CN115269918B - Big data information system construction and operation management system and method - Google Patents
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Abstract
The invention discloses a system and a method for constructing and operating and maintaining a large data information system, which relate to the technical field of operation and maintenance of large data video information systems and comprise the following steps of S100: constructing an information system for security management of the intelligent community; editing the regional attribute labels of all regional parts in the intelligent community; step S200: performing preliminary establishment of auxiliary identifications in all monitoring video streams; step S300: performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications; step S400: inputting security management requirements, carrying out requirement analysis on the security management requirements, carrying out intelligent retrieval on the monitoring video streams, and reserving corresponding retrieval records between each security management requirement and each monitoring video stream; and according to the security control result of each time, the auxiliary identification among all the monitoring video streams in the information system is adjusted, and the information operation and maintenance management of all the monitoring video streams in the information system is realized.
Description
Technical Field
The invention relates to the technical field of operation and maintenance of a big data video information system, in particular to a system and a method for constructing, operating and maintaining based on the big data video information system.
Background
At present, safety management is carried out on the intelligent communities, namely monitoring, distribution and control are carried out on all areas in the intelligent communities, then monitoring conditions in all areas are monitored in real time by community management staff in a background, a certain labor force and labor time are needed to be paid, meanwhile, due to the fact that a plurality of monitoring devices are arranged, individual monitoring visual angles are overlooked or not timely monitored, and accordingly community hidden danger is further caused or friction disputes of personnel or property in the communities are caused; once dispute mediation and evidence seeking are required by retrieving video information, a plurality of monitoring visual angles are required to be retrieved as much as possible, so that a principal or an adjusting person can conveniently know event facts in detail, and a manager is required to conduct multi-visual-angle investigation on a target place or a target person in video streams generated in all monitoring devices in a community, so that huge labor capacity and labor burden are brought to the manager.
Disclosure of Invention
The invention aims to provide a system and a method for constructing, operating and maintaining a system based on big data information so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the method for constructing and operating and maintaining the management based on the big data information system comprises the following steps:
step S100: collecting monitoring video streams of all monitoring devices in the intelligent community in real time, and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
step S200: the information system integrates information of each monitoring video stream imported by each monitoring device based on the three-dimensional construction diagram of the intelligent community; analyzing the monitoring coverage condition of each monitoring video stream, and initially establishing auxiliary identifiers in all the monitoring video streams;
step S300: performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
step S400: the management personnel inputs security management requirements to the system, the information system analyzes the requirements of the security management requirements, locks a monitoring area related to the security management requirements based on big data, intelligently retrieves the monitoring video streams based on the auxiliary identification condition among the monitoring video streams in the information system, and reserves the corresponding retrieval records among the security management requirements and the monitoring video streams; and according to the security control result of each time, the auxiliary identification among all the monitoring video streams in the information system is adjusted, and the information operation and maintenance management of all the monitoring video streams in the information system is realized.
Further, step S100 includes:
step S101: acquiring a three-dimensional construction diagram of the smart community, identifying construction features of each regional part in the smart community based on the three-dimensional construction diagram of the smart community, and performing a first regional attribute tag on each regional part in the smart community in the three-dimensional construction diagram of the smart community 1 Content editing of (a); first region attribute tag 1 The content editing options of (1) comprise community road sections, community intersections, community buildings, community parking lots, community corridor and community entrances and exits;
step S102: based on the first regional attribute tag in each region in the intelligent community 1 Is classified according to the difference in (a) and (b), obtaining a class area part; according to the three-dimensional construction diagram of the intelligent community, carrying out region distinguishing numbering on each region part of the same region part based on the difference of azimuth information; based on the region numbers corresponding to the region parts, completing the second region attribute tag of the region parts in the intelligent community 2 Content editing of (a);
step S103: information integration of the regional attribute tags is carried out on each regional part in the three-dimensional structural diagram of the intelligent community, and the comprehensive regional attribute Tag corresponding to each regional part is obtained: [ tag ] 1 ；tag 2 ]；
The three-dimensional structure diagram based on the intelligent community carries out editing processing of the regional attribute labels on all regions of the intelligent community, so that all community region information covered by all monitoring video streams in the information system is arranged later, and monitoring information capture of all community regions in all monitoring video streams is realized.
Further, step S200 includes:
step S201: respectively extracting monitoring video streams corresponding to all monitoring devices in the information system, capturing monitoring pictures appearing in all the monitoring video streams, and identifying the area parts of the monitoring coverage of all the monitoring video streams based on the monitoring pictures to respectively obtain a plurality of area parts of the monitoring coverage of all the monitoring video streams; extracting a three-dimensional construction diagram of the intelligent community, wherein in the three-dimensional construction diagram of the intelligent community, comprehensive area attribute tags of a plurality of area parts are extracted, and comprehensive area attribute tags contained in each monitoring video stream are collected to obtain a comprehensive area attribute Tag set corresponding to each monitoring video stream;
step S202: sequentially setting each monitoring video stream as a video stream to be processed, setting first attribute characteristic information of the video stream to be processed as target characteristic information, and setting a comprehensive region attribute tag set corresponding to the target characteristic information as a target set Aa; extracting the comprehensive region attribute tag set corresponding to the first attribute feature information of other monitoring video streams in sequence, if the comprehensive region attribute tag set Bb exists,the set C is a set formed by merging overlapping area parts corresponding to overlapping comprehensive area attribute tags between the comprehensive area attribute tag set Bb and the comprehensive area attribute tag set Aa, and c= { C 1 ,c 2 ,…,c n -a }; wherein c 1 ,c 2 ,…,c n The 1 st, 2 nd, … th and n th area parts which are overlapped in the video stream to be processed and other monitoring video streams are respectively represented;
step S203: the video stream to be processed is successively connected with other monitoring video streams, and complementary marks are built based on all area parts in the set C; forms of complementary labels, e.gWherein A represents a video stream to be processed; />Representing the i-th region part c between the video stream A to be processed and the monitoring video stream B i Auxiliary identification established between the two, wherein the monitoring video stream B is based on the region part c for the video stream A to be processed i Auxiliary monitoring video stream of the video camera;
the above-mentioned process of overlapping coverage area screening is performed on the monitoring video streams generated in each monitoring device, so as to screen out each monitoring video stream covering the same community area based on the monitoring situation in each video stream, where these video streams are often generated in different monitoring devices, and the different monitoring devices have different monitoring view angles for the same monitoring area due to the problem of installation angles, and are equivalent to monitoring information with multiple angles for those same community areas; and establishing auxiliary identification between all monitoring video streams covered with the same community area based on the coverage area, if video information is required to be checked in the area later, multi-angle checking can be realized, the monitoring dead angles of the area are checked, repeated calling of all monitoring video streams is reduced, and the working efficiency is improved.
Further, step S300 includes:
step S301: checking auxiliary identifiers for each video stream to be processed respectively, and extracting all auxiliary monitoring video streams corresponding to the auxiliary identifiers; the auxiliary monitoring video stream corresponding to the auxiliary identifier on each video stream to be processed is set to comprise { B } 1 ,B 2 ,…,B m -a }; wherein B is 1 ,B 2 ,…,B m The 1 st, 2 nd, … th and m th auxiliary monitoring video streams corresponding to the 1 st, 2 nd, … th and m th auxiliary identifiers on the video streams to be processed are respectively represented; set each video stream to be processed { B } 1 ,B 2 ,…,B m The corresponding area part of each auxiliary monitoring video stream on the auxiliary identifier in the } is correspondinglyWherein (1)>Sequentially representing the video stream to be processed and B 1 ,B 2 ,…,B m A corresponding region portion;
step S302: extracting monitoring pictures D from the video stream to be processed, and respectively extracting auxiliary monitoring video streams B from the video stream to be processed 1 ,B 2 ,…,B m Extract the monitoring picture dB 1 ,dB 2 ,…,dB m The method comprises the steps of carrying out a first treatment on the surface of the Sequentially combining the monitoring picture D with the monitoring picture dB j Is set as a pair of contrast groups (D, dB) j ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein dB is j ∈(dB 1 ,dB 2 ,…,dB m ) The method comprises the steps of carrying out a first treatment on the surface of the The monitoring picture D and the monitoring picture dB of each pair of the counter pictures respectively j In the corresponding region partLocking is carried out;
step S303: each pair of the images is respectively based on the locked area partPerforming comparison of monitoring visual angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value Deviation coverage threshold S Threshold value The method comprises the steps of carrying out a first treatment on the surface of the Acquiring each pair of picture facing area portions->Offset viewing angle angel at monitoring viewing angle Offset of deflection ；
Step S304: if angel Offset of deflection >angel Threshold value Reserving a region-based part between a corresponding auxiliary monitoring video stream and a video stream to be processedIs a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value Each pair of picture facing area portions is acquired +.>Deviation coverage S over monitoring coverage Offset of deflection If S Offset of deflection >S Threshold value The corresponding auxiliary monitoring video stream and the video stream to be processed are reserved based on the regional part +.>Is a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value And S is Offset of deflection >S Threshold value The corresponding auxiliary monitoring video stream and the video stream to be processed are based on the regional part +.>Removing the auxiliary mark of the (2);
the process of removing the auxiliary identifier is equivalent to screening out the most comprehensive monitoring view angles and monitoring coverage areas of the overlapping coverage monitoring areas in all video streams in a plurality of video streams with overlapping coverage monitoring areas, removing the video streams with overlapping view angles or overlapping monitoring coverage areas in the overlapping coverage monitoring areas, and leaving the most representative or clear monitoring video streams in the corresponding monitoring view angles or monitoring ranges, so that the workload of a subsequent manager for performing multi-view investigation on the overlapping coverage areas is reduced, and the workload of the manager is scientifically reduced.
Further, when the auxiliary identifier is provided between the video stream to be processed and two or more auxiliary monitoring video streams based on the area portion C, the processing steps include:
step S311: respectively extracting monitoring pictures from two or more auxiliary monitoring video streams, and locking an area part C of the monitoring pictures extracted from the two or more auxiliary monitoring video streams; based on the locked area part C, performing pairwise comparison of monitoring view angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value ' deviation coverage threshold S Threshold value ’；
Step S312: respectively acquiring a deviation angle angel of each two monitoring image facing area parts C on the monitoring angle Offset of deflection ' if angel Offset of deflection ’>angel Threshold value 'A'; preserving auxiliary identifiers based on the area part C between two auxiliary monitoring video streams and a certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' acquiring the deviation coverage area S of the area part C of each two monitoring pictures on the monitoring coverage area Offset of deflection ' if S Offset of deflection ’>S Threshold value ' reserving auxiliary identifiers based on the area part C between two auxiliary monitoring video streams and a certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' and S Offset of deflection ’>S Threshold value ' an offset view angel in the monitored view based on the area part C between the video stream to be processed Offset of deflection The smaller auxiliary monitoring video stream is removed from the auxiliary identification based on the area part C between the smaller auxiliary monitoring video stream and the video stream to be processed; wherein S is Threshold value ’<S Threshold value ；S Offset of deflection ’<S Offset of deflection ；angel Threshold value ’<angel Threshold value 。
Further, step S400 includes:
step S401: the method comprises the steps of performing demand analysis on security management demands input by management personnel, and locking security management objects related to the security management demands; the security control object comprises a specific community area, property and person; when the security control object is a specific property or person, locking the activity track of the property or person in all the monitoring video streams, wherein the activity track refers to all community areas where the property or person moves or is located;
step S402: taking a community area as a prompting message for video retrieval, retrieving all monitoring video streams with auxiliary marks between all monitoring video streams and the community area, and regularly splicing all monitoring video streams based on monitoring angles or monitoring ranges displayed on the community area; the regular splicing mode comprises the steps of splicing the community area from overlooking to looking up, and splicing the monitoring range of the community area from big to small.
For better realizing the method, a system for constructing and operating and maintaining a management system based on a big data information system is also provided, and the system comprises: the system comprises a data collection processing module, a data information integration module, an auxiliary identifier establishment module, an input information processing module, a video information intelligent calling module and an information operation and maintenance management module;
the data collection processing module is used for collecting monitoring video streams of all monitoring devices in the intelligent community in real time and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
the data information integration module receives the data in the data collection processing module and integrates information of the monitoring video streams imported by the monitoring devices based on the three-dimensional structure diagram of the intelligent community;
the auxiliary identifier building module is used for analyzing the monitoring coverage condition of each monitoring video stream and carrying out preliminary building of auxiliary identifiers in all the monitoring video streams; the method comprises the steps of performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
the input information processing module is used for receiving security management requirements input by management personnel to the system, analyzing the requirements of the security management requirements, and locking a monitoring area related to the security management requirements based on big data;
the intelligent video information retrieving module is used for receiving the data input into the information processing module and intelligently retrieving the monitoring video streams based on the auxiliary identification condition among the monitoring video streams;
the information operation and maintenance management module is used for receiving the data in the video information intelligent calling module and reserving corresponding calling records between each security management requirement and each monitoring video stream; and according to the security control result of each time, the auxiliary identification among the monitoring video streams is adjusted, and the information operation and maintenance management of the monitoring video streams is realized.
Further, the auxiliary identifier building module comprises an auxiliary identifier initial building unit and an auxiliary identifier calibration and check unit;
the auxiliary identifier initial building unit is used for receiving the data in the data information integration module, analyzing the monitoring coverage condition of each monitoring video stream and performing initial building of auxiliary identifiers in all the monitoring video streams;
the auxiliary identifier calibration and check unit is used for receiving the data in the data information integration module and the auxiliary identifier initial building unit, calibrating and checking all the auxiliary identifiers initially built by each monitoring video stream, and eliminating invalid auxiliary identifiers to obtain final auxiliary identifiers of each monitoring video stream.
Further, the data information integration module comprises an area information processing unit and an area attribute tag integration unit;
the regional information processing unit is used for receiving the data in the data collection processing module and editing the regional attribute labels of all the regions in the intelligent community;
and the regional attribute label integrating unit is used for receiving the data in the regional information processing unit and processing the information of the regional attribute labels for each monitoring video stream.
Compared with the prior art, the invention has the following beneficial effects: the intelligent management and intelligent multi-angle calling of the monitoring video stream information generated by each monitoring device in the intelligent community can be realized; based on checking community area information covered in each monitoring video stream, establishing auxiliary identification between the monitoring video streams which cover the same community area and have different monitoring visual angles or different monitoring coverage areas and the same covered community area; the intelligent calling device can realize the combined intelligent calling of the monitoring video streams in different areas, realize the multi-angle comprehensive information viewing of different areas, reduce the labor capacity of community managers, and effectively improve the security management work efficiency of the community managers based on the community monitoring video.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for constructing and operating and maintaining management based on a big data information system;
fig. 2 is a schematic structural diagram of the big data information system construction and operation management system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: the method for constructing and operating and maintaining the management based on the big data information system comprises the following steps:
step S100: collecting monitoring video streams of all monitoring devices in the intelligent community in real time, and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
wherein, step S100 includes:
step S101: acquiring a three-dimensional construction diagram of the smart community, identifying construction features of each regional part in the smart community based on the three-dimensional construction diagram of the smart community, and performing a first regional attribute tag on each regional part in the smart community in the three-dimensional construction diagram of the smart community 1 Content editing of (a); first region attribute tag 1 The content editing options of (1) comprise community road sections, community intersections, community buildings, community parking lots, community corridor and community entrances and exits;
step S102: based on the first regional attribute tag in each region in the intelligent community 1 Is classified according to the difference in (a) and (b), obtaining a class area part; according to the three-dimensional construction diagram of the intelligent community, carrying out region distinguishing numbering on each region part of the same region part based on the difference of azimuth information; based on the region numbers corresponding to the region parts, completing the second region attribute tag of the region parts in the intelligent community 2 Content editing of (a);
step S103: information integration of the regional attribute tags is carried out on each regional part in the three-dimensional structural diagram of the intelligent community, and the comprehensive regional attribute Tag corresponding to each regional part is obtained: [ tag ] 1 ；tag 2 ]；
Step S200: the information system integrates information of each monitoring video stream imported by each monitoring device based on the three-dimensional construction diagram of the intelligent community; analyzing the monitoring coverage condition of each monitoring video stream, and initially establishing auxiliary identifiers in all the monitoring video streams;
wherein, step S200 includes:
step S201: respectively extracting monitoring video streams corresponding to all monitoring devices in the information system, capturing monitoring pictures appearing in all the monitoring video streams, and identifying the area parts of the monitoring coverage of all the monitoring video streams based on the monitoring pictures to respectively obtain a plurality of area parts of the monitoring coverage of all the monitoring video streams; extracting a three-dimensional construction diagram of the intelligent community, wherein in the three-dimensional construction diagram of the intelligent community, comprehensive area attribute tags of a plurality of area parts are extracted, and comprehensive area attribute tags contained in each monitoring video stream are collected to obtain a comprehensive area attribute Tag set corresponding to each monitoring video stream;
step S202: sequentially setting each monitoring video stream as a video stream to be processed, setting first attribute characteristic information of the video stream to be processed as target characteristic information, and setting a comprehensive region attribute tag set corresponding to the target characteristic information as a target set Aa; extracting the comprehensive region attribute tag set corresponding to the first attribute feature information of other monitoring video streams in sequence, if the comprehensive region attribute tag set Bb exists,the set C is a set formed by merging overlapping area parts corresponding to overlapping comprehensive area attribute tags between the comprehensive area attribute tag set Bb and the comprehensive area attribute tag set Aa, and c= { C 1 ,c 2 ,…,c n -a }; wherein c 1 ,c 2 ,…,c n The 1 st, 2 nd, … th and n th area parts which are overlapped in the video stream to be processed and other monitoring video streams are respectively represented;
step S203: the video stream to be processed is successively connected with other monitoring video streams, and complementary marks are built based on all area parts in the set C; forms of complementary labels, e.gWherein A represents a video stream to be processed; />Representing the i-th region part c between the video stream A to be processed and the monitoring video stream B i Auxiliary identification established between the two, wherein the monitoring video stream B is based on the region part c for the video stream A to be processed i Auxiliary monitoring video stream of the video camera;
for example, in the video stream a to be processed, the area portion covered by the monitoring includes Tag1: [ community intersections; 1], tag2: [ community intersections; 3], tag3: [ community segment; 2], tag1: [ Community building; 2];
there is a surveillance video stream B, and the area part of the surveillance coverage includes Tag1: [ community intersections; 3], tag2: [ community segment; 1], tag3: [ community segment; 2], tag1: [ Community building; 4];
the overlapping area part existing between the video stream A to be processed and the monitoring video stream B comprises a community intersection; 3], [ community road section; 2];
establishing a community-based intersection between the processing video stream A and the monitoring video stream B; 3]Is a complement of the tag:establishing a community-based road section between the processing video stream A and the monitoring video stream B; 2]Is a complement of the tag: :
step S300: performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
wherein, step S300 includes:
step S301: checking auxiliary identifiers for each video stream to be processed respectively, and extracting all auxiliary monitoring video streams corresponding to the auxiliary identifiers; setting auxiliary marks corresponding to the auxiliary marks on each video stream to be processedThe surveillance video stream includes { B } 1 ,B 2 ,…,B m -a }; wherein B is 1 ,B 2 ,…,B m The 1 st, 2 nd, … th and m th auxiliary monitoring video streams corresponding to the 1 st, 2 nd, … th and m th auxiliary identifiers on the video streams to be processed are respectively represented; set each video stream to be processed { B } 1 ,B 2 ,…,B m The corresponding area part of each auxiliary monitoring video stream on the auxiliary identifier in the } is correspondinglyWherein (1)>Sequentially representing the video stream to be processed and B 1 ,B 2 ,…,B m A corresponding region portion;
step S302: extracting monitoring pictures D from the video stream to be processed, and respectively extracting auxiliary monitoring video streams B from the video stream to be processed 1 ,B 2 ,…,B m Extract the monitoring picture dB 1 ,dB 2 ,…,dB m The method comprises the steps of carrying out a first treatment on the surface of the Sequentially combining the monitoring picture D with the monitoring picture dB j Is set as a pair of contrast groups (D, dB) j ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein dB is j ∈(dB 1 ,dB 2 ,…,dB m ) The method comprises the steps of carrying out a first treatment on the surface of the The monitoring picture D and the monitoring picture dB of each pair of the counter pictures respectively j In the corresponding region partLocking is carried out;
step S303: each pair of the images is respectively based on the locked area partPerforming comparison of monitoring visual angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value Deviation coverage threshold S Threshold value The method comprises the steps of carrying out a first treatment on the surface of the Acquiring each pair of picture facing area portions->Deviation in monitoring viewing angleViewing angle angel Offset of deflection ；
Step S304: if angel Offset of deflection >angel Threshold value Reserving a region-based part between a corresponding auxiliary monitoring video stream and a video stream to be processedIs a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value Each pair of picture facing area portions is acquired +.>Deviation coverage S over monitoring coverage Offset of deflection If S Offset of deflection >S Threshold value The corresponding auxiliary monitoring video stream and the video stream to be processed are reserved based on the regional part +.>Is a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value And S is Offset of deflection >S Threshold value The corresponding auxiliary monitoring video stream and the video stream to be processed are based on the regional part +.>Removing the auxiliary mark of the (2);
the processing steps when the auxiliary identifier is provided between the video stream to be processed and two or more auxiliary monitoring video streams based on the region part C at the same time include:
step S311: respectively extracting monitoring pictures from two or more auxiliary monitoring video streams, and locking an area part C of the monitoring pictures extracted from the two or more auxiliary monitoring video streams; based on the locked area part C, performing pairwise comparison of monitoring view angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value ' deviation coverage threshold S Threshold value ’；
Step S312: respectively acquiring a deviation angle angel of each two monitoring image facing area parts C on the monitoring angle Offset of deflection ' if angel Offset of deflection ’>angel Threshold value 'A'; preserving auxiliary identifiers based on the area part C between two auxiliary monitoring video streams and a certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' acquiring the deviation coverage area S of the area part C of each two monitoring pictures on the monitoring coverage area Offset of deflection ' if S Offset of deflection ’>S Threshold value ' reserving auxiliary identifiers based on the area part C between two auxiliary monitoring video streams and a certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' and S Offset of deflection ’>S Threshold value ' an offset view angel in the monitored view based on the area part C between the video stream to be processed Offset of deflection The smaller auxiliary monitoring video stream is removed from the auxiliary identification based on the area part C between the smaller auxiliary monitoring video stream and the video stream to be processed; wherein S is Threshold value ’<S Threshold value ；S Offset of deflection ’<S Offset of deflection ；angel Threshold value ’<angel Threshold value ；
Step S400: the management personnel inputs security management requirements to the system, the information system analyzes the requirements of the security management requirements, locks a monitoring area related to the security management requirements based on big data, intelligently retrieves the monitoring video streams based on the auxiliary identification condition among the monitoring video streams in the information system, and reserves the corresponding retrieval records among the security management requirements and the monitoring video streams; according to the security control result of each time, the auxiliary identification among all monitoring video streams in the information system is adjusted, and the information operation and maintenance management of all monitoring video streams in the information system is realized;
wherein, step S400 includes:
step S401: the method comprises the steps of performing demand analysis on security management demands input by management personnel, and locking security management objects related to the security management demands; the security control object comprises a specific community area, property and person; when the security control object is a specific property or person, locking the activity track of the property or person in all the monitoring video streams, wherein the activity track refers to all community areas where the property or person moves or is located;
step S402: taking a community area as a prompting message for video retrieval, retrieving all monitoring video streams with auxiliary marks between all monitoring video streams and the community area, and regularly splicing all monitoring video streams based on monitoring angles or monitoring ranges displayed on the community area; the regular splicing mode comprises the steps of splicing the community area from overlooking to looking up, and splicing the monitoring range of the community area from big to small.
For better realizing the method, a system for constructing and operating and maintaining a management system based on a big data information system is also provided, and the system comprises: the system comprises a data collection processing module, a data information integration module, an auxiliary identifier establishment module, an input information processing module, a video information intelligent calling module and an information operation and maintenance management module;
the data collection processing module is used for collecting monitoring video streams of all monitoring devices in the intelligent community in real time and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
the data information integration module receives the data in the data collection processing module and integrates information of the monitoring video streams imported by the monitoring devices based on the three-dimensional structure diagram of the intelligent community;
the data information integration module comprises an area information processing unit and an area attribute tag integration unit;
the regional information processing unit is used for receiving the data in the data collection processing module and editing the regional attribute labels of all the regions in the intelligent community;
the regional attribute tag integration unit is used for receiving the data in the regional information processing unit and processing the information of the regional attribute tags for each monitoring video stream;
the auxiliary identifier building module is used for analyzing the monitoring coverage condition of each monitoring video stream and carrying out preliminary building of auxiliary identifiers in all the monitoring video streams; the method comprises the steps of performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
the auxiliary identifier establishing module comprises an auxiliary identifier initial establishing unit and an auxiliary identifier calibration checking unit;
the auxiliary identifier initial building unit is used for receiving the data in the data information integration module, analyzing the monitoring coverage condition of each monitoring video stream and performing initial building of auxiliary identifiers in all the monitoring video streams;
the auxiliary identifier calibration and check unit is used for receiving the data in the data information integration module and the auxiliary identifier initial building unit, calibrating and checking all the auxiliary identifiers initially built by each monitoring video stream, and eliminating invalid auxiliary identifiers to obtain final auxiliary identifiers of each monitoring video stream;
the input information processing module is used for receiving security management requirements input by management personnel to the system, analyzing the requirements of the security management requirements, and locking a monitoring area related to the security management requirements based on big data;
the intelligent video information retrieving module is used for receiving the data input into the information processing module and intelligently retrieving the monitoring video streams based on the auxiliary identification condition among the monitoring video streams;
the information operation and maintenance management module is used for receiving the data in the video information intelligent calling module and reserving corresponding calling records between each security management requirement and each monitoring video stream; and according to the security control result of each time, the auxiliary identification among the monitoring video streams is adjusted, and the information operation and maintenance management of the monitoring video streams is realized.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The method for constructing and operating the management based on the big data information system is characterized by comprising the following steps:
step S100: collecting monitoring video streams of all monitoring devices in the intelligent community in real time, and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
step S200: the information system integrates information of each monitoring video stream imported by each monitoring device based on the three-dimensional construction diagram of the intelligent community; analyzing the monitoring coverage condition of each monitoring video stream, and initially establishing auxiliary identifiers in all the monitoring video streams;
step S200 includes:
step S201: respectively extracting monitoring video streams corresponding to all monitoring devices in an information system, capturing monitoring pictures appearing in all the monitoring video streams, and identifying area parts of each monitoring video stream monitoring coverage based on the monitoring pictures to respectively obtain a plurality of area parts of each monitoring video stream monitoring coverage; extracting a three-dimensional construction diagram of the intelligent community, wherein in the three-dimensional construction diagram of the intelligent community, the comprehensive area attribute tags of the plurality of area parts are extracted, and the comprehensive area attribute tags contained in each monitoring video stream are collected to obtain a comprehensive area attribute Tag set corresponding to each monitoring video stream;
step S202: sequentially setting each monitoring video stream as a video stream to be processed, setting first attribute characteristic information of the video stream to be processed as target characteristic information, and setting a comprehensive region attribute tag set corresponding to the target characteristic information as a target set Aa; extracting the comprehensive region attribute tag set corresponding to the first attribute feature information of other monitoring video streams in sequence, if the comprehensive region attribute tag set Bb exists,the set C is a set formed by merging overlapping area parts corresponding to overlapping comprehensive area attribute tags between the comprehensive area attribute tag set Bb and the comprehensive area attribute tag set Aa, and c= { C 1 ,c 2 ,…,c n -a }; wherein c 1 ,c 2 ,…,c n Respectively representing the 1 st, 2 nd, … th and n th area parts which are overlapped in the video stream to be processed and the other monitoring video streams;
step S203: establishing complementary marks between the video stream to be processed and the other monitoring video streams successively based on all area parts in the set C; forms of the complementary tags such asWherein A represents a video stream to be processed;representing the i-th region part c between the video stream A to be processed and the monitoring video stream B i Auxiliary identification established between the two, wherein the monitoring video stream B is the video stream A to be processed based on the region part c i Auxiliary monitoring video stream of the video camera;
step S300: performing calibration and check on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
step S400: a manager inputs security management requirements to a system, the information system analyzes the security management requirements, locks a monitoring area related to the security management requirements based on big data, intelligently retrieves the monitoring video streams based on auxiliary identification conditions among the monitoring video streams in the information system, and reserves corresponding retrieval records among the security management requirements and the monitoring video streams; and according to the security control result of each time, the auxiliary identification among all the monitoring video streams in the information system is adjusted, and the information operation and maintenance management of all the monitoring video streams in the information system is realized.
2. The big data based information system construction and operation management method according to claim 1, wherein the step S100 comprises:
step S101: acquiring a three-dimensional construction diagram of the smart community, identifying construction features of each regional part in the smart community based on the three-dimensional construction diagram of the smart community, and performing a first regional attribute tag on each regional part in the smart community in the three-dimensional construction diagram of the smart community 1 Content editing of (a); the first region attribute tag 1 The content editing options of (1) comprise community road sections, community intersections, community buildings, community parking lots, community corridor and community entrances and exits;
step S102: based on the first regional attribute tag in each region in the intelligent community 1 Is classified according to the difference in (a) and (b), obtaining a class area part; according to the three-dimensional construction diagram of the intelligent community, respectively numbering the area parts of the same area part based on the difference of azimuth information; based on the region numbers corresponding to the region parts, completing the second region attribute tag of the region parts in the intelligent community 2 Content editing of (a);
step S103: information integration of region attribute labels is carried out on each region part in the three-dimensional structural diagram of the intelligent community, and a pair of each region part is obtainedThe comprehensive region attribute Tag: [ tag ] 1 ；tag 2 ]。
3. The big data based information system construction and operation and maintenance management method according to claim 2, wherein the step S300 includes:
step S301: checking auxiliary identifiers for each video stream to be processed respectively, and extracting all auxiliary monitoring video streams corresponding to the auxiliary identifiers; the auxiliary monitoring video stream corresponding to the auxiliary identifier on each video stream to be processed is set to comprise { B } 1 ,B 2 ,…,B m -a }; wherein B is 1 ,B 2 ,…,B m The 1 st, 2 nd, … th and m th auxiliary monitoring video streams corresponding to the 1 st, 2 nd, … th and m th auxiliary identifiers on the video streams to be processed are respectively represented; set each video stream to be processed { B } 1 ,B 2 ,…,B m The corresponding area part of each auxiliary monitoring video stream on the auxiliary identifier in the } is correspondinglyWherein (1)>Sequentially representing the video stream to be processed and B 1 ,B 2 ,…,B m A corresponding region portion;
step S302: extracting monitoring pictures D from the video stream to be processed, and respectively extracting auxiliary monitoring video streams B from the video stream to be processed 1 ,B 2 ,…,B m Extract the monitoring picture dB 1 ,dB 2 ,…,dB m The method comprises the steps of carrying out a first treatment on the surface of the Sequentially combining the monitoring picture D with the monitoring picture dB j Is set as a pair of contrast groups (D, dB) j ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein dB is j ∈(dB 1 ,dB 2 ,…,dB m ) The method comprises the steps of carrying out a first treatment on the surface of the The monitoring picture D and the monitoring picture dB of each pair of the counter pictures respectively j In the corresponding region partLocking is carried out;
step S303: each pair of the images is respectively based on the locked area partPerforming comparison of monitoring visual angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value Deviation coverage threshold S Threshold value The method comprises the steps of carrying out a first treatment on the surface of the Acquiring each pair of picture facing area portions->Offset viewing angle angel at monitoring viewing angle Offset of deflection ；
Step S304: if angel Offset of deflection >angel Threshold value Reserving a region-based part between the corresponding auxiliary monitoring video stream and the video stream to be processedIs a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value Acquiring each pair of picture facing region portionsDeviation coverage S over monitoring coverage Offset of deflection If S Offset of deflection >S Threshold value The corresponding region-based part between the auxiliary monitoring video stream and the video stream to be processed is reserved>Is a secondary identification of (2); if angel Offset of deflection ≤angel Threshold value And S is Offset of deflection >S Threshold value The corresponding auxiliary monitoring video stream and the video stream to be processed are based on regional part +.>Is eliminated.
4. The method for constructing and managing an operation and maintenance based on a big data information system according to claim 3, wherein the processing step when an auxiliary identifier is provided between a video stream to be processed and two or more auxiliary monitoring video streams based on the area portion C at the same time comprises:
step S311: respectively extracting monitoring pictures from the two or more auxiliary monitoring video streams, and locking a region part C of the monitoring pictures extracted from the two or more auxiliary monitoring video streams; based on the locked area part C, performing pairwise comparison of monitoring view angles and monitoring coverage areas; setting an offset viewing angle threshold angel Threshold value ' deviation coverage threshold S Threshold value ’；
Step S312: respectively acquiring a deviation angle angel of each two monitoring image facing area parts C on the monitoring angle Offset of deflection ' if angel Offset of deflection ’>angel Threshold value 'A'; preserving auxiliary identifiers based on the area part C between the two auxiliary monitoring video streams and the certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' acquiring the deviation coverage area S of the area part C of each two monitoring pictures on the monitoring coverage area Offset of deflection ' if S Offset of deflection ’>S Threshold value ' reserving auxiliary identifiers based on the area part C between the two auxiliary monitoring video streams and the certain video stream to be processed; if angel Offset of deflection ’≤angel Threshold value ' and S Offset of deflection ’>S Threshold value ' an offset view angel in the monitoring view based on the area part C between the video stream to be processed Offset of deflection The smaller auxiliary monitoring video stream is removed from the auxiliary identification based on the area part C between the smaller auxiliary monitoring video stream and the video stream to be processed; wherein S is Threshold value ’<S Threshold value ；S Offset of deflection ’<S Offset of deflection ；angel Threshold value ’<angel Threshold value 。
5. The big data based information system construction and operation management method according to claim 1, wherein the step S400 includes:
step S401: performing demand analysis on security management demands input by management personnel, and locking security management objects related to the security management demands; the security control object comprises a specific community area, property and person; when the security control object is a specific property or person, locking the activity track of the property or person in all monitoring video streams, wherein the activity track refers to all community areas where the property or person moves or is located;
step S402: taking the community area as a prompt message for video retrieval, retrieving all monitoring video streams with auxiliary marks between all the monitoring video streams and the community area, and regularly splicing all the monitoring video streams based on monitoring angles or monitoring ranges displayed on the community area; the regular splicing mode comprises splicing the community area from overlooking to looking up and splicing the monitoring range of the community area from big to small.
6. A big data based information system construction and operation and maintenance management system applied to the big data based information system construction and operation and maintenance management method of any one of claims 1 to 5, characterized in that the system comprises: the system comprises a data collection processing module, a data information integration module, an auxiliary identifier establishment module, an input information processing module, a video information intelligent calling module and an information operation and maintenance management module;
the data collection processing module is used for collecting monitoring video streams of all monitoring devices in the intelligent community in real time and constructing an information system for security management of the intelligent community; building data of the intelligent community are obtained, and a three-dimensional construction diagram of the intelligent community is generated; in the three-dimensional construction diagram of the intelligent community, editing the regional attribute labels of all regional parts in the intelligent community;
the data information integration module receives the data in the data collection processing module and integrates information of the monitoring video streams imported by the monitoring devices based on the three-dimensional construction diagram of the intelligent community;
the auxiliary identifier building module is used for analyzing the monitoring coverage condition of each monitoring video stream and performing preliminary building of auxiliary identifiers in all the monitoring video streams; the method comprises the steps of performing calibration checking on all auxiliary identifications initially established by each monitoring video stream, and removing invalid auxiliary identifications to obtain final auxiliary identifications of each monitoring video stream;
the input information processing module is used for receiving security management requirements input by management staff to a system, analyzing the security management requirements, and locking a monitoring area related to the security management requirements based on big data;
the intelligent video information retrieving module is used for receiving the data in the input information processing module and performing intelligent retrieving on the monitoring video streams based on the auxiliary identification condition among the monitoring video streams;
the information operation and maintenance management module is used for receiving the data in the intelligent video information calling module and reserving corresponding calling records between each security management requirement and each monitoring video stream; and according to the security control result of each time, the auxiliary identification among the monitoring video streams is adjusted, and the information operation and maintenance management of the monitoring video streams is realized.
7. The big data information system-based construction and operation management system according to claim 6, wherein the auxiliary identifier building module comprises an auxiliary identifier initial building unit and an auxiliary identifier calibration checking unit;
the auxiliary identifier initial establishing unit is used for receiving the data in the data information integrating module, analyzing the monitoring coverage condition of each monitoring video stream and initially establishing auxiliary identifiers in all the monitoring video streams;
the auxiliary identifier calibration and check unit is used for receiving the data in the data information integration module and the auxiliary identifier initial building unit, calibrating and checking all auxiliary identifiers initially built by each monitoring video stream, and eliminating invalid auxiliary identifiers to obtain final auxiliary identifiers of each monitoring video stream.
8. The large data information system construction and operation management system according to claim 6, wherein the data collection processing module comprises a region information processing unit, and the data information integration module comprises a region attribute tag integration unit;
the regional information processing unit is used for editing regional attribute labels of all regions in the intelligent community;
the regional attribute label integrating unit is used for receiving the data in the regional information processing unit and processing the information of the regional attribute labels for each monitoring video stream.
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