD; when the matching degree FPD of the precaution list meets L2< FPD, judging that the image to be verified is successfully matched, and sending a precaution early warning signal to an early warning scheduling module through the cloud platform; when the matching degree FPD of the precaution list is more than 0 and less than or equal to L2, marking the visiting person as a stranger and generating an entrance forbidding signal; wherein L1 is a preset white list matching threshold, and L2 is a preset precautionary list matching threshold.
Further, the early warning dispatch module receives the early warning signal and schedules the staff, and the method comprises the following steps:
when the early warning scheduling module receives the high-definition camera position, marking the high-definition camera position as a target position, acquiring workers in a circle with the target position as the center of the circle and R1 as the radius, acquiring the distance between the workers and the target position, and marking the distance as a working distance; wherein R1 presets a radius threshold;
when the early warning scheduling module receives a slight threat signal, K1 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a medium threat signal, K2 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a serious threat signal, K3 workers with the shortest working distance are dispatched to reach the target position; wherein K1, K2 and K3 are preset people number threshold values, and K1 is more than 0 and less than 1.5 multiplied by K1 and less than or equal to K2 and more than 2 multiplied by K2 and less than or equal to K3;
and sending the dispatching records of the workers to a data storage module for storage through the cloud platform.
Further, registering and logging in specifically includes:
the user is connected with the registration login module through the intelligent terminal; the intelligent terminal comprises an intelligent mobile phone, a tablet personal computer and a notebook computer, and is in wireless connection with the registration login module;
the user sends the registration information to the registration login module through the intelligent terminal; the registration information comprises a name, a mobile phone number authenticated by a real name, a face image acquired in real time and a visiting affair;
acquiring a white list data table and a key precaution list data table from a data storage module through a cloud platform; analyzing and matching the registration information with the white list data table, and sending a registration completion signal to the intelligent terminal of the user through the registration login module when the matching is successful; when the matching is unsuccessful, the registration information is analyzed and matched with the key precaution list data table, and when the matching is successful, a passing prohibition signal is sent to the intelligent terminal of the user through the registration login module; when the matching is unsuccessful, generating a registration signal and sending the registration signal to a registration login module;
the registration login module registers according to the registration information, sends a registration success signal to the intelligent terminal of the specific personnel after the registration is completed, and meanwhile adds the registration information to the white list data table;
and sending the registration information, the registration completion signal sending record, the prohibition of the signal sending record and the registration success signal sending record to the data storage module for storage through the cloud platform.
Further, the early warning scheduling module provides early warning information for the user after receiving the early warning signal, and the method comprises the following steps:
the method comprises the steps that the mobile phone number of a registered user is obtained through a data storage module, the mobile phone number is located, and when the position of the mobile phone number is located in a monitoring area, the mobile phone number is marked as a target mobile phone number;
acquiring a linear distance between a target mobile phone number and a target position, and marking the linear distance as ZJ;
when the straight-line distance ZJ is smaller than or equal to a preset safety distance threshold value, planning an avoiding route for a user; the avoidance route takes the target mobile phone number as a starting point and a safety exit of the monitoring area as a key point, and the shortest distance between the avoidance route and the target position is not less than a preset shortest distance threshold value;
and sending the avoiding route to a target mobile phone number, and enabling the user to be far away from the target position according to the avoiding route.
Further, high definition digtal camera adjusts through the action cloud platform, includes:
extracting the strangers in the monitoring video according to the time sequence, and marking the strangers as MRi；
When the number of clients MRiWhen the value is equal to 0, controlling the action holder not to act; when the number of clients MRiWhen the content of the organic acid is more than or equal to 1,
and adjusting the action holder to ensure that the stranger image in the monitoring video is at the central position of the monitoring video, and the area occupied by the client image accounts for more than one half of the monitoring video.
Further, the safety protection module is used for virus detection of files in the data storage module, and the specific monitoring steps are as follows:
v1: calculating a digital abstract of a file in a data storage module by a Hash algorithm;
v2: counting the proportion of the number of the digital abstracts to the total number of the files, which is different from the comparison result of the digital abstracts and the digital abstracts database, and marking the proportion as E; the digital abstract database is stored in the data storage module;
v3: carrying out opening speed test on files in the data storage module, and marking the average value of the opening speed as
V4: by the formula
Acquiring a virus threat coefficient B; the delta 1 and the delta 2 are preset proportionality coefficients, and the delta 1 and the delta 2 are both larger than 0;
v5: when the virus threat coefficient is more than 0 and less than or equal to J1, judging that the file is not attacked by the virus, and sending a green safety signal to the early warning scheduling module through the processor; and when the virus threat coefficient J1 is less than B, judging that the file is attacked by the virus, interrupting the reading of the data storage module through the control of the processor, and simultaneously sending a virus attack signal to the early warning scheduling module through the processor.
Example two:
the acquisition and analysis module is in communication connection with the vehicle barrier gate; the acquisition and analysis module acquires the license plate number through the monitoring camera; and matching the license plate number with a vehicle white list and a vehicle black list in the data storage module and executing corresponding operation according to a matching result.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The working principle of the invention is as follows:
a user registers through an intelligent terminal, and sends registration login information to a data storage module for storage; acquiring a serial number i of a high-definition camera, acquiring a monitoring video of a monitoring area through the high-definition camera, and sending the monitoring video to a collection analysis module; the acquisition analysis module receives the monitoring video and then performs video primary analysis on the monitoring video; after the character information is identified in the monitoring video, generating an image analysis signal, and carrying out image analysis on the monitoring video by a collecting and analyzing module; when the visitor is marked as a stranger, extracting the stranger number in the monitoring video, and marking the stranger number as N; determining a threat level and a high-definition camera position according to the stranger number N; when the threat level is a third level, sending a slight threat signal and the position of the high-definition camera to an early warning scheduling module through a processor; when the threat level is a second level, sending a medium threat signal and the position of the high-definition camera to the early warning scheduling module through the processor; when the threat level is a first level, sending a serious threat signal and the position of a high-definition camera to an early warning scheduling module through a processor; the early warning scheduling module dispatches workers to a target position for processing according to the early warning signal;
when the early warning scheduling module receives the high-definition camera position, marking the high-definition camera position as a target position, acquiring workers in a circle with the target position as the center of the circle and R1 as the radius, acquiring the distance between the workers and the target position, and marking the distance as a working distance; when the early warning scheduling module receives a slight threat signal, K1 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a medium threat signal, K2 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a serious threat signal, K3 workers with the shortest working distance are dispatched to reach the target position.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A smart park emergency early warning management system based on cloud computing is characterized by comprising a cloud platform, an early warning scheduling module, a data storage module, a registration and login module, an acquisition and analysis module and a safety protection module;
the cloud platform is respectively in communication connection with the early warning scheduling module, the data storage module, the registration and login module, the acquisition and analysis module and the safety protection module;
the registration login module is used for a user to perform registration login through the intelligent terminal and sending registration login information to the data storage module for storage;
the data storage module stores a white list data table and a key precaution list data table; the white list data table is the registered personnel, and the key precaution list is the preset person who is forbidden to pass through;
the acquisition and analysis module is in communication connection with the high-definition camera, supports the high-definition cameras with different video stream protocols, and converts the different video stream protocols into standard protocols inside the acquisition and analysis module in a dynamic link library manner; the acquisition and analysis module is used for acquiring and analyzing the video image of the visitor.
2. The intelligent park emergency early warning management system based on cloud computing of claim 1, wherein the acquisition and analysis module is used for acquiring and analyzing video images of visitors through a high-definition camera, and comprises:
acquiring the number i, i-1, 2, … …, n of the high-definition camera; acquiring a monitoring video of a monitoring area through a high-definition camera, and sending the monitoring video to a collection analysis module; the monitoring area is a target monitoring area of the high-definition camera;
the acquisition analysis module receives the monitoring video and then performs video primary analysis on the monitoring video; the video initial analysis is to identify the character information in the monitoring video; after the character information is identified in the monitoring video, generating an image analysis signal, and carrying out image analysis on the monitoring video by a collecting and analyzing module;
when the visitor is marked as a stranger, extracting the stranger number in the monitoring video, and marking the stranger number as N; determining a threat level and a high-definition camera position according to the stranger number N; wherein N is a non-0 natural number;
when the threat level is a third level, sending a slight threat signal and the position of the high-definition camera to an early warning scheduling module through the cloud platform; when the threat level is a second level, sending a medium threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform; when the threat level is a first level, sending a serious threat signal and the position of a high-definition camera to an early warning scheduling module through a cloud platform;
sending the early warning signal sending records to a data storage module through a cloud platform for storage, wherein the early warning signals comprise a slight threat signal, a medium threat signal and a serious threat signal.
3. The cloud-computing-based intelligent campus emergency alert management system according to claim 2, wherein the determination of the threat level specifically comprises:
when the number of strangers N is 1, acquiring the number of occurrences of the strangers in the high-definition camera, and marking the number of occurrences as CC; when the number of occurrences CC satisfies CC < L3, judging that the stranger threat level is a third level; when the occurrence frequency CC meets that L3 is not more than CC, judging that the stranger threat level is a second level; wherein L3 is a preset occurrence threshold, and L3 is greater than 0;
when the number of strangers N is greater than 1, acquiring the number of times of the contact of the strangers in the high-definition camera, and marking the number of times of the contact as PC; the meeting face means that at least two of strangers appear in one monitoring image at the same time; when the number of times of face collision PC meets the condition that PC is less than L4, judging that the threat level of the stranger is a second level; when the number of times of face collision PC meets the condition that L4 is not more than PC, judging that the threat level of the stranger is a first level; wherein L4 is a preset number threshold of times of surface contact, and L4 is greater than 0;
sending the position of the high-definition camera to an early warning scheduling module through the cloud platform;
sending the threat level to a data storage module through a cloud platform for storage; the threat levels include a first level, a second level, and a third level.
4. The cloud-computing-based intelligent campus emergency alert management system of claim 2, wherein the image analysis specifically comprises:
decomposing the monitoring video into monitoring images frame by frame, and carrying out image preprocessing on the monitoring images; the image preprocessing comprises image segmentation, image correction, image enhancement and gray scale transformation;
extracting a facial image of the visitor through the monitoring image after image preprocessing, and marking the facial image of the visitor as an image to be verified;
matching the image to be verified with the face image in the white list data table to obtain a white list matching degree, and marking the white list matching degree as BPD; when the white list matching degree BPD meets L1< BPD, judging that the image to be verified is successfully matched, and generating an admission signal through a cloud platform; when the white list matching degree BPD meets 0 and the BPD is less than or equal to L1, matching the image to be verified with the key precaution list data table to obtain the matching degree, and marking the precaution list matching degree as FPD; when the matching degree FPD of the precaution list meets L2< FPD, judging that the image to be verified is successfully matched, and sending a precaution early warning signal to an early warning scheduling module through the cloud platform; when the matching degree FPD of the precaution list meets 0< FPD is less than or equal to L2, the visiting person is marked as a stranger, and an entrance forbidding signal is generated; wherein L1 is a preset white list matching threshold, and L2 is a preset precautionary list matching threshold.
5. The intelligent park emergency early warning management system based on cloud computing of claim 1, wherein the early warning scheduling module receives early warning signals to schedule workers, and comprises:
when the early warning scheduling module receives the high-definition camera position, marking the high-definition camera position as a target position, acquiring workers in a circle with the target position as the center of the circle and R1 as the radius, acquiring the distance between the workers and the target position, and marking the distance as a working distance; wherein R1 presets a radius threshold;
when the early warning scheduling module receives a slight threat signal, K1 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a medium threat signal, K2 workers with the shortest working distance are dispatched to reach the target position; when the early warning scheduling module receives a serious threat signal, K3 workers with the shortest working distance are dispatched to reach the target position; wherein K1, K2 and K3 are preset people number thresholds, and 0< K1<1.5 xK 1 ≤ K2<2 xK 2 ≤ K3;
and sending the dispatching records of the workers to a data storage module for storage through the cloud platform.
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