Integrated public safety emergency response auxiliary method and system

Abstract

The invention belongs to the technical field of public safety assistance, and discloses an integrated public safety emergency response assistance method and system, and the method comprises the steps: generating a patrol task, and distributing an optimal patrol path for an intelligent robot based on the regional importance degree and the patrol task; analyzing obstacle information on the optimal patrol path by using a real-time positioning technology, and adjusting the optimal patrol path in real time based on the obstacle information to obtain an advancing path of the intelligent robot; a sensor carried by the intelligent robot is used for obtaining behavior information of the field personnel in the advancing path, a data analysis and identification technology is used for identifying and processing the behavior information to obtain abnormal conditions of the field personnel, and emergency processing is carried out on the field personnel; and dynamic data of the intelligent robot in the emergency processing process are acquired to evaluate the emergency response efficiency, and the advancing path of the intelligent robot is adjusted based on a response efficiency result. According to the rescue and capture auxiliary platform, the law enforcement and rescue supporting capacity of the auxiliary platform is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of public safety assistance, and particularly to an integrated public safety emergency response assistance method and system. Background Art

[0002] A public safety area generally refers to an area delimited by the government, police or other relevant departments within a certain range to protect public safety and order, such as customs, tourist attractions, stadiums, shopping malls and performance venues. Taking customs as an example, with the accelerated development of the free trade port and the implementation of customs closure operations, the demand for anti-smuggling arrests in areas such as coasts, docks and airports has increased rapidly. To ensure the normal response to emergencies within the public safety area, in the prior art, police officers or volunteers are often arranged to conduct patrols within the area.

[0003] However, the traditional patrol and law enforcement methods in the prior art are difficult to meet the current needs in terms of response speed, arrest efficiency and consumption of human resources. Limited by the number of personnel and physical strength, it is difficult to achieve all-weather and high-frequency patrols. After suspicious behavior is detected, the response time of police officers is relatively long, and the best disposal opportunity is easily missed. At the same time, the traditional patrol method is difficult to conduct real-time analysis and processing of a large amount of patrol data, affecting the timeliness and accuracy of decision-making. The high-intensity patrol tasks have relatively high requirements for the physical strength and mental state of police officers and volunteers, easily leading to fatigue and a decline in work efficiency.

[0004] Therefore, how to provide an integrated public safety emergency response assistance method and system is an urgent problem to be solved at present. Summary of the Invention

[0005] Embodiments of the present invention provide an integrated public safety emergency response assistance method and system, which is an urgent problem to be solved at present, so as to solve the problem that the patrol and law enforcement methods in the prior art are difficult to meet the current needs in terms of response speed, arrest efficiency and consumption of human resources.

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary part is not a general review, nor is it intended to identify key / important constituent elements or delineate the protection scope of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the subsequent detailed description.

[0007] According to the first aspect of the embodiments of the present invention, an integrated public safety emergency response assistance method is provided.

[0008] In one embodiment, the integrated public safety emergency response assistance method includes:

[0009] Generate patrol tasks based on the layout information within the public security area, and allocate the optimal patrol path for the intelligent robot based on the regional importance and the patrol tasks;

[0010] Use simultaneous localization and visual analysis technology to analyze the obstacle information on the optimal patrol path, and adjust the optimal patrol path in real time based on the obstacle information to obtain the travel path of the intelligent robot;

[0011] Use the sensors carried by the intelligent robot to obtain the behavior information of the on-site personnel within the travel path, and adopt data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of the on-site personnel, and conduct emergency treatment on the on-site personnel according to the abnormal condition results;

[0012] Obtain the dynamic data of the intelligent robot during the emergency treatment process, evaluate the emergency response efficiency based on the dynamic data, and adjust the travel path of the intelligent robot based on the response efficiency results.

[0013] In one embodiment, generating patrol tasks based on the layout information within the public security area and allocating the optimal patrol path for the intelligent robot based on the regional importance and the patrol tasks includes:

[0014] Obtain the facility layout map and historical patrol information within the public security area to generate a patrol assistance list, and combine the patrol assistance list, patrol point information, and patrol item information to obtain a patrol task list;

[0015] Represent the patrol point and patrol item information attributes in matrix form respectively, and map the patrol item information to the patrol points according to the matrix representation results to obtain a point-item association set to obtain patrol tasks;

[0016] Perform initial allocation of the intelligent robot for the generated patrol tasks through a matching degree function, and optimize and reorganize the initial allocation results by combining the fitness function and the regional importance to obtain the optimal allocation result;

[0017] Combine the optimal allocation result of the intelligent robot's patrol tasks with a path planning algorithm to generate a patrol path, and select the patrol path with the lowest operating cost as the optimal patrol path allocated to the intelligent robot.

[0018] In one embodiment, performing initial allocation of the intelligent robot for the generated patrol tasks through a matching degree function, and optimizing and reorganizing the initial allocation results by combining the fitness function and the regional importance to obtain the optimal allocation result includes:

[0019] Generate a response set and a task set based on the number of intelligent robots and patrol tasks, express the task allocation problem according to the response set and the task set, and analyze the task matching degree of the intelligent robot using the expression results and the patrol responsibilities;

[0020] The matching degree results are used to allocate tasks in a cyclic manner to obtain an initial allocation result, and the task distance and time interval dispersion degree of the intelligent robot corresponding to the initial allocation result are evaluated;

[0021] Based on the task distance and time interval dispersion degree, the probability of the intelligent robot completing the inspection task is evaluated to determine the fitness function, and the initial allocation result is optimized according to the fitness function and the regional importance degree to obtain the optimal allocation result.

[0022] In one embodiment, combining the optimal allocation result of the inspection task of the intelligent robot with the path planning algorithm to generate an inspection path, and selecting the inspection path with the lowest operation cost as the optimal inspection path for the intelligent robot allocation includes:

[0023] Based on the optimal allocation result of the inspection task of the intelligent robot, the inspection points and inspection items during the inspection process are obtained, and several sets of moving points are set at the inspection points as the initial points according to the path planning algorithm;

[0024] Calculate the step length between any two sets of initial points, initialize the pheromone concentration equally according to the step length result and the required end time of the inspection task, and analyze the moving path of the starting initial point during the process of moving to the last initial point;

[0025] Obtain the moving path with the pheromone concentration within the preset interval in the moving path as the inspection path of the intelligent robot, calculate the total duration of the intelligent robot inspection path to complete the inspection task, analyze the power operation cost based on the total duration, and select the inspection path with the lowest operation cost as the optimal inspection path for the intelligent robot allocation.

[0026] In one embodiment, using the sensors carried by the intelligent robot to obtain the behavior information of the on-site personnel in the traveling path, and using data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of the on-site personnel, and performing emergency treatment on the on-site personnel according to the abnormal condition results includes:

[0027] Carry a positioning sensor, an environmental perception monitor and a crowd analysis sensor in the intelligent robot to capture the behavior information of the on-site personnel in the traveling area of the public safety area;

[0028] Based on the behavior information and data analysis and discrimination technology, obtain the behavior actions and facial expressions of the on-site personnel, and use the facial results to predict the physiological characteristics of the on-site personnel, and combine the physiological characteristics with the suspicious physiological standards and rescue physiological standards to judge the abnormal condition information of the on-site personnel;

[0029] The human-computer interaction platform receives the abnormal condition information of the on-site personnel. If the abnormal condition indicates that there is a suspicious condition for the on-site personnel, use the behavior actions to perform a secondary prediction on the corresponding on-site personnel;

[0030] If the prediction result still indicates that there are suspicious situations with the on-site personnel, the human-machine interaction platform generates a response assistance strategy and feeds it back to the intelligent robot, and the intelligent robot captures and processes the on-site personnel based on the assistance strategy;

[0031] If the abnormal situation indicates that there are physiological abnormalities with the on-site personnel, the intelligent robot is used to carry an optical heart rate monitor and an infrared sensor to obtain the physiological data of the on-site personnel;

[0032] Based on the physiological data results, a safety emergency assistance strategy is generated and fed back to the intelligent robot, and the intelligent robot rescues and processes the on-site personnel according to the strategy.

[0033] In one embodiment, based on the behavior information and data analysis discrimination technology, the behavior actions and facial expressions of the on-site personnel are obtained, and the physiological characteristics of the on-site personnel are predicted using the facial results. Combining the physiological characteristics with the suspicious physiological criteria and the rescue physiological criteria to judge the abnormal situation information of the on-site personnel includes:

[0034] Using the face key point detection technology to preprocess the picture data containing the on-site personnel, and dividing the face area into several groups of facial trigger areas and action trigger areas;

[0035] Based on the preset data analysis discrimination recognition model, the facial trigger area and the action trigger area are recognized to obtain the fusion feature of the facial expression and the action behavior;

[0036] Using the facial expression fusion feature to predict the physiological characteristics of the on-site personnel, matching the physiological characteristics with the suspicious physiological criteria and the rescue physiological criteria, and judging the abnormal situation information of the on-site personnel according to the matching result.

[0037] In one embodiment, based on the preset data analysis discrimination recognition model, the facial trigger area and the action trigger area are recognized to obtain the fusion feature of the facial expression and the action behavior, including:

[0038] Using the preset data analysis discrimination recognition model to extract the local features of the facial expression and the action in the corresponding facial trigger area and action trigger area to obtain the local features of the facial and action trigger areas;

[0039] Input the local features into the activation layer of the data analysis discrimination recognition model to perform facial expression and action unit recognition, and obtain the activation features of the facial expression and the action;

[0040] Cut the facial trigger area and the action trigger area and input them into the preset data analysis discrimination recognition model to extract the features of the entire face of the on-site personnel and the whole body of the on-site personnel, obtain the global features of the on-site personnel, and fuse the activation features and the global features at the feature level to obtain the fusion feature of the facial expression and the action behavior.

[0041] In one embodiment, the physiological characteristics of on-site personnel are predicted using facial expression fusion features, and the physiological characteristics are matched with suspicious physiological criteria and rescue physiological criteria. The abnormal condition information of the on-site personnel is determined according to the matching result, including:

[0042] The facial expression fusion features are trained using a non-uniform grid to obtain an expression feature dataset for the feature information of key points of facial expression changes;

[0043] Local movement operations are performed on the expression feature dataset using elastic grid nodes, similarity tests are performed based on the movement results, and a cost function between the corresponding physiological characteristics in the expression feature dataset and the suspicious physiological criteria and rescue physiological criteria features is obtained;

[0044] The difference between the cost functions corresponding to the suspicious physiological criteria and the rescue physiological criteria is compared. If the cost function of the suspicious physiological criteria is greater than the cost function of the rescue physiological criteria, it indicates that there is a suspicious situation for the on-site personnel;

[0045] If the cost function of the suspicious physiological criteria is less than the cost function of the rescue physiological criteria, it indicates that the on-site personnel have physiological abnormalities. If the cost function of the suspicious physiological criteria is equal to the cost function of the rescue physiological criteria, secondary prediction is performed on the corresponding on-site personnel using behavioral actions.

[0046] In one embodiment, the expression of the cost function is:

[0047]

[0048] In the formula, C represents the cost function, β represents the elastic parameter of the elastic grid, T represents the total number of nodes of the elastic grid, W(v j ) represents the deformation amount of the j-th elastic grid node, P j ′ and P respectively represent the decomposition value and the reference standard decomposition value of the expression feature dataset, and R(Pj′,P) represents the similarity.

[0049] According to the second aspect of the embodiments of the present invention, an integrated public safety emergency response assistance system is provided.

[0050] In one embodiment, the emergency response assistance system includes:

[0051] An intelligent robot task allocation unit, configured to generate patrol tasks according to the layout information in the public safety area, and allocate an optimal patrol path for the intelligent robot based on the regional importance and the patrol tasks;

[0052] A dynamic navigation obstacle avoidance processing unit, configured to analyze the obstacle information on the optimal patrol path using real-time positioning and visual analysis technologies, and adjust the optimal patrol path in real time based on the obstacle information to obtain the traveling path of the intelligent robot;

[0053] An intelligent robot analysis and assistance unit is used to obtain the behavior information of on-site personnel within the travel path by using the sensors carried by the intelligent robot, and adopt data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of on-site personnel, and conduct emergency treatment for on-site personnel according to the results of the abnormal conditions;

[0054] An emergency response efficiency evaluation unit is used to obtain the dynamic data of the intelligent robot during the emergency treatment process, evaluate the emergency response efficiency according to the dynamic data, and adjust the travel path of the intelligent robot based on the response efficiency results.

[0055] According to the third aspect of the embodiments of the present invention, a computer device is provided.

[0056] In one embodiment, the computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0057] According to the fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided.

[0058] In one embodiment, a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0059] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0060] The present invention integrates an intelligent robot and a human-computer interaction platform to form a complete rescue and arrest assistance platform, significantly improving the collaborative ability of the overall function and the comprehensive efficiency of the system. At the same time, it evaluates the emotional state within the public safety on-site area, more accurately judges suspiciousness, enhances the law enforcement and rescue support ability of the assistance platform, reduces the manual workload, and changes the problem of fatigue of staff and decline in work efficiency caused by high-intensity patrol tasks during the traditional monitoring process.

[0061] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0063] Figure 1 is a flowchart of an integrated public safety emergency response assistance method shown according to an exemplary embodiment;

[0064] Figure 2It is a schematic block diagram of an integrated public safety emergency response assistance system shown according to an exemplary embodiment;

[0065] Figure 3 It is a schematic structural diagram of a computer device shown according to an exemplary embodiment. Detailed implementation manners

[0066] The following description and the drawings fully illustrate the specific implementation manners herein, enabling those skilled in the art to practice them. Parts and features of some embodiments may be included in or replaced by parts and features of other embodiments. The scope of the embodiments herein includes the entire scope of the claims and all available equivalents of the claims. In this document, terms such as "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a structure, device or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such structure, device or equipment. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the structure, device or equipment including the said element. The embodiments herein are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0067] Terms such as "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. in this document indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. They are only for the convenience of describing this document and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as a limitation to the present invention. In the description of this document, unless otherwise specified and limited, the terms "mounted", "connected", "coupled" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the communication inside two elements. It can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0068] In this document, unless otherwise stated, the term "plurality" means two or more.

[0069] In this text, the character " / " indicates an "or" relationship between the preceding and following objects. For example, A / B means: A or B.

[0070] In this text, the term "and / or" is an associative relationship describing an object, indicating that three relationships can exist. For example, A and / or B means: A or B, or, the three relationships of A and B.

[0071] It should be understood that although the various steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear description in this text, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0072] Each module in the device or system of this application can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0073] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0074] Figure 1 An embodiment of the integrated public safety emergency response assistance method of the present invention is shown.

[0075] In this alternative embodiment, the integrated public safety emergency response assistance method includes:

[0076] Step S101, generating a patrol task according to the layout information in the public safety area, and allocating an optimal patrol path for the intelligent robot based on the regional importance and the patrol task;

[0077] Step S102, analyzing the obstacle information on the optimal patrol path by using the simultaneous localization and visual analysis technology, and adjusting the optimal patrol path in real time based on the obstacle information to obtain the traveling path of the intelligent robot;

[0078] Step S103, using the sensors carried by the intelligent robot to obtain the behavior information of the on-site personnel in the traveling path, and using the data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of the on-site personnel, and performing emergency treatment on the on-site personnel according to the abnormal condition results;

[0079] Step S104: Obtain the dynamic data of the intelligent robot during the emergency handling process, evaluate the emergency response efficiency based on the dynamic data, and adjust the traveling path of the intelligent robot based on the response efficiency result.

[0080] In this alternative embodiment, when generating the patrol task according to the layout information in the public safety area and allocating the optimal patrol path for the intelligent robot based on the regional importance and the patrol task, the facility layout map and the historical patrol information in the public safety area can be obtained to generate a patrol assistance list, and the patrol assistance list, the patrol point information, and the patrol item information are combined to obtain a patrol task list; the patrol point and the patrol item information attributes are respectively represented in matrix form, and the patrol item information is mapped to the patrol point according to the matrix representation result to obtain a point-item association set to obtain the patrol task; the generated patrol task is initially allocated to the intelligent robot through a matching function, and the initial allocation result is optimized and reorganized by combining the fitness function and the regional importance to obtain the optimal allocation result; the optimal allocation result of the patrol task of the intelligent robot is combined with the path planning algorithm to generate a patrol path, and the patrol path with the lowest operating cost is selected as the optimal patrol path allocated to the intelligent robot.

[0081] In this alternative embodiment, when initially allocating the generated patrol task to the intelligent robot through a matching function, and optimizing and reorganizing the initial allocation result by combining the fitness function and the regional importance to obtain the optimal allocation result, a response set and a task set can be generated based on the number of intelligent robots and patrol tasks, the task allocation problem is described according to the response set and the task set, and the task matching degree of the intelligent robot is analyzed by using the description result and the patrol responsibility; the matching result is used to allocate tasks in a cyclic manner to obtain the initial allocation result, and the task distance proximity and the time interval dispersion degree of the intelligent robot corresponding to the initial allocation result are evaluated; the fitness function is determined based on the task distance proximity and the time interval dispersion degree to evaluate the probability of the intelligent robot completing the patrol task, and the initial allocation result is optimized according to the fitness function and the regional importance to obtain the optimal allocation result.

[0082] In this alternative embodiment, when combining the optimal allocation result of the inspection tasks of the intelligent robot with the path planning algorithm to generate an inspection path and selecting the inspection path with the lowest operating cost as the optimal inspection path for the intelligent robot allocation, the inspection points and inspection items during the inspection can be obtained based on the optimal allocation result of the inspection tasks of the intelligent robot, and several sets of moving points can be set at the inspection points as initial points according to the path planning algorithm; calculate the step lengths between any two sets of initial points, initialize the pheromone concentration equally according to the step length results and the required end time of the inspection tasks, and analyze the moving path of the starting initial point during the movement to the last initial point; obtain the moving path with the pheromone concentration within the preset interval in the moving path as the inspection path of the intelligent robot, calculate the total duration for the intelligent robot inspection path to complete the inspection tasks, analyze the power consumption operating cost based on the total duration, and select the inspection path with the lowest operating cost as the optimal inspection path for the intelligent robot allocation.

[0083] It should be noted that when the human-machine interaction platform receives a new inspection task, the task allocator first calls the detailed layout map of the inspection area within the public security area, combines the historical inspection data and the actual situation of the day, divides the area into several partitions with different importance levels, and then reasonably allocates police officers, volunteers, and intelligent robot resources according to the importance of each partition, and plans the optimal inspection path for each allocated object. For example, increase the investment of police officers and robots in important partitions and optimize their inspection paths to increase the inspection frequency, and increase the number of robots in partitions with lower risks to cooperate with a small amount of manpower for inspections.

[0084] During the inspection process of the intelligent robot, the navigation travels autonomously according to the preset path, while real-time monitoring the environmental images, identifying the obstacles ahead through computer vision algorithms, and adjusting the traveling path in real time to ensure the smooth completion of the inspection tasks. It is powered continuously by a high-efficiency lithium battery to support the long-term and high-intensity inspection requirements of the intelligent robot.

[0085] In this alternative embodiment, when analyzing obstacle information on the optimal patrol path using instant positioning and visual analysis technology and adjusting the traveling path of the intelligent robot in real time based on the obstacle information, the Simultaneous Localization and Mapping (SLAM) technology is used to locate the intelligent robot in the patrol area and generate a two-dimensional or three-dimensional map of the surrounding environment; multi-modal sensors (such as lidar, ultrasonic sensors) are used to monitor the environment in real time and collect obstacle data on the patrol path, including information such as position, size, shape, and material; computer vision technology (such as object detection algorithms YOLO, Mask R-CNN) is used to analyze the images or videos collected by the camera to identify the types of obstacles (such as pedestrians, vehicles, boxes, etc.). If there are dynamic obstacles (such as pedestrians), analyze their movement trajectories and speeds and predict their possible future positions; according to the visual analysis results, classify the obstacles into dynamic obstacles (such as moving devices or pedestrians) and static obstacles (such as fixed buildings or obstacles), extract the relevant features of the obstacles for subsequent path planning adjustment; compare the detected obstacles with the current optimal path to evaluate whether the path needs to be adjusted. For dynamic obstacles, use a prediction algorithm (such as Kalman filtering) to predict their future positions and evaluate their potential impact on the path. Based on the updated environmental information, use a real-time path planning algorithm to calculate a new optimal path. While considering avoiding obstacles, maintain the goals of the patrol task. If the obstacle is small or short-lived (such as a dropped item), the robot may try to bypass or cross the obstacle. If the obstacle is dynamic and unpredictable, the robot may choose to wait or re-plan the path. According to the newly calculated optimal path, the intelligent robot executes the movement of the path through the controller.

[0086] In this alternative embodiment, when using the sensors carried by the intelligent robot to obtain the behavior information of on-site personnel within the travel path, and adopting data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of on-site personnel, and performing emergency treatment on on-site personnel according to the results of the abnormal conditions, a positioning sensor, an environmental perception monitor, and a crowd analysis sensor can be carried in the intelligent robot to capture the behavior information of on-site personnel within the travel area of the public safety area; based on the behavior information and data analysis and discrimination technology, obtain the behavior actions and facial expressions of on-site personnel, and use the facial results to predict the physiological characteristics of on-site personnel, and combine the physiological characteristics with the suspicious physiological standards and rescue physiological standards to judge the abnormal condition information of on-site personnel; the human-computer interaction platform receives the abnormal condition information of on-site personnel. If the abnormal condition indicates that there is a suspicious condition for on-site personnel, then use the behavior actions to perform a secondary prediction on the corresponding on-site personnel; if the prediction result still indicates that there is a suspicious condition for on-site personnel, then the human-computer interaction platform generates a response assistance strategy and feedbacks it to the intelligent robot, and the intelligent robot performs capture processing on on-site personnel based on the assistance strategy; if the abnormal condition indicates that there is a physiological abnormal condition for on-site personnel, then use the optical heart rate monitor and infrared sensor carried by the intelligent robot to obtain the physiological data of on-site personnel; generate a safety emergency assistance strategy based on the results of the physiological data and feedback it to the intelligent robot, and the intelligent robot performs rescue processing on on-site personnel according to the strategy.

[0087] When the intelligent robot is performing inspection tasks, it captures environmental images through a monitoring camera, collects on-site sounds through a voice collector, obtains the physiological data of the monitored personnel through an optical heart rate monitor and an infrared sensor, identifies the behavior actions and facial expressions in the images, analyzes the emotional characteristics through voice signals, combines the heart rate and heat change data, comprehensively evaluates the emotional state of the monitored personnel, judges the suspiciousness based on the behavior and emotion analysis results, and triggers an alarm when necessary. When the robot or on-site personnel discovers suspicious behavior, the system will trigger an alarm. After receiving the alarm signal, the human-computer interaction platform quickly dispatches the nearest police officers and robot resources for on-site processing. The police officers and volunteers collect evidence on-site and decide whether to take further actions based on the evidence collection results. All alarm data and evidence collection data will be marked and stored for subsequent analysis and optimization of decision-making.

[0088] In this alternative embodiment, when obtaining the behavioral actions and facial expressions of on-site personnel based on behavioral information and data analysis discrimination technology, and using the facial results to predict the physiological characteristics of on-site personnel, and combining the physiological characteristics with suspicious physiological criteria and rescue physiological criteria to judge the abnormal condition information of on-site personnel, the face key point detection technology can be used to preprocess the picture data containing on-site personnel, and divide the face area into several groups of facial trigger areas and action trigger areas; based on a preset data analysis discrimination recognition model, identify the facial trigger areas and action trigger areas to obtain the fused features of facial expressions and action behaviors; use the fused features of facial expressions to predict the physiological characteristics of on-site personnel, match the physiological characteristics with suspicious physiological criteria and rescue physiological criteria, and judge the abnormal condition information of on-site personnel according to the matching results.

[0089] In this alternative embodiment, when identifying the facial trigger areas and action trigger areas based on a preset data analysis discrimination recognition model to obtain the fused features of facial expressions and action behaviors, the preset data analysis discrimination recognition model can be used to extract the local features of facial expressions and actions in the corresponding facial trigger areas and action trigger areas to obtain the local features of the facial and action trigger areas; input the local features into the activation layer of the data analysis discrimination recognition model to identify the facial expression and action units, and obtain the activation features of the facial expressions and actions; cut the facial trigger areas and action trigger areas and input them into the preset data analysis discrimination recognition model to extract the features of the entire face of the on-site personnel and the whole body of the on-site personnel to obtain the global features of the on-site personnel, and fuse the activation features and the global features at the feature level to obtain the fused features of facial expressions and action behaviors.

[0090] In this alternative embodiment, when using the fused features of facial expressions to predict the physiological characteristics of on-site personnel, matching the physiological characteristics with suspicious physiological criteria and rescue physiological criteria, and judging the abnormal condition information of on-site personnel according to the matching results, a non-uniform grid can be used to train the fused features of facial expressions to obtain an expression feature dataset for the key point feature information of facial expression changes; use elastic grid nodes to perform local movement operations on the expression feature dataset, conduct similarity tests based on the movement results, and obtain the cost function between the corresponding physiological characteristics in the expression feature dataset and the suspicious physiological criteria and rescue physiological criteria features; compare the difference between the cost functions corresponding to the suspicious physiological criteria and the rescue physiological criteria. If the cost function of the suspicious physiological criteria is greater than the cost function of the rescue physiological criteria, it means that there is a suspicious situation for the on-site personnel; if the cost function of the suspicious physiological criteria is less than the cost function of the rescue physiological criteria, it means that the on-site personnel have physiological abnormalities. If the cost function of the suspicious physiological criteria is equal to the cost function of the rescue physiological criteria, use the behavioral actions to perform a secondary prediction on the corresponding on-site personnel.

[0091] In this alternative embodiment, the expression of the cost function is:

[0092]

[0093] Wherein, C represents the cost function, β represents the elastic parameter of the elastic grid, T represents the total number of nodes of the elastic grid, and W(v j ) represents the deformation of the j-th elastic grid node, and P j ′ and P respectively represent the decomposition value and the reference standard decomposition value of the facial expression feature dataset, and R(Pj′,P) represents the similarity.

[0094] In this alternative embodiment, when obtaining the dynamic data of the intelligent robot during the emergency handling process, evaluating the emergency response efficiency according to the dynamic data, and adjusting the traveling path of the intelligent robot based on the response efficiency result, the dynamic data of the intelligent robot during the emergency handling process (such as response time, path consumption time, operation time) can be obtained through timestamp recording, and the collected dynamic data is analyzed. Among them, the rescue time is decomposed into response time, path consumption time, and rescue operation time to identify the bottleneck links; the rescue effect analyzes the rescue success rate and quantifies the goal achievement degree (such as 80% rescue effect is partially successful); the capture efficiency calculates key indicators such as target positioning accuracy, escape times, and capture completion rate, and presents the change trend of the dynamic data in a graph; the following evaluation indicators are defined according to the dynamic data: efficiency score, efficiency classification, and bottleneck analysis. If the efficiency is low, analyze the following possible problems:

[0095] Path planning problems: The path is too long, there are many obstacles, and the dynamic environment changes greatly; Task execution problems: The target recognition is inaccurate, and the rescue or capture operation takes too long; External environment problems: Such as complex terrain or interference signals; And according to the efficiency evaluation result, select an appropriate path planning strategy.

[0096] Figure 2 An embodiment of an integrated public security emergency response assistance system of the present invention is shown.

[0097] In this alternative embodiment, the emergency response assistance system includes:

[0098] An intelligent robot task allocation unit 201, configured to generate a patrol task according to the layout information in the public security area, and allocate an optimal patrol path for the intelligent robot based on the regional importance and the patrol task;

[0099] A dynamic navigation obstacle avoidance processing unit 202, configured to analyze the obstacle information on the optimal patrol path by using real-time positioning and visual analysis technologies, and adjust the optimal patrol path in real time based on the obstacle information to obtain the traveling path of the intelligent robot;

[0100] The intelligent robot analysis and assistance unit 203 is used to obtain the behavior information of on-site personnel in the traveling path by using the sensors carried by the intelligent robot, and adopt data analysis and discrimination technology to identify and process the behavior information to obtain the abnormal conditions of on-site personnel, and perform emergency treatment on on-site personnel according to the results of the abnormal conditions;

[0101] The emergency response efficiency evaluation unit 204 is used to obtain the dynamic data of the intelligent robot during the emergency treatment process, evaluate the emergency response efficiency according to the dynamic data, and adjust the traveling path of the intelligent robot based on the response efficiency result.

[0102] The core of this embodiment is to construct an integrated public safety emergency response assistance platform integrating intelligent robots, volunteer recruitment, training and publicity systems, assistance rescue and arrest supporting systems, and data analysis and optimization modules, which is specifically as follows:

[0103] (1) The intelligent robot system adopts a modular design. Each functional module (such as rescue equipment, medical equipment, environmental monitoring module, arrest equipment, etc.) can be quickly assembled and replaced according to actual needs, improving the flexibility and adaptability of the system. It adopts advanced power technology to ensure that the intelligent robot has the ability to run for a long time and charge quickly in complex environments, meeting the needs of emergency rescue and arrest. At the same time, it integrates a variety of sensors including positioning sensors, environmental perception sensors, crowd analysis sensors, etc. to achieve real-time and accurate on-site monitoring and data analysis. Combining SLAM (Simultaneous Localization and Mapping) and deep learning algorithms, it realizes autonomous navigation, path planning and dynamic obstacle avoidance in complex environments, and combines with technologies such as image recognition and voice recognition to automatically identify emergency situations and quickly make rescue and arrest decisions. During the rescue process, it can be equipped with an AED automatic external defibrillator, a first aid drug management system and vital sign monitoring equipment, capable of performing basic medical first aid, and providing remote medical guidance and crowd management solutions. At the same time, it integrates multi-channel communication technology to ensure stable connection with the command center, on-site personnel and medical teams, realizing real-time transmission and sharing of information.

[0104] (2) Volunteer recruitment, training and publicity system: During the rescue process, use online channels such as social media and professional rescue forums to release recruitment information, attract and screen suitable volunteers, organize activities such as rescue knowledge lectures and simulation drills to improve public participation and life-saving awareness; establish cooperative relationships with universities, rescue organizations, etc. to jointly cultivate professional life-saving talents, including basic training (basic rescue knowledge, first aid skills, psychological counseling, etc.), special training (water rescue, mountain search and rescue, crowd control, etc.) and actual combat drills to ensure that life-saving personnel have comprehensive rescue capabilities.

[0105] (3) Assistance in rescue and capture function: Identify the behavior actions and facial images of the monitored personnel through the image data obtained by the monitoring camera, collect the voice signals of the monitored personnel through the voice collector, collect the heart rate signals of the monitored personnel through the optical heart rate monitor, collect the chest heat change signals of the monitored personnel through the infrared sensor, and the emotion recognizer evaluates the emotional state of the monitored personnel through the facial image, voice signal, heart rate signal and chest heat change signal, and analyzes and determines their suspiciousness based on the behavior actions and emotional state of the monitored personnel.

[0106] After determining that the monitored personnel are highly suspicious, activate the warning light and issue a warning through the voice alarm, and at the same time send an alarm signal to the human-computer interaction platform. After receiving the alarm signal, the human-computer interaction platform preferentially dispatches the nearest police officers and volunteers to conduct on-site confirmation and handling. The data storage uses encrypted storage technology to ensure the security and privacy of all patrol data, and supports the rapid retrieval and backtracking of data. At the same time, the camera of the intelligent terminal supports high-definition video recording and real-time transmission to ensure the authenticity and effectiveness of on-site evidence collection. The intelligent robot is equipped with a variety of sensors and can operate stably under different environmental conditions, including complex public security patrol environments such as low light, high temperature, and high humidity.

[0107] At the same time, it is assumed that when the intelligent robot is performing rescue work in the public security area, the intelligent robot discovers an emergency and sends a distress signal through the one-key alarm device. After receiving the alarm, the emergency response platform automatically locates the on-site location, dispatches the intelligent robot and volunteers. The intelligent robot arrives at the scene quickly according to the preset navigation path and combined with real-time environment perception. After the intelligent robot arrives, it automatically conducts environmental monitoring, identifies the trapped personnel, and provides preliminary medical support (such as cardiopulmonary resuscitation, drug delivery, etc.). The volunteers conduct subsequent rescue according to the real-time feedback information of the intelligent robot.

[0108] Generally speaking, as the command center of the system, the human-computer interaction platform is responsible for task allocation, data processing and storage. According to the patrol task requirements, it reasonably allocates police officers, volunteers and robot resources, and plans the optimal patrol path for each. The platform combines the layout map of the patrol area, historical patrol data and real-time usage situation, divides the patrol area into different importance zones, and adjusts the resource allocation strategy according to the importance degree of the zones; receives the suspicious personnel data, alarm data and evidence collection data from the robot in real time, marks the received data, and stores it in the data storage for subsequent analysis and review; safely and efficiently stores all received data, supports the rapid retrieval and backtracking of data, and ensures the integrity and reliability of law enforcement data.

[0109] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 3As shown in the figure. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0110] Those skilled in the art can understand that Figure 3 the structure shown in the figure is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0111] In addition, the present invention also provides a computer device, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it implements the steps in the above method embodiments.

[0112] Furthermore, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0113] Those of ordinary skill in the art can understand that all or part of the processes of implementing the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it may include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided by the present invention may include at least one of non-volatile and volatile memories. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory may include random access memory (RAM) or an external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0114] The present invention is not limited to the structures that have been described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. An integrated public safety emergency response assistance method, characterized in that: The emergency response assistance method includes: Generate patrol tasks based on the layout information in the public safety area, and assign the optimal patrol path to the intelligent robot based on the importance of the area and the patrol task; Use real-time positioning and visual analysis technology to analyze the obstacle information on the optimal patrol path, and adjust the optimal patrol path in real time based on the obstacle information to obtain the travel path of the intelligent robot; The sensors carried by the intelligent robot are used to obtain the behavior information of the on-site personnel in the travel path, and the data analysis and identification technology is used to identify and process the behavior information to obtain the abnormal conditions of the on-site personnel, and emergency treatment is carried out on the on-site personnel according to the abnormal condition results; The dynamic data of the intelligent robot during the emergency handling process is obtained, and the emergency response efficiency is evaluated based on the dynamic data, and the travel path of the intelligent robot is adjusted based on the response efficiency results.

2. The integrated public safety emergency response assistance method according to claim 1, characterized in that: Generating patrol tasks according to the layout information in the public safety area, and allocating optimal patrol paths for intelligent robots based on the importance of the area and the patrol tasks include: Obtain the facility layout diagram and historical inspection information in the public safety area to generate an inspection auxiliary list, and combine the inspection auxiliary list, inspection point information and inspection item information to obtain an inspection task list; Represent the inspection points and inspection item information attributes in matrix form respectively, and map the inspection item information to the inspection points according to the matrix representation results, and obtain the point-item association set to obtain the inspection task; The generated inspection tasks are initialized and allocated to intelligent robots through the matching function, and the initial allocation results are optimized and reorganized in combination with the fitness function and the importance of the area to obtain the optimal allocation result; The optimal patrol task allocation result of the intelligent robot is combined with the path planning algorithm to generate a patrol path, and the patrol path with the lowest operating cost is selected as the optimal patrol path for the intelligent robot.

3. The integrated public safety emergency response assistance method according to claim 2 is characterized in that: The generated inspection tasks are initialized and allocated to the intelligent robot through the matching function, and the initial allocation results are optimized and reorganized in combination with the fitness function and the importance of the area to obtain the optimal allocation result, including: Generate response sets and task sets based on the number of intelligent robots and patrol tasks, express the task allocation problem based on the response sets and task sets, and use the expression results and patrol responsibilities to analyze the task matching degree of the intelligent robot; Using the matching results, tasks are assigned in a cyclic manner to obtain the initial assignment results, and the task distance and time interval dispersion of the intelligent robot corresponding to the initial assignment results are evaluated; The fitness function is determined by evaluating the probability of the intelligent robot completing the inspection task based on the task distance and time interval dispersion, and the initialization allocation result is optimized according to the fitness function and the importance of the area to obtain the optimal allocation result.

4. The integrated public safety emergency response assistance method according to claim 3 is characterized in that: The method of combining the optimal patrol task allocation result of the intelligent robot with the path planning algorithm to generate a patrol path, and selecting the patrol path with the lowest operating cost as the optimal patrol path for the intelligent robot includes: The inspection points and items in the inspection process are obtained based on the optimal allocation results of the inspection tasks of the intelligent robot, and several groups of moving points are set as the initial points at the inspection points according to the path planning algorithm; Calculate the step length between any two groups of initial points, initialize the pheromone concentration according to the step length result and the required end time of the inspection task, and analyze the movement path of the starting initial point in the process of moving to the last initial point; The moving path with pheromone concentration in the preset range is obtained as the patrol path of the intelligent robot, and the total time for the intelligent robot to complete the patrol task is calculated. Based on the analysis of the power operating cost of the total time, the patrol path with the lowest operating cost is selected as the optimal patrol path for the intelligent robot.

5. The integrated public safety emergency response assistance method according to claim 1, characterized in that: The method of using sensors carried by the intelligent robot to obtain behavior information of on-site personnel in the travel path, and using data analysis and identification technology to identify and process the behavior information to obtain abnormal conditions of on-site personnel, and performing emergency treatment on on-site personnel according to the abnormal condition results includes: The intelligent robot is equipped with positioning sensors, environmental perception monitors and crowd analysis sensors to capture the behavior information of on-site personnel in the public safety area; Based on behavioral information and data analysis and identification technology, the behavioral movements and facial expressions of the on-site personnel are obtained, and the facial results are used to predict the physiological characteristics of the on-site personnel. The physiological characteristics are combined with suspicious physiological standards and rescue physiological standards to determine the abnormal condition information of the on-site personnel; The human-computer interaction platform receives abnormal condition information from on-site personnel. If the abnormal condition indicates that the on-site personnel are suspicious, the behavioral actions are used to make secondary predictions for the corresponding on-site personnel. If the prediction result still indicates that there is a suspicious situation among the on-site personnel, the human-computer interaction platform generates a response auxiliary strategy and feeds it back to the intelligent robot, and the intelligent robot captures and processes the on-site personnel based on the auxiliary strategy; If the abnormal condition indicates that the on-site personnel have abnormal physiological conditions, the optical heart rate monitor and infrared sensor carried by the intelligent robot are used to obtain the on-site personnel's physiological data; Based on the physiological data results, a safety emergency assistance strategy is generated and fed back to the intelligent robot, which then rescues the on-site personnel according to the strategy.

6. The integrated public safety emergency response assistance method according to claim 5, characterized in that: The behavior information and data analysis and identification technology is used to obtain the behavior and facial expressions of the on-site personnel, and the facial results are used to predict the physiological characteristics of the on-site personnel. The physiological characteristics are combined with suspicious physiological standards and rescue physiological standards to judge the abnormal condition information of the on-site personnel, including: The image data containing the on-site personnel is preprocessed using the facial key point detection technology, and the facial area is subdivided into several groups of facial trigger areas and action trigger areas; Based on the preset data analysis and recognition model, the facial trigger area and the action trigger area are identified to obtain the fusion features of facial expression and action behavior; The facial expression fusion features are used to predict the physiological characteristics of the on-site personnel, and the physiological characteristics are matched with suspicious physiological standards and rescue physiological standards. The abnormal condition information of the on-site personnel is judged based on the matching results.

7. The integrated public safety emergency response assistance method according to claim 6, characterized in that: The facial trigger area and the action trigger area are identified based on the preset data analysis and recognition model to obtain the fusion features of facial expression and action behavior, including: The local features of facial expressions and actions in the corresponding facial trigger area and action trigger area are extracted by using a preset data analysis recognition model to obtain the local features of the facial and action trigger areas; The local features are input into the activation layer of the data analysis recognition model to recognize facial expressions and action units, and the activation features of facial expressions and actions are obtained; The facial trigger area and the action trigger area are cut into blocks and input into the preset data analysis recognition model to extract the features of the whole face and the whole body of the on-site personnel, obtain the global features of the on-site personnel, and fuse the activation features with the global features at the feature level to obtain the fusion features of facial expressions and action behaviors.

8. The integrated public safety emergency response assistance method according to claim 7, characterized in that: The method of using facial expression fusion features to predict the physiological characteristics of the on-site personnel, matching the physiological characteristics with suspicious physiological standards and rescue physiological standards, and judging the abnormal condition information of the on-site personnel according to the matching results includes: The facial expression fusion features are trained using non-uniform grids to obtain an expression feature dataset targeting the key feature information of facial expression changes. The elastic grid nodes are used to implement local movement operations on the expression feature dataset, and similarity tests are performed based on the movement results to obtain the cost function between the corresponding physiological features in the expression feature dataset and the suspicious physiological standard and rescue physiological standard features. Compare the difference between the cost functions corresponding to the suspicious physiological standard and the rescue physiological standard. If the cost function of the suspicious physiological standard is greater than the cost function of the rescue physiological standard, it means that there is a suspicious situation among the on-site personnel; If the cost function of the suspicious physiological standard is less than the cost function of the rescue physiological standard, it means that the on-site personnel have physiological abnormalities. If the cost function of the suspicious physiological standard is equal to the cost function of the rescue physiological standard, the behavioral actions are used to make a secondary prediction of the corresponding on-site personnel.

9. The integrated public safety emergency response assistance method according to claim 8, characterized in that: The expression of the cost function is: In the formula, C represents the cost function, β represents the elastic parameter of the elastic grid, T represents the total number of nodes of the elastic grid, and W(v j ) represents the deformation of the jth elastic mesh node, P j ′ and P represent the decomposition value of the expression feature dataset and the reference standard decomposition value respectively, and R(Pj′,P) represents the similarity.

10. An integrated public safety emergency response auxiliary system, characterized in that: The emergency response assistance system includes: An intelligent robot task allocation unit is used to generate patrol tasks based on the layout information in the public safety area, and allocate the optimal patrol path for the intelligent robot based on the importance of the area and the patrol task; The dynamic navigation obstacle avoidance processing unit is used to analyze the obstacle information on the optimal patrol path using real-time positioning and visual analysis technology, and adjust the optimal patrol path in real time based on the obstacle information to obtain the travel path of the intelligent robot; The intelligent robot analysis auxiliary unit is used to use the sensors carried by the intelligent robot to obtain the behavior information of the on-site personnel in the travel path, and use data analysis and identification technology to identify and process the behavior information to obtain the abnormal conditions of the on-site personnel, and perform emergency treatment on the on-site personnel according to the abnormal condition results; The emergency response efficiency evaluation unit is used to obtain the dynamic data of the intelligent robot during the emergency handling process, evaluate the emergency response efficiency according to the dynamic data, and adjust the travel path of the intelligent robot based on the response efficiency results.

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