CN113449709A - Non-motor vehicle traffic control method and device based on artificial intelligence and storage medium - Google Patents
Non-motor vehicle traffic control method and device based on artificial intelligence and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of community property management and discloses a non-motor vehicle traffic control method, a non-motor vehicle traffic control device and a storage medium based on artificial intelligence, wherein the method comprises the steps of acquiring a license plate number of a non-motor vehicle entering a community outlet area and a first face image of a rider; determining whether the non-motor vehicle is a cell registration vehicle based on the license plate number; determining whether the rider is a cell standing person based on the first face image; if the non-motor vehicle is a cell registration vehicle and the riding personnel are not cell frequent flyers, generating a question related to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle and playing the question in voice; converting the response voice for the question into a response text; matching the reply text with the registration information of the non-motor vehicle; and executing the traffic management policy corresponding to the matching result based on the matching result. The method, the device and the storage medium disclosed by the invention can prevent the non-motor vehicle from being stolen, and achieve a better anti-theft effect.
Description
Technical Field
The invention belongs to the technical field of community property management, and particularly relates to a non-motor vehicle traffic control method and device based on artificial intelligence and a storage medium.
Background
The non-motor vehicles gradually become daily travel tools for most citizens due to the advantages of energy conservation, environmental protection, convenient travel and the like, but meanwhile, the events that the non-motor vehicles parked in the community are stolen frequently occur.
In order to prevent the battery car from being stolen, a common method is to install a monitoring device in a parking area of the non-motor vehicle in a cell, and to prevent the non-motor vehicle from being stolen by monitoring the parking area of the non-motor vehicle. However, due to the large number of non-motorized vehicles in a cell, some non-motorized vehicles often fail to park in the monitoring area of the monitoring device, thereby resulting in a situation in which the non-motorized vehicles are stolen.
Therefore, how to provide an effective solution to prevent the theft of non-motor vehicles in a cell has become an urgent problem in the prior art.
Disclosure of Invention
The invention aims to provide a non-motor vehicle traffic control method, a non-motor vehicle traffic control device and a storage medium based on artificial intelligence, so that traffic control of non-motor vehicles in a community is facilitated, and the non-motor vehicles are prevented from being stolen.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a non-motor vehicle traffic control method based on artificial intelligence, which comprises the following steps:
acquiring a license plate number of a non-motor vehicle entering an exit area of a cell and a first face image of a rider on the non-motor vehicle;
determining whether the non-motor vehicle is a cell registration vehicle based on the license plate number;
determining whether the rider is a cell standing person based on the first face image;
if the non-motor vehicle is a cell registration vehicle and the riding personnel are not cell frequent flyers, generating a question related to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle and playing the question in voice;
converting a response voice to the question into a response text;
matching the reply text with the registration information of the non-motor vehicle;
and executing a traffic management policy corresponding to the matching result based on the matching result.
In one possible design, the method further includes:
judging whether a second face image matched with the first face image exists in a second face image of a historical riding person on the non-motor vehicle in a historical record of the non-motor vehicle entering a cell;
generating a question related to attribution of the non-motorized vehicle based on the registration information of the non-motorized vehicle if the non-motorized vehicle is a cell registration vehicle and the rider is not a cell resident, comprising:
generating a question related to attribution of the non-motor vehicle based on registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle, the rider is not a cell resident, and a face image matching the first face image does not exist in the second face image.
In one possible design, the executing, based on the matching result, a traffic management policy corresponding to the matching result includes:
if the reply text matches the registration information for the non-motor vehicle, opening a cell exit and associating the first facial image with the non-motor vehicle.
In one possible design, the generating a question related to attribution of the non-motorized vehicle based on the registration information of the non-motorized vehicle if the non-motorized vehicle is a cell registration vehicle and the rider is not a cell resident comprises:
generating a question related to attribution of the non-motorized vehicle based on the registration information of the non-motorized vehicle if the non-motorized vehicle is a cell registration vehicle, the rider is not a cell frequent occupant, and the first facial image is not associated with the non-motorized vehicle.
In one possible design, the executing, based on the matching result, a traffic management policy corresponding to the matching result includes:
if the reply text does not match the registration information of the non-motor vehicle, matching the first facial image with a facial image in a pre-established blacklist library;
if the face image matched with the first face image exists in the blacklist library, sending an alarm prompt;
and if the face image matched with the first face image does not exist in the blacklist library, generating prompt information to remind entrance guard personnel to carry out passage control.
In one possible design, the method further includes:
acquiring a monitoring video of a monitored area of a cell;
identifying a trajectory of a non-motor vehicle within the surveillance video;
when a target non-motor vehicle which enters a no-parking area exists, sending a voice control instruction to voice equipment of the no-parking area so as to enable the voice equipment to send out prompt voice.
In one possible design, after issuing the voice control instruction to the voice device in the no-stop zone, the method further includes:
identifying and marking the license plate number of the target non-motor vehicle;
when the license plate number of the non-motor vehicle entering the district exit area is the marked license plate number, sending out a voice prompt; and
canceling the marking of the license plate number of the target non-motor vehicle.
In a second aspect, the invention provides an artificial intelligence-based non-motor vehicle traffic control device, which includes:
an acquisition unit configured to acquire a license plate number of a non-motor vehicle entering an exit area of a cell and a first face image of a rider on the non-motor vehicle;
a first determination unit configured to determine whether the non-motor vehicle is a cell registration vehicle based on the license plate number;
a second determination unit configured to determine whether the rider is a cell standing person based on the first face image;
a generation unit configured to generate a question related to attribution of the non-motor vehicle based on registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle and the rider is not a cell resident;
a playing unit for playing the question by voice;
a conversion unit for converting a response voice to the question into a response text;
a matching unit for matching the reply text with the registered information of the non-motor vehicle;
and the control unit is used for executing the traffic management policy corresponding to the matching result based on the matching result.
In a third aspect, the invention provides an artificial intelligence-based non-motor vehicle traffic control device, which includes a memory, a processor and a transceiver, which are sequentially connected in a communication manner, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the artificial intelligence-based non-motor vehicle traffic control method.
In a fourth aspect, the present invention provides a computer-readable storage medium, having stored thereon instructions, which, when run on a computer, perform the artificial intelligence-based non-motor vehicle traffic management and control method as described in any one of the above.
At least one technical scheme adopted by one or more embodiments of the invention can achieve the following beneficial effects:
the method comprises the steps of determining whether a non-motor vehicle entering the exit area of a cell is a cell registered vehicle or not based on a license plate number, determining whether a rider is a cell frequent keeper or not based on a first face image, generating a question related to non-motor vehicle attribution according to registration information of the non-motor vehicle when the non-motor vehicle is a cell registered vehicle and the rider is not the cell frequent keeper, then judging that a response text aiming at the question is matched with the registration information of the non-motor vehicle, and executing a traffic management strategy corresponding to a matching result based on the matching result. Therefore, when the non-motor vehicle is driven to leave the cell, corresponding traffic management strategies can be adopted according to different situations, so that the situation that the non-motor vehicle is stolen is avoided, and a better anti-theft effect is achieved.
Drawings
Fig. 1 is a flowchart of a method for managing and controlling passage of a non-motor vehicle based on artificial intelligence according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an artificial intelligence-based non-motor vehicle traffic control device according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of another artificial intelligence-based non-motor vehicle traffic control device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In order to prevent the non-motor vehicle from being stolen, the embodiment of the application provides a non-motor vehicle traffic control method, a non-motor vehicle traffic control device and a storage medium based on artificial intelligence.
The non-motor vehicle traffic control method based on artificial intelligence can be applied to a background management terminal, and the background management terminal can be an entrance guard control host of a community entrance and exit, a background monitoring server or a monitoring host of the community and the like. For convenience of description, the embodiments of the present specification are described with reference to a background management terminal as an execution subject unless otherwise specified. The non-motor vehicle mainly refers to a battery vehicle for branding.
It is to be understood that the execution body does not constitute a limitation on the embodiments of the present description.
Optionally, the flow of the non-motor vehicle traffic control method based on artificial intelligence is shown in fig. 1, and may include the following steps:
step S101, acquiring a license plate number of a non-motor vehicle entering a community exit area and a first face image of a rider on the non-motor vehicle.
In the embodiment of the application, the area of the exit of the cell is provided with the image acquisition equipment, when a rider needs to leave the cell from the area of the exit of the cell when riding a non-motor vehicle, the image acquisition equipment can be used for acquiring the license plate image of the non-motor vehicle and the first face image of the rider on the non-motor vehicle, and the license plate number of the non-motor vehicle can be identified through license plate identification.
In this embodiment, the number of the image capturing devices may be one or more, for example, one image capturing device may be respectively disposed in front of and behind the area of the exit of the cell, the image capturing device disposed in front of the area of the exit of the cell is used to obtain a first face image of a rider on the non-motor vehicle, and the image capturing device disposed behind the area of the exit of the cell is used to obtain a license plate image of the non-motor vehicle. The image acquisition equipment in front of the district outlet area can be a face recognition camera of the district for owner traffic control.
And step S102, determining whether the non-motor vehicle is a cell registration vehicle or not based on the license plate number.
The background management terminal registers vehicle information of non-motor vehicles of cell users in advance, wherein the vehicle information comprises license plate numbers of the non-motor vehicles, owner information (such as owner names, contact phones and the like) and owner addresses and the like. After the license plate number of the non-motor vehicle is obtained, the background management terminal judges whether the non-motor vehicle is a cell registered vehicle or not according to the registered vehicle information.
And step S103, determining whether the passengers are the community standing persons or not based on the first face image.
In order to control passage through face recognition, the background management terminal also records face images of community residents in advance, after the first face image of the rider is obtained, feature matching is carried out on the first face image and the recorded face image of the community resident, and if the face image of the community resident has the face image with the feature matching degree exceeding the preset matching degree with the first face image, the rider is judged to be a community permanent person. Otherwise, the rider is determined not to be a cell resident.
And step S104, if the non-motor vehicle is a cell registration vehicle and the riding personnel is not a cell frequent flyer, generating a question related to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle and playing the question in voice.
If the non-motor vehicle is a cell check-in vehicle and the rider is not a cell resident, the rider may temporarily borrow the non-motor vehicle in recognition of the owner of the non-motor vehicle or the non-motor vehicle may be stolen by the rider. Therefore, in order to identify whether the non-motor vehicle is stolen by a rider, when the non-motor vehicle is a cell registered vehicle and the rider is not a cell resident, a question related to the attribution of the non-motor vehicle can be generated based on the registered information of the non-motor vehicle and played back by voice. If the non-motor vehicle is not a cell registration vehicle and/or the rider is a cell resident, the cell exit is opened directly for normal traffic of the non-motor vehicle.
The registration information of the non-motor vehicle comprises a license plate number, vehicle owner information (vehicle owner name, contact telephone and the like) and a vehicle owner address, wherein the license plate number can be directly known, but if the registration information is unfamiliar with the vehicle owner, a rider can obviously not know the vehicle owner name, the vehicle owner address and the like. Thus, in generating a non-motor vehicle attribution related question, a question related to the owner's name and/or the owner's address may be generated. Such as "what the owner's name or surname is", "several units the owner lives in", etc.
In one or more embodiments of the present application, before generating the problem related to the attribution of the non-motor vehicle, it may be further determined whether a facial image matching the first facial image exists in the second facial image of the historical riders on the non-motor vehicle in the history of the entering of the non-motor vehicle into the cell. If the facial image matched with the first facial image exists in the second facial image of the historical riding personnel on the non-motor vehicle in the historical record, the situation that the riding personnel on the non-motor vehicle rides the non-motor vehicle to enter and exit the cell once is shown, and the riding personnel is familiar with the owner of the non-motor vehicle, so that the problem related to the attribution of the non-motor vehicle does not need to be generated, and the exit of the cell is directly opened to facilitate the normal passing of the non-motor vehicle.
If the second facial image does not have a facial image that matches the first facial image, then it is indicated that a rider on the non-motor vehicle, who is unfamiliar with the owner of the non-motor vehicle, has not ridden the non-motor vehicle into or out of the cell. Therefore, if the non-motor vehicle is a cell registration vehicle, the rider is not a cell frequent flyer, and there is no face image matching the first face image in the second face image, a problem relating to the attribution of the non-motor vehicle is generated based on the registration information of the non-motor vehicle.
In one or more embodiments of the present application, the facial images of persons familiar with the owner of the non-motor vehicle may also be associated with (the license plate number of) the non-motor vehicle. If the first facial image is associated with a non-motor vehicle, it indicates that the rider is familiar with the owner of the non-motor vehicle, and therefore does not need to generate the problems associated with non-motor vehicle ownership, but rather directly opens the cell exit to facilitate normal traffic for the non-motor vehicle. If the non-motor vehicle is a cell registration vehicle, the rider is not a cell frequent occupant, and the first facial image is not associated with the non-motor vehicle, then a problem is generated relating to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle.
In one or more embodiments of the present application, before generating the problem related to the non-motor vehicle affiliation, it may be determined whether a common travel record of a rider and a registered user of the non-motor vehicle exists in the history image according to the acquired history image, and if so, it indicates that the rider is familiar with the owner of the non-motor vehicle. If the non-motor vehicle is a cell registered vehicle, the rider is not a cell resident, and a common travel record of the rider and a registered user of the non-motor vehicle does not exist in the acquired history image, a problem related to attribution of the non-motor vehicle is generated based on the registered information of the non-motor vehicle.
The fact that the common travel record of the riding person and the registered users of the non-motor vehicle exists in the history image can mean that the registered users of the riding person and the non-motor vehicle exist in the history image at the same time, the distance between the two does not exceed a preset distance, the face orientation between the two is opposite, or the two have interactive action.
Step S105 converts the response voice to the question into a response text.
In order to avoid theft of non-motor vehicles, which are not the cell residents, but are the vehicles of the cell residents, it is necessary for the riders to respond to the voice play question to verify that the riders are familiar with the owner of the vehicle. In the embodiment of the application, the area of the outlet of the cell is provided with the voice collecting device, the answer voice of the riding personnel for the question can be collected and uploaded to the background management terminal, and the answer voice is converted into the answer text by the background management terminal.
Step S106, matching the reply text with the registration information of the non-motor vehicle.
And if the matching degree of the reply text and the registration information of the non-motor vehicle exceeds a set threshold value, determining that the reply text is matched with the registration information of the non-motor vehicle, and otherwise, determining that the reply text is not matched with the registration information of the non-motor vehicle.
In step S107, a traffic management policy corresponding to the matching result is executed based on the matching result.
Specifically, if the reply text does not match the registered information of the non-motor vehicle, the first face image is matched with the face images in the black list library established in advance.
In this embodiment, the blacklist library may be established in a third-party server, such as a public security networking system. Or the system can be established in a background management terminal.
After the reply text is matched with the registration information of the non-motor vehicle, if the reply text is not matched with the registration information of the non-motor vehicle, the first face image can be matched with the face image in a pre-established blacklist library, a large number of face images of a thief are recorded in the blacklist library, if the face image matched with the first face image exists in the blacklist library, the non-motor vehicle is probably stolen, and an alarm prompt can be given to prompt a doorkeeper to take corresponding measures.
If the face image matched with the first face image does not exist in the blacklist library, the possibility that the non-motor vehicle is stolen is indicated, and prompt information is generated at the moment to remind a guard to carry out manual inquiry so as to carry out traffic control according to a manual inquiry result.
If the reply text is matched with the registration information of the non-motor vehicle, it indicates that the rider is familiar with the owner of the vehicle and the non-motor vehicle does not belong to the stolen situation, at the moment, the opening of the cell outlet can be controlled, and meanwhile, the first face image is associated with the non-motor vehicle, so that the rider can directly pass when riding the non-motor vehicle again to leave the cell, the passing efficiency is ensured, and the travelling experience is improved.
In summary, according to the artificial intelligence-based non-motor vehicle traffic control method provided in the embodiment of the present application, it is determined whether a non-motor vehicle entering a cell exit area is a cell registered vehicle based on a license plate number, it is determined whether a rider is a cell frequent flyer based on a first face image, and when the non-motor vehicle is a cell registered vehicle and the rider is not a cell frequent flyer, a question related to non-motor vehicle affiliation is generated according to registration information of the non-motor vehicle, then it is determined that a reply text for the question matches with the registration information of the non-motor vehicle, and a traffic management policy corresponding to a matching result is executed based on the matching result. Therefore, when the non-motor vehicle is driven to leave the cell, corresponding traffic management strategies can be adopted according to different situations, so that the situation that the non-motor vehicle is stolen is avoided, and a better anti-theft effect is achieved. Meanwhile, if the reply text is matched with the registration information of the non-motor vehicle, the first face image is associated with the non-motor vehicle, so that the rider can directly pass when riding the non-motor vehicle again and leaving the cell, the passing efficiency is ensured, and the traveling experience is improved. In addition, the historical record of the non-motor vehicle entering the cell, whether the first face image of the rider is associated with the non-motor vehicle and the common trip record of the rider and the registered users of the non-motor vehicle are also considered before the problem related to the attribution of the non-motor vehicle is generated, so that the personnel normally driving the non-motor vehicle can be further accurately analyzed, the personnel normally driving the non-motor vehicle can timely pass through the system, and the passing experience is improved.
On the basis of the foregoing technical solution, the present embodiment further specifically proposes a first possible design for preventing illegal parking of a non-motor vehicle, which may include, but is not limited to, the following steps:
step S201, a monitoring video of a monitored area of a cell is obtained.
In the embodiment of the application, the cell is provided with video monitoring equipment for acquiring a monitoring video of a monitored area of the cell. The monitored area can be downstairs of the cell or some important monitoring area in the cell.
And step S202, identifying the running track of the non-motor vehicle in the monitoring video.
Specifically, when the moving track of the non-motor vehicle in the surveillance video is identified, the non-motor vehicle in each frame of image of the surveillance video can be identified in a contour identification mode, and then the moving track of the non-motor vehicle is calculated according to the pixel coordinates of the non-motor vehicle in the adjacent image frame of the surveillance video.
Step S203, when the target non-motor vehicle which is driven into the no-parking area exists, sending a voice control instruction to the voice equipment of the no-parking area so as to enable the voice equipment to send out prompt voice.
A no-parking area is arranged in the cell, and the no-parking area may be an area where each unit building is located in the cell, a doorway area of each unit building, an area near an elevator, or other areas where parking of non-motor vehicles is prohibited in the cell, and the embodiment of the present invention is not particularly limited.
The non-stop area is provided with voice equipment for reminding a user of not parking the non-motor vehicle in violation of rules and regulations through broadcast voice.
After the running track of the non-motor vehicle is identified, whether a target non-motor vehicle driving into the no-parking area exists can be judged according to the running track of the non-motor vehicle and the position of the no-parking area. If the target non-motor vehicle driving into the no-parking area exists, a voice control instruction is sent to the voice equipment of the no-parking area, so that the voice equipment sends prompt voice to remind a user of not stopping the non-motor vehicle in the no-parking area, the non-motor vehicle is prevented from being randomly stopped and placed, the order of the cell is purified, and safety accidents caused by illegal parking are avoided.
And step S204, identifying and marking the license plate number of the target non-motor vehicle.
Step S205, when the license plate number of the non-motor vehicle entering the district exit area is the marked license plate number, a voice prompt is sent out, and the marking of the license plate number of the target non-motor vehicle is cancelled.
When the license plate number of the non-motor vehicle entering the district exit area is the marked license plate number, the license plate number of the non-motor vehicle entering the district exit area is marked, namely the non-motor vehicle entering the district exit area drives into the no-parking area, and at the moment, a voice prompt is sent out to provide a user so as to prevent the user from parking the non-motor vehicle into the no-parking area next time when parking the non-motor vehicle, so that the non-motor vehicle is prevented from being parked randomly and randomly, the order of the district is purified, and the safety accident caused by illegal parking is avoided. Meanwhile, after the voice prompt is sent out, the mark of the license plate number of the target non-motor vehicle is cancelled, when the non-motor vehicle exits the cell next time, the repeated reminding is not carried out, and the influence on the passing experience of a user due to the repeated reminding is avoided.
Referring to fig. 2, an embodiment of the present application provides an artificial intelligence-based non-motor vehicle traffic control apparatus, including:
an acquisition unit configured to acquire a license plate number of a non-motor vehicle entering an exit area of a cell and a first face image of a rider on the non-motor vehicle;
a first determination unit configured to determine whether the non-motor vehicle is a cell registration vehicle based on the license plate number;
a second determination unit configured to determine whether the rider is a cell standing person based on the first face image;
a generation unit configured to generate a question related to attribution of the non-motor vehicle based on registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle and the rider is not a cell resident;
a playing unit for playing the question by voice;
a conversion unit for converting a response voice to the question into a response text;
a matching unit for matching the reply text with the registered information of the non-motor vehicle;
and the control unit is used for executing the traffic management policy corresponding to the matching result based on the matching result.
As shown in fig. 3, an embodiment of the present application further provides another artificial intelligence-based non-motor vehicle traffic control apparatus, which includes a memory, a processor and a transceiver, which are sequentially connected in a communication manner, where the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the artificial intelligence-based non-motor vehicle traffic control apparatus method according to the foregoing embodiment.
By way of specific example, the Memory may include, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Flash Memory (Flash Memory), a first-in-first-out Memory (FIFO), a first-in-last-out Memory (FILO), and/or the like; the processor may not be limited to a processor adopting an architecture processor such as a model STM32F105 series microprocessor, an arm (advanced RISC machines), an X86, or a processor of an integrated NPU (neutral-network processing unit); the transceiver may be, but is not limited to, a WiFi (wireless fidelity) wireless transceiver, a bluetooth wireless transceiver, a General Packet Radio Service (GPRS) wireless transceiver, a ZigBee protocol (ieee 802.15.4 standard-based low power local area network protocol), a 3G transceiver, a 4G transceiver, and/or a 5G transceiver, etc.
The embodiment of the present application provides a computer-readable storage medium storing instructions including the above-mentioned instructions of the artificial intelligence-based non-motor vehicle traffic control method, that is, the computer-readable storage medium stores instructions that, when running on a computer, perform the artificial intelligence-based non-motor vehicle traffic control method as described above. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, floppy disks, optical disks, hard disks, flash memories, flash disks and/or Memory sticks (Memory sticks), etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
The present embodiment also provides a computer program product containing instructions which, when run on a computer, can be used to make the computer execute the artificial intelligence based method for managing and controlling the passage of non-motor vehicles according to the above embodiments, wherein the computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
Finally, it should be noted that: the above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A non-motor vehicle traffic control method based on artificial intelligence is characterized by comprising the following steps:
acquiring a license plate number of a non-motor vehicle entering an exit area of a cell and a first face image of a rider on the non-motor vehicle;
determining whether the non-motor vehicle is a cell registration vehicle based on the license plate number;
determining whether the rider is a cell standing person based on the first face image;
if the non-motor vehicle is a cell registration vehicle and the riding personnel are not cell frequent flyers, generating a question related to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle and playing the question in voice;
converting a response voice to the question into a response text;
matching the reply text with the registration information of the non-motor vehicle;
and executing a traffic management policy corresponding to the matching result based on the matching result.
2. The artificial intelligence based non-motor vehicle traffic management and control method according to claim 1, further comprising:
judging whether a second face image matched with the first face image exists in a second face image of a historical riding person on the non-motor vehicle in a historical record of the non-motor vehicle entering a cell;
generating a question related to attribution of the non-motorized vehicle based on the registration information of the non-motorized vehicle if the non-motorized vehicle is a cell registration vehicle and the rider is not a cell resident, comprising:
generating a question related to attribution of the non-motor vehicle based on registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle, the rider is not a cell resident, and a face image matching the first face image does not exist in the second face image.
3. The artificial intelligence-based non-motor vehicle traffic control method according to claim 1, wherein executing a traffic management policy corresponding to the matching result based on the matching result comprises:
if the reply text matches the registration information for the non-motor vehicle, opening a cell exit and associating the first facial image with the non-motor vehicle.
4. The artificial intelligence-based non-motor vehicle traffic management and control method according to claim 3, wherein the generating of the question related to the attribution of the non-motor vehicle based on the registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle and the rider is not a cell resident comprises:
generating a question related to attribution of the non-motorized vehicle based on the registration information of the non-motorized vehicle if the non-motorized vehicle is a cell registration vehicle, the rider is not a cell frequent occupant, and the first facial image is not associated with the non-motorized vehicle.
5. The artificial intelligence-based non-motor vehicle traffic control method according to claim 1, wherein executing a traffic management policy corresponding to the matching result based on the matching result comprises:
if the reply text does not match the registration information of the non-motor vehicle, matching the first facial image with a facial image in a pre-established blacklist library;
if the face image matched with the first face image exists in the blacklist library, sending an alarm prompt;
and if the face image matched with the first face image does not exist in the blacklist library, generating prompt information to remind entrance guard personnel to carry out passage control.
6. The artificial intelligence based non-motor vehicle traffic management and control method according to claim 1, further comprising:
acquiring a monitoring video of a monitored area of a cell;
identifying a trajectory of a non-motor vehicle within the surveillance video;
when a target non-motor vehicle which enters a no-parking area exists, sending a voice control instruction to voice equipment of the no-parking area so as to enable the voice equipment to send out prompt voice.
7. The artificial intelligence-based non-motor vehicle traffic control method according to claim 6, wherein after the voice control instruction is issued to the voice device in the no-parking area, the method further comprises:
identifying and marking the license plate number of the target non-motor vehicle;
when the license plate number of the non-motor vehicle entering the district exit area is the marked license plate number, sending out a voice prompt; and
canceling the marking of the license plate number of the target non-motor vehicle.
8. The utility model provides a current management and control device of non-motor vehicle based on artificial intelligence which characterized in that includes:
an acquisition unit configured to acquire a license plate number of a non-motor vehicle entering an exit area of a cell and a first face image of a rider on the non-motor vehicle;
a first determination unit configured to determine whether the non-motor vehicle is a cell registration vehicle based on the license plate number;
a second determination unit configured to determine whether the rider is a cell standing person based on the first face image;
a generation unit configured to generate a question related to attribution of the non-motor vehicle based on registration information of the non-motor vehicle if the non-motor vehicle is a cell registration vehicle and the rider is not a cell resident;
a playing unit for playing the question by voice;
a conversion unit for converting a response voice to the question into a response text;
a matching unit for matching the reply text with the registered information of the non-motor vehicle;
and the control unit is used for executing the traffic management policy corresponding to the matching result based on the matching result.
9. An artificial intelligence-based non-motor vehicle traffic control device, comprising a memory, a processor and a transceiver which are sequentially connected in a communication manner, wherein the memory is used for storing a computer program, the transceiver is used for receiving and sending messages, and the processor is used for reading the computer program and executing the artificial intelligence-based non-motor vehicle traffic control method according to any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon instructions for performing the artificial intelligence based method for managing the passage of a non-motor vehicle according to any one of claims 1 to 7 when the instructions are executed on a computer.
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