Law enforcement audio and video data analysis and transmission method and platform

Abstract

The present invention provides a method and platform for analyzing and transmitting law enforcement audio and video data, involving data processing technology. This method can achieve real-time data collection, efficient processing, and accurate display during law enforcement in complex scenarios, such as a busy and crowded market, thereby ensuring information sharing and collaborative work among law enforcement personnel. In such scenarios, where there are dense crowds, numerous stalls, and a complex and changing environment, to achieve information sharing and collaborative work among law enforcement personnel, each officer can view the video data of others. If an anomaly occurs at a particular officer's location, the remaining officers can quickly plan a route to that location based on the distribution of obstacles in the scene, enabling efficient information sharing among officers and improving collaborative efficiency.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a method and platform for analyzing and transmitting law enforcement audio and video data. Background Art

[0002] Law enforcement in complex settings like bustling, crowded markets presents numerous challenges. Markets are characterized by dense crowds, numerous stalls, narrow roads, and irregular layouts, creating a complex and ever-changing law enforcement environment. In this process, efficient information sharing and collaboration among law enforcement personnel are key to improving both efficiency and quality.

[0003] In traditional law enforcement, information transmission between officers primarily relies on verbal descriptions over walkie-talkies. However, this method of communication presents numerous drawbacks. In noisy law enforcement environments, voice transmissions over walkie-talkies are easily interfered with, resulting in unclear information reception. Furthermore, due to language limitations and time constraints, officers often struggle to fully and accurately convey key information when verbally describing the situation on the scene, leading to omissions and unclear descriptions. For example, during law enforcement at a market, when a sudden conflict occurs in a particular area, officers describing the situation over walkie-talkies may fail to accurately convey key information such as the number of individuals involved, their characteristics, and the surrounding environment, making it difficult for other officers to make effective decisions. Furthermore, with traditional methods, officers struggle to obtain real-time information from their colleagues about their work, preventing them from quickly grasping the overall situation on the scene. This creates a serious information silo phenomenon, significantly hindering coordination and cooperation among officers and reducing law enforcement efficiency.

[0004] Therefore, how to achieve efficient information sharing and collaborative work among law enforcement personnel has become an urgent problem that needs to be solved today. Summary of the Invention

[0005] The present invention provides a method and platform for analyzing and transmitting law enforcement audio and video data, which can realize efficient information sharing and collaborative work among law enforcement personnel.

[0006] A first aspect of the present invention provides a method for analyzing and transmitting law enforcement audio and video data, comprising:

[0007] Receive law enforcement video data from each user in real time based on wireless communication;

[0008] Generate display data based on the real-time location of each user and the law enforcement video data and transmit it to the display device of each user, wherein the display device is provided with two windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users;

[0009] When determining the display data, determine the display points of the real-time locations of the remaining users on the regional layout map, divide the display points whose distance is less than the distance threshold into the same display group, and obtain the display data based on the corresponding video quantity and video similarity;

[0010] Determine the target location of the abnormal user, determine the distribution information and height parameters of the obstacles based on the on-site video data of the monitoring equipment, and generate a reference path for wireless transmission to the display devices of the remaining users.

[0011] Optionally, in a possible implementation of the first aspect, obtaining display data in combination with the corresponding number of videos and video similarity includes:

[0012] Determine the display points of the real-time locations of the remaining users on the regional layout map;

[0013] The display points whose distance is less than the distance threshold are divided into the same display group, and the display attribute is determined to be a single attribute or a combination of attributes based on the number of corresponding videos and video similarity;

[0014] Taking the center point of the display group of the single attribute as a reference, generating a single number of first areas and displaying the law enforcement video data to obtain display data; or,

[0015] Taking the center point of the display group of the combined attributes as a reference, a second area of ​​the combined number is generated and the law enforcement video data is displayed to obtain display data.

[0016] Optionally, in a possible implementation of the first aspect, display locations with distances less than a distance threshold are grouped into the same display group, and the display attributes are determined as a single attribute or a combination of attributes based on the number of corresponding videos and video similarity, including:

[0017] Determine that the number of videos is equal to a single number of display groups corresponding to a single attribute;

[0018] For a display group with more videos than a single video, obtaining the video similarity of each of the law enforcement video data in the display group, and when the video similarity is greater than a similarity threshold, determining the corresponding single attribute, and selecting any one of the law enforcement video data for display;

[0019] When the video similarity is less than a similarity threshold, the corresponding combination attribute is determined, and the number of videos is determined as the number of combinations.

[0020] Optionally, in a possible implementation of the first aspect, determining the target location of the abnormal user, determining the distribution information and height parameters of obstacles based on the on-site video data of the monitoring device, and generating a reference path and wirelessly transmitting it to the display devices of the remaining users includes:

[0021] Obtaining the distribution information based on an obstacle area in the on-site video data whose pixel values ​​are not within a preset pixel interval;

[0022] Acquire the height parameters of each position point in the obstacle area, and determine that the area corresponding to the position point whose height parameter is less than the height threshold is the crossable area;

[0023] The on-site video data is divided into multiple grid areas, and the grid areas including the cross-row area and the non-obstruction area are determined as candidate areas. The preferred areas in the candidate areas are connected to obtain a reference path from the real-time location of the current user to the target location of the abnormal user and send it to the display device of the current user.

[0024] Optionally, in a possible implementation of the first aspect, dividing the live video data into a plurality of grid areas includes:

[0025] Dividing the live video data into a plurality of initial grid areas according to initial specifications;

[0026] Obtaining an initial area ratio of an obstacle area in each of the grid areas, and determining a grid area having an area ratio greater than a ratio threshold as a high-density area;

[0027] Dividing the high-density area into four equal parts to form a plurality of sub-areas;

[0028] Calculate the area proportion of each sub-region again. If there is still a sub-region whose area proportion exceeds the proportion threshold, continue to divide the sub-region into four equal parts until the area proportion of all sub-regions is less than the proportion threshold.

[0029] Optionally, in a possible implementation of the first aspect, determining a grid area including a crossable area and a non-obstruction area as a candidate area, connecting preferred areas among the candidate areas, obtaining a reference path from the current user's real-time location to the target location of the abnormal user, and sending the reference path to the current user's display device includes:

[0030] determining a straight line direction from the real-time position to the target position;

[0031] Obtaining an angle between a direction from the real-time position to a center point of each candidate area and the direction of the straight line, and determining a candidate grade of each candidate area based on a correspondence between an angle interval and a candidate grade, wherein the angle interval and the candidate grade are inversely proportional;

[0032] sequentially determining the candidate area with the highest candidate level among the adjacent candidate areas in the straight line direction as the preferred area, and recording the number of turning points;

[0033] When the number of turning points is greater than the number threshold and the candidate levels of adjacent candidate areas are all less than the level threshold, backtrack to the previous turning point, redetermine the preferred area and connect them, and obtain the reference path and send it to the display device of the current user.

[0034] Optionally, in a possible implementation of the first aspect, sequentially determining the candidate area with the highest candidate level among the adjacent candidate areas in the straight line direction as the preferred area, and recording the number of turning points, includes:

[0035] When determining the preferred area, if there are multiple candidate areas with the same candidate level, the candidate area with the smallest angle is selected as the preferred area;

[0036] The angle between the newly selected preferred area and the straight line direction is obtained. When the angle is greater than the angle threshold, the number of turns is recorded as one.

[0037] Optionally, in a possible implementation of the first aspect, determining the turning point and redetermining the preferred area through the following steps include:

[0038] Determine the previous preferred area when the last turning number was recorded as the turning node;

[0039] The remaining candidate areas adjacent to the turning point are traversed again to determine that the candidate area with the highest candidate level, excluding the candidate areas with recorded turning times, is the preferred area.

[0040] Optionally, in a possible implementation of the first aspect, obtaining on-site video data of the monitoring device through the following steps includes:

[0041] Determine that the users whose real-time locations are smaller than the monitoring distance are in the same monitoring group;

[0042] Controlling each of the monitoring devices to go to the center of each of the monitoring groups to shoot video, and obtaining on-site video data collected by each of the monitoring devices;

[0043] When the monitoring group changes, the monitoring devices are reallocated and each monitoring device is controlled to shoot a video of the monitoring group closest to it.

[0044] A second aspect of the present invention provides a law enforcement audio and video data analysis and transmission platform, comprising:

[0045] A receiving module, used for receiving law enforcement video data of each user in real time based on wireless communication;

[0046] A display module is used to generate display data based on the real-time location of each user and the law enforcement video data and transmit it to the display device of each user, wherein the display device is provided with two windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users;

[0047] a determination module, configured to determine the display points of the real-time locations of the remaining users on the regional layout map when determining the display data, group the display points whose distance is less than a distance threshold into the same display group, and obtain the display data based on the corresponding number of videos and video similarity;

[0048] The guidance module is used to determine the target location of the abnormal user, determine the distribution information and height parameters of the obstacles based on the on-site video data of the monitoring equipment, and generate a reference path for wireless transmission to the display devices of the remaining users.

[0049] The beneficial effects of the present invention are as follows:

[0050] 1. This invention receives real-time law enforcement video data from each law enforcement officer, combines it with their real-time location, and generates display data, which is then transmitted to each user's display device. This significantly improves the efficiency and quality of information acquisition for law enforcement officers, enables efficient information sharing and collaborative work among law enforcement officers, breaks down information barriers, and significantly enhances the effectiveness of collaborative law enforcement.

[0051] 2. After determining the target location of an abnormal user, the present invention uses drones to collect on-site video data and plan a route by analyzing obstacle distribution information and obstacle height parameters. This allows law enforcement officers to quickly and safely avoid obstacles and reach the target location along the optimal path, effectively improving the emergency response speed and handling efficiency of law enforcement operations and significantly reducing time wasted due to inappropriate path selection.

[0052] 3. The present invention reasonably groups law enforcement personnel into monitoring groups by setting monitoring distances, and controls the monitoring equipment to accurately go to the center of each monitoring group to shoot videos, which can ensure that comprehensive and complete on-site video data is collected. When the monitoring group changes due to factors such as personnel movement during the law enforcement process, the monitoring equipment can be quickly reallocated to shoot the nearest monitoring group. This greatly improves the efficiency of monitoring equipment use and avoids waste of resources. The collected video data can reflect the actual situation at the law enforcement scene in real time and accurately, providing reliable and timely information support for law enforcement command and decision-making, and helping law enforcement work to proceed smoothly. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flow chart of a method for analyzing and transmitting law enforcement audio and video data provided by an embodiment of the present invention;

[0054] Figure 2 This is display data corresponding to user A provided in an embodiment of the present invention;

[0055] Figure 3 It is a structural diagram of a law enforcement audio and video data analysis and transmission platform provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0057] The present invention can achieve real-time data collection, efficient processing, and accurate display during law enforcement in complex scenarios, such as busy and crowded markets, ensuring information sharing and collaborative work among law enforcement officers. In such scenarios, where there are dense crowds, numerous stalls, and a complex and changing environment, to achieve information sharing and collaborative work among law enforcement officers, each officer can view the video data of other officers. If an anomaly occurs at a particular officer's location, the remaining officers can quickly plan a path to that location based on the distribution of obstacles in the scene, enabling efficient information sharing among law enforcement officers and improving collaborative efficiency.

[0058] See also Figure 1 , is a flow chart of a method for analyzing and transmitting law enforcement audio and video data provided by an embodiment of the present invention, Figure 1 The execution subject of the method shown may be a software and / or hardware device. The execution subject of the present application may include but is not limited to at least one of the following: user equipment, network equipment, etc. Among them, the user equipment may include but is not limited to computers, smart phones, personal digital assistants (PDAs) and the electronic devices mentioned above. Network equipment may include but is not limited to a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers, wherein cloud computing is a type of distributed computing, a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. It includes steps S1 to S3, as follows:

[0059] S1, receives law enforcement video data from each user in real time based on wireless communication.

[0060] Law enforcement video data refers to on-site dynamic image data captured by law enforcement personnel through equipment such as law enforcement recorders when they are performing their duties. It contains visual information such as scene images and character movements.

[0061] It is understandable that the video data during the law enforcement process directly records the overall scene, personnel behavior and other important situations. Obtaining this data in a timely manner will help law enforcement personnel share on-site information and achieve efficient collaborative work.

[0062] S2, generating display data based on the real-time location of each user and the law enforcement video data and transmitting it to the display device of each user, wherein the display device is provided with dual windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users.

[0063] Combining law enforcement video data with the user's real-time location to generate display data allows law enforcement officers to more comprehensively and intuitively grasp the overall situation at the scene and view the specific locations and on-site conditions of their colleagues. The dual-window display mode allows law enforcement officers to view the actual situation at their own location while also referencing the on-site conditions of other personnel, facilitating collaboration, breaking down information barriers, and improving collaborative efficiency.

[0064] Display data is obtained by integrating other officers' law enforcement video data with their location information, and then displaying it on the officer's display device. The display device is a VR device equipped with dual-window functionality. Actual data refers to the live footage viewed by officers through the display device's window, allowing them to intuitively grasp the real-time context of their surroundings.

[0065] For example, during a comprehensive law enforcement operation at a market, numerous law enforcement officers are deployed across different areas of the market. The cloud server captures the real-time location and enforcement video data transmitted by each officer's terminal device. After binding each officer's video data with their location information, it generates display data. This display data is then transmitted to the VR device worn by each officer. One window on the VR device displays a live view of the officer, including the trading status of their stall and the surrounding environment. Another window displays their enforcement video footage superimposed on the other officers' locations, against a backdrop of the market layout. By operating the VR device, officers can freely switch between viewing videos of officers in different locations, achieving comprehensive monitoring of the entire market scene.

[0066] In some embodiments, the display data corresponding to each user may be generated according to the following steps, including:

[0067] Determine the display points of the real-time locations of the remaining users on the regional layout map; divide the display points whose distance is less than the distance threshold into the same display group, and determine whether the display attribute is a single attribute or a combined attribute based on the corresponding number of videos and video similarity; based on the center point of the display group of the single attribute as a reference, generate a single number of first areas and display the law enforcement video data to obtain display data; or, based on the center point of the display group of the combined attribute as a reference, generate a combined number of second areas and display the law enforcement video data to obtain display data.

[0068] The regional layout map details the site structure, stall layout, and road layout. Display points are specific locations marked on the regional layout map based on the real-time location of law enforcement officers. For example, during a law enforcement operation for a large-scale promotional event at a market, four law enforcement officers were deployed to patrol and maintain order in different areas of the market. The cloud server can obtain real-time location information transmitted by each law enforcement officer's terminal device. For each law enforcement officer, the display points of the remaining three officers, excluding the current officer, can be marked on the market regional layout map.

[0069] The distance threshold is a manually set distance standard for determining whether display points belong to the same group. When the distance between two display points is less than this threshold, they are assigned to the same display group. A display group is a collection of display points whose distance is less than the distance threshold. Law enforcement officers in the same display group are relatively close in space. For example, if the distance threshold is set to 10 meters, for user A, the display points of users B, C, and D can be analyzed. If no other display points are close to user B's display point, this display point can be assigned to display group A. If the distance between the display points of users C and D is less than 10 meters, these two display points are assigned to the same display group B.

[0070] The number of videos is the number of law enforcement video data collected by the law enforcement personnel included in the display group. Video similarity is the degree of similarity in content between the law enforcement video data in the display group, which can be calculated using algorithms such as image recognition and content analysis. A single attribute is a display attribute determined when the number of videos in the display group is small or the video similarity is high, which means that the law enforcement video data in the group has high consistency or similarity. A combined attribute is a display attribute determined when the number of videos in the display group is large and the video similarity is low, which indicates that the law enforcement video data in the group are quite different. In some embodiments, the display attributes of the display group can be determined by the following steps:

[0071] Determine that a display group whose number of videos is equal to a single number corresponds to a single attribute; for a display group whose number of videos is greater than a single number, obtain the video similarity of each of the law enforcement video data in the display group; when the video similarity is greater than a similarity threshold, determine its corresponding single attribute, and select any one of the law enforcement video data for display; when the video similarity is less than the similarity threshold, determine its corresponding combined attribute, and determine the number of videos as the combined number.

[0072] The "Single Quantity" is the number of display areas generated when the display group is a single attribute, typically one, for centrally displaying the law enforcement video data within that group. The "Combination Quantity" is the number of display areas generated when the display group is a combination attribute, typically equal to the number of videos within the group, for separately displaying the different law enforcement video data within the group. The "Similarity Threshold" is a manually set standard value for determining video similarity. When the video similarity of a display group exceeds this value, the display group is determined to be a single attribute; when it is less than this value, it is determined to be a combination attribute.

[0073] Understandably, the quantity and content of law enforcement video data within each display group vary. A unified presentation method can easily lead to information redundancy or omission of key information. By clarifying the rules for determining display group attributes, the appropriate presentation method can be selected based on the number and similarity of videos. Similar videos can be displayed collectively to reduce the interference of duplicate information; videos with significant differences can be displayed separately to ensure comprehensive information presentation, thereby improving the efficiency and quality of information obtained by law enforcement personnel and enhancing collaborative law enforcement effectiveness.

[0074] For example, for display group A, which contains one law enforcement officer and has one video, we can directly determine that display group A corresponds to a single attribute. Display group B has two law enforcement officers and has two videos. The calculated video similarity is less than the preset similarity threshold, so we determine that display group B corresponds to a combination of attributes, and the number of combinations is 2.

[0075] The first area is a display area generated based on the center point of a single attribute display group, and is used to display the law enforcement video data in the group. The second area is multiple display areas generated based on the center point of a combined attribute display group, and each area corresponds to a law enforcement video data in the display group.

[0076] For example, see Figure 2 , which is display data corresponding to user A, provided in an embodiment of the present invention. For display group A, which has a single attribute, a first area containing one display window is generated with the center point of display group A as the reference. For display group B, which has a combined attribute, a second area containing two display windows is generated with the center point of display group B as the reference. The display data generated using the first and second areas, as well as the location information of each user, can be transmitted to user A's VR device. When viewing the data through the VR device, user A can clearly understand the video display status of each display group and switch between them as needed.

[0077] This approach allows for precise identification of display group attributes, preventing information clutter caused by repeated display of similar videos and preventing the loss of key information from uniformly displaying significantly different videos. This allows law enforcement officers to quickly focus on effective information and improve information acquisition efficiency. It also allows law enforcement officers to more clearly and comprehensively understand the law enforcement activities of their colleagues. When handling emergencies, they can quickly determine support directions and strategies based on the displayed data, enhancing coordination and cooperation among law enforcement officers and improving overall law enforcement efficiency.

[0078] S3, determine the target location of the abnormal user, determine the distribution information and height parameters of the obstacles based on the on-site video data of the monitoring device, and generate a reference path and wirelessly transmit it to the display devices of the remaining users.

[0079] When encountering abnormal situations during law enforcement, such as law enforcement officers encountering obstacles or needing to deal with emergencies urgently, accurately determining the target location and planning a reference path to avoid obstacles can help other law enforcement officers arrive at the scene quickly and safely, improve the emergency response capabilities and handling efficiency of law enforcement actions, and ensure the safety of law enforcement officers and the smooth completion of law enforcement tasks.

[0080] Abnormal users are law enforcement officers who encounter special circumstances during market enforcement and require support from other law enforcement officers or need to travel to a specific target location. The target location is the designated location where the abnormal user is located. The monitoring equipment is a drone equipped with a high-resolution camera, lidar, and other equipment, which is used to collect video data from the market site and obtain environmental information. On-site video data is dynamic video information of the law enforcement scene collected by the drone, including the on-site environment, objects, and other conditions. Obstacle distribution information is information such as the spatial location of obstacles such as stalls and crowds determined by analyzing on-site video data. The height parameter is the vertical height value of the obstacle. The reference path is a feasible route planned from the current location of the remaining users to the target location of the abnormal user based on the on-site conditions, providing navigation guidance for law enforcement officers.

[0081] Understandably, markets are densely populated, with numerous stalls arranged irregularly, and narrow, winding roads. Knowing only the target location without understanding the distribution and height of obstacles can lead law enforcement officers to find themselves with nowhere to go or risk traversing dangerous areas. For example, makeshift stalls can block access to the road. If officers, unaware of their distribution, blindly proceed to their target location, potentially blocking their path and delaying enforcement. Understanding the height of obstacles can help determine whether they are surmountable. For example, if the target location is blocked by a row of low-rise stalls, officers can bypass them if they can determine that these stalls are surmountable, avoiding the long, surrounding passages. By accurately identifying surmountable obstacles, route restrictions can be effectively overcome, shortening the physical distance to the target location, optimizing routes, and improving traffic efficiency.

[0082] Based on the above embodiment, the specific implementation of step S3 may be:

[0083] S31 , obtaining the distribution information according to the obstacle area in the on-site video data whose pixel values ​​are not within a preset pixel interval.

[0084] In order to accurately understand the distribution of obstacles on site and subsequently plan a safe and feasible path, the location, shape and other distribution information of the obstacle area can be determined by analyzing the range of pixel values ​​in the on-site video data.

[0085] The preset pixel interval is a pre-set range of pixel values ​​corresponding to the road, which serves as a reference standard for determining whether an obstacle zone is present. An obstacle zone is defined as an area in the on-site video data where the pixel values ​​are outside the corresponding road pixel value range. This area is likely to contain objects or conditions that could obstruct the passage of law enforcement officers.

[0086] It can be understood that using the pixel values ​​corresponding to the road as the preset pixel interval to determine the distribution information of the obstacle area can more specifically identify areas that may affect the passage of law enforcement personnel.

[0087] S32, obtaining the height parameters of each position point in the obstacle area, and determining that the area corresponding to the position point whose height parameter is less than the height threshold is a crossable area.

[0088] Within a defined obstacle zone, the height parameters of each location are obtained and compared with the height threshold to determine the crossable area. This is to create a relatively safe and feasible passage area for law enforcement officers in complex obstacle environments. This can minimize detours while ensuring the safety of law enforcement officers, improve the efficiency of law enforcement operations, and enable law enforcement officers to respond more flexibly to on-site situations.

[0089] The height threshold is a manually set height standard used to determine whether the area corresponding to a location point can be crossed by law enforcement officers. The crossable area is the area within the obstacle area corresponding to the location point whose height parameter is less than the height threshold.

[0090] In practical applications, drones equipped with LiDAR (LiDAR) technology can be used to scan locations within a defined obstacle zone. The LiDAR emits a laser beam and measures the time delay of the reflected light, thereby determining the height of objects at each location.

[0091] Clearly defining crossable zones allows law enforcement officers to accurately determine which areas are safe to cross when faced with obstacles, avoiding the dangers of blindly attempting to cross over high obstacles. Furthermore, the rational use of crossable zones can optimize law enforcement routes, reduce unnecessary detours, and improve the speed and efficiency of law enforcement operations, helping officers reach their target locations more quickly and complete their enforcement tasks.

[0092] S33, divide the on-site video data into multiple grid areas, determine the grid area containing the cross-row area and the non-obstruction area as the candidate area, connect the preferred areas in the candidate area, obtain the reference path from the real-time position of the current user to the target position of the abnormal user, and send it to the display device of the current user.

[0093] Grid regions are small areas divided into specific patterns and sizes by dividing the on-site video data. This facilitates detailed analysis and processing of the scene, with each grid region representing a local area. Non-obstruction zones are areas within the law enforcement scene where traffic is freely accessible. Candidate zones are grid regions that include both crossable and non-obstruction zones. These areas are considered potential candidates for forming part of the path. Preferred zones are selected from the candidate regions as being more suitable for forming part of the final path. These preferred zones are connected to form a complete reference path.

[0094] Dividing on-site video data into multiple grid areas, further identifying candidate and preferred areas, and ultimately generating a reference path is intended to simplify and structure the complex on-site environment, allowing for more efficient planning of feasible routes from the current law enforcement officer's location to the target location of the abnormal user. This generated reference path provides law enforcement officers with clear navigation guidance, enabling them to reach their destination quickly and accurately, improving the accuracy and efficiency of law enforcement operations.

[0095] In some embodiments, the live video data may be divided into a plurality of grid areas by the following steps, including:

[0096] The on-site video data is divided into a plurality of initial grid areas according to the initial specifications; the area ratio of the obstacle area in each of the initial grid areas is obtained, and the grid area whose area ratio is greater than the ratio threshold is determined to be a high-density area; the high-density area is divided into four equal parts to form a plurality of sub-areas; the area ratio of each sub-area is calculated again, and if there is still a sub-area whose area ratio exceeds the ratio threshold, the sub-area is continued to be divided into four equal parts until the area ratio of all sub-areas is less than the ratio threshold.

[0097] Dividing live video data into multiple initial grid regions allows for preliminary structural processing of complex live environments, facilitating detailed analysis of each region and understanding the situation within each area. Initial specifications are pre-set criteria for dividing the grid regions, such as the size and shape of each grid region, such as a rectangle, which determine the basic characteristics of the initial grid regions.

[0098] By calculating the area ratio of the obstacle zone in each initial grid area and identifying high-density areas, we can identify areas with a relatively dense distribution of obstacles. These areas require special attention in route planning because they may have a significant impact on the passage of law enforcement officers. By identifying high-density areas and performing more detailed processing on these areas, we can ensure that the planned path can avoid or reasonably pass through these complex areas. The area ratio is the ratio of the area of ​​the obstacle zone to the total area of ​​each initial grid area, which reflects the density of obstacles in the grid area. The ratio threshold is an artificially set ratio standard used to determine whether a grid area is a high-density area. When the area ratio of a grid area is greater than this threshold, it is determined to be a high-density area. High-density areas are areas where obstacles are relatively densely distributed.

[0099] By dividing high-density areas into multiple sub-areas, we can more carefully analyze the obstacle distribution and traffic conditions within each sub-area. We then recalculate the area proportions of the sub-areas and further divide those sub-areas that exceed the threshold into four equal parts. This allows us to continuously refine the high-density area divisions until the obstacle density in all sub-areas is within an acceptable range. This ensures that the situation in each area is accurately assessed and addressed during path planning, preventing areas with excessively dense obstacles from affecting the rationality and safety of the path.

[0100] For example, when the high-density area is rectangular, it can be divided into multiple smaller rectangular areas by continuously quartering it. Each sub-area contains a part of the scene of the original high-density area, making the analysis of the area more detailed and able to more accurately understand the obstacle distribution of each part.

[0101] In some embodiments, step S33 of "determining a grid area including a crossable area and a non-obstructed area as a candidate area, connecting preferred areas among the candidate areas, obtaining a reference path from the current user's real-time location to the target location of the abnormal user, and sending the reference path to the display device of the current user" can be implemented by the following steps:

[0102] S331, determining the direction of a straight line from the real-time position to the target position.

[0103] Determining the direction of a straight line from the officer's real-time location to the target location provides a basic guide for subsequent path planning. In complex law enforcement environments, clarifying the straight line direction helps the planned path extend as close to the target location as possible, preventing the path from straying too far from the target. This improves the efficiency and accuracy of path planning, allowing officers to reach the target location more quickly.

[0104] S332, obtaining the angle between the direction from the real-time position to the center point of each candidate area and the straight line direction, and determining the candidate level of each candidate area according to the corresponding relationship between the angle interval and the candidate level, wherein the angle interval and the candidate level are inversely proportional.

[0105] By calculating the angle between the real-time location and the direction of the line to the center point of each candidate area, and then determining the candidate level based on the angle range, the candidate areas can be prioritized. Candidate areas with smaller angles are closer to the line direction and more conducive to extending the path toward the target location. These areas are assigned higher candidate levels, making them easier to select during path planning, making the planned path closer to the line direction and improving path efficiency and rationality.

[0106] The angle intervals are pre-defined ranges based on the angle size, such as ±15° for one interval and ±15°-±45° for another. The candidate level is the priority assigned to the candidate area based on the angle interval. The angle interval and candidate level are inversely proportional, meaning that the smaller the angle, the higher the candidate level.

[0107] S333: sequentially determine the candidate area with the highest candidate level among the adjacent candidate areas in the straight line direction as the preferred area, and record the number of turning points.

[0108] The candidate with the highest ranking among the adjacent candidate areas along the straight line is selected as the preferred area. This ensures that the path, as it extends toward the target location, chooses the area closest to the straight line as much as possible, making the path more direct and efficient. The number of turns is recorded to evaluate and optimize the path. Excessive turns may indicate that the path is not ideal and requires adjustment.

[0109] The number of turns is the number of times the path direction changes during the path planning process. Recording the number of turns helps to evaluate the tortuosity of the path.

[0110] In some embodiments, the preferred area can be determined and the number of turns can be recorded by the following steps:

[0111] When determining the preferred area, when there are multiple candidate areas with the same candidate level, the candidate area with the smallest angle is selected as the preferred area; the angle between the newly selected preferred area and the straight line direction is obtained, and when the angle is greater than the angle threshold, the number of turns is recorded as 1.

[0112] When selecting the preferred zone, if multiple candidate zones with the same rank appear, the zone with the smallest angle to the straight line is selected. This optimizes path planning, ensuring the path follows the straight line as closely as possible, given the same rank. This reduces path curvature and improves efficiency, allowing officers to reach their target location more quickly and avoiding a longer or more complex path caused by selecting a zone with a significant deviation from the straight line.

[0113] Obtaining the angle between the newly selected preferred area and the straight line direction and recording the number of turns when the angle exceeds the angle threshold allows quantification and monitoring of path turns. During path planning, excessive turns can lead to path complexity and inefficiency. By recording the number of turns, subsequent path evaluation and optimization can determine whether the path needs adjustment.

[0114] The angle threshold is a pre-set angle standard. When the angle is greater than this threshold, it is considered that the path has turned.

[0115] For example, during an enforcement operation, candidate area A has been selected as the preferred area and connected to the current path. The angle between the line connecting the center point of candidate area A and the enforcement officer's real-time location and the straight line is calculated to be 8°. Assuming the angle threshold is set to 10°, since 8° is less than 10°, no turning count is recorded. Then, during the next selection of the preferred area, candidate area D is selected. The angle between the line connecting the center point of candidate area D and the enforcement officer's real-time location and the straight line is calculated to be 15°. Since 15° is greater than 10°, one turning count is recorded, and the turning count is increased by one.

[0116] S334, when the number of turning points is greater than the number threshold and the candidate levels of adjacent candidate areas are all less than the level threshold, backtrack to the previous turning point, re-determine the preferred area and connect it, and obtain the reference path and send it to the display device of the current user.

[0117] When the number of turns exceeds the threshold and the candidate levels of adjacent candidate areas are all below the threshold, the current route plan may be too tortuous and lack suitable high-level candidate areas. By backtracking to the previous turning point and re-determining the preferred area, a more optimal path can be found, avoiding overly complex and inefficient routes. The resulting reference path is sent to the current user's display device, providing navigation guidance for law enforcement officers, allowing them to follow the planned path to the target location.

[0118] The number threshold is a pre-set criterion for the number of turns. When the number of turns on a path exceeds this threshold, the path is considered to require adjustment. The level threshold is a pre-set candidate level. When the candidate levels of adjacent candidate areas are all below this threshold, it is considered that there are no suitable high-priority candidate areas to choose from. Turning nodes are key locations where a path changes direction during extension and are the starting points for path adjustments.

[0119] In some embodiments, the turning point can be determined and the preferred area can be re-determined by the following steps, including:

[0120] The previous preferred area when the number of turning points was recorded last time is determined as the turning node; the remaining candidate areas adjacent to the turning node are traversed again to determine the candidate area with the highest candidate level, excluding the candidate area with the number of turning points recorded, as the preferred area.

[0121] It's understandable that identifying the previous preferred zone as the turning point, when the last turning count was recorded, is intended to identify the starting point of the path's turn, allowing for replanning the path from this location to avoid continuing along the original, irrational path. By identifying the turning point, the path planning process can be retraced to a relatively reasonable state, providing a basis for reselecting the preferred zone.

[0122] After determining a turning point, the remaining candidate areas adjacent to that node are retraversed to find a more appropriate path extension direction at that location. Candidate areas with a recorded number of turning points are excluded because they cause the path to turn and may not be the optimal choice. The area with the highest candidate ranking is selected as the preferred area to select an area that is closest to the straight line direction and more conducive to path optimization at the current location, making the replanned path more reasonable and efficient. This avoids repeated selection of candidate areas that may lead to unreasonable paths and improves path planning quality.

[0123] The above method can help reduce the number of turns in the route, improve the efficiency of the route, and enable law enforcement personnel to reach the target location more smoothly.

[0124] In addition, in some embodiments, the on-site video data of the monitoring device may be obtained by the following steps, including:

[0125] Determine that the users whose real-time positions are smaller than the monitoring distance are in the same monitoring group; control each monitoring device to go to the center position of each monitoring group to shoot video, and obtain the on-site video data collected by each monitoring device; when the monitoring group changes, reallocate the monitoring devices and control each monitoring device to shoot video of the monitoring group closest to it.

[0126] By grouping users whose real-time locations are closer than the monitoring distance into the same monitoring group, users at the law enforcement site can be rationally grouped and managed, allowing for more efficient use of monitoring equipment for video data collection. This grouping ensures that monitoring equipment can focus on law enforcement personnel within a certain range, improving monitoring efficiency and avoiding wasted monitoring equipment resources. It also makes the collected video data more targeted, reflecting the law enforcement situation within a specific area.

[0127] The monitoring distance is a pre-set distance used to determine whether law enforcement officers belong to the same monitoring group. When the distance between two law enforcement officers' real-time locations is less than this monitoring distance, they are classified as the same group. A monitoring group is a group of law enforcement officers whose real-time locations are less than the monitoring distance and is the target group for video capture by the monitoring equipment.

[0128] Controlling monitoring equipment to capture video from the center of the monitoring group ensures maximum coverage of the group's law enforcement officers and the scene, capturing comprehensive and accurate on-site video data. The center of the monitoring group provides a good view of the positions of all officers within the group. Shooting from this position reduces blind spots and improves the integrity of the video data.

[0129] When the monitoring group changes, for example, law enforcement officers move out of the original monitoring group or new law enforcement officers join, the monitoring equipment can be reallocated and allowed to shoot video of the nearest monitoring group. This can adapt to the dynamic changes at the law enforcement scene and ensure that the monitoring equipment can always effectively monitor the law enforcement officers.

[0130] For example, if law enforcement officer A moves to a different area due to a mission, the original monitoring group will change. The system detects the change and recalculates the distances between each monitoring device and the newly formed monitoring group. Suppose the drone's current location is closer to the newly formed monitoring group X and farther from monitoring group Y. The drone is reassigned and directed to the center of monitoring group X to capture video footage, capturing on-site law enforcement data in the area where monitoring group X resides.

[0131] Through the above methods, the monitoring equipment can adapt to the dynamic changes of the law enforcement scene in a timely manner to ensure the continuity and effectiveness of monitoring.

[0132] See also Figure 3 , is a schematic diagram of the structure of a law enforcement audio and video data analysis and transmission platform provided by an embodiment of the present invention, the law enforcement audio and video data analysis and transmission platform comprising:

[0133] A receiving module, used for receiving law enforcement video data of each user in real time based on wireless communication;

[0134] A display module is used to generate display data based on the real-time location of each user and the law enforcement video data and transmit it to the display device of each user, wherein the display device is provided with two windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users;

[0135] a determination module, configured to determine the display points of the real-time locations of the remaining users on the regional layout map when determining the display data, group the display points whose distance is less than a distance threshold into the same display group, and obtain the display data based on the corresponding number of videos and video similarity;

[0136] The guidance module is used to determine the target location of the abnormal user, determine the distribution information and height parameters of the obstacles based on the on-site video data of the monitoring equipment, and generate a reference path for wireless transmission to the display devices of the remaining users.

[0137] Figure 3 The apparatus of the embodiment shown can be used to perform Figure 1 The implementation principles and technical effects of the steps in the method embodiment shown are similar and will not be repeated here.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing and transmitting law enforcement audio and video data, characterized in that: include: Receive law enforcement video data from each user in real time based on wireless communication; Generate display data based on the real-time location of each user and the law enforcement video data and transmit it to the display device of each user, wherein the display device is provided with two windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users; Generate display data corresponding to each user according to the following steps, including: Determine the display points of the real-time locations of the remaining users on the regional layout map; The display points whose distance is less than the distance threshold are divided into the same display group, and the display attribute is determined to be a single attribute or a combination of attributes based on the number of corresponding videos and video similarity; Taking the center point of the display group of the single attribute as a reference, generating a single number of first areas and displaying the law enforcement video data to obtain display data; or, Taking the center point of the display group of the combined attributes as a reference, generating a combined number of second areas and displaying the law enforcement video data to obtain display data; Determine the target location of abnormal users, determine the distribution information and height parameters of obstacles based on the on-site video data of the monitoring equipment, and generate a reference path for wireless transmission to the display devices of other users, including: Obtaining the distribution information based on an obstacle area in the on-site video data whose pixel values ​​are not within a preset pixel interval; Acquire the height parameters of each position point in the obstacle area, and determine that the area corresponding to the position point whose height parameter is less than the height threshold is the crossable area; The on-site video data is divided into multiple grid areas, and the grid areas including the cross-row area and the non-obstruction area are determined as candidate areas. The preferred areas in the candidate areas are connected to obtain a reference path from the real-time location of the current user to the target location of the abnormal user and send it to the display device of the current user.

2. The method according to claim 1, characterized in that Display points with distances less than the distance threshold are divided into the same display group. Based on the number of corresponding videos and video similarity, the display attributes are determined as a single attribute or a combination of attributes, including: Determine that the number of videos is equal to a single number of display groups corresponding to a single attribute; For a display group with more videos than a single video, obtaining the video similarity of each of the law enforcement video data in the display group, and when the video similarity is greater than a similarity threshold, determining the corresponding single attribute, and selecting any one of the law enforcement video data for display; When the video similarity is less than a similarity threshold, the corresponding combination attribute is determined, and the number of videos is determined as the number of combinations.

3. The method according to claim 1, characterized in that Dividing the live video data into a plurality of grid areas includes: Dividing the live video data into a plurality of initial grid areas according to initial specifications; Obtaining an initial area ratio of an obstacle area in each of the grid areas, and determining a grid area having an area ratio greater than a ratio threshold as a high-density area; Dividing the high-density area into four equal parts to form a plurality of sub-areas; Calculate the area proportion of each sub-region again. If there is still a sub-region whose area proportion exceeds the proportion threshold, continue to divide the sub-region into four equal parts until the area proportion of all sub-regions is less than the proportion threshold.

4. The method according to claim 1, wherein Determining a grid area including a crossable area and a non-obstructed area as a candidate area, connecting preferred areas in the candidate area, obtaining a reference path from the current user's real-time location to the target location of the abnormal user, and sending the reference path to the current user's display device, including: determining a straight line direction from the real-time position to the target position; Obtaining an angle between a direction from the real-time position to a center point of each candidate area and the direction of the straight line, and determining a candidate grade of each candidate area based on a correspondence between an angle interval and a candidate grade, wherein the angle interval and the candidate grade are inversely proportional; sequentially determining the candidate area with the highest candidate level among the adjacent candidate areas in the straight line direction as the preferred area, and recording the number of turning points; When the number of turning points is greater than the number threshold and the candidate levels of adjacent candidate areas are all less than the level threshold, backtrack to the previous turning point, redetermine the preferred area and connect them, and obtain the reference path and send it to the display device of the current user.

5. The method according to claim 4, characterized in that The candidate area with the highest candidate level among the adjacent candidate areas in the straight line direction is sequentially determined as the preferred area, and the number of turning points is recorded, including: When determining the preferred area, if there are multiple candidate areas with the same candidate level, the candidate area with the smallest angle is selected as the preferred area; The angle between the newly selected preferred area and the straight line direction is obtained. When the angle is greater than the angle threshold, the number of turns is recorded as one.

6. The method according to claim 4, characterized in that The following steps are used to determine the turning point and redefine the optimal area, including: Determine the previous preferred area when the last turning number was recorded as the turning node; The remaining candidate areas adjacent to the turning point are traversed again to determine that the candidate area with the highest candidate level, excluding the candidate areas with recorded turning times, is the preferred area.

7. The method according to claim 1, characterized in that The following steps are used to obtain on-site video data from monitoring equipment: Determine that the users whose real-time locations are smaller than the monitoring distance are in the same monitoring group; Controlling each of the monitoring devices to go to the center of each of the monitoring groups to shoot video, and obtaining on-site video data collected by each of the monitoring devices; When the monitoring group changes, the monitoring devices are reallocated and each monitoring device is controlled to shoot a video of the monitoring group closest to it.

8. A law enforcement audio and video data analysis and transmission platform using the law enforcement audio and video data analysis and transmission method according to claim 1, characterized in that: include: A receiving module, used for receiving law enforcement video data of each user in real time based on wireless communication; A display module is used to generate display data based on the real-time location of each user and the law enforcement video data and transmit it to the display device of each user, wherein the display device is provided with two windows, one for displaying the actual data and the other for display data associated with the real-time location of the remaining users; The guidance module is used to determine the target location of the abnormal user, determine the distribution information and height parameters of the obstacles based on the on-site video data of the monitoring equipment, and generate a reference path for wireless transmission to the display devices of the remaining users.

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