CN-122022329-A - Visual emergency command scheduling system and method for multi-source police service data fusion

CN122022329ACN 122022329 ACN122022329 ACN 122022329ACN-122022329-A

Abstract

The invention discloses a multisource police service data fusion emergency command visual dispatching system and method, in particular relates to the technical field of data processing and information retrieval, and is used for solving the problem that an existing command system is disjointed from instruction intention and execution effect due to lack of an accurate feedback channel from an execution end to a command end; the method comprises the steps of constructing a police dynamic mapping object corresponding to a physical police unit in a visual space, responding to a defined instruction area and generating a graphical scheduling instruction, receiving execution feedback data of an associated police unit, carrying out global interaction and track optimization on multi-source feedback data based on collaborative relation constraint analyzed from the instruction, generating a trusted execution track set, analyzing the instruction into a dynamic constraint condition and calculating a meeting state sequence based on the track, determining matching degree through analyzing a sequence entropy value, finally evaluating execution deviation characteristics according to the matching degree and carrying out associated labeling in the visual space, and thus forming a complete command control closed loop.

Inventors

WANG JUN
TIAN HU
LIU XIONG
QUAN JIANG
YAN YANG
Yi Bangxian

Assignees

湖北集防科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260129

Claims (10)

1. The visual scheduling method for the emergency command of the multisource police service data fusion is characterized by comprising the following steps of: S1, building a police service dynamic mapping object corresponding to a physical space police force unit in a visual space based on geographic information data, video monitoring data and police force unit positioning data; S2, responding to an instruction area containing the police dynamic mapping object defined in a visual space, and judging whether a graphical scheduling instruction associated with the instruction area exists or not; S3, when a graphical scheduling instruction exists, receiving execution feedback data from police force units associated with an instruction area; S4, determining cooperative relation constraint among the police force units in the instruction area, and performing global interaction and track optimization on execution feedback data of a plurality of associated police force units from different data sources based on the cooperative relation constraint to generate a trusted execution track set conforming to the cooperative relation constraint; S5, analyzing the graphical scheduling instruction into a plurality of dynamic constraint conditions, calculating a satisfied state sequence based on a trusted execution track set, and determining the matching degree by analyzing entropy values of the satisfied state sequence; S6, evaluating execution deviation characteristics of the police dynamic mapping object based on the matching degree, and marking the execution deviation characteristics in a visual space in an associated mode.
2. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S1 comprises: Identifying police units from the video monitoring data and extracting video position information of the police units; Aligning the video position information of the police force unit with the police force unit positioning data in time and space dimensions to obtain aligned police force unit position information; and mapping the aligned police force unit position information to a visual space by combining with geographic information data to generate a police service dynamic mapping object.
3. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S2 comprises: acquiring position information of one or more police dynamic mapping objects in a visual space; Determining a closed geographic range containing the corresponding one or more police dynamic mapping objects as an instruction area according to the position information of the one or more police dynamic mapping objects; based on the type and the number of the police service dynamic mapping objects contained in the instruction area, whether the graphical scheduling instruction associated with the instruction area exists or not is judged by combining with a preset command rule.
4. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S3 comprises: Analyzing the effective time range and the space action range of the instruction from the graphical scheduling instruction; determining police force unit identifications positioned in the space action range of the instruction based on the police service dynamic mapping object; Receiving positioning data and video clip data from corresponding police units according to the police unit identification and the effective time range of the instruction; and performing time stamp alignment on the received positioning data and the video clip data to form execution feedback data associated with the police force unit identifier.
5. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S4 comprises: analyzing the coordination requirements on the action sequence and the relative position relation of each police force unit from the graphical scheduling instruction, and taking the coordination requirements as coordination relation constraint; According to the constraint of the cooperative relationship, consistency and interaction are carried out on execution feedback data of the same police force unit from different data sources in time and space, and data points consistent with the interaction are screened out; Based on the data points consistent with each other, the tracks of the associated police units are synchronously smoothed and optimized by combining the requirements on the relative position relation in the cooperative relation constraint, and a trusted execution track set conforming to the cooperative relation constraint is generated.
6. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 5, wherein the method is characterized in that execution feedback data of the same police service unit from different data sources are subjected to consistency mutual evidence in time and space according to cooperative relation constraint, and data points with consistency mutual evidence are screened out, wherein the method comprises the steps of aligning coordinate points from positioning data with coordinate points identified by video segment data through a unified time reference, calculating the space Euclidean distance between the coordinate points from different data sources in the same time slice, judging that a plurality of coordinate points in corresponding time slices are consistent with each other if the space Euclidean distance is smaller than a preset consistency threshold, and screening corresponding time slices and corresponding coordinate point sets into data points with consistency mutual evidence.
7. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S5 comprises: Extracting requirements on time nodes, space positions and action states from the graphical scheduling instruction to form a plurality of dynamic constraint conditions with effective time windows; Aiming at the trusted execution track of each police force unit in the trusted execution track set, calculating the deviation between the track parameter of the trusted execution track and the target value of the dynamic constraint condition in the effective time window of the dynamic constraint condition, and marking the state of each time point as satisfied or not according to whether the deviation exceeds a deviation threshold value to obtain a satisfied state sequence of each police force unit corresponding to each dynamic constraint condition; and respectively calculating the permutation entropy of each satisfied state sequence, and determining the matching degree based on the statistical characteristics of all permutation entropy.
8. The visual scheduling method for emergency command based on multi-source police service data fusion according to claim 7, wherein the visual scheduling method for emergency command based on multi-source police service data fusion is characterized by calculating arrangement entropy of each satisfied state sequence respectively, determining matching degree based on statistical characteristics of all arrangement entropy, extracting symbolized arrangement modes of each satisfied state sequence according to preset embedding dimension and time delay, counting occurrence frequency of each arrangement mode, calculating arrangement entropy values of the satisfied state sequence according to the frequency, and carrying out average operation on the arrangement entropy values of all police force units corresponding to all dynamic constraint conditions, wherein the obtained average arrangement entropy values are used as final matching degree.
9. The visual scheduling method for emergency command of multi-source police service data fusion according to claim 1, wherein S6 comprises: Comparing the matching degree with a preset matching degree threshold value, and determining an execution deviation grade; selecting a corresponding visual mark style from a preset visual mark style library according to the execution deviation level; binding the selected visual marking style with the police dynamic mapping object associated with the instruction area, and rendering and displaying the bound police dynamic mapping object in the visual space.
10. An emergency command visual dispatching system for multi-source police service data fusion, which is used for realizing the emergency command visual dispatching method for multi-source police service data fusion as claimed in any one of claims 1-9, and is characterized by comprising the following steps: The mapping construction module is used for constructing police dynamic mapping objects corresponding to the physical space police units in the visualized space based on geographic information data, video monitoring data and police unit positioning data; The existence judging module is used for responding to the instruction area containing the police dynamic mapping object defined in the visual space and judging whether the graphical scheduling instruction associated with the instruction area exists or not; the feedback receiving module is used for receiving execution feedback data from police force units associated with the instruction area when the graphical scheduling instruction exists; The optimization interaction module is used for determining the cooperative relation constraint among the police force units in the instruction area, performing global interaction and track optimization on the execution feedback data of the plurality of associated police force units from different data sources based on the cooperative relation constraint, and generating a trusted execution track set conforming to the cooperative relation constraint; the matching calculation module is used for analyzing the graphical scheduling instruction into a plurality of dynamic constraint conditions, calculating a satisfied state sequence based on a trusted execution track set, and determining the matching degree by analyzing the entropy value of the satisfied state sequence; And the feature labeling module is used for evaluating the execution deviation features of the police dynamic mapping object based on the matching degree and labeling the execution deviation features in the visualized space in an associated mode.

Description

Visual emergency command scheduling system and method for multi-source police service data fusion Technical Field The invention relates to the technical field of data processing and information retrieval, in particular to an emergency command visual dispatching system and method for multi-source police service data fusion. Background In the field of public safety emergency command, particularly when facing large-scale activity security and emergency handling, a modern command system generally adopts a multi-source data fusion and visual scheduling technology. Typical system architecture can access and integrate data from different sources, such as geographic information data, video monitoring data, police unit positioning data and various police service data, the heterogeneous data are comprehensively displayed on a unified electronic map base map after being processed to form a global situation map, commanders conduct research and judgment based on the visual situation, and specific scheduling instructions, such as police deployment instructions or action route planning, are generated through interactive operations such as circle selection and plotting on the map and are issued to a front line execution unit for improving situation awareness capability and command decision efficiency. However, the existing visual command scheduling method of multi-source data fusion has limitations, namely, an established command control loop is incomplete, a system mainly realizes unidirectional command issuing and macroscopic state display from a command end to an execution end, but fails to effectively construct a real-time and accurate feedback comparison channel from a real physical environment of the execution end to a visual space of the command end, so that an abstract command space defined by a command personnel on a map and a complex action space faced by first-line personnel lack of consistency guarantee, the command side cannot intuitively confirm whether a graphical command issued by the command side is accurately understood and strictly executed or not, and cannot timely perceive execution path deviation caused by field environment interference, positioning error or cognitive deviation, the command intention and execution actual effect are disjointed, the accuracy and reliability of command scheduling are weakened, and the handling effect and operation risk are possibly directly influenced in a dynamic emergency scene. Disclosure of Invention Aiming at the technical problems existing in the prior art, the invention provides a visual emergency command scheduling system and method for multi-source police service data fusion. The technical scheme for solving the technical problems is as follows: the visual scheduling method of the emergency command for the multi-source police service data fusion comprises the following steps: S1, building a police service dynamic mapping object corresponding to a physical space police force unit in a visual space based on geographic information data, video monitoring data and police force unit positioning data; S2, responding to an instruction area containing the police dynamic mapping object defined in a visual space, and judging whether a graphical scheduling instruction associated with the instruction area exists or not; S3, when a graphical scheduling instruction exists, receiving execution feedback data from police force units associated with an instruction area; S4, determining cooperative relation constraint among the police force units in the instruction area, and performing global interaction and track optimization on execution feedback data of a plurality of associated police force units from different data sources based on the cooperative relation constraint to generate a trusted execution track set conforming to the cooperative relation constraint; S5, analyzing the graphical scheduling instruction into a plurality of dynamic constraint conditions, calculating a satisfied state sequence based on a trusted execution track set, and determining the matching degree by analyzing entropy values of the satisfied state sequence; S6, evaluating execution deviation characteristics of the police dynamic mapping object based on the matching degree, and marking the execution deviation characteristics in a visual space in an associated mode. Further, S1 includes: Identifying police units from the video monitoring data and extracting video position information of the police units; Aligning the video position information of the police force unit with the police force unit positioning data in time and space dimensions to obtain aligned police force unit position information; and mapping the aligned police force unit position information to a visual space by combining with geographic information data to generate a police service dynamic mapping object. Further, S2 includes: acquiring position information of one or more police dynamic mapping objects in a visual space; Determining a cl