A safety protection design method and device for community streets

Abstract

This application discloses a security protection design method and device for community streets. The community street security protection design method includes: acquiring historical alarm record information of the community; acquiring the location information of frequently occurring alarms; generating a monitoring range in a virtual reality model of the community; acquiring information on the range of personnel with assistance; determining whether a monitoring range meets a first preset condition based on the information on the range of personnel with assistance; if so, setting up a camera device, a sound effect playback device, and a lighting device in the virtual reality model for the monitoring range that meets the first preset condition; and arranging and associating the camera device, sound effect playback device, and lighting device in the real scene according to the virtual reality model. This application enables the use of video evidence, video identification, sound effect playback device, and lighting device for deterrence and intimidation when problems occur in the monitoring range, and allows personnel in the control room to understand the situation at any time through the virtual reality model.

Description

Technical Field

[0001] This application relates to the field of street monitoring technology, and in particular to a security protection design method, a community street monitoring method, and a security protection design device for community streets. Background Technology

[0002] Most existing communities are multi-functional, meaning they are relatively large and may include military and civilian housing, commercial facilities, green spaces, and even kindergartens. This can lead to some areas becoming sparsely populated and potentially dangerous at night. Although these areas are within the community, their remoteness can prevent people from receiving assistance in case of emergencies.

[0003] Therefore, it is desirable to have a technical solution to overcome or at least mitigate one of the aforementioned defects of the prior art.

[0004] Application content

[0005] The purpose of this application is to provide a design method for security protection in community streets to overcome or at least mitigate one of the aforementioned defects of the prior art.

[0006] To achieve the above objectives, this application provides a community street safety protection design method, which includes:

[0007] Obtain community historical alarm records;

[0008] The location information of frequently occurring alarms is obtained based on the community's historical alarm records.

[0009] Obtain virtual reality models of the community;

[0010] The monitoring area is generated in the virtual reality model of the community;

[0011] Obtain information on the scope of personnel who can provide assistance;

[0012] Based on the information on the scope of personnel providing assistance, determine whether there is a monitoring area that meets the first preset condition. If so, then...

[0013] In the virtual reality model, a camera device, a sound playback device, and a lighting device are set up for the monitoring range that meets the first preset conditions.

[0014] Based on the various camera devices set in the virtual reality model, camera devices are set up at corresponding positions in the real scene and associated with the camera devices in the virtual reality model;

[0015] Based on the various camera devices set in the virtual reality model, set up sound effects playback devices at corresponding positions in the real scene and associate them with the sound effects playback devices in the virtual reality model.

[0016] Based on the lighting devices set in the virtual reality model, set up the corresponding lighting devices in the real scene and associate them with the lighting devices in the virtual reality model.

[0017] Optionally, the community historical alarm record information includes case type information and location coordinate information corresponding to each case type;

[0018] The location information of frequently occurring alarms is obtained based on the community's historical alarm records, including:

[0019] Based on the location coordinate information corresponding to each case type, the location coordinate information is clustered to obtain multiple clusters;

[0020] For each cluster, a virtual circle is set that can contain the coordinate information of each location under the cluster, and the radius information of the virtual circle is obtained. The coordinate information included in each virtual circle is the location information of the frequent alarm.

[0021] Optionally, generating the monitoring scope in the virtual reality model of the community includes:

[0022] Obtain the center coordinates of each cluster in the virtual reality model of the community;

[0023] Using each of the aforementioned center coordinates as a point and the radius information of the virtual circle corresponding to each center coordinate as the radius, each monitoring range is obtained in the virtual reality model of the community. A center coordinate and the radius information of a virtual circle are used to generate a monitoring range.

[0024] Optionally, each of the assisted personnel range information includes multiple range coordinate points;

[0025] The step of determining whether a monitoring area meets the first preset condition based on the information of the scope of assisting personnel includes:

[0026] For each area requiring monitoring, the following processing is performed:

[0027] Each coordinate point within the monitoring range is compared with the coordinate points of each range with assisting personnel range information to obtain the number of coordinate points within the monitoring range that are different from any of the range coordinate points with assisting personnel range information. The coordinate points that are different from any of the range coordinate points with assisting personnel range information are called uncovered coordinate points.

[0028] Determine if the percentage of uncovered coordinate points within the total number of coordinate points in the monitored area is higher than a preset percentage. If so, then...

[0029] Confirm that the area to be monitored meets the first preset condition.

[0030] This application also provides a community street monitoring method, said community street monitoring method being used in accordance with the community street security protection design method described above, said community street monitoring method comprising:

[0031] The cloud acquires video stream information transmitted by each camera device;

[0032] The cloud performs image and audio recognition on each video stream to determine if there are any special circumstances. If so, then...

[0033] Get the current time information;

[0034] Interference information is generated based on the current time information and sent to the sound effects playback device and / or lighting device.

[0035] Optionally, the cloud performs image recognition and audio recognition on each video stream to determine if there are any special circumstances, including:

[0036] The first recognition result is obtained by recognizing each frame of the video stream information;

[0037] The audio information in the video stream is identified to obtain a second identification result;

[0038] Based on the first identification result and the second identification result, determine whether there are any special circumstances.

[0039] Optionally, the step of identifying each frame of the video stream information to obtain a first identification result includes:

[0040] Obtain the improved YOLOv8 model;

[0041] Each frame of image is input into the improved YOLOv8 model to obtain human-shaped target information in the image;

[0042] Obtain the trained SVM action classifier;

[0043] Extract feature information from each humanoid target;

[0044] The feature information is input into the trained SVM action classifier to obtain action classification information, which is used as the first recognition result.

[0045] Optionally, the step of identifying the audio information in the video stream information to obtain a second identification result includes:

[0046] Obtain the semantic recognition model;

[0047] Extract audio features from the acquired audio information;

[0048] The audio features are input into the semantic recognition model to obtain the semantic recognition result, which is then used as the second recognition result.

[0049] Optionally, determining whether there are special circumstances based on the first identification result and the second identification result includes:

[0050] When the first identification result is the same as the second identification result, it is determined that there is a special case.

[0051] This application also provides a safety protection design device for community streets, the safety protection design device for community streets comprising:

[0052] A community historical alarm record information acquisition module, which is used to acquire community historical alarm record information;

[0053] A frequent alarm location information acquisition module is used to acquire frequent alarm location information based on the community's historical alarm record information;

[0054] A virtual reality model acquisition module, which is used to acquire virtual reality models of the community;

[0055] A monitoring range acquisition module is used to generate the monitoring range in the virtual reality model of the community.

[0056] The module for obtaining information on the scope of assisting personnel is used to obtain information on the scope of assisting personnel.

[0057] The judgment module is used to determine whether there is a monitoring range that meets the first preset condition based on the information on the range of personnel who need to assist.

[0058] A virtual reality model installation module is used to set up a camera device, a sound playback device, and a lighting device in the virtual reality model for a monitoring range that meets the first preset conditions.

[0059] A real-world camera installation module is used to install camera devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the camera devices in the virtual reality model.

[0060] A real-world sound effects playback device installation module is used to set up sound effects playback devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the sound effects playback devices in the virtual reality model.

[0061] A real-world lighting installation module is used to install lighting devices at corresponding positions in the real-world scene according to the various lighting devices set in the virtual reality model, and to associate them with the lighting devices in the virtual reality model.

[0062] The community street security protection design method proposed in this application first generates the area to be monitored, then determines the area to be supervised, and installs corresponding camera devices, sound playback devices, and lighting devices in the area to be supervised. This enables the use of video evidence, video identification, sound playback devices, and lighting devices to drive away or intimidate people in the event of a problem in these areas. The virtual reality model allows people in the control room to understand the situation at any time. Attached Figure Description

[0063] Figure 1 This is a flowchart illustrating a community street security protection design method according to an embodiment of this application.

[0064] Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0066] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the scope of protection of this application.

[0067] Figure 1 This is a flowchart illustrating a community street security protection design method according to an embodiment of this application.

[0068] like Figure 1 The safety protection design methods for community streets shown include:

[0069] Step 1: Obtain historical alarm records from the community;

[0070] Step 2: Obtain the location information of frequently occurring alarms based on the community's historical alarm records;

[0071] Step 3: Obtain the community's virtual reality model;

[0072] Step 4: Generate the monitoring area in the virtual reality model of the community;

[0073] Step 5: Obtain information on the scope of personnel who can provide assistance;

[0074] Step 6: Based on the information on the scope of personnel providing assistance, determine whether there is a monitoring area that meets the first preset condition. If so, then...

[0075] Step 7: In the virtual reality model, set up a camera device, a sound playback device, and a lighting device for the monitoring area that meets the first preset conditions;

[0076] Step 8: Based on the various camera devices set in the virtual reality model, set up the camera devices in the corresponding positions in the real scene and associate them with the camera devices in the virtual reality model;

[0077] Step 9: Based on the corresponding positions of the various camera devices set in the virtual reality model in the real scene, set up the sound effects playback devices and associate them with the sound effects playback devices in the virtual reality model;

[0078] Step 10: Set up the lighting devices in the real scene according to the corresponding positions of the lighting devices set in the virtual reality model, and associate them with the lighting devices in the virtual reality model.

[0079] In this embodiment, the community historical alarm record information includes case type information and the location coordinates corresponding to each case type. It is understood that the community historical alarm record information may also include other information, such as the number of people, facial images, and physical appearance images.

[0080] In this embodiment, obtaining the location information of frequently occurring alarms based on the community's historical alarm records includes:

[0081] Based on the location coordinate information corresponding to each case type, the location coordinate information is clustered to obtain multiple clusters;

[0082] For each cluster, a virtual circle is set that can contain the coordinate information of each location under the cluster, and the radius information of the virtual circle is obtained. The coordinate information included in each virtual circle is the location information of the frequent alarm.

[0083] In this embodiment, the application uses the k-means clustering algorithm for clustering.

[0084] In this embodiment, after clustering is completed, a virtual circle is set with the center point of each cluster as the center. The radius of the virtual circle is such that all points belonging to the cluster can be located within the virtual circle.

[0085] In this embodiment, generating the monitoring scope in the virtual reality model of the community includes:

[0086] Obtain the center coordinates of each cluster in the virtual reality model of the community;

[0087] Using each of the aforementioned center coordinates as a point and the radius information of the virtual circle corresponding to each center coordinate as the radius, each monitoring range is obtained in the virtual reality model of the community. A center coordinate and the radius information of a virtual circle are used to generate a monitoring range.

[0088] In this embodiment, each of the assisting personnel range information includes multiple range coordinate points. Specifically, the assisting personnel range information includes a coordinate point group and assisting personnel information. One coordinate point group corresponds to at least one assisting personnel information. The assisting personnel information represents the information of the person who can provide assistance, and the coordinate point group represents the assisting personnel information corresponding to that coordinate point group, or the matters within that coordinate point group. In this embodiment, the assisting personnel range information is set to determine densely populated areas. Although densely populated areas also need video surveillance, most densely populated areas will not use the design method of this application, especially will not install the sound playback device and lighting device of this application, because the purpose of this application is mainly for relatively remote areas far from densely populated areas. This is why this application first determines the monitoring range.

[0089] The step of determining whether a monitoring area meets the first preset condition based on the information of the scope of assisting personnel includes:

[0090] For each area requiring monitoring, the following processing is performed:

[0091] Each coordinate point within the monitoring range is compared with the coordinate points of each range with assisting personnel range information to obtain the number of coordinate points within the monitoring range that are different from any of the range coordinate points with assisting personnel range information. The coordinate points that are different from any of the range coordinate points with assisting personnel range information are called uncovered coordinate points.

[0092] Determine if the percentage of uncovered coordinate points within the total number of coordinate points in the monitored area is higher than a preset percentage. If so, then...

[0093] Confirm that the area to be monitored meets the first preset condition.

[0094] For example, suppose there are three coordinate points (ABC) within a monitored area, and two coordinate points (DF) within the range information of the assisting personnel. Suppose coordinate points A and D are the same, and coordinate points B and F are the same. Suppose the preset percentage is 40%, and now one of the three coordinate points is different, which is about 33%, then it is judged as no. For example, if we have four coordinate points, but only two are the same, then it is judged as yes.

[0095] This application also provides a community street monitoring method, which is used to monitor a community street designed using the community street security protection design method described above. In other words, the community street designed using the community street security protection design method of this application can be monitored using the community street monitoring method of this application.

[0096] The community street monitoring methods in this application include:

[0097] The cloud acquires video stream information transmitted by each camera device;

[0098] The cloud performs image and audio recognition on each video stream to determine if there are any special circumstances. If so, then...

[0099] Get the current time information;

[0100] Interference information is generated based on the current time information and sent to the sound effects playback device and / or lighting device.

[0101] Using the method of this application, when special circumstances occur, it is possible to determine which type of interference information to use based on the current time information. For example, if the current time is daytime, using a lighting device is meaningless, and in this case, only a sound effect playback device is used. However, if it is nighttime, the sound effect playback device and the lighting device can be used simultaneously, or the lighting device can be used alone.

[0102] It is understood that the generation of interference information can be set as needed. For example, when image recognition and audio recognition are performed on each video stream information separately through the cloud, since semantic recognition technology and image recognition technology are used, the results obtained include action behavior or sound behavior. Action behavior may be fighting, and sound behavior may be arguing. At this time, different interference information can be set according to different behaviors. It is understood that the setting of interference information is not the content protected by this application, so it will not be elaborated further. It is understood that interference information may be playing certain onomatopoeic sounds (such as police sirens, dog barks, etc.), and lights may be certain strong flashing lights.

[0103] In this embodiment, the cloud performs image recognition and audio recognition on each video stream to determine if there are any special circumstances, including:

[0104] The first recognition result is obtained by recognizing each frame of the video stream information;

[0105] The audio information in the video stream is identified to obtain a second identification result;

[0106] Based on the first identification result and the second identification result, determine whether there are any special circumstances.

[0107] In this embodiment, the step of identifying each frame of the video stream information to obtain a first identification result includes:

[0108] Obtain the improved YOLOv8 model;

[0109] Each frame of image is input into the improved YOLOv8 model to obtain human-shaped target information in the image;

[0110] Obtain the trained SVM action classifier;

[0111] Extract feature information from each humanoid target;

[0112] The feature information is input into the trained SVM action classifier to obtain action classification information, which is used as the first recognition result.

[0113] In this embodiment, the improved YOLOv8 model of this application has the following features:

[0114] The improved YOLOv8 model in this application modifies the existing C2f layer as follows:

[0115] The C2f module employs a chunking operation, which uniformly divides the input feature map into multiple sub-parts. Each sub-part is processed independently through a bottleneck layer or other convolutional operations. Finally, the processed features are concatenated together. The C2f module allows for richer gradient flow, enhances feature extraction capabilities, and reduces computational complexity.

[0116] This application replaces the bottleneck layer of the prior art. Specifically, the bottleneck layer of the prior art includes a depthwise separable convolutional layer, which is replaced by a ghost convolutional module in this application, and the last convolutional layer of the bottleneck layer is replaced by the weighted convolutional module of this application.

[0117] Global average pooling is performed on the feature maps, and a two-layer MLP (Multilayer Perceptron) module with a softmax activation function is used to generate dynamic weights α. Next, ghost convolution is applied to generate "ghost features" on the "base features." The features are then concatenated, and finally, the dynamic weights α generated in the first step are assigned values. That is, assuming we have already generated k dynamic weights from α1 to α2 based on the input... k At this point, each basic feature after ghost convolution generates a ghost feature. Then, the basic features and ghost features are concatenated to form a combined feature that has both basic features and ghost features. There are a total of k such combined features. After that, k dynamic weights are assigned to these k combined features one by one, and finally summed.

[0118] Specifically, the formula of this application can be expressed as follows:

[0119]

[0120] Where ω primary,k It is the k-th standard convolutional kernel. f is the number of ghost features generated for each input feature map. i It is a linear transformation function, α k It is the kth dynamic weight, and * indicates the convolution operation.

[0121] When calculating the loss function, the comprehensive loss function typically includes classification loss, localization loss, and keypoint loss. The definitions are as follows:

[0122] ζ=λ cls ζ cls +λ locζ loc +λ pose ζ pose ;

[0123] Where, ζ cls This refers to classification loss, which measures the difference between the predicted and true classes. Cross-entropy loss is used. loc ζ is the specified bit loss, which measures the difference between the predicted bounding box and the ground truth bounding box. pose This refers to the pose estimation loss, which measures the difference between the predicted keypoint locations and the actual keypoint locations. It uses the mean squared error (MSE). λ cls , λ loc , λ pose These are the weight hyperparameters for the corresponding loss terms, used to balance the contribution of different loss terms to the total loss.

[0124] ζ cls The formula for calculating classification loss is as follows:

[0125]

[0126] Where N is the number of samples, C is the number of categories, and y i,c The true label of sample i belonging to category c. It is the probability of class c predicted by the model.

[0127] ζ loc The formula for calculating positioning loss is as follows:

[0128]

[0129] Among them, b i It is the true bounding box of sample i. It is the bounding box predicted by the model.

[0130] ζ pose The formula for calculating attitude estimation loss is as follows:

[0131]

[0132] Where K is the number of key points, p i,j It is the true location of the j-th keypoint in sample i. It is the position of the j-th key point predicted by the model.

[0133] The improved YOLO model of this application has a significantly increased number of parameters after adding weighted convolution and ghost convolution. Therefore, by combining ghost convolution and weighted convolution and replacing the C2f layer in yolov8n with the scheme of this application, a lightweight model with a significantly reduced number of parameters and computational cost while maintaining the accuracy is obtained.

[0134] In this embodiment, the step of identifying the audio information in the video stream information to obtain a second identification result includes:

[0135] Obtain the semantic recognition model;

[0136] Extract audio features from the acquired audio information;

[0137] The audio features are input into the semantic recognition model to obtain the semantic recognition result, which is then used as the second recognition result.

[0138] In this embodiment, determining whether there are special circumstances based on the first identification result and the second identification result includes:

[0139] When the first identification result is the same as the second identification result, it is determined that there is a special case.

[0140] It is understandable that other solutions may also be included. For example, when the first recognition result is different from the second recognition result, the duration of the currently acquired video stream information is obtained. If the duration is less than the first duration threshold (e.g., 5 seconds), the recognition of this application continues until the second duration threshold (e.g., 10 seconds) is reached. This approach can prevent situations where the application cannot be recognized due to unclear actual circumstances or because the acquired content is insufficient, thus preventing recognition errors. By increasing the monitoring duration, more video and audio information can be acquired, which may further increase the accuracy of recognition.

[0141] It is understandable that other judgment methods can be set, which will not be elaborated here.

[0142] This application also provides a community street security protection design device, which includes a community historical alarm record information acquisition module, a frequent alarm location information acquisition module, a virtual reality model acquisition module, a monitoring range acquisition module, an assistance personnel range information acquisition module, a judgment module, a virtual reality model installation module, a real-world camera device installation module, a real-world sound playback device installation module, and a real-world lighting device installation module.

[0143] The community historical alarm record information acquisition module is used to acquire community historical alarm record information;

[0144] The frequent alarm location information acquisition module is used to acquire the frequent alarm location information based on the community's historical alarm records.

[0145] The virtual reality model acquisition module is used to acquire virtual reality models from the community;

[0146] The monitoring range acquisition module is used to generate the monitoring range in the virtual reality model of the community;

[0147] The module for obtaining information on the scope of personnel providing assistance is used to obtain information on the scope of personnel providing assistance.

[0148] The judgment module is used to determine whether there is a monitoring range that meets the first preset condition based on the information on the range of personnel who can assist.

[0149] The virtual reality model installation module is used to set up camera devices, sound playback devices, and lighting devices in the virtual reality model for the monitoring range that meets the first preset conditions;

[0150] The real-world camera installation module is used to set up camera devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the camera devices in the virtual reality model;

[0151] The real-world sound effects playback device installation module is used to set up sound effects playback devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the sound effects playback devices in the virtual reality model.

[0152] The real-world lighting installation module is used to set up lighting devices in the corresponding positions in the real-world scene according to the various lighting devices set in the virtual reality model, and to associate them with the lighting devices in the virtual reality model.

[0153] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and will not be repeated here.

[0154] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the above-described community street security protection design method.

[0155] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, enables the implementation of the above-described community street security protection design method.

[0156] Figure 2This is an exemplary structural diagram of an electronic device capable of implementing the community street security protection design method provided in one embodiment of this application.

[0157] like Figure 2 As shown, the electronic device includes an input device 501, an input interface 502, a central processing unit 503, a memory 504, an output interface 505, and an output device 506. The input interface 502, central processing unit 503, memory 504, and output interface 505 are interconnected via a bus 507. The input device 501 and output device 506 are connected to the bus 507 via the input interface 502 and output interface 505, respectively, and thus connected to other components of the electronic device. Specifically, the input device 504 receives input information from the outside and transmits it to the central processing unit 503 via the input interface 502. The central processing unit 503 processes the input information based on computer-executable instructions stored in the memory 504 to generate output information, temporarily or permanently storing the output information in the memory 504, and then transmitting the output information to the output device 506 via the output interface 505. The output device 506 outputs the output information to the outside of the electronic device for user use.

[0158] In other words, Figure 2 The illustrated electronic device may also be implemented as including: a memory storing computer-executable instructions; and one or more processors, which can be coupled when executing the computer-executable instructions. Figure 1 The description describes the safety protection design methods used in community streets.

[0159] In one embodiment, Figure 2 The electronic device shown can be implemented as including: a memory 504 configured to store executable program code; and one or more processors 503 configured to run the executable program code stored in the memory 504 to execute the community street security protection design method in the above embodiments.

[0160] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0161] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0162] Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, DVD or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0163] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] Furthermore, it is clear that the word "comprising" does not exclude other units or steps. Multiple units, modules, or devices recited in the apparatus claims may also be implemented by a single unit or overall apparatus via software or hardware.

[0165] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutively marked blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or the overall flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0166] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0167] Furthermore, it is clear that the word "comprising" does not exclude other units or steps. Multiple units, modules, or devices recited in the apparatus claims may also be implemented by a single unit or overall apparatus via software or hardware.

[0168] Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A safety protection design method for community streets, characterized in that, The community street safety protection design method includes: Obtain community historical alarm records; The location information of frequently occurring alarms is obtained based on the community's historical alarm records. Obtain virtual reality models of the community; The monitoring area is generated in the virtual reality model of the community; Obtain information on the range of personnel providing assistance; wherein each piece of information on the range of personnel providing assistance includes multiple range coordinate points; Based on the information on the scope of personnel providing assistance, determine whether there is a monitoring area that meets the first preset condition. If so, then... In the virtual reality model, a camera device, a sound playback device, and a lighting device are set up for the monitoring range that meets the first preset conditions. Based on the various camera devices set in the virtual reality model, camera devices are set up at corresponding positions in the real scene and associated with the camera devices in the virtual reality model; Based on the various camera devices set in the virtual reality model, set up sound effects playback devices at corresponding positions in the real scene and associate them with the sound effects playback devices in the virtual reality model. Based on the lighting devices set in the virtual reality model, set up the corresponding lighting devices in the real scene and associate them with the lighting devices in the virtual reality model; The step of determining whether a monitoring area meets the first preset condition based on the information of the scope of assisting personnel includes: For each area requiring monitoring, the following processing is performed: Each coordinate point within the monitoring range is compared with the coordinate points of each range with assisting personnel range information to obtain the number of coordinate points within the monitoring range that are different from any of the range coordinate points with assisting personnel range information. The coordinate points that are different from any of the range coordinate points with assisting personnel range information are called uncovered coordinate points. Determine if the percentage of uncovered coordinate points within the total number of coordinate points in the monitored area is higher than a preset percentage. If so, then... Confirm that the area to be monitored meets the first preset condition.

2. The community street safety protection design method as described in claim 1, characterized in that, The community historical alarm record information includes case type information and location coordinates information corresponding to each case type; The location information of frequently occurring alarms is obtained based on the community's historical alarm records, including: Based on the location coordinate information corresponding to each case type, the location coordinate information is clustered to obtain multiple clusters; For each cluster, a virtual circle is set that can contain the coordinate information of each location under the cluster, and the radius information of the virtual circle is obtained. The coordinate information included in each virtual circle is the location information of the frequent alarm.

3. The community street safety protection design method as described in claim 2, characterized in that, The process of generating the monitoring scope in the virtual reality model of the community includes: Obtain the center coordinates of each cluster in the virtual reality model of the community; Using each of the aforementioned center coordinates as a point and the radius information of the virtual circle corresponding to each center coordinate as the radius, the monitoring ranges are obtained in the virtual reality model of the community. A center coordinate and the radius information of a virtual circle are used to generate a monitoring range.

4. A community street monitoring method, wherein the community street monitoring method is used to monitor a community street designed using the security protection design method for community streets as described in any one of claims 1 to 3, characterized in that, The community street monitoring method includes: The cloud acquires video stream information transmitted by each camera device; The cloud performs image and audio recognition on each video stream to determine if there are any special circumstances. If so, then... Get the current time information; Interference information is generated based on the current time information and sent to the sound effects playback device and / or lighting device.

5. The community street monitoring method as described in claim 4, characterized in that, The cloud platform performs image and audio recognition on each video stream to determine if there are any special circumstances, including: The first recognition result is obtained by recognizing each frame of the video stream information; The audio information in the video stream is identified to obtain a second identification result; Based on the first identification result and the second identification result, determine whether there are any special circumstances.

6. The community street monitoring method as described in claim 5, characterized in that, The step of identifying each frame of the video stream information to obtain the first identification result includes: Obtain the improved YOLOv8 model; Each frame of image is input into the improved YOLOv8 model to obtain human-shaped target information in the image; Obtain the trained SVM action classifier; Extract feature information from each humanoid target; The feature information is input into the trained SVM action classifier to obtain action classification information, which is used as the first recognition result.

7. The community street monitoring method as described in claim 6, characterized in that, The step of identifying the audio information in the video stream information to obtain the second identification result includes: Obtain the semantic recognition model; Extract audio features from the acquired audio information; The audio features are input into the semantic recognition model to obtain the semantic recognition result, which is then used as the second recognition result.

8. The community street monitoring method as described in claim 7, characterized in that, Based on the first identification result and the second identification result, determine whether there are any special circumstances, including: When the first identification result is the same as the second identification result, it is determined that there is a special case.

9. A safety protection design device for community streets, characterized in that, The safety protection design device for community streets includes: A community historical alarm record information acquisition module, which is used to acquire community historical alarm record information; A frequent alarm location information acquisition module is used to acquire frequent alarm location information based on the community's historical alarm record information; A virtual reality model acquisition module, which is used to acquire virtual reality models of the community; A monitoring range acquisition module is used to generate the monitoring range in the virtual reality model of the community. The module for obtaining information on the scope of assisting personnel is used to obtain information on the scope of assisting personnel; wherein, each information on the scope of assisting personnel includes multiple scope coordinate points; The judgment module is used to determine whether there is a monitoring range that meets the first preset condition based on the information on the range of personnel who need to assist. A virtual reality model installation module is used to set up a camera device, a sound playback device, and a lighting device in the virtual reality model for a monitoring range that meets the first preset conditions. A real-world camera installation module is used to install camera devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the camera devices in the virtual reality model. A real-world sound effects playback device installation module is used to set up sound effects playback devices at corresponding positions in the real-world scene according to the various camera devices set in the virtual reality model and associate them with the sound effects playback devices in the virtual reality model. A real-world lighting installation module is used to install lighting devices at corresponding positions in the real-world scene according to the various lighting devices set in the virtual reality model and to associate them with the lighting devices in the virtual reality model. The step of determining whether a monitoring area meets the first preset condition based on the information of the scope of assisting personnel includes: For each area requiring monitoring, the following processing is performed: Each coordinate point within the monitoring range is compared with the coordinate points of each range with assisting personnel range information to obtain the number of coordinate points within the monitoring range that are different from any of the range coordinate points with assisting personnel range information. The coordinate points that are different from any of the range coordinate points with assisting personnel range information are called uncovered coordinate points. Determine if the percentage of uncovered coordinate points within the total number of coordinate points in the monitored area is higher than a preset percentage. If so, then... Confirm that the area to be monitored meets the first preset condition.

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