CN115002150A - Intelligent community intelligent epidemic situation management and control system and method - Google Patents
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Abstract
The invention discloses an intelligent epidemic situation control system and method for a smart community, and relates to the technical field of smart communities. The problem of current epidemic situation prevention and control do not have the linkage, need artifical information of verifying, report to the police, still adopt the cell-phone to sweep the sign indicating number self-service registration, the information can't verify its accuracy and authenticity, has the epidemic prevention leak, causes the epidemic situation to spread, and operating time is long, detection efficiency is low, and personnel's gathering density is high, and the epidemic prevention security is relatively poor is solved. This intelligent epidemic situation management and control system and method of wisdom community, each equipment of expert's personnel of community and system are managed through getting through to the epidemic situation management and control platform, realize contactless, convenient personnel experience of passing through, whole healthy contactless opening the door, the epidemic prevention efficiency of controlling has effectively been improved, fully with the help of the thing networking, network communication technologies such as sensor network are in the same place property management, the security protection, system integration such as communication, realize non-contact verification, when avoiding cross infection, the false rate that reduces manual operation has also improved data acquisition's authenticity and accuracy.
Description
Technical Field
The invention relates to the technical field of intelligent communities, in particular to an intelligent epidemic situation control system and method for an intelligent community.
Background
The community is the first line of epidemic situation joint defense joint control and also the most effective defense line of external defense input and internal defense diffusion. The community defense line is kept, so that the channel for spreading the epidemic situation can be effectively cut off. However, the current community epidemic situation management still has the following problems:
the residential building management and control in the jurisdiction area of the community still adopts a manual management and control mode, the human resource consumption is high, a large amount of conditions of high human labor force and high human cost are caused, the management and control efficiency is low, the resident experience is poor, and management and control personnel cannot screen the entrance and exit of foreign people;
epidemic situation prevention and control are not linked, information needs to be verified manually and an alarm is given, a mobile phone code scanning self-service registration is still adopted, the information cannot be checked for accuracy and authenticity, epidemic situation diffusion is caused due to epidemic prevention holes, the operation time is long, the detection efficiency is low, the gathering density of personnel is high, and the epidemic prevention safety is poor.
Disclosure of Invention
The invention aims to provide an intelligent epidemic situation control system and method for a smart community, an epidemic situation control platform achieves non-contact and convenient personnel passing experience, is healthy and non-contact in the whole process, automatically discriminates the authority of owners, rejects outsiders, safely checks customs, effectively improves the prevention, control and epidemic prevention efficiency, fully integrates systems for property management, security protection, communication and the like by means of network communication technologies such as the Internet of things and a sensor network, achieves non-contact check, avoids cross infection, reduces the error rate of manual operation, improves the authenticity and accuracy of data acquisition, and solves the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
the utility model provides an intelligent epidemic situation management and control system of wisdom community, including epidemic situation management and control platform, mobile communication network, high in the clouds database and management and control terminal, epidemic situation management and control platform carries out data interaction through mobile communication network with the management and control terminal, the high in the clouds database carries out data interaction with epidemic situation management and control platform, the management and control terminal includes face identification camera, the temperature detection camera, face automatic identification entrance guard, vehicle automatic identification entrance guard and intelligent voice assistant, carry out data interaction through the LAN respectively between the management and control terminal and constitute terminal acquisition system, terminal acquisition system carries out data interaction with GPS positioning system respectively, GPS positioning system carries out data interaction with epidemic situation management and control platform.
Further, the management and control terminal comprises a terminal data acquisition module, a terminal equipment positioning module, a terminal equipment interaction module and a data classification transmission module, the terminal data acquisition module acquires multi-source data, the terminal data acquisition module transmits acquired data to the terminal equipment positioning module, the terminal equipment positioning module interacts with a GPS positioning system in real time, positioning identification is carried out on the acquired data, interaction between equipment is carried out on the management and control terminal through the terminal equipment interaction module, the terminal equipment positioning module transmits the data after identification positioning to the data classification transmission module, the data classification transmission module extracts characteristics from the received data, and the data classification transmission is carried out to the epidemic situation management and control platform according to the extracted characteristics.
Further, the epidemic situation management and control platform comprises a front-end data management module and a rear-end community management module, the front-end data management module comprises a collected data processing module, a management and control area analysis module, a personnel density analysis module, a moving range analysis module, a behavior track analysis module, a vehicle track analysis module and a display module, and the rear-end community management module comprises an abnormal early warning module, an epidemic prevention alarm module, an epidemic situation prevention and control rescue module, a rescue scheme making module, a feedback analysis module and an equipment control module.
Further, the data that management and control terminal was gathered is received to the data processing module that gathers, and carry out classification management according to the transmission extraction mode of data, compare video data and locating data respectively and fuse, management and control regional analysis module carries out regional management and control to personnel information and quantity in the region according to the locating data, personnel density analysis module carries out personnel density analysis according to video data and regional management and control data, the data according to gathering are carried out personnel and are compared to the migration range analysis module, confirm the different data of same personnel, confirm personnel's migration range, action orbit analysis module carries out the orbit analysis according to personnel's migration range, and judge the accuracy of migration range, vehicle information is discerned to vehicle track analysis module, and search and analysis vehicle track to the license plate, judge vehicle track security.
Furthermore, the display module respectively carries out data interaction with the management and control area analysis module, the personnel density analysis module, the movement range analysis module, the behavior track analysis module and the vehicle track analysis module, the display module dynamically displays real-time videos, information layers such as display grids, party organizations, events, comprehensive treatment, population, buildings, components and workers are displayed, distribution condition data of all the jurisdiction areas and personnel and vehicles are displayed, a space query analysis tool is provided, an epidemic situation key prevention and control personnel behavior track graph is provided, and bidirectional association operation of a GPS positioning system and an epidemic situation management and control platform is supported.
Further, the abnormal early warning module respectively realizes accurate recognition of people, vehicles and abnormal behaviors through AI intelligent early warning on data analyzed by the personnel density analysis module, the movement range analysis module, the behavior track analysis module and the vehicle track analysis module, the AI intelligent early warning comprises crowd situation early warning and behavior early warning, the crowd situation early warning comprises the warning of exceeding the number of regional personnel, increasing the density of local personnel and gathering personnel, the behavior early warning comprises the warning of rapid movement, article leaving/moving and line crossing invasion, the equipment control module controls terminal equipment, personnel in a safety threshold can enter and exit the community, the abnormal early warning is prompted to the personnel with a critical safety threshold, the epidemic prevention alarm module alarms the behavior track and the density data exceeding the warning threshold, the epidemic prevention and control rescue module receives the epidemic prevention and control rescue alarm to intensively rescue infected epidemic situation personnel and suspected personnel thereof, the rescue scheme making module makes a scheme for the rescuers, the rescue is implemented by the rescuers, and the rescue results are fed back to the feedback analysis module faithfully.
Further, the cloud database comprises an identity authentication database, a behavior track database and a decision scheme database, wherein the identity authentication database, the behavior track database and the decision scheme database are respectively used for data interaction, the identity authentication database stores identity authentication information, face recognition information and monitoring video data, the behavior track database stores geographic position data, behavior data and path track data, the identity authentication database corresponds to the behavior track database one by one, the decision scheme database stores historical scheme data and feedback data, the cloud database provides a data basis for the epidemic situation control platform, and the epidemic situation control platform is used for data interaction with a government management department through a mobile communication network and provides a management basis for the management and control of the epidemic situation of the government management department.
Further, the process of comparing the personnel according to the collected data, determining different data of the same personnel and determining the movement range of the personnel by the movement range analysis module comprises the following steps:
acquiring data acquired by the control terminal, and extracting personnel data from the data;
preprocessing the personnel data to obtain the number of personnel contained in the personnel data;
establishing corresponding personnel storage spaces based on the personnel number, performing personnel comparison by using the storage data of the cloud database, and respectively acquiring pre-stored information corresponding to each personnel;
inputting the pre-stored information into a corresponding personnel storage space, and establishing personnel information;
establishing a time axis according to the data length of the acquired data;
inputting the acquired data into the time axis to generate dynamic data;
extracting an initial position corresponding to each person from the dynamic data, determining the actual position of each initial position in the community, and analyzing the position characteristics of the person;
dividing the dynamic data into a plurality of unit data sections, and respectively acquiring the moving position corresponding to each person in each unit data section;
acquiring the initial position of the same person and the moving position corresponding to each unit data segment, establishing a person moving track, and generating a moving characteristic corresponding to each person according to the moving track;
meanwhile, extracting the data proportion of each person information in each unit data segment, and generating the pause feature of each person;
acquiring a target unit data segment where the maximum pause feature corresponding to each person is located, and generating a position attribute based on the sequence of the target data segment in the dynamic data;
extracting the action behavior of each person in the corresponding target unit data segment and combining the corresponding position attribute to obtain the communication characteristics among different persons;
establishing movement data corresponding to each person according to the position characteristics, the movement characteristics and the communication characteristics corresponding to each person;
and analyzing the community environment contained in the mobile data to generate a mobile range corresponding to each person.
Further, the step of analyzing the personnel density by the personnel density analysis module according to the video data and the area management and control data includes:
performing brightness detection on the video data, and selecting an adaptive brightness compensation function according to a detection result; compensating the video data by using the brightness compensation function to obtain compensated video data;
performing framing processing on the compensated video data to obtain a processing result;
extracting character feature points of each frame of image in the processing result to obtain a feature point extraction result;
comparing the feature point extraction results of each frame of image, and selecting the feature points of the target person appearing in each frame of image;
calculating the current people flow degree in the compensated video data according to the characteristic points of the target person:
wherein T is the current people flow degree in the compensated video data, and beta is the video number
According to the corresponding environment scaling, cos is expressed as cosine, pi is expressed as circumference ratio, alpha is expressed as environment coverage ratio in the compensated video data, M is expressed as the number of frame images, and i is expressed asFor the ith frame image, N is the number of the characteristic points of the target person, j is the jth characteristic point of the target person, ln is the natural logarithm, and p ij The contour coefficient of the jth target person feature point in the ith frame image is expressed as a ij Expressed as a weighting coefficient expressed as the jth target person feature point in the ith frame image, b ij The offset coefficient of the jth target person characteristic point in the ith frame image is represented, and p' is represented as the overall contour coefficient in the compensated video data;
determining the maximum expected pedestrian volume degree of a target area corresponding to the video data according to the area management and control data;
calculating the density coefficient of the pedestrian flow of the target area according to the maximum expected pedestrian flow degree and the current pedestrian flow degree:
wherein F is the people flow density coefficient of the target area, T 1 Expressed as the maximum expected degree of pedestrian flow, θ 1 Expressing the first weight value of the human flow degree to the calculation result, s is expressed as the ratio of human body characteristics in the compensated video data, s 1 Expressed as the ratio of other features in the compensated video data, theta, to the human body features 2 Expressing a second weight value of the feature proportion to the calculated result, Q expressing available space in the compensated video data, Q 1 Expressed as the maximum visualization space in the compensated video data, θ 3 The table is a third weight value of the space proportion to the calculation result;
and analyzing the people flow density of the target area according to the people flow density coefficient of the target area.
The invention provides another technical scheme, and a control method of an intelligent epidemic situation control system of an intelligent community comprises the following steps:
the method comprises the following steps: the management and control terminal acquires terminal data through a terminal acquisition system, performs classified transmission and data positioning on the acquired data through a terminal data acquisition module and a terminal equipment positioning module, and conveys the positioning data to a front-end data management module according to classification;
step two: the front-end data management module is used for respectively carrying out classification management and analysis on the acquired data, judging high-risk personnel, carrying out dynamic monitoring and data display in real time, carrying out data interaction on the data of each community and strengthening the relation among the communities;
step three: the back-end community management module conducts community equipment management and control according to the data of the front-end data management module, all equipment and systems of community people are communicated, an identity authentication system is unified, and non-contact and convenient personnel passing experience is achieved by means of technologies such as face recognition.
Compared with the prior art, the invention has the beneficial effects that:
according to the intelligent epidemic situation control system and method for the intelligent community, linkage and intercommunication between communities are achieved through the terminal acquisition system, the establishment of an epidemic situation control platform is taken as a basis, a unified epidemic situation prevention and control system is established, information service integration is achieved intelligently, systems for property management, security protection, communication and the like are integrated together fully by means of network communication technologies such as the Internet of things and the sensor network, non-contact check is achieved, cross infection is avoided, the error rate of manual operation is reduced, and authenticity and accuracy of data acquisition are improved.
According to the intelligent epidemic situation control system and method for the smart community, an epidemic situation control platform detects body temperature through an A I algorithm, on-site voice reminding is achieved, face information is captured intelligently, all devices and systems of community people are communicated, an identity authentication system is unified, non-contact and convenient personnel passing experience is achieved by means of technologies such as face recognition, door opening is achieved in a healthy and non-contact mode in the whole process, scientific and technological travel services are warm, opening is not needed, face brushing and passing are conducted safely, hands are released noninductively, owners are allowed to screen automatically, outsiders are rejected, safety is kept, prevention and control efficiency is effectively improved, and a cloud database provides management basis for epidemic situation control of government management departments.
Drawings
FIG. 1 is an overall module topology of the present invention;
FIG. 2 is a block diagram of a management and control terminal according to the present invention;
FIG. 3 is a block diagram of an epidemic situation management and control platform according to the present invention;
FIG. 4 is a block diagram of a cloud database according to the present invention;
FIG. 5 is a block diagram illustrating a connection between a cloud database and an epidemic situation management and control platform according to the present invention;
FIG. 6 is a flowchart of a method of the epidemic situation management system of the present invention.
In the figure: 1. an epidemic situation control platform; 11. a front-end data management module; 111. a data acquisition processing module; 112. a control area analysis module; 113. a personnel density analysis module; 114. a moving range analysis module; 115. a behavior trace analysis module; 116. a vehicle trajectory analysis module; 117. a display module; 12. a back-end community management module; 121. an anomaly early warning module; 122. an epidemic prevention alarm module; 123. an epidemic situation prevention and control rescue module; 124. a rescue scheme making module; 125. a feedback analysis module; 126. a device control module; 2. a mobile communication network; 3. a cloud database; 31. an identity authentication database; 32. a behavior trace database; 33. a decision scheme database; 4. a control terminal; 41. a terminal data acquisition module; 42. a terminal device positioning module; 43. a terminal device interaction module; 44. a data classification transmission module; 5. a GPS positioning system; 6. a government regulatory department.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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. 1-2, an intelligent community intelligent epidemic situation management and control system comprises an epidemic situation management and control platform 1, a mobile communication network 2, a cloud database 3 and a management and control terminal 4, wherein the epidemic situation management and control platform 1 and the management and control terminal 4 perform data interaction through the mobile communication network 2, the cloud database 3 performs data interaction with the epidemic situation management and control platform 1, the management and control terminal 4 comprises a face recognition camera, a temperature detection camera, a face automatic recognition entrance guard, a vehicle automatic recognition entrance guard and an intelligent voice assistant, the management and control terminal 4 performs data interaction through a local area network to form a terminal acquisition system, the terminal acquisition system performs data interaction with a GPS positioning system 5, the GPS positioning system 5 performs data interaction with the epidemic situation management and control platform 1, the management and control terminal 4 comprises a terminal data acquisition module 41, a terminal equipment positioning module 42, a terminal equipment interaction module 43 and a data classification transmission module 44, the terminal data acquisition module 41 is used for carrying out multi-source data acquisition, the terminal data acquisition module 41 is used for transmitting acquired data to the terminal equipment positioning module 42, the terminal equipment positioning module 42 is used for carrying out real-time interaction with the GPS positioning system 5 and positioning identification on the acquired data, the control terminal 4 is used for carrying out interaction among equipment through the terminal equipment interaction module 43, the terminal equipment positioning module 42 is used for transmitting the data after identification positioning to the data classification transmission module 44, the data classification transmission module 44 is used for extracting characteristics of the received data and carrying out classification transmission to the epidemic situation control platform 1 according to the extracted characteristics, social interval linkage and intercommunication are realized through the terminal acquisition system, the epidemic situation control platform 1 is built as a basis to construct a uniform epidemic situation prevention and control system, information service integration is intelligently realized, and property management, material industry management and material industry management are carried out by fully utilizing network communication technologies such as the Internet of things, sensor network and the like, The security and protection system, the communication system and the like are integrated together, non-contact checking and inspection are realized, cross infection is avoided, the error rate of manual operation is reduced, and the authenticity and the accuracy of data acquisition are improved;
referring to fig. 3, the epidemic situation management and control platform 1 includes a front-end data management module 11 and a back-end community management module 12, the front-end data management module 11 includes a collected data processing module 111, a management and control area analysis module 112, a personnel density analysis module 113, a movement range analysis module 114, a behavior trajectory analysis module 115, a vehicle trajectory analysis module 116 and a display module 117, the back-end community management module 12 includes an anomaly early warning module 121, an epidemic prevention alarm module 122, an epidemic situation prevention and control rescue module 123, a rescue scheme making module 124, a feedback analysis module 125 and an equipment control module 126, the collected data processing module 111 receives data collected by the management and control terminal 4, performs classification management according to a transmission and extraction manner of the data, compares and fuses video data and positioning data, the management and control area analysis module 112 performs area management and control according to personnel information and quantity in an area, the personnel density analysis module 113 performs personnel density analysis according to video data and area management and control data, the movement range analysis module 114 performs personnel comparison according to collected data to determine different data of the same personnel, the movement range of the personnel is determined, the behavior track analysis module 115 performs track analysis according to the movement range of the personnel and judges the accuracy of the movement range, the vehicle track analysis module 116 recognizes vehicle information, searches and analyzes vehicle tracks according to license plates and judges the safety of the vehicle tracks, the display module 117 performs data interaction with the management and control area analysis module 112, the personnel density analysis module 113, the movement range analysis module 114, the behavior track analysis module 115 and the vehicle track analysis module 116 respectively, the display module 117 performs real-time video dynamic display, and displays information layers such as grids, party organizations, events, comprehensive treatment, population, buildings, components, workers and the like, the method comprises the steps of displaying data of distribution conditions of all jurisdictions and personnel and vehicles, providing a space query analysis tool, providing a behavior trace diagram of important epidemic situation prevention and control personnel, supporting the bidirectional association operation of a GPS (global positioning system) 5 and an epidemic situation control platform 1, wherein an abnormity early warning module 121 respectively realizes the accurate identification of people, vehicles and abnormal behaviors through AI intelligent early warning on data analyzed by a personnel density analysis module 113, a movement range analysis module 114, a behavior trace analysis module 115 and a vehicle trace analysis module 116, the AI intelligent early warning comprises crowd situation early warning and behavior early warning, the crowd situation early warning comprises the exceeding of the quantity of regional personnel, the increase of local personnel density and personnel gathering early warning, the behavior early warning comprises rapid movement, article leaving/removing and offline invasion early warning, an equipment control module 126 controls terminal equipment, personnel in and out of a safety threshold value can enter and exit, and abnormal early warning is carried out on personnel in a critical safety threshold value, the epidemic prevention alarming module 122 gives an alarm to the action track and the density data which exceed the alarming threshold value, the epidemic situation prevention control rescue module 123 receives the epidemic situation prevention control rescue alarm and carries out centralized rescue on the people infected with the epidemic situation and the suspected people, the rescue scheme making module 124 makes a scheme for the rescuers, the scheme is implemented by the rescuers, the rescue result is fed back to the feedback analysis module 125, the epidemic situation control platform 1 detects the body temperature through an AI algorithm, prompts by on-site voice, captures facial information intelligently, gets through all the equipment and systems of community people, unifies an identity authentication system, realizes non-contact and convenient personnel passing experience by relying on technologies such as face recognition and the like, opens the door healthily and contactlessly in the whole process, has temperature for scientific and technological trip service, does not need to open, brushes the face safely, passes noninductive, releases both hands, enables the owner authority to be automatically discriminated, rejects outsiders, safely checks the customs, and effectively improves the prevention and control epidemic prevention efficiency;
referring to fig. 4-5, the cloud database 3 includes an identity authentication database 31, a behavior trajectory database 32, and a decision scheme database 33, the identity authentication database 31, the behavior trajectory database 32, and the decision scheme database 33 respectively perform data interaction, the identity authentication database 31 stores identity authentication information, face recognition information, and monitoring video data, the behavior trajectory database 32 stores geographic position data, behavior data, and path trajectory data, the identity authentication database 31 corresponds to the behavior trajectory database 32 one to one, the decision scheme database 33 stores history scheme data and feedback data, the cloud database 3 provides a data base for the epidemic situation control platform 1, and the epidemic situation control platform 1 performs data interaction with the government management department 6 through the mobile communication network 2 to provide a management basis for the government management department 6 to manage and control the epidemic situation.
In one example, the process of the movement range analysis module 114 comparing the persons according to the collected data, determining different data of the same person, and determining the movement range of the person includes:
acquiring data acquired by the control terminal 4, and extracting personnel data from the data;
preprocessing the personnel data to obtain the number of personnel contained in the personnel data;
establishing corresponding personnel storage spaces based on the personnel number, performing personnel comparison by using the storage data of the cloud database 3, and respectively acquiring pre-stored information corresponding to each personnel;
inputting the pre-stored information into a corresponding personnel storage space, and establishing personnel information;
establishing a time axis according to the data length of the acquired data;
inputting the acquired data into the time axis to generate dynamic data;
extracting an initial position corresponding to each person from the dynamic data, determining the actual position of each initial position in the community, and analyzing the position characteristics of the person;
dividing the dynamic data into a plurality of unit data sections, and respectively acquiring a moving position corresponding to each person in each unit data section;
acquiring the initial position of the same person and the moving position corresponding to each unit data segment, establishing a person moving track, and generating a moving characteristic corresponding to each person according to the moving track;
meanwhile, extracting the data proportion of each person information in each unit data segment, and generating the pause feature of each person;
acquiring a target unit data segment where the maximum pause feature corresponding to each person is located, and generating a position attribute based on the sequence of the target data segment in the dynamic data;
extracting the action behavior of each person in the corresponding target unit data segment and combining the corresponding position attribute to obtain the communication characteristics among different persons;
establishing movement data corresponding to each person according to the position characteristics, the movement characteristics and the communication characteristics corresponding to each person;
and analyzing the community environment contained in the mobile data, and generating a mobile range corresponding to each person.
In this example, the people data represents information generated by people currently active within the community;
in this example, the pre-stored information represents information entered in advance by community personnel;
in this example, the time axis represents a time progress corresponding to the acquisition duration of the data;
in this example, the initial position represents the position of the personnel data in the total data, and may also represent the position of the personnel in the community;
in this example, the location features represent the location where a person enters the detection area;
in this example, the location attribute represents a collection of parameters that express the location of the community in a single data segment.
The working principle of the technical scheme is as follows: firstly, extracting personnel data from data collected by a control terminal, analyzing the number of personnel contained in the personnel data to establish a personnel storage space corresponding to the data, comparing the personnel by utilizing the stored data in a cloud database to obtain pre-stored information corresponding to each personnel, establishing personnel information, then establishing a time axis according to the data length of the data to generate dynamic data, extracting an initial position corresponding to each personnel information from the dynamic data, analyzing the position characteristics of the corresponding personnel in a community, dividing the dynamic data into a plurality of unit data sections, respectively acquiring a mobile position corresponding to each personnel information from each unit data section, acquiring the initial position of the same personnel and the mobile position corresponding to each unit data section, acquiring the mobile characteristics corresponding to each personnel, and according to the data occupation ratio of each personnel information in each unit data section, the method comprises the steps of obtaining a target unit data segment with the largest pause characteristic of each person, generating a position attribute, obtaining communication characteristics among different persons according to action behaviors of each person in the corresponding target unit data segment and the corresponding position attribute, establishing mobile data corresponding to each person according to the position characteristics, the mobile characteristics and the communication characteristics corresponding to each person, and finally generating a mobile range corresponding to each person by analyzing a community environment contained in the mobile data.
The beneficial effects of the above technical scheme are as follows: through the activity data of analysts in the community, the moving range of the current personnel who move in the community can be known, the activity data of different personnel can be rapidly acquired by utilizing a data analysis method to analyze the trajectory of the personnel, the communication characteristics among different personnel can be analyzed, therefore, more comprehensive analyst behaviors are taken as the basis for the behaviors of follow-up analysts and the safety of judgment personnel, and the stability and the comprehensiveness of the system are improved to a certain extent.
In one embodiment, the step of analyzing the person density by the person density analysis module 113 according to the video data and the region management data includes:
performing brightness detection on the video data, and selecting an adaptive brightness compensation function according to a detection result; compensating the video data by using the brightness compensation function to obtain compensated video data;
performing framing processing on the compensated video data to obtain a processing result;
extracting character feature points of each frame of image in the processing result to obtain a feature point extraction result;
comparing the feature point extraction results of each frame of image, and selecting the feature points of the target person appearing in each frame of image;
calculating the current people flow degree in the compensated video data according to the characteristic points of the target person:
wherein T represents the current people flow degree in the compensated video data, beta represents the environment scaling corresponding to the video data, cos represents cosine, pi represents circumference ratio, alpha represents the environment coverage ratio in the compensated video data, M represents the number of framing images, i represents the ith frame image, N represents the number of target character feature points, j represents the jth target character feature point, ln represents natural logarithm, and p represents the number of target character feature points ij The contour coefficient of the jth target person feature point in the ith frame image is expressed as a ij Expressed as a weighting coefficient expressed as the jth target person feature point in the ith frame image, b jj Expressed as the bias coefficient of the jth target person feature point in the ith frame image, and p' expressed as the overall contour in the compensated video dataA coefficient;
determining the maximum expected pedestrian volume degree of a target area corresponding to the video data according to the area management and control data;
calculating the density coefficient of the pedestrian flow of the target area according to the maximum expected pedestrian flow degree and the current pedestrian flow degree:
wherein F is the people flow density coefficient of the target area, T 1 Expressed as the maximum expected degree of pedestrian flow, θ 1 Expressing the first weight value of the human flow degree to the calculation result, s is expressed as the ratio of human body characteristics in the compensated video data, s 1 Expressed as the ratio of other features in the compensated video data, theta, except for the human body feature 2 Expressing a second weight value of the feature proportion to the calculated result, Q expressing available space in the compensated video data, Q 1 Expressed as the maximum visualization space in the compensated video data, θ 3 The table is a third weight value of the space proportion to the calculation result;
and analyzing the people flow density of the target area according to the people flow density coefficient of the target area.
The beneficial effects of the above technical scheme are: can be more intuitive and efficient by compensating for video data
The method and the device accurately determine the human body characteristics in the video data, lay a foundation for follow-up people stream density assessment, further, preliminarily assess whether the current people stream density in the video data is excessive or not by calculating the current people stream degree in the compensated video data, improve the practicability, further, intuitively assess the people stream density in a target area according to the people stream density coefficient by calculating the people stream density coefficient in the target area, and enable assessment results to be more reasonable and accurate.
Referring to fig. 6, a method for intelligent epidemic situation management and control of a smart community includes the following steps:
the method comprises the following steps: the management and control terminal 4 collects terminal data through a terminal collection system, performs classified transmission and data positioning on the collected data through a terminal data collection module 41 and a terminal equipment positioning module 42, and conveys the positioning data to the front-end data management module 11 according to classification;
step two: the front-end data management module 11 respectively performs classified management and analysis on the acquired data, judges high-risk personnel, performs dynamic monitoring and data display in real time, performs data interaction on the data of each community, and strengthens the relation among the communities;
step three: the back-end community management module 12 manages and controls community equipment according to the data of the front-end data management module 11, gets through each equipment and system of community people, unifies an identity authentication system, and realizes non-contact and convenient personnel passing experience by relying on technologies such as face recognition.
In conclusion, the intelligent community intelligent epidemic situation control system and method realize linkage and intercommunication among communities through a terminal acquisition system, build an epidemic situation control platform 1 as a basis, construct a unified epidemic situation prevention and control system, intelligently realize information service integration, fully integrate systems of property management, security protection, communication and the like through network communication technologies such as Internet of things, sensor networks and the like, realize non-contact check, avoid cross infection, reduce the error rate of manual operation, improve the authenticity and accuracy of data acquisition, detect body temperature through an AI algorithm by the epidemic situation control platform 1, perform field voice reminding, intelligently capture facial information, get through all devices and systems of community personnel, unify an identity authentication system, realize non-contact and convenient personnel passing experience by relying on technologies such as face recognition and the like, realize healthy and non-contact door opening in the whole course, science and technology trip service has the temperature, need not to open, and safe face brushing, noninductive current releases both hands, and the owner authority is automatic to be discriminated, refuses the outsider, and safety is held up, has effectively improved prevention and control epidemic prevention efficiency, and high in the clouds database 3 provides the management basis for 6 epidemic situation management and control of government administrative department.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (10)
1. The utility model provides an intelligent epidemic situation management and control system of wisdom community, includes epidemic situation management and control platform (1), mobile communication network (2), high in the clouds database (3) and management and control terminal (4), its characterized in that: epidemic situation management and control platform (1) and management and control terminal (4) carry out data interaction through mobile communication network (2), high in the clouds database (3) carries out data interaction with epidemic situation management and control platform (1), management and control terminal (4) include the face identification camera, the temperature detection camera, face automatic identification entrance guard, vehicle automatic identification entrance guard and intelligent voice assistant, carry out data interaction through the LAN respectively between management and control terminal (4) and constitute terminal acquisition system, terminal acquisition system carries out data interaction with GPS positioning system (5) respectively, GPS positioning system (5) carries out data interaction with epidemic situation management and control platform (1).
2. The intelligent epidemic situation control system of claim 1, wherein: the management and control terminal (4) comprises a terminal data acquisition module (41), a terminal equipment positioning module (42), a terminal equipment interaction module (43) and a data classification transmission module (44), wherein the terminal data acquisition module (41) is used for acquiring multi-source data, the terminal data acquisition module (41) is used for transmitting acquired data to the terminal equipment positioning module (42), the terminal equipment positioning module (42) is used for carrying out real-time interaction with the GPS positioning system (5), the collected data are positioned and identified, interaction between the devices is carried out on the control terminal (4) through a terminal device interaction module (43), the data after identification positioning are transmitted to a data classification transmission module (44) through a terminal device positioning module (42), the data classification transmission module (44) extracts characteristics of the received data, and the characteristics are classified and transmitted to the epidemic situation control platform (1) according to the extracted characteristics.
3. The intelligent epidemic situation control system of claim 1, wherein: epidemic situation management and control platform (1) includes front end data management module (11) and rear end community management module (12), front end data management module (11) is including data processing module (111) gathers, management and control area analysis module (112), personnel density analysis module (113), moving range analysis module (114), action track analysis module (115), vehicle track analysis module (116) and display module (117), rear end community management module (12) are including unusual early warning module (121), epidemic prevention alarm module (122), epidemic situation prevention and control rescue module (123), rescue scheme makes module (124), feedback analysis module (125) and equipment control module (126).
4. The intelligent epidemic situation control system of claim 3, wherein: the collected data processing module (111) receives the data collected by the control terminal (4), and carries out classification management according to the transmission and extraction mode of data, respectively carries out comparison and fusion on the video data and the positioning data, a control area analysis module (112) carries out area control on personnel information and quantity in an area according to the positioning data, a personnel density analysis module (113) carries out personnel density analysis according to the video data and the area control data, a moving range analysis module (114) carries out personnel comparison according to the collected data, determines different data of the same personnel, determines the moving range of the personnel, a behavior trajectory analysis module (115) carries out trajectory analysis according to the moving range of the personnel, and the accuracy of the moving range is judged, a vehicle track analysis module (116) identifies vehicle information, and searches and analyzes vehicle tracks aiming at the license plate to judge the safety of the vehicle tracks.
5. The intelligent epidemic situation control system of claim 4, wherein: the display module (117) is respectively in data interaction with the control area analysis module (112), the personnel density analysis module (113), the moving range analysis module (114), the behavior track analysis module (115) and the vehicle track analysis module (116), the display module (117) is used for displaying information layers such as a display grid, party organization, events, comprehensive treatment, population, building, components, workers and the like in real time and dynamically, data of distribution conditions of all jurisdiction areas and personnel and vehicles are displayed, a space query analysis tool is provided, an epidemic situation key prevention and control personnel behavior track graph is provided, and bidirectional association operation of a GPS positioning system (5) and an epidemic situation control platform (1) is supported.
6. The intelligent epidemic situation control system of claim 3, wherein: the abnormity early warning module (121) respectively realizes the accurate identification of people, vehicles and abnormal behaviors through AI intelligent early warning on data analyzed by the personnel density analysis module (113), the movement range analysis module (114), the behavior track analysis module (115) and the vehicle track analysis module (116), the AI intelligent early warning comprises crowd situation early warning and behavior early warning, the crowd situation early warning comprises regional personnel number exceeding, local personnel density increasing and personnel gathering early warning, the behavior early warning comprises rapid movement, article leaving/removing and offline intrusion early warning, the equipment control module (126) controls terminal equipment, personnel in a safety threshold can enter and exit a community, the personnel with a critical safety threshold carry out abnormity early warning prompt, the epidemic prevention alarm module (122) alarms the behavior track and density data exceeding the warning threshold, the epidemic situation prevention control rescue module (123) receives the epidemic situation prevention control rescue alarm, the persons infected with the epidemic situation and the suspected persons are rescued in a centralized manner, a rescue scheme making module (124) makes a scheme for the rescuers, the scheme is implemented by the rescuers, and the rescue result is fed back to a feedback analysis module (125) faithfully.
7. The intelligent epidemic situation control system of claim 1, wherein: the cloud database (3) comprises an identity authentication database (31), a behavior track database (32) and a decision scheme database (33), the identity authentication database (31), the behavior track database (32) and the decision scheme database (33) are respectively used for data interaction, the identity authentication database (31) stores identity authentication information, face recognition information and monitoring video data, the behavior track database (32) stores geographic position data, behavior data and path track data, the identity authentication database (31) corresponds to the behavior track database (32) one by one, the decision scheme database (33) stores historical scheme data and feedback data, the cloud database (3) provides a data base for the epidemic situation control platform (1), the epidemic situation control platform (1) is used for data interaction with a government management department (6) through a mobile communication network (2), provides management basis for epidemic situation management and control of government administrative departments (6).
8. The intelligent epidemic situation control system of claim 4 wherein: the process that the moving range analysis module (114) compares people according to the collected data, determines different data of the same person and determines the moving range of the person comprises the following steps:
acquiring data acquired by the control terminal (4), and extracting personnel data from the data;
preprocessing the personnel data to obtain the number of personnel contained in the personnel data;
establishing corresponding personnel storage spaces based on the personnel number, performing personnel comparison by using the storage data of the cloud database (3), and respectively acquiring pre-stored information corresponding to each personnel;
inputting the pre-stored information into a corresponding personnel storage space, and establishing personnel information;
establishing a time axis according to the data length of the acquired data;
inputting the acquired data into the time axis to generate dynamic data;
extracting an initial position corresponding to each person from the dynamic data, determining the actual position of each initial position in the community, and analyzing the position characteristics of the person;
dividing the dynamic data into a plurality of unit data sections, and respectively acquiring a moving position corresponding to each person in each unit data section;
acquiring the initial position of the same person and the moving position corresponding to each unit data segment, establishing a person moving track, and generating a moving characteristic corresponding to each person according to the moving track;
meanwhile, extracting the data proportion of each person information in each unit data segment, and generating the pause feature of each person;
acquiring a target unit data segment where the maximum pause feature corresponding to each person is located, and generating a position attribute based on the sequence of the target data segment in the dynamic data;
extracting the action behavior of each person in the corresponding target unit data segment, and combining the action behavior with the corresponding position attribute to obtain the communication characteristics among different persons;
establishing movement data corresponding to each person according to the position characteristics, the movement characteristics and the communication characteristics corresponding to each person;
and analyzing the community environment contained in the mobile data, and generating a mobile range corresponding to each person.
9. The intelligent epidemic control system of claim 4, wherein the personnel density analysis module (113) performs personnel density analysis according to the video data and the area control data, and comprises:
performing brightness detection on the video data, and selecting an adaptive brightness compensation function according to a detection result;
compensating the video data by using the brightness compensation function to obtain compensated video data;
performing framing processing on the compensated video data to obtain a processing result;
extracting character feature points of each frame of image in the processing result to obtain a feature point extraction result;
comparing the feature point extraction results of each frame of image, and selecting the feature points of the target person appearing in each frame of image;
calculating the current people flow degree in the compensated video data according to the characteristic points of the target people:
wherein T represents the current pedestrian volume degree in the compensated video data, beta represents the environment scaling corresponding to the video data, cos represents cosine, pi represents circumference ratio, and alpha represents the environment coverage in the compensated video dataThe coverage rate, M is the number of the frame images, i is the ith frame image, N is the number of the characteristic points of the target person, j is the jth characteristic point of the target person, ln is the natural logarithm, p ij The contour coefficient of the jth target person feature point in the ith frame image is expressed as a ij Expressed as a weighting coefficient expressed as the jth target person feature point in the ith frame image, b ij The offset coefficient of the jth target person characteristic point in the ith frame image is represented, and p' is represented as the overall contour coefficient in the compensated video data;
determining the maximum expected pedestrian volume degree of a target area corresponding to the video data according to the area management and control data;
calculating the density coefficient of the pedestrian flow of the target area according to the maximum expected pedestrian flow degree and the current pedestrian flow degree:
wherein F is the people flow density coefficient of the target area, T 1 Expressed as the maximum expected degree of pedestrian flow, θ 1 Expressing the first weight value of the human flow degree to the calculation result, s is expressed as the ratio of human body characteristics in the compensated video data, s 1 Expressed as the ratio of other features in the compensated video data, theta, except for the human body feature 2 Expressing a second weight value of the feature proportion to the calculated result, Q expressing available space in the compensated video data, Q 1 Expressed as the maximum visualization space in the compensated video data, θ 3 The table is a third weight value of the space proportion to the calculation result;
and analyzing the people flow density of the target area according to the people flow density coefficient of the target area.
10. A management and control method of the intelligent community intelligent epidemic management and control system according to any one of claims 1-9, wherein: the method comprises the following steps:
the method comprises the following steps: the control terminal (4) collects terminal data through a terminal collection system, performs classified transmission and data positioning on the collected data through a terminal data collection module (41) and a terminal equipment positioning module (42), and conveys the positioning data to the front-end data management module (11) according to classification;
step two: the front-end data management module (11) respectively carries out classified management and analysis on the acquired data, judges high-risk personnel, carries out dynamic monitoring and data display in real time, carries out data interaction on the data of each community and strengthens the relation among the communities;
step three: the back-end community management module (12) conducts community equipment management and control according to the data of the front-end data management module (11), all equipment and systems of community people are communicated, an identity authentication system is unified, and non-contact and convenient personnel passing experience is achieved by means of technologies such as face recognition.
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