A parking lot early warning management method, device, equipment and medium

Abstract

The application discloses a parking lot early warning management method, which combines a pickup device and a digital twin to confirm the position of parking lot congestion, improves the management efficiency of the parking lot, and comprises the following steps: receiving a congestion process warning fed back by a target pickup device, wherein the pickup device is arranged at a plurality of different preset positions of the parking lot; generating suspected congestion warning information according to the congestion process warning fed back by the target pickup device, wherein the suspected congestion warning information comprises a suspected congestion event area; and when a corresponding digital twin model of the parking lot exists, generating a visual display interface according to the suspected congestion event area and the digital twin model.

Description

Technical Field

[0001] This invention relates to the field of intelligent parking, and in particular to a parking lot early warning management method, device, equipment, and medium. Background Technology

[0002] With the continuous development of information technology and people's increasing demands for parking experience, the traditional parking management model, characterized by low management efficiency, poor technology, and difficulty in ensuring safety, can no longer meet the practical needs of traffic management and people's parking. There is an urgent need to enhance the intelligence of dynamic parking lot management and improve the user experience by leveraging digital innovation and big data through digital means. Summary of the Invention

[0003] This invention provides a parking lot early warning management method, device, computer equipment, and storage medium to address user experience issues related to parking lot use.

[0004] A parking lot early warning management method includes:

[0005] The system receives congestion warnings from the target microphones, wherein microphones are located at multiple preset locations in the parking lot.

[0006] Based on the congestion warning fed back by the target microphone, a suspected congestion alarm message is generated, which includes the suspected congestion event area;

[0007] When the parking lot has a corresponding digital twin model, a visual display interface is generated based on the suspected congestion event area and the digital twin model.

[0008] A parking lot early warning management device, comprising:

[0009] A collection device receives congestion warnings from target microphones, wherein microphones are arranged at multiple different preset locations in the parking lot;

[0010] The processing device generates suspected congestion alarm information based on the congestion warning fed back by the target microphone, the suspected congestion alarm information including the suspected congestion event area;

[0011] The output device generates a visual display interface based on the suspected congestion event area and the digital twin model when the parking lot has a corresponding digital twin model.

[0012] A parking lot early warning management system, characterized in that the parking lot early warning management system includes a cloud platform and at least one microphone deployed in the parking lot;

[0013] The microphone is used to identify congestion alarms in the parking lot;

[0014] The cloud platform is used to receive congestion warnings from target microphones, wherein microphones are deployed at multiple preset locations in the parking lot; based on the congestion warnings from the target microphones, it generates suspected congestion alarm information, which includes suspected congestion event areas; when the parking lot has a corresponding digital twin model, it generates a visual display interface based on the suspected congestion event areas and the digital twin model.

[0015] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the parking lot early warning management method described above.

[0016] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described parking lot early warning management method.

[0017] The aforementioned parking lot early warning management methods, devices, computer equipment, and storage media are applied in the field of intelligent parking, particularly for parking lot early warning management systems. They utilize digital twin models and microphones to quickly locate vehicle congestion locations and, through data analysis and optimization, prevent vehicle congestion from being reported to staff via a cloud platform. This allows staff to quickly and efficiently arrive at the scene to handle the situation, improving the user experience of the parking lot. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a parking lot early warning management method according to an embodiment of the present invention;

[0020] Figure 2 This is a flowchart of a parking lot early warning management method according to an embodiment of the present invention;

[0021] Figure 3 This is a flowchart of a parking lot early warning management method according to an embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of a pickup according to an embodiment of the present invention;

[0023] Figure 5 This is a parking lot early warning management diagram according to one embodiment of the present invention;

[0024] Figure 6 A computer device diagram illustrating a parking lot early warning management method according to an embodiment of the present invention; Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] This invention provides a parking lot early warning management method applicable to various parking lots equipped with digital twins and microphones. This method improves the user experience by using a digital twin model for digital management, significantly enhancing the intelligence of dynamic parking lot management. The following detailed descriptions of various embodiments illustrate the parking lot early warning management method provided by this invention.

[0027] First, to facilitate understanding of the embodiments of the present invention, some terms or concepts involved in the embodiments of the present invention will be briefly introduced as follows:

[0028] pickup:

[0029] Microphones are generally divided into digital microphones and analog microphones. The microphone in this embodiment of the invention is a digital microphone, which is a sound sensing device that converts analog audio signals into digital signals and performs corresponding digital signal processing through a digital signal processing system.

[0030] Digital Twin:

[0031] The digital twin in this invention embodiment comprehensively utilizes multiple technologies to achieve real-time bidirectional synchronous mapping and virtual-real interaction between physical and digital spaces. In addition to human-computer interaction, it includes interaction types such as the physical world shaping the digital world using sensor data, and the digital world modifying the physical world through actuators.

[0032] In one embodiment, such as Figure 1 As shown, a parking lot early warning management method is provided, which is applied to... Figure 1 Taking the server in the example, the following steps are included:

[0033] S10: Receive congestion warning from the target microphone, wherein microphones are arranged at multiple preset locations in the parking lot;

[0034] Specifically, microphones are installed at different locations within the parking lot to collect the sounds of vehicles within the parking lot and to determine the types of vehicle sounds.

[0035] S20: Based on the congestion warning fed back by the target microphone, generate suspected congestion alarm information, which includes the suspected congestion event area;

[0036] Specifically, when the microphone receives a sound, it determines the sound type; if the sound type is a horn, it generates an alarm and records the number of alarms; when the number of alarms exceeds a preset threshold, an alarm will be generated, and an alarm name and alarm time will be generated; or, when the microphone receives a sound, it records the cumulative duration of the sound; when the cumulative duration of the sound received by the microphone exceeds a preset time threshold, a warning name and alarm time will be generated.

[0037] S30: When the parking lot has a corresponding digital twin model, a visual display interface is generated based on the suspected congestion event area and the digital twin model.

[0038] Specifically, the digital twin model is equivalent to a map that allows staff to see the parking lot situation. When a vehicle honks its horn in a certain area, and the honking time is relatively long or the number of honks is high within a certain period of time, the microphone in that area receives the sound. The microphone at the corresponding position in the digital twin model will generate a semi-transparent light column indicating the distance of the sound source received by the microphone. The closer the vehicle is to the sound source, the darker the color of the semi-transparent light column; the farther the vehicle is from the sound source, the lighter the color of the semi-transparent light column. The light column generated by the microphone in the digital twin model is semi-transparent so that the digital twin map can still be seen, making it easier to see suspected congestion locations in the digital twin model.

[0039] In this embodiment of the invention, microphones are deployed at multiple preset locations in the parking lot to receive congestion warnings from target microphones. Based on the congestion warnings from the target microphones, suspected congestion alarm information is generated. When a corresponding digital twin model exists in the parking lot, a visual display interface is generated based on the suspected congestion event area and the digital twin model. This visual display is presented to the on-duty staff, solving the problem that traditional parking management cannot promptly alleviate vehicle congestion, further improving parking lot management efficiency, and addressing the time lag between the occurrence and handling of the problem.

[0040] In one embodiment, a parking lot early warning processing method is provided. Figure 2 As shown, step S20, which generates a visual display interface based on the suspected congestion event area and the digital twin model, specifically includes the following steps:

[0041] S21: Mark the microphone position on the digital twin model, wherein the microphone position is the same as the preset microphone position in the parking lot;

[0042] Specifically, microphone identifiers are generated in the digital twin model, and each microphone identifier corresponds one-to-one with the location of a microphone in the parking lot. When a suspected congestion occurs at the same location in the parking lot corresponding to the digital twin model, a visual interface can be generated for staff to view.

[0043] S22: The digital twin model uses semi-transparent light pillars to simulate the monitored sound volume and direction;

[0044] Specifically, the microphones in the parking lot have the ability to detect the volume. The closer the vehicle horn is to the microphone, the louder the sound becomes. The color of the translucent light column generated by the corresponding microphone icon in the digital twin model becomes darker. For example, if the vehicle horn sound is from a sound source 50 to 60 meters away from the microphone, the color is darkest in the 50 to 60 meter range, and gradually becomes lighter in the remaining range.

[0045] S23: Determine the suspected congestion area based on the semi-transparent light beam simulated by the microphone.

[0046] Specifically, each microphone collects sound from a specific area. If a vehicle honks in the parking lot, all microphones in that area will receive the horn sound. Depending on the distance of the horn sound from the vehicle, different translucent light beams of varying colors will be generated. These translucent light beams will be superimposed, such as... Figure 4 As shown, the area superimposed by the translucent light beams can be used to identify suspected congested areas.

[0047] In this embodiment of the invention, in a parking lot equipped with a digital twin, based on the sound collected by the microphone, and depending on the size and distance of the sound source, the color depth of the translucent light column of the microphone in the digital twin model is also different. Based on the color depth, staff can determine the location of suspected congestion by observing the color of the light column, thereby improving the efficiency of congestion resolution.

[0048] In one embodiment, a parking lot early warning processing method is provided. Step S20, which involves generating a visual display interface based on the suspected congestion event area and the digital twin model, specifically includes the following steps:

[0049] 231: When any microphone has direction-finding capability, it monitors the direction of sound based on the sound source and marks the direction of the sound source based on the monitoring results;

[0050] Specifically, a microphone can monitor the volume of a sound, and a microphone with direction-finding capabilities can also monitor the direction of the sound and provide an approximate direction of the sound source. For example, if a vehicle is honking near a microphone, and the microphone has direction-finding capabilities, such as... Figure 4 As shown, the approximate direction of the vehicle's horn can be determined, for example, 45 to 90 degrees north of east. A semi-transparent beam of light is used to visualize the direction of the sound. When multiple microphones in the parking lot collect the same vehicle's sound, each microphone will generate a different visualization.

[0051] S232: Visualize the direction of the sound source using a semi-transparent light column, wherein the transparency of the semi-transparent light column varies according to the volume of the sound detected by the microphone, and the lower the volume of the detected sound, the higher the transparency.

[0052] Specifically, when the microphone detects sound, a semi-transparent light pillar is used to mark the direction of the sound source. The color intensity of the semi-transparent light pillar changes according to the distance between the sound source and the microphone. The semi-transparent light pillar is presented in the form of a colored semi-transparent light pillar with a certain contrast to the background, which also facilitates the viewing of the digital twin model by staff. For example, as... Figure 4 As shown in the diagram, the translucent light column described in the image changes direction according to the direction of the sound source collected by the microphone, and its color gradually changes according to the intensity of the sound collected by the microphone. For example, assuming the vehicle sound source is 50-60 meters away from the microphone, the color is darkest in the 50-60m range in the digital twin model, gradually becoming lighter in the rest of the range.

[0053] In one embodiment, a parking lot early warning processing method is described. In step S30, as follows... Figure 3 As shown, based on the congestion warnings fed back by the microphone, a suspected congestion alarm message is generated, which specifically includes the following steps:

[0054] S31: When each microphone receives a vehicle horn sound, it records the sound and generates a congestion warning, and reports the congestion warning to the cloud platform. The congestion warning includes the start time of the sound reception, the end time of the sound, and the microphone number that received the sound.

[0055] Specifically, the microphone connects to a cloud platform. By recording the start and end times of the sound received by the microphone, as well as the microphone ID, it can record horn sounds generated within a certain period. By statistically analyzing the cumulative duration and occurrence time of each horn sound, it can accurately determine whether there is suspected congestion in the area and generate an alarm record to feed back to staff. When multiple microphones in the parking lot receive the same vehicle horn sound, all receiving microphones will generate a congestion warning alarm record and upload it to the cloud platform. For example, when a microphone receives a vehicle horn sound, it records the time of the horn sound, the end time of the horn sound, and the microphone ID that received the horn sound, and uploads it to the cloud platform to generate a congestion warning record. Although a congestion warning is generated every time a horn sound occurs, only when congestion warnings are generated frequently within a certain period, exceeding a preset threshold, will a suspected congestion alarm be generated to notify staff for handling.

[0056] S32A: The cloud platform determines the duration of each vehicle horn sound based on the collected start and end times of each sound and performs statistics on the duration of the vehicle horn sound. When the cumulative duration of the vehicle horn sound exceeds the preset cumulative threshold within a certain period of time, the suspected congestion alarm information is generated.

[0057] Specifically, the cloud platform records the time of each horn blast and calculates the duration of the horn blast based on the start and end times. For example, if a vehicle horn blast starts at 12:20 and ends at 12:21, the duration is determined to be 60 seconds. The cloud platform tracks the duration of each horn blast, and if it exceeds a preset cumulative time threshold within a certain period, a suspected congestion alarm is generated. For instance, if a microphone first collects a horn blast at 12:20 and ends at 12:21, then collects a second horn blast at 12:23 and ends at 12:25, the cloud platform calculates a cumulative horn blast time of three minutes within five minutes, thus generating a suspected congestion alarm. Specifically, if the cumulative duration of horn sounds does not exceed a preset threshold within a certain time period, or if multiple horn sounds exceed the threshold but the interval between each sound is too long, no alarm record will be generated. For example, if a microphone first collects horn sounds at 12:20 and the first horn sound ends at 12:21, the cumulative horn sound duration does not exceed the preset threshold and lasts for two minutes, no suspected congestion alarm record will be generated. Or, if a microphone first collects horn sounds at 10:20 and the first horn sound ends at 10:21, and the next horn sound starts at 11:00 and ends at 11:02, although the cumulative horn sound duration exceeds the preset threshold of two minutes, the time interval is too long, so no suspected congestion alarm record will be generated. All the above examples are for illustrative purposes only and do not constitute any limitation.

[0058] S32B: The cloud platform counts the number of times a vehicle honks its horn. If the number of horns exceeds a preset threshold within a certain period of time, a suspected congestion alarm is generated.

[0059] Specifically, when vehicle horns are heard in a parking lot, the cloud platform will analyze the sounds collected by the microphones and generate congestion warnings. If the number of horn sounds collected by the microphones exceeds a preset threshold within a certain period, a suspected congestion alarm will be generated. For example, a suspected congestion alarm is generated if ten alarm records are generated within one minute. If the parking lot's microphones receive more than ten vehicle horn sounds within one minute, exceeding the preset threshold, a suspected congestion alarm will be generated, indicating severe traffic congestion in the area, requiring immediate attention from staff. Specifically, if the number of times a vehicle honks its horn within a certain period does not exceed a preset threshold, no suspected congestion alarm will be generated. Alternatively, if the number of horn sounds exceeds the threshold but the interval between each sound is too long, no alarm record will be generated. For example, if the microphone receives only 5 horn sounds within one minute, which does not exceed the preset threshold, no suspected congestion alarm will be generated. Or, even if the number of horn sounds exceeds the preset threshold of 10, if they occur within one hour (not one minute), no suspected congestion alarm will be generated. All the above examples are for illustrative purposes only and do not constitute any limitation.

[0060] In this embodiment of the invention, a parking lot early warning processing method is provided. This method uses a microphone to collect sound, judges the collected sound, and when the sound collected by the microphone is a horn sound, records the sound received by each microphone as a vehicle horn sound, generates a congestion process alarm, and reports the congestion process warning to a cloud platform. The congestion process warning includes the start time of the received sound, the end time of the sound, and the microphone number receiving the sound. The cloud platform determines the duration of each vehicle horn sound based on the collected start and end times and statistically analyzes the duration. When the cumulative duration of vehicle horn sounds exceeds a preset cumulative threshold within a certain period, a suspected congestion alarm is generated. If the cumulative duration of horn sounds does not exceed the preset threshold within a certain time period, or if multiple horn sounds exceed the threshold but the interval between each sound is too long, no alarm record is generated. Alternatively, the cloud platform can count the number of times a vehicle honks its horn. If the number of horns exceeds a preset threshold within a certain period, a suspected congestion alarm will be generated. If the number of horns does not exceed the preset threshold within a certain period, no suspected congestion alarm will be generated. Alternatively, if the number of horns exceeds the threshold multiple times but the interval between each horn is too long, no alarm record will be generated. The embodiments of the present invention can enable on-site staff to accurately receive alarm information and quickly process the alarmed area. If the area has a digital twin model, the suspected congestion area can be determined based on the sound from the microphone, and a semi-transparent light column can be used to visualize the digital twin model.

[0061] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0062] In one embodiment, a parking lot early warning processing device is provided, which corresponds one-to-one with the parking lot early warning processing method described in the above embodiments. For example... Figure 5 As shown, the parking lot early warning processing device includes a collection module, a processing module, and an output module. Detailed descriptions of each functional module are as follows:

[0063] A collection device receives congestion warnings from target microphones, wherein microphones are arranged at multiple different preset locations in the parking lot;

[0064] Specifically, when vehicles become congested in a parking lot, they will honk their horns. By deploying microphones in different locations within the parking lot, these horn sounds can be collected, allowing parking lot staff to address the congestion situation promptly.

[0065] The processing device generates suspected congestion alarm information based on the congestion warning fed back by the target microphone, the suspected congestion alarm information including the suspected congestion event area;

[0066] Specifically, after the microphone collects the sound, it will judge the sound. When the sound collected by the microphone is a horn tone, it will count the number of times the sound is heard. When the number of horn tones exceeds a preset number, an alarm record will be generated. When the duration of the horn tone exceeds a preset threshold, an alarm information record containing the start time of the sound, the end time of the sound, and the microphone number will also be generated. The alarm record includes the name of the alarm and the time of the alarm. Based on the alarm information record, the area of ​​suspected congestion event can be identified.

[0067] The output device generates a visual display interface based on the suspected congestion event area and the digital twin model when the parking lot has a corresponding digital twin model.

[0068] Specifically, when the parking lot has a digital twin model, the microphone collects vehicle sounds and generates a visual interface in the digital twin model. The visual interface includes the direction of the sound collected by the microphone. Semi-transparent light pillars appear in the digital twin model to indicate the direction of the sound source. The depth of the color of the semi-transparent light pillars in this direction indicates the distance of the sound source from the microphone. The closer the sound source is to the microphone, the darker the color. Based on the depth of the color of the semi-transparent light pillars, suspected congestion areas can be identified, and staff can quickly arrive to deal with the congestion.

[0069] This invention provides a parking lot early warning management device, applicable to various parking lots equipped with digital twins and microphones. The device includes: a collection unit for receiving congestion warnings from target microphones, wherein microphones are positioned at multiple preset locations within the parking lot; a processing unit for generating suspected congestion alarm information based on the congestion warnings from the target microphones, the suspected congestion alarm information including a suspected congestion event area; and an output unit for generating a visual display interface based on the suspected congestion event area and the digital twin model when a corresponding digital twin model exists for the parking lot. This parking lot early warning management device improves the user experience by using a digital twin model for digital management of the parking lot, significantly enhancing the intelligence level of dynamic parking lot management.

[0070] Specific limitations regarding the parking lot early warning processing device can be found in the limitations of the parking lot early warning processing method described above, and will not be repeated here. Each module in the aforementioned parking lot early warning processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0071] In one embodiment, a parking lot early warning management system is provided, which includes a cloud platform and at least one microphone deployed in the parking lot. The functions of each system are described in detail below:

[0072] The microphone is used to identify congestion alarms in the parking lot. The microphone monitors vehicle sounds in the parking lot and judges the sounds. When the sound collected by the microphone is a horn, it counts the number of sounds. When the number of horn sounds exceeds a preset number, an alarm record is generated. When the duration of the horn sound exceeds a preset threshold, an alarm information record containing the start time, end time, and microphone number is also generated and uploaded to the cloud platform.

[0073] The cloud platform is used to receive congestion warnings from target microphones, wherein microphones are deployed at multiple preset locations in the parking lot; based on the congestion warnings from the target microphones, it generates suspected congestion alarm information, which includes suspected congestion event areas; when the parking lot has a corresponding digital twin model, it generates a visual display interface based on the suspected congestion event areas and the digital twin model.

[0074] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database is used for parking lot early warning processing. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a parking lot early warning processing method.

[0075] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0076] A cloud platform includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement all the steps of the parking lot early warning management method; to avoid repetition, these steps will not be described again here.

[0077] In one embodiment, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements all the steps of the parking lot early warning management method, which will not be described in detail here to avoid repetition.

[0078] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0079] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A parking lot early warning management method, characterized in that, include: The system receives congestion warnings from the target microphones, wherein microphones are located at multiple preset locations in the parking lot. Based on the congestion warning fed back by the target microphone, a suspected congestion alarm message is generated, which includes the suspected congestion event area; When the parking lot has a corresponding digital twin model, a visual display interface is generated based on the suspected congestion event area and the digital twin model; The step of generating a visual display interface based on the suspected congestion event area and the digital twin model includes: The microphone positions are marked on the digital twin model, wherein the microphone positions are the same as the preset microphone positions in the parking lot; The digital twin model uses semi-transparent light beams to simulate the monitored sound volume and direction; The suspected congestion area is determined based on the semi-transparent light beam simulated by the microphone.

2. The parking lot early warning management method according to claim 1, characterized in that, The system generates a visual display interface based on the suspected congestion event area and the digital twin model, and also includes: When any microphone has direction-finding capability, it can monitor the direction of sound based on the sound source and mark the direction of the sound source based on the monitoring results; The direction of the sound source is visualized using a semi-transparent light bar, wherein the transparency of the semi-transparent light bar varies according to the volume of the sound detected by the microphone; the lower the volume of the detected sound, the higher the transparency.

3. The parking lot early warning management method according to claim 1, characterized in that, The suspected congestion alarm information also includes the alarm name and alarm time; Based on the sound detected by the microphone, the suspected congestion location is determined, and a suspected congestion alarm message is generated. The alarm message includes: alarm name, alarm time, and suspected event area.

4. The parking lot early warning management method according to claim 1, characterized in that, The step of generating suspected congestion alarm information based on the congestion warning fed back by the microphone includes: When each microphone receives a vehicle horn sound, it records the sound and generates a congestion warning, which is then reported to the cloud platform. The congestion warning includes the start time of the sound reception, the end time of the sound, and the microphone number that received the sound. The cloud platform determines the duration of each vehicle horn sound based on the collected start and end times of each sound and performs statistics on the duration of the vehicle horn sounds. When the cumulative duration of the vehicle horn sounds exceeds a preset cumulative threshold within a certain period of time, the suspected congestion alarm information is generated. The cloud platform counts the number of times a vehicle honks its horn. If the number of horns exceeds a preset threshold within a certain period of time, a suspected congestion alarm is generated.

5. The parking lot early warning management method according to claim 1, characterized in that, When a congestion warning is issued, the method further includes: Receive event information corresponding to the congestion warning, the event information including the event name of the congestion warning, the sound start time, the sound end time, and the microphone number; The event information corresponding to the congestion warning will be archived.

6. A parking lot early warning processing device, characterized in that: A collection device receives congestion warnings from target microphones, wherein microphones are arranged at multiple different preset locations in the parking lot; The processing device generates suspected congestion alarm information based on the congestion warning fed back by the target microphone, the suspected congestion alarm information including the suspected congestion event area; The output device generates a visual display interface based on the suspected congestion event area and the digital twin model when the parking lot has a corresponding digital twin model. The step of generating a visual display interface based on the suspected congestion event area and the digital twin model includes: marking the microphone position on the digital twin model, wherein the microphone position is the same as the preset microphone position in the parking lot; using a semi-transparent light column in the digital twin model to simulate the sound volume and direction of the monitored sound; and determining the suspected congestion area based on the semi-transparent light column simulated by the microphone.

7. A parking lot early warning management system, characterized in that, The parking lot early warning management system includes a cloud platform and at least one microphone deployed in the parking lot; The microphone is used to identify congestion alarms in the parking lot; The cloud platform is used to receive congestion warnings from target microphones, wherein microphones are deployed at multiple preset locations in the parking lot; based on the congestion warnings from the target microphones, suspected congestion alarm information is generated, including suspected congestion event areas; when the parking lot has a corresponding digital twin model, a visual display interface is generated based on the suspected congestion event areas and the digital twin model; The step of generating a visual display interface based on the suspected congestion event area and the digital twin model includes: marking the microphone position on the digital twin model, wherein the microphone position is the same as the preset microphone position in the parking lot; using a semi-transparent light column in the digital twin model to simulate the sound volume and direction of the monitored sound; and determining the suspected congestion area based on the semi-transparent light column simulated by the microphone.

8. A cloud platform, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the parking lot early warning management method as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the parking lot early warning management method as described in any one of claims 1 to 5.

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