Vehicle remote alarm method, device and equipment and storage medium

Abstract

The invention discloses a vehicle remote alarm method, device and equipment and a storage medium, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining vehicle filtering environment data, carrying out the personnel approaching detection based on the vehicle filtering environment data, and determining a personnel approaching state; detecting a target person based on the vehicle filtering environment data and the person approaching state to determine a traffic police sticking strip state; and carrying out notification distribution on the state of the traffic police sticker to complete vehicle remote alarm, wherein the notification distribution comprises application push distribution, short message push distribution and telephone push distribution. According to the invention, radar, laser radar and camera data are integrated to obtain vehicle filtering environment data, personnel approaching detection is carried out, and a deep learning algorithm is utilized to accurately identify a traffic police sticking strip state, so that a vehicle owner is notified in real time in a manner of application pushing, short message and telephone, fine caused by temporary parking is effectively avoided, and the service life of the vehicle owner is prolonged. And meanwhile, the vehicle parking safety is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a vehicle remote alarm method, device, equipment and storage medium. Background Art

[0002] With the increase in the popularity of cars, people's daily travel has been greatly facilitated. In some cases, Figure 1 People will choose to park temporarily on the roadside for convenience. However, this temporary parking sometimes occupies road resources and causes traffic disorder, especially when vehicles occupy the road for a long time, which will interfere with normal traffic order. In order to maintain traffic order, the traffic police department will take measures such as warning or issuing tickets to vehicles occupying road resources. If the owner fails to detect and remove the vehicle in time, he will face a fine. Therefore, the demand for real-time monitoring of vehicle status and timely warning of traffic police enforcement is growing, so as to reduce the penalties for temporary parking.

[0003] At present, the existing practice is to use a parking lot-based early warning detection system, which mainly relies on monitoring equipment in the parking lot to monitor the status of vehicles. When abnormal situations occur, it can actively warn. At the same time, there is also a sentinel function based on the vehicle itself, which mainly realizes the collection of anti-theft or safety accidents.

[0004] However, in existing practices, vehicles are usually not in standard parking lots, and the parking lot warning system relies on fixed monitoring facilities and cannot cover non-standard parking scenarios such as roadside parking. Therefore, the vehicle itself is required to complete the perception and warning function. The vehicle's own sentinel function is mainly to realize the collection of anti-theft or safety accidents. It lacks recognition of traffic police behavior and cannot provide warnings before traffic police issue tickets. Therefore, how to more effectively identify traffic police tickets and make remote alarms in time has become an urgent problem to be solved.

[0005] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0006] The main purpose of this application is to provide a vehicle remote alarm method, device, equipment and storage medium, aiming to solve the technical problem of how to more effectively identify traffic police tickets and make remote alarms in a timely manner.

[0007] To achieve the above purpose, the present application proposes a vehicle remote alarm method, the method comprising:

[0008] Acquire vehicle filtering environment data, and perform person approach detection based on the vehicle filtering environment data to determine the person approach status;

[0009] Detecting a target person based on the vehicle filtering environment data and the person approaching status to determine the traffic police ticketing status;

[0010] The traffic police ticket status is notified and distributed to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

[0011] In one embodiment, the step of obtaining vehicle filtering environment data includes:

[0012] Get radar data, lidar data, and camera video data;

[0013] Determining vehicle environment data based on the radar data, the lidar data, and the camera video data;

[0014] The vehicle environment data is filtered to determine vehicle filtered environment data.

[0015] In one embodiment, the step of performing human approach detection based on the vehicle filtering environment data and determining the human approach status comprises:

[0016] Acquire a person approaching perception algorithm;

[0017] Matching personnel characteristics based on the personnel approach perception algorithm and the vehicle filtering environment data to determine a matching result, wherein the personnel characteristics include target personnel size and target movement speed;

[0018] The person approaching status is obtained based on the matching result.

[0019] In one embodiment, the step of determining the traffic police ticket status based on the vehicle filtering environment data and the person approaching status detecting the target person includes:

[0020] Get the deep learning model;

[0021] Identify the vehicle filtering environment data based on the deep learning model to determine the image person target information;

[0022] Extracting the identity features of the traffic police based on the target information of the person in the image to perform identity recognition and determine the identity recognition status, wherein the identity features of the traffic police include uniform features and equipment features;

[0023] Extracting the traffic police action features based on the identity recognition state to perform ticket pasting action recognition and determine the ticket pasting behavior state, wherein the traffic police action features include typical ticket pasting actions, hand movements and dwell time;

[0024] The traffic police ticketing status is obtained based on the identity recognition status and the ticketing behavior status.

[0025] In one embodiment, the step of notifying and distributing the traffic police ticket status to complete the vehicle remote alarm includes:

[0026] Acquiring ticketing confirmation information based on the traffic police ticketing status;

[0027] Determine the emergency priority of the event based on the confirmation information of the posting behavior;

[0028] Generate warning notification content information based on the emergency priority of the event, the warning notification content information including time information, location information, event type information, warning screenshot information or video information;

[0029] The warning notification content information is packaged based on the emergency priority of the event and distributed to complete the vehicle remote alarm.

[0030] In one embodiment, the step of packaging the warning notification content information based on the emergency priority of the event for notification distribution to complete the vehicle remote alarm includes:

[0031] Obtain channel notification distribution methods, which include application push distribution, SMS push distribution, and phone push distribution;

[0032] Packaging the warning notification content information into standardized message format information;

[0033] The standardized message format information is notified and distributed based on the emergency priority of the event and the channel notification distribution method to complete the vehicle remote alarm.

[0034] In one embodiment, after the step of packaging the warning notification content information based on the emergency priority of the event for notification distribution to complete the vehicle remote alarm, the step further includes:

[0035] Obtaining an event details page and reconfirming the operation instruction, wherein the event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information, and event level visual prompt information;

[0036] Analyze the event behavior status based on the event details page to obtain feedback information, wherein the feedback information includes confirmation information, false alarm marking information, and ignored event information;

[0037] Based on the feedback information and the reconfirmation operation instruction, the vehicle-mounted sound and light warning is remotely activated to complete the vehicle remote alarm.

[0038] In addition, to achieve the above purpose, the present application also proposes a vehicle remote alarm device, the vehicle remote alarm device comprising:

[0039] An acquisition module, used to acquire vehicle filtering environment data, and perform personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status;

[0040] A processing module, configured to detect a target person based on the vehicle filtering environment data and the person approaching state and determine the state of the traffic police ticketing;

[0041] The execution module is used to notify and distribute the traffic police ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

[0042] In addition, to achieve the above objectives, the present application also proposes a vehicle remote alarm device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle remote alarm method described above.

[0043] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle remote alarm method described above are implemented.

[0044] One or more technical solutions proposed in this application have at least the following technical effects:

[0045] The present embodiment proposes a vehicle remote alarm method, which obtains vehicle filtering environment data, and performs human approach detection based on the vehicle filtering environment data to determine the human approach status; detects the target person based on the vehicle filtering environment data and the human approach status to determine the traffic police ticket status; and distributes the traffic police ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution, and phone push distribution. This application integrates radar, lidar, and camera data to obtain vehicle filtering environment data, performs human approach detection, and uses deep learning algorithms to accurately identify the traffic police ticket status, thereby notifying the owner in real time by application push, SMS, and phone, effectively avoiding fines due to temporary parking, while improving vehicle parking safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0048] Figure 1 A flowchart of the first embodiment of the vehicle remote alarm method of the present application is provided;

[0049] Figure 2 A flow chart of the second embodiment of the vehicle remote alarm method of the present application;

[0050] Figure 3 A schematic diagram of a brief process of a vehicle remote alarm method provided in an embodiment of the present application;

[0051] Figure 4 This is a schematic diagram of the module structure of the vehicle remote alarm device according to an embodiment of the present application;

[0052] Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the vehicle remote alarm method in the embodiment of the present application.

[0053] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0054] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0055] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0056] The main solution of the embodiment of the present application is: obtaining vehicle filtering environment data, and performing person approach detection based on the vehicle filtering environment data to determine the person approach status; detecting the target person based on the vehicle filtering environment data and the person approach status to determine the traffic police ticket status; and notifying and distributing the traffic police ticket status to complete vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and phone push distribution.

[0057] In this embodiment, for the convenience of description, the following description is made by taking the identification of the vehicle remote alarm device as the execution subject.

[0058] In the prior art, vehicles are usually not in standard parking lots, and the parking lot warning system relies on fixed monitoring facilities and cannot cover non-standard parking scenarios such as roadside parking. Therefore, the vehicle itself is required to complete the perception and warning function. The sentinel function of the vehicle itself is mainly to realize the collection of anti-theft or safety accidents, and lacks recognition of traffic police behavior, and cannot provide warnings before the traffic police issue tickets.

[0059] The present application provides a solution, which obtains vehicle filtering environment data, and performs human approach detection based on the vehicle filtering environment data to determine the human approach status; detects the target person based on the vehicle filtering environment data and the human approach status to determine the traffic police ticket status; and notifies and distributes the traffic police ticket status to complete vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and phone push distribution.

[0060] From the above embodiments, it can be seen that the present application integrates radar, lidar and camera data to obtain vehicle filtering environment data, performs human approach detection and uses deep learning algorithms to accurately identify the status of traffic police tickets, thereby notifying the car owner in real time via application push, SMS and phone calls, effectively avoiding fines caused by temporary parking, and improving vehicle parking safety.

[0061] Based on this, the embodiment of the present application provides a vehicle remote alarm method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle remote alarm method of the present application.

[0062] In this embodiment, the vehicle remote alarm method includes steps S10 to S30:

[0063] Step S10, acquiring vehicle filtering environment data, and performing personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status;

[0064] It should be noted that the vehicle filtering environment data reflects the characteristics of the real-time dynamic information of the vehicle surrounding environment after pre-processing, and the person approaching state reflects the characteristics of the dynamic behavior and position information of the person identified in the vehicle surrounding environment.

[0065] It can be understood that the environment detection module can be used to detect the environment around the vehicle and collect vehicle environment data. The environment detection module includes a camera, an ultrasonic sensor, a millimeter-wave radar, a lidar and a software algorithm. The software algorithm is a dynamic perception algorithm, that is, it analyzes the collected vehicle environment data and determines the proximity of people around the vehicle.

[0066] In addition, it should be noted that the vehicle filtered environment data can be obtained by intelligently filtering and analyzing the collected vehicle environment data. The vehicle filtered environment data may include obstacle locations, moving object speeds, moving object directions, and target personnel characteristics, thereby identifying whether there are people approaching the vehicle. This can reduce false alarms and missed alarms, provide more accurate environmental perception, and thus improve the accuracy of early warnings. By real-time monitoring of environmental changes around the vehicle, potential security threats can be discovered in a timely manner, such as intrusion or ticketing by others, thereby enhancing the safety of the vehicle. The vehicle owner can be notified through remote alarms, which helps the vehicle owner take timely measures to reduce fines caused by temporary parking.

[0067] For ease of understanding, the following description is made by taking the determination of a person's approaching state as an example, wherein the information collection device is an environment detection module, and the storage device is a memory.

[0068] When the environment detection module is in standby mode, the radar sensor will continue to work to detect obstacles in front and on the sides, and the camera will continue to capture and process road images. In order to reduce energy consumption, the camera will use low-power image sensors and image processing algorithms, and the lidar sensor will also be in a low-power working state to reduce energy consumption and improve system efficiency. If the system detects a potential threat, such as someone approaching the vehicle, the vehicle being touched and shaken, or the system detects changes in the external environment, such as changes in light or the appearance of moving objects, it will immediately switch from standby mode to active mode to capture and record related events, that is, trigger the awakening of the environment detection module to obtain radar data, lidar data and camera video data. The camera captures the target image and obtains clear video or pictures of the dynamic surroundings of the vehicle. The radar detects the distance, moving direction and speed of the target, and identifies whether it is a fast-moving object or a slow-moving object, such as a vehicle or pedestrian. The lidar can construct a 3D image of the surrounding environment by emitting a laser beam and receiving the reflected signal. Model, to achieve more accurate spatial perception, determine vehicle environmental data based on the radar data, the lidar data and the camera video data, that is, use an algorithm to fuse radar signals, lidar signals and camera videos to improve the accuracy of dynamic detection and avoid false alarms of a single sensor, such as leaves fluttering and animals passing by, filter the vehicle environmental data to determine vehicle filtered environmental data, that is, filter common environmental noise in various sensors, such as distant vehicles and wind-blown leaves, obtain a person approaching perception algorithm, such as setting a target moving speed threshold and matching the target size with the human body size, match person features based on the person approaching perception algorithm and the vehicle filtered environmental data, determine a matching result, and obtain a person approaching status based on the matching result, that is, when the matching result is a successful match, it is determined to be a person approaching event, and when the matching result is a failed match, it is determined to be no person approaching event, and continue to standby or monitor, thereby obtaining a person approaching status, and perform subsequent processing based on the vehicle filtered environmental data and the person approaching status.

[0069] In a feasible implementation, step S10 may include steps A11 to A13:

[0070] Step A11, acquiring radar data, lidar data and camera video data;

[0071] It should be noted that the radar data reflects the characteristics of the distance, speed and direction information of the target moving object relative to the radar, the lidar data reflects the characteristics of the position and shape of the target moving object relative to the lidar, and the camera video data reflects the characteristics of the dynamic information of the target moving object displayed by the camera.

[0072] It can be understood that the radar data can represent the information of the target objects detected around the vehicle, and the lidar data is distributed in multiple layers linearly, which can represent the precise three-dimensional position information of the object. The lidar data provides rich color and texture information for object classification and identification.

[0073] Step A12, determining vehicle environment data based on the radar data, the lidar data and the camera video data;

[0074] It should be noted that the vehicle environment data reflects the comprehensive information collected around the vehicle, which may include the location of obstacles, the speed of moving objects, the direction of moving objects and the characteristics of target personnel.

[0075] It is understandable that different sensors have their own advantages in different aspects. By fusing data from multiple sensors, the system can reduce false positives and false negatives of a single sensor, improve the accuracy of perception, perceive the environment more accurately, and better adapt to complex and changing environments, such as vehicles driving in cities, suburbs, and highways, ensuring that the system can operate effectively in various scenarios.

[0076] Step A13, filtering the vehicle environment data to determine vehicle filtered environment data.

[0077] It is understandable that by filtering out invalid data and noise, data that can improve system performance and generalization capabilities can be prioritized, thereby improving the effectiveness of training, effectively reducing false positives and negatives, and providing more accurate environmental perception.

[0078] In another feasible implementation, step S10 may include steps B11 to B13:

[0079] Step B11, obtaining a person approaching perception algorithm;

[0080] It should be noted that the person approaching perception algorithm reflects the characteristics of the rules set for determining whether a person is approaching a vehicle.

[0081] It can be understood that the person approaching perception algorithm can accurately identify the state of a person approaching the vehicle, and can maintain stable performance even when the environment changes or the sensor is disturbed.

[0082] Step B12, matching personnel characteristics based on the personnel approach perception algorithm and the vehicle filtering environment data to determine a matching result, wherein the personnel characteristics include target personnel size and target moving speed;

[0083] It should be noted that the matching result reflects the characteristics of the state of the person when approaching the vehicle.

[0084] It can be understood that by accurately matching personal characteristics and behavior patterns and accurately identifying the characteristics of people approaching vehicles, it can adapt to different environmental conditions and scenarios, and maintain high-accuracy recognition whether in complex urban environments or on highways.

[0085] Step B13, obtaining the person approaching status based on the matching result.

[0086] It should be noted that the person approaching state reflects the characteristics of identifying the presence of people around the vehicle.

[0087] It can be understood that the person approaching status can characterize the judgment result of the person approaching the vehicle, and identify the characteristics and behaviors of the person, accurately match the characteristics and behavior patterns of the person, significantly reduce false alarms and missed alarms, and provide more accurate person approaching warnings.

[0088] Step S20, detecting the target person based on the vehicle filtering environment data and the person approaching state to determine the traffic police ticket status;

[0089] It should be noted that the traffic police ticketing status reflects the characteristics of the identification result obtained by identifying the traffic police's ticketing behavior.

[0090] It can be understood that the traffic police ticketing status includes the identity recognition status and the ticketing behavior status. The identity recognition status is to extract the traffic police's identity features for identity recognition, and the ticketing behavior status is to extract the traffic police's action features for ticketing action recognition, thereby representing the state in which the vehicle is identified by the traffic police as temporarily parked and ticketed, and accurately identifying the traffic police's ticketing behavior. Once the system recognizes that the traffic police has posted a ticket, it can quickly notify the owner through the remote early warning notification module, so that the owner can respond in time, move the vehicle in time, and increase road safety.

[0091] For ease of understanding, the following is explained by taking the determination of the traffic police ticket status as an example, wherein the information collection device is an environmental detection module, the storage device is a memory, and the processing device is a traffic police identification and ticket warning module.

[0092] The traffic police identification and ticket warning module obtains a deep learning model, that is, performs target detection, uses the deep learning model to identify the human targets in the image, outputs the target category and position, such as pedestrians, traffic police and target frame coordinates, filters out background interference or other irrelevant targets, such as animals and vehicles, through the deep learning model, identifies the vehicle based on the deep learning model to filter the environmental data to determine the image human target information, extracts the traffic police identity features based on the image human target information for identity recognition, and determines the identity recognition status. The traffic police identity features include uniform features and equipment features, that is, the uniform features and equipment features are used to identify the identity of the person, wherein uniform feature recognition is to determine whether it is a traffic police uniform through features such as color and reflective stripes, and equipment feature recognition is to analyze whether the target carries typical ticket tools, such as folders and ticket devices, and extracts traffic police action features based on the identity recognition status for ticket action recognition The traffic police's action characteristics include typical ticket-sticking actions, hand actions and dwell time, that is, using an action recognition algorithm to analyze the traffic police's action sequence, wherein typical ticket-sticking action recognition is to approach the vehicle and determine whether the target is gradually approaching a specific position of the vehicle, such as the front windshield area; hand action recognition is to determine whether the target's hand action conforms to the characteristic trajectory of taking out and posting tickets; dwell time recognition is to determine whether the target stays beside the vehicle for more than a set time threshold, such as the time threshold is set to 3 seconds; the traffic police's ticket-sticking status is obtained based on the identity recognition status and the ticket-sticking behavior status, that is, when the identity recognition status is to identify the identity as a traffic police and the ticket-sticking behavior status is to identify the existence of a ticket-sticking action, then the traffic police's ticket-sticking status is to identify the traffic police's ticket-sticking, and a vehicle remote warning is performed; otherwise, the traffic police's ticket-sticking status is to not identify the traffic police's ticket-sticking, and re-detection is performed, and subsequent processing is performed based on the traffic police's ticket-sticking status.

[0093] In a feasible implementation, step S20 may include steps C11 to C15:

[0094] Step,C11, obtain the deep learning model;

[0095] It should be noted that the deep learning model reflects the features that can recognize and process image data.

[0096] It can be understood that the deep learning model can process the image information in the vehicle filtering environment data, identify the human targets in the image, and output the category and location of the target, accurately identify the traffic police from the complex environment background, reduce false alarms and missed alarms, and provide more accurate recognition results.

[0097] Step C12, identifying the vehicle filtering environment data based on the deep learning model to determine the image person target information;

[0098] It should be noted that the image person target information reflects the characteristics of the position and category information of the person target identified in the image.

[0099] It can be understood that the image person target information can represent the detected person target, such as a traffic policeman or a pedestrian, and the exact position in the image.

[0100] Step C13, extracting the identity features of the traffic police based on the target information of the person in the image to perform identity recognition and determine the identity recognition status, wherein the identity features of the traffic police include uniform features and equipment features;

[0101] It should be noted that the identity recognition state reflects the characteristics of confirming the identity of a person based on the person target information in the image.

[0102] It is understandable that by extracting specific identity features of the person in the image, such as uniform features and equipment features, the identity of the person can be determined. Uniform features may include the color, style and reflective stripes of the clothing, and equipment features may include the equipment carried by the person, such as a ticket holder or a law enforcement recorder, thereby more accurately distinguishing between traffic police and other pedestrians or objects and reducing false alarms.

[0103] Step C14, extracting the traffic police action features based on the identity recognition state to perform ticket pasting action recognition and determine the ticket pasting behavior state, wherein the traffic police action features include typical ticket pasting actions, hand movements and dwell time;

[0104] It should be noted that the ticket pasting behavior status reflects the characteristics of identifying the traffic police's ticket pasting action.

[0105] It is understandable that by analyzing the action characteristics of the traffic police, the state of the ticketing behavior can be determined, including typical ticketing actions, hand movements and dwell time, thereby triggering the corresponding alarm mechanism, responding in time and quickly notifying the car owner to take action, reducing fines caused by ticketing and increasing road safety.

[0106] Step C15, obtaining the traffic police ticketing status based on the identity recognition status and the ticketing behavior status.

[0107] It is understandable that by accurately identifying the identity of the traffic police and recognizing the action of issuing a ticket, the status of the traffic police issuing a ticket can be obtained, thereby quickly notifying the car owner to take action, reducing the fines caused by issuing tickets, increasing road safety, and significantly improving user satisfaction.

[0108] Step S30, the traffic police ticket status is notified and distributed to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

[0109] It is understandable that emergency priorities are generated based on the status of traffic tickets, and events of different urgency are identified and classified to ensure that high-priority events can be handled quickly. Confirmation information is generated to confirm the status of traffic tickets, thereby selecting the most appropriate notification method based on different levels of urgency and user preferences to ensure that information can be conveyed to users in a timely and accurate manner.

[0110] For ease of understanding, the status of obtaining a traffic ticket is taken as an example for explanation, wherein the information collection device is an environmental detection module, the storage device is a memory, and the execution device is a remote warning notification module.

[0111] The remote warning notification module obtains the status of traffic police ticketing, obtains the ticketing confirmation information based on the traffic police ticketing status, determines the emergency priority of the event based on the ticketing confirmation information, and generates warning notification content information based on the emergency priority of the event, the warning notification content information includes time information, location information, event type information, warning screenshot information or video information, obtains the channel notification distribution method, the channel notification distribution method includes application push distribution, SMS push distribution and phone push distribution, packages the warning notification content information into standardized message format information, and notifies and distributes the standardized message format information based on the emergency priority of the event and the channel notification distribution method to complete the vehicle remote alarm.

[0112] The user feedback and interaction module obtains an event details page and a reconfirmation operation instruction, wherein the event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information and event level visual prompt information, and obtains feedback information based on analyzing the event behavior status on the event details page, wherein the feedback information includes confirmation information, false alarm marking information and ignored event information, and remotely activates the vehicle-mounted sound and light warning based on the feedback information and the reconfirmation operation instruction to complete the vehicle remote alarm.

[0113] The present embodiment proposes a vehicle remote alarm method, which obtains vehicle filtering environment data, and performs personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status; detects the target person based on the vehicle filtering environment data and the personnel approach status to determine the traffic police ticket status; and notifies and distributes the traffic police ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution. The present invention solves the technical problem of how to more effectively identify the traffic police ticket for remote alarm. Compared with the prior art, the present application collects vehicle surrounding environment data by integrating sensors such as radar, laser radar and camera to realize dynamic perception of the vehicle body surrounding environment, uses personnel approach perception algorithm and deep learning model to accurately detect the personnel approach status and traffic police ticket behavior, and notifies the owner in real time through application push, SMS and telephone and other methods, realizes remote warning for users, and optimizes the system recognition ability in combination with user feedback, provides users with real-time safety monitoring during vehicle parking, effectively improves vehicle parking safety, can identify the approach of surrounding personnel and traffic police, and automatically reminds users when traffic police start to issue tickets, reduces fines caused by temporary parking, and improves the user experience of car owners to ensure road safety.

[0114] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be repeated later.

[0115] In this embodiment, refer to Figure 2 , Figure 2 This is a flow chart of the second embodiment of the vehicle remote alarm method of the present application, wherein step S30 specifically includes steps S31 to S34:

[0116] Step S31, obtaining traffic ticketing confirmation information based on the traffic police ticketing status;

[0117] It should be noted that the ticketing confirmation information reflects the characteristics of the system's ability to identify and confirm the traffic police's ticketing behavior.

[0118] It is understandable that the confirmation information of the ticketing behavior needs to be obtained in real time to ensure that the system responds quickly, so that users can be notified and take action in time to reduce fines caused by failure to move the car in time. By accurately judging the emergency priority of the event, the system can allocate notification resources more reasonably to ensure that important information is conveyed first, which significantly improves the system's adaptability and user satisfaction.

[0119] For ease of understanding, the status of obtaining a traffic ticket is taken as an example for explanation, wherein the information collection device is an environmental detection module, the storage device is a memory, and the execution device is a remote warning notification module.

[0120] The remote warning notification module obtains the confirmation information of the traffic police ticketing status based on the traffic police ticketing status, that is, based on the traffic police ticketing status, it receives the confirmation information of the traffic police ticketing status from the traffic police identification and ticketing warning module, obtains the ticketing behavior confirmation information, and performs subsequent processing based on the ticketing behavior confirmation information.

[0121] Step S32, determining the emergency priority of the event based on the confirmation information of the posting behavior;

[0122] It should be noted that the emergency priority of the event reflects the characteristics of the level assessed according to the urgency of the event.

[0123] It is understandable that by accurately determining the emergency priority of an event, the system can quickly respond to high-priority events, reduce the number of tickets users receive for not responding in a timely manner, and improve road safety, increasing user trust and satisfaction with the system.

[0124] For ease of understanding, the example of obtaining confirmation information of the ticket posting behavior is used for explanation, wherein the information collection device is an environment detection module, the storage device is a memory, and the execution device is a remote warning notification module.

[0125] The remote warning notification module obtains the confirmation information of the ticket posting behavior, and determines the emergency priority of the event based on the confirmation information of the ticket posting behavior, that is, judges the urgency of the matter, including high priority, medium priority and low priority. For example, the ticket posting behavior has been confirmed, it is suspected that the ticket is posted but requires user confirmation, and it is an ordinary approach event. Subsequent processing is performed based on the emergency priority of the event.

[0126] Step S33, generating warning notification content information based on the emergency priority of the event, wherein the warning notification content information includes time information, location information, event type information, warning screenshot information or video information;

[0127] It should be noted that the warning notification content information reflects the detailed information and data characteristics contained when the warning notification is generated.

[0128] It can be understood that the warning notification content information includes time information, location information, event type information, warning screenshot information or video information, and can be quickly and accurately conveyed to users, thereby improving the timeliness and accuracy of the warning, enabling users to understand the event situation more clearly, providing comprehensive and personalized warning notification content, reducing the possibility of false alarms and missed alarms, and improving the reliability and accuracy of the system.

[0129] For ease of understanding, the generation of early warning notification content information is taken as an example for explanation, wherein the information collection device is an environmental detection module, the storage device is a memory, and the execution device is a remote early warning notification module.

[0130] The remote warning notification module obtains the emergency priority of the event, and generates warning notification content information based on the emergency priority of the event. The warning notification content information includes time information, location information, event type information, warning screenshot information or video information, that is, the notification content is generated, including time, location, event type, warning screenshot or video, and subsequent processing is performed based on the warning notification content information.

[0131] Step S34, packaging the warning notification content information based on the emergency priority of the event for notification distribution to complete the vehicle remote alarm.

[0132] It is understandable that the system can adjust the recognition model parameters according to the false alarm information marked by the user to reduce misjudgments, and the application APP provides event history records, so that users can view processed or unprocessed events at any time, thereby optimizing the system and providing feedback to provide more accurate judgment results.

[0133] For ease of understanding, the example of obtaining the emergency priority of an event and the content information of a warning notification is used for explanation, wherein the information collection device is an environmental detection module, the storage device is a memory, and the execution device is a remote warning notification module.

[0134] The remote warning notification module obtains the emergency priority of the event and the warning notification content information, obtains the channel notification distribution method, the channel notification distribution method includes application push distribution, SMS push distribution and telephone push distribution, packages the warning notification content information into standardized message format information, that is, performs data encapsulation, packages the notification content into a standardized message format, and performs notification distribution on the standardized message format information based on the emergency priority of the event and the channel notification distribution method to complete the vehicle remote alarm, that is, performs application push distribution, APP push, sends the notification to the user's mobile phone in real time through the push service, performs SMS push distribution, SMS notification, sends a short notification information, performs telephone push distribution, telephone reminder, and triggers voice notification when the user does not respond in time, and dynamically adjusts the notification order and method according to the urgency of the event. High-priority events give priority to sending SMS and phone calls, while medium and low priority events are mainly pushed by APP.

[0135] The user feedback and interaction module pushes the message from the remote warning notification module to the user's mobile terminal such as application APP and SMS, obtains the event details page and reconfirms the operation instructions. The event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information and event level visual prompt information, that is, after the user opens the notification, he can enter the event details page, view the event time, view the event location, view the vehicle surrounding images or videos, such as screenshots and real-time videos, view the system's preliminary analysis results, such as whether the traffic police has issued a ticket, and provide event level visual prompts, such as high-level visual prompts, medium-level visual prompts and low-level visual prompts. Feedback information is obtained based on the analysis of the event behavior status on the event details page, and the feedback information includes confirmation information , false alarm mark information and ignored event information, that is, the user operates the option to confirm the event, confirms that the system analyzes the traffic police's ticketing behavior correctly, generates confirmation information, the system records the event and prompts the user to mark the confirmation information. If the user believes that the system recognition is incorrect, such as an ordinary pedestrian being mistaken for a traffic policeman, submit a false alarm mark. If the event is unimportant, the user submits the ignored event information, the system records it but does not send further reminders, and remotely activates the on-board sound and light warning based on the feedback information and the re-confirmation operation instruction to complete the vehicle remote alarm, that is, upload the user's feedback information to the cloud server, upload the confirmation mark and false alarm mark to the cloud, and the system will prompt the user to confirm again to avoid misoperation, such as remote honking. Users can activate the on-board sound and light warning through the application APP to alert traffic police or surrounding people, and turn on the on-board camera for real-time monitoring.

[0136] In a feasible implementation, step S30 may include steps D11 to D13:

[0137] Step D11, obtaining a channel notification distribution method, wherein the channel notification distribution method includes application push distribution, SMS push distribution, and phone push distribution;

[0138] It should be noted that the channel distribution method reflects the characteristics of different channels and methods used to deliver the warning notification information to the user.

[0139] It is understandable that warning notification information can be delivered in a timely manner through the channel distribution method, and the most appropriate distribution channel can be flexibly selected according to the urgency of the event and the user's preference, thereby improving the efficiency of information transmission, receiving warning information in the shortest time, and responding quickly.

[0140] Step D12, packaging the warning notification content information into standardized message format information;

[0141] It should be noted that the standardized message format information reflects the characteristics of a unified and standardized message format used when packaging the warning notification content.

[0142] It can be understood that the standardized message format ensures the consistency of different warning notification content information when it is transmitted between different channels and platforms, which facilitates parsing and processing. Through the standardized message format, different systems and modules can seamlessly exchange and process data, improving the compatibility and interoperability of the system, simplifying the information processing flow, reducing the time for conversion and adaptation, and improving the efficiency of information transmission.

[0143] Step D13, based on the emergency priority of the event and the channel notification distribution method, the standardized message format information is notified and distributed to complete the vehicle remote alarm.

[0144] It is understandable that the system needs to determine the priority of notifications based on the urgency of the event, ensuring that high-priority events can be quickly communicated to users, adapt notification content according to different notification channels, ensure that information can be conveyed in the most appropriate manner, and dynamically adjust notification distribution strategies based on user feedback and behavior patterns to make the system more flexible and adaptable to the needs of different users.

[0145] In another feasible implementation manner, step S30 may include steps E11 to E13:

[0146] Step E11, obtaining an event details page and reconfirming the operation instruction, wherein the event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information, and event level visual prompt information;

[0147] It should be noted that the event details page reflects the characteristics of a comprehensive and detailed event information display interface provided to the user, and the re-confirmation operation instruction reflects the characteristics of the user further confirming and feeding back the warning information.

[0148] It is understandable that the event details page may include the time, location, type, and related image or video information of the event, so that users can quickly understand the specific circumstances of the event and make more accurate judgments and responses. The re-confirmation operation instruction allows users to make further confirmation or feedback, allowing users to handle warning information more conveniently, and use user feedback to optimize the warning algorithm to improve the accuracy of the system.

[0149] Step E12, analyzing the event behavior status based on the event details page to obtain feedback information, wherein the feedback information includes confirmation information, false alarm marking information, and ignored event information;

[0150] It should be noted that the feedback information reflects the characteristics of recording the user's feedback information on the accuracy of the identified traffic police ticket status.

[0151] It is understandable that the feedback information can enable the system to self-learn and adapt according to the user's actual experience, improve the accuracy of warnings and user satisfaction, identify and reduce false alarms, and improve the accuracy of warnings.

[0152] Step E13, based on the feedback information and the reconfirmation operation instruction, remotely activate the vehicle sound and light warning to complete the vehicle remote alarm.

[0153] It is understandable that the system can remotely control the vehicle's sound and light warning system, and can respond in time even if the user is not on site. By remotely activating the sound and light warning, it can promptly remind people or vehicles around it, reduce the danger caused by failure to discover the situation in time, and enhance the safety of the vehicle and the surrounding environment.

[0154] This embodiment proposes a vehicle remote alarm method, which obtains the ticket confirmation information based on the traffic police ticket status; determines the emergency priority of the event based on the ticket confirmation information; generates warning notification content information based on the emergency priority of the event, and the warning notification content information includes time information, location information, event type information, warning screenshot information or video information; and packages the warning notification content information based on the emergency priority of the event for notification distribution to complete the vehicle remote alarm. The technical problem of how to make remote alarms more timely is solved. Compared with the existing technology, this application identifies the traffic police ticketing behavior by analyzing the radar, lidar and camera data around the vehicle, determines the emergency priority of the event, and generates a warning notification containing key information such as time, location and event type, which is quickly conveyed to the car owner through multiple channels such as application push, SMS and phone calls, thereby improving the response speed to the traffic police ticketing behavior, reducing temporary parking fines, and improving user experience and vehicle parking safety.

[0155] For example, in order to help understand the implementation process of the vehicle remote alarm method obtained by combining this embodiment with the above-mentioned embodiment 1, please refer to Figure 3 , Figure 3 A brief flow chart of a vehicle remote alarm method is provided, specifically:

[0156] The vehicle remote alarm system of the present application includes an environment detection module, a traffic police identification and ticket warning module, a remote warning notification module and a user feedback and interaction module. The environment detection module includes sensor hardware and corresponding software algorithms. The traffic police identification and ticket warning module is combined with feature recognition, so that the system can efficiently identify traffic police and their ticketing behavior when parking. The remote warning notification module allows users to grasp abnormal conditions around the vehicle at any time, respond to and deal with potential risks in a timely manner. The user feedback and interaction module allows users to understand the vehicle status at any time, and complete event processing through simple interaction, which greatly improves the practicality and convenience of the system. Referring to Example 1, the vehicle filtering environment data is obtained, and based on the vehicle filtering environment data, a person approach detection is performed to determine the person approaching status; based on the vehicle filtering environment data and the person approaching status, the target person is detected to determine the traffic police ticketing status; the traffic police ticketing status is notified and distributed to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and phone push distribution. Referring to Example 2, based on the traffic police ticketing status, confirmation information of the ticketing behavior is obtained; based on the ticketing behavior confirmation information, the emergency priority of the event is determined; based on the emergency priority of the event, early warning notification content information is generated, and the early warning notification content information includes time information, location information, event type information, early warning screenshot information or video information; based on the emergency priority of the event, the early warning notification content information is packaged for notification distribution to complete the vehicle remote alarm.

[0157] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle remote alarm method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0158] This application also provides a vehicle remote alarm device, please refer to Figure 4 , the vehicle remote alarm device comprises:

[0159] The acquisition module 10 is used to acquire vehicle filtering environment data, and perform personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status;

[0160] A processing module 20, configured to detect a target person based on the vehicle filtering environment data and the person approaching state and determine a traffic police ticketing state;

[0161] The execution module 30 is used to notify and distribute the traffic ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

[0162] The acquisition module 10 is also used to acquire radar data, lidar data and camera video data;

[0163] Determining vehicle environment data based on the radar data, the lidar data, and the camera video data;

[0164] The vehicle environment data is filtered to determine vehicle filtered environment data.

[0165] The acquisition module 10 is also used to acquire a person approaching perception algorithm;

[0166] Matching personnel characteristics based on the personnel approach perception algorithm and the vehicle filtering environment data to determine a matching result, wherein the personnel characteristics include target personnel size and target movement speed;

[0167] The person approaching status is obtained based on the matching result.

[0168] The processing module 20 is also used to obtain a deep learning model;

[0169] Identify the vehicle filtering environment data based on the deep learning model to determine the image person target information;

[0170] Extracting the identity features of the traffic police based on the target information of the person in the image to perform identity recognition and determine the identity recognition status, wherein the identity features of the traffic police include uniform features and equipment features;

[0171] Extracting the traffic police action features based on the identity recognition state to perform ticket pasting action recognition and determine the ticket pasting behavior state, wherein the traffic police action features include typical ticket pasting actions, hand movements and dwell time;

[0172] The traffic police ticketing status is obtained based on the identity recognition status and the ticketing behavior status.

[0173] The execution module 30 is further used to obtain the ticketing behavior confirmation information based on the traffic police ticketing status;

[0174] Determine the emergency priority of the event based on the confirmation information of the posting behavior;

[0175] Generate warning notification content information based on the emergency priority of the event, the warning notification content information including time information, location information, event type information, warning screenshot information or video information;

[0176] The warning notification content information is packaged based on the emergency priority of the event and distributed to complete the vehicle remote alarm.

[0177] The execution module 30 is further used to obtain a channel notification distribution method, wherein the channel notification distribution method includes application push distribution, SMS push distribution and telephone push distribution;

[0178] Packaging the warning notification content information into standardized message format information;

[0179] The standardized message format information is notified and distributed based on the emergency priority of the event and the channel notification distribution method to complete the vehicle remote alarm.

[0180] The execution module 30 is further used to obtain an event details page and reconfirm the operation instruction, wherein the event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information and event level visual prompt information;

[0181] Analyze the event behavior status based on the event details page to obtain feedback information, wherein the feedback information includes confirmation information, false alarm marking information, and ignored event information;

[0182] Based on the feedback information and the reconfirmation operation instruction, the vehicle-mounted sound and light warning is remotely activated to complete the vehicle remote alarm.

[0183] The vehicle remote alarm device provided by the present application adopts the vehicle remote alarm method in the above embodiment, which can solve the technical problem of how to more effectively identify traffic police tickets and make remote alarms in a timely manner. Compared with the prior art, the beneficial effects of the vehicle remote alarm device provided by the present application are the same as the beneficial effects of the vehicle remote alarm method provided by the above embodiment, and the other technical features of the vehicle remote alarm device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0184] The present application provides a vehicle remote alarm device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle remote alarm method in the above-mentioned embodiment one.

[0185] Reference below Figure 5 , which shows a schematic diagram of the structure of a vehicle remote alarm device suitable for implementing an embodiment of the present application. The vehicle remote alarm device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The vehicle remote alarm device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0186] like Figure 5 As shown, the vehicle remote alarm device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the vehicle remote alarm device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the vehicle remote alarm device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a vehicle remote alarm device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0187] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0188] The vehicle remote alarm device provided by the present application adopts the vehicle remote alarm method in the above embodiment, which can solve the technical problem of how to more effectively identify traffic police tickets and make remote alarms in a timely manner. Compared with the prior art, the beneficial effects of the vehicle remote alarm device provided by the present application are the same as the beneficial effects of the vehicle remote alarm method provided by the above embodiment, and the other technical features in the vehicle remote alarm device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0189] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0190] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0191] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle remote alarm method in the above-mentioned embodiment.

[0192] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0193] The computer-readable storage medium may be included in the vehicle remote alarm device; or may exist independently without being assembled into the vehicle remote alarm device.

[0194] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle remote alarm device, the vehicle remote alarm device: obtains vehicle filtering environment data, and performs personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status; detects the target person based on the vehicle filtering environment data and the personnel approach status to determine the traffic police ticket status; and notifies and distributes the traffic police ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and phone push distribution.

[0195] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0196] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0197] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0198] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle remote alarm method, and can solve the technical problem of how to more effectively identify traffic police tickets and make remote alarms in a timely manner. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle remote alarm method provided by the above-mentioned embodiment, and will not be repeated here.

[0199] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle remote alarm method, characterized in that: The method includes: Acquire vehicle filtering environment data, and perform person approach detection based on the vehicle filtering environment data to determine the person approach status; Detecting the target person based on the vehicle filtering environment data and the person approaching status to determine the traffic police ticketing status; The traffic police ticket status is notified and distributed to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

2. The method according to claim 1, characterized in that The step of obtaining vehicle filtering environment data comprises: Get radar data, lidar data, and camera video data; Determining vehicle environment data based on the radar data, the lidar data, and the camera video data; The vehicle environment data is filtered to determine vehicle filtered environment data.

3. The method according to claim 1, characterized in that The step of performing personnel approach detection based on the vehicle filtering environment data and determining the personnel approach status comprises: Acquire a person approaching perception algorithm; Matching personnel characteristics based on the personnel approach perception algorithm and the vehicle filtering environment data to determine a matching result, wherein the personnel characteristics include target personnel size and target movement speed; The person approaching status is obtained based on the matching result.

4. The method according to claim 1, characterized in that The step of detecting a target person based on the vehicle filtering environment data and the person approaching state and determining the state of a traffic police ticket includes: Get the deep learning model; Identify the vehicle filtering environment data based on the deep learning model to determine the image person target information; Extracting the identity features of the traffic police based on the target information of the person in the image to perform identity recognition and determine the identity recognition status, wherein the identity features of the traffic police include uniform features and equipment features; Extracting the traffic police action features based on the identity recognition state to perform ticket pasting action recognition and determine the ticket pasting behavior state, wherein the traffic police action features include typical ticket pasting actions, hand movements and dwell time; The traffic police ticketing status is obtained based on the identity recognition status and the ticketing behavior status.

5. The method according to claim 1, characterized in that The step of notifying and distributing the traffic police ticket status to complete the vehicle remote alarm includes: Acquiring ticketing confirmation information based on the traffic police ticketing status; Determine the emergency priority of the event based on the confirmation information of the posting behavior; Generate warning notification content information based on the emergency priority of the event, the warning notification content information including time information, location information, event type information, warning screenshot information or video information; The warning notification content information is packaged based on the emergency priority of the event and distributed to complete the vehicle remote alarm.

6. The method according to claim 5, characterized in that The step of packaging the warning notification content information based on the emergency priority of the event and distributing the notification to complete the vehicle remote alarm includes: Obtain channel notification distribution methods, which include application push distribution, SMS push distribution, and phone push distribution; Packaging the warning notification content information into standardized message format information; The standardized message format information is notified and distributed based on the emergency priority of the event and the channel notification distribution method to complete the vehicle remote alarm.

7. The method according to claim 5, characterized in that After the step of packaging the warning notification content information based on the emergency priority of the event and distributing the notification to complete the vehicle remote alarm, the following step further includes: Obtaining an event details page and reconfirming the operation instruction, wherein the event details page includes event time information, event location information, vehicle surrounding image information, vehicle surrounding video information, preliminary analysis result information, and event level visual prompt information; Analyze the event behavior status based on the event details page to obtain feedback information, wherein the feedback information includes confirmation information, false alarm marking information, and ignored event information; Based on the feedback information and the reconfirmation operation instruction, the vehicle-mounted sound and light warning is remotely activated to complete the vehicle remote alarm.

8. A vehicle remote alarm device, characterized in that: The device comprises: An acquisition module, used to acquire vehicle filtering environment data, and perform personnel approach detection based on the vehicle filtering environment data to determine the personnel approach status; A processing module, configured to detect a target person based on the vehicle filtering environment data and the person approaching state and determine the state of the traffic police ticketing; The execution module is used to notify and distribute the traffic police ticket status to complete the vehicle remote alarm, and the notification distribution includes application push distribution, SMS push distribution and telephone push distribution.

9. A vehicle remote alarm device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle remote alarm method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle remote alarm method according to any one of claims 1 to 7 are implemented.

Images