CN117011803A - Electric vehicle monitoring method, device, equipment, medium and shared electric vehicle system - Google Patents
Electric vehicle monitoring method, device, equipment, medium and shared electric vehicle system Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 135
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000006399 behavior Effects 0.000 claims abstract description 60
- 238000001514 detection method Methods 0.000 claims abstract description 34
- 230000009471 action Effects 0.000 claims abstract description 33
- 238000012806 monitoring device Methods 0.000 claims abstract description 8
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 description 6
- 230000001133 acceleration Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 2
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
Abstract
The invention provides an electric vehicle monitoring method, an electric vehicle monitoring device, electric vehicle monitoring equipment, a medium and a shared electric vehicle system, and relates to the technical field of electric vehicle supervision, wherein the electric vehicle monitoring method comprises the following steps: acquiring first monitoring data of the electric vehicle; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the electric vehicle pushing behavior is determined to exist, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera. By the mode, dependence on external security monitoring video is eliminated; after determining that the user pushes the electric vehicle, judging whether the electric vehicle enters a building or an elevator or not, and directly detecting the electric vehicle in real time based on the second monitoring data, so that the use of a complex model is reduced, the detection pressure is reduced, and meanwhile, the accuracy of a judgment result is improved in a double detection mode, and the supervision of the electric vehicle user's illegal behaviors is realized.
Description
Technical Field
The invention relates to the technical field of electric vehicle supervision, in particular to an electric vehicle monitoring method, an electric vehicle monitoring device, electric vehicle monitoring equipment, a medium and a shared electric vehicle system.
Background
Electric vehicles are popular in the market as convenient vehicles, but the illegal behaviors of users when using the electric vehicles are still endless. The electric vehicle enters a building and even takes an elevator, so that fire accidents are easy to cause, and therefore, the user needs to monitor the illegal actions of pushing the electric vehicle into the building and taking the elevator to go upstairs.
Currently, illegal behaviors of users can be monitored based on security monitoring cameras arranged in building entrances and exits or elevators.
However, in a building or an elevator where the security monitoring camera is not installed, supervision of user illegal behaviors cannot be achieved. In addition, since the security monitoring video is not normally opened to the outside, in an actual application scene, it is difficult to monitor the user illegal behaviors through the security monitoring video.
For operators sharing electric vehicles, the actions of entering buildings and taking elevators by the user cart need to be monitored, and user illegal actions are managed, but data in a security system are generally difficult to obtain.
Disclosure of Invention
The invention provides an electric vehicle monitoring method, device, equipment, medium and a shared electric vehicle system, which are used for solving the defect that in the prior art, illegal behaviors of electric vehicle users are difficult to monitor in a building or an elevator without a security monitoring camera or in a scene that security monitoring video is not opened.
The invention provides an electric vehicle monitoring method, which comprises the following steps: acquiring first monitoring data of the electric vehicle; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
According to the electric vehicle monitoring method provided by the invention, the first monitoring data comprise electric door state data, cushion bearing weight data acquired based on a sensor and auxiliary pushing system state data; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data, including: if the magnitude of the decrease of the cushion load magnitude exceeds the first preset threshold value based on the cushion load weight data and the electric door is in the no-output state based on the electric door state data or the auxiliary pushing system is in the starting state based on the auxiliary pushing system state data, the behavior of pushing the electric vehicle by the user is determined.
According to the electric vehicle monitoring method provided by the invention, the first monitoring data comprise electric door state data and driving speed data; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data, including: and if the driving speed value is lower than the second preset threshold value based on the driving speed data and the electric door is in the no-output state based on the electric door state data, determining that the behavior of pushing the electric vehicle exists for the user.
According to the electric vehicle monitoring method provided by the invention, whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data, and the method comprises the following steps: inputting the gesture data into a gesture detection model; the gesture detection model is obtained by training based on gesture data samples and corresponding sample detection results; and acquiring a first judging result which is output by the gesture detection model and is used for judging whether the user of the electric vehicle has illegal behaviors.
According to the electric vehicle monitoring method provided by the invention, whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data, and the method comprises the following steps: inputting the image data into an image recognition model; the image recognition model is obtained based on elevator environment samples, indoor environment samples, outdoor environment samples and corresponding sample labels; and acquiring a second judging result which is output by the image recognition model and is used for judging whether the electric vehicle user has illegal behaviors or not.
According to the electric vehicle monitoring method provided by the invention, the image recognition model is arranged at the rear-end server; inputting image data into an image recognition model, comprising: uploading the image data to a back-end server; the back-end server inputs the image data to the image recognition model.
The invention also provides an electric vehicle monitoring device, which comprises: the acquisition module is used for acquiring first monitoring data of the electric vehicle; the first judging module is used for judging whether the behavior of pushing the electric vehicle exists or not based on the first monitoring data; the second judging module is used for acquiring second monitoring data of the electric vehicle if the user is determined to have the behavior of pushing the electric vehicle, and judging whether the user of the electric vehicle has illegal behaviors according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the electric vehicle monitoring method according to any one of the above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of monitoring an electric vehicle as described in any of the above.
The invention also provides a shared electric vehicle system, comprising: the system comprises a plurality of shared electric vehicles, wherein identification marks are arranged on the shared electric vehicles; the user terminal is used for requesting to use the shared electric vehicle by scanning the identification mark; the server issues a command to start the shared electric vehicle requested to be used by the user terminal according to the request and payment information of the user terminal; the shared electric vehicle is also used for executing the electric vehicle monitoring method according to any one of the above alone or in combination with a server.
The method, the device, the equipment, the medium and the shared electric vehicle system for monitoring the electric vehicle acquire first monitoring data of the electric vehicle; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera. By the mode, as the gesture data or the image data shot by the vehicle-mounted camera can be directly acquired based on the components configured by the electric vehicle, dependence on external security monitoring video is eliminated; most users push the electric vehicle into a building or an elevator in a pushing manner, so that whether the users have the action of pushing the electric vehicle or not can be judged based on the first monitoring data, and preliminary judgment on the illegal actions of the users of the electric vehicle is realized; after determining that the user pushes the electric vehicle, judging whether the electric vehicle enters a building or an elevator or not, and directly detecting the electric vehicle in real time based on the second monitoring data, so that the use of a complex model is reduced, the detection pressure is reduced, and meanwhile, the accuracy of a judgment result is improved in a double detection mode, and the supervision of the electric vehicle user's illegal behaviors is realized.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an electric vehicle monitoring method provided by the invention;
fig. 2 is a schematic structural diagram of the electric vehicle monitoring device provided by the invention;
fig. 3 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flow chart of an electric vehicle monitoring method provided by the present invention, in this embodiment, the electric vehicle monitoring method specifically includes steps S110 to S130, and each step specifically includes the following steps:
s110: and acquiring first monitoring data of the electric vehicle.
The first monitoring data of the electric vehicle refers to data reflecting the running state of the electric vehicle, such as running speed data, acceleration data, running direction data, cushion bearing weight data, and the like.
The first monitoring data may be acquired by a sensor provided on the electric vehicle.
S120: and judging whether the behavior of pushing the electric vehicle exists or not based on the first monitoring data.
The first monitoring data may reflect a relevant behavior of the user.
For example, if the cushion load data is basically unchanged or fluctuates in a small extent during the running of the electric vehicle, it is indicated that the user is running on a smooth road, and if the fluctuation range of the cushion load data is greater than a certain threshold value, it is indicated that the user is running on a rugged road. If the running speed drops rapidly, the user is indicated to be probably braking.
Because the first monitoring data can reflect the related behavior of the user, whether the behavior of pushing the electric vehicle exists or not can be judged based on the first monitoring data.
Most users push the electric vehicle into a building or an elevator in a pushing manner, so that whether the electric vehicle user has illegal behaviors can be primarily judged based on whether the user has the behavior of pushing the electric vehicle.
S130: if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors is judged according to the second monitoring data.
The second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
The posture data refers to data reflecting the posture of the electric vehicle, and can be acquired by a sensor.
In general, the sensor may comprise an inertial measurement unit (Inertial measurement unit, IMU), which is a device for measuring the three-axis attitude angle (or angular velocity) and acceleration of the object. An inertial measurement unit is provided with a triaxial gyroscope and three-directional accelerometers to measure angular velocity and acceleration of an object in three-dimensional space, and to calculate the attitude of the object therefrom.
The gesture data may reflect an offence of the user of the electric vehicle.
For example, when the electric vehicle is located in the running elevator, the ascending or descending of the elevator affects the acceleration of the electric vehicle in the vertical direction, so that the posture of the electric vehicle finally calculated by the inertia measurement unit changes, and further, the electric vehicle user can be judged to have illegal behaviors.
The image data shot by the vehicle-mounted camera comprises a video or an image of the environment where the electric vehicle is located, so that whether the electric vehicle user has illegal behaviors can be judged based on the environment where the electric vehicle is located in the image data shot by the vehicle-mounted camera.
After determining that the user has the action of pushing the electric vehicle, whether the electric vehicle enters the elevator can be judged based on second monitoring data of the electric vehicle, so that secondary judgment on the illegal action of the user of the electric vehicle is realized, and the accuracy of a judgment result is improved through a double detection mode.
Optionally, second monitoring data is input to the trained model to enable automatic identification judgment.
Optionally, a manual identification determination is made by the relevant staff based on the second monitoring data.
According to the electric vehicle monitoring method, first monitoring data of an electric vehicle are obtained; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera. By the mode, as the gesture data or the image data shot by the vehicle-mounted camera can be directly acquired based on the components configured by the electric vehicle, dependence on external security monitoring video is eliminated; most users push the electric vehicle into a building or an elevator in a pushing manner, so that whether the users have the action of pushing the electric vehicle or not can be judged based on the first monitoring data, and preliminary judgment on the illegal actions of the users of the electric vehicle is realized; after determining that the user pushes the electric vehicle, judging whether the electric vehicle enters a building or an elevator or not, and directly detecting the electric vehicle in real time based on the second monitoring data, so that the use of a complex model is reduced, the detection pressure is reduced, and meanwhile, the accuracy of a judgment result is improved in a double detection mode, and the supervision of the electric vehicle user's illegal behaviors is realized.
In some embodiments, the first monitoring data includes door status data, cushion load weight data acquired based on the sensor, and auxiliary propulsion system status data.
In particular, the cushion load weight data may be acquired based on a weight sensor or a pressure sensor.
Alternatively, a weight sensor or pressure sensor may be mounted on the cushion of the electric vehicle to directly acquire cushion load weight data.
Optionally, after the electric vehicle is suspended, a weight sensor or a pressure sensor is installed at the bottom of the electric vehicle, and the cushion bearing weight data is indirectly determined based on the data acquired by the weight sensor or the pressure sensor installed at the bottom of the electric vehicle.
Judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data, including: and if the magnitude of the decrease of the cushion load magnitude exceeds the first preset threshold value based on the cushion load weight data and the electric switch is in the no-output state based on the electric switch state data, determining that the behavior of pushing the electric vehicle exists for the user.
Most users push the electric vehicle into a building or an elevator in a pushing manner, and the users need to get off the electric vehicle before pushing the electric vehicle, and the getting off action can cause the change of the cushion bearing weight due to the existence of the getting off action, so that the cushion bearing weight data acquired based on the sensor is changed.
Specifically, if the magnitude of the drop in the cushion load magnitude exceeds the first preset threshold, it is indicated that the user may be pushing off the vehicle.
However, in a practical scenario, the user may also be able to walk the electric vehicle into a building or an elevator by stepping, since the user does not need to get off but sits on the seat and steps, the seat load data acquired based on the sensor is unchanged. Therefore, the detection accuracy of the method for determining that the user has the action of pushing the electric vehicle based on the cushion bearing weight data obtained by the sensor is not high, and the pedaling action of the user cannot be detected.
In order to improve the accuracy of the judgment result, cooperative judgment based on the valve state data is also required.
Specifically, if it is determined that the magnitude of the drop in the cushion load magnitude exceeds a first preset threshold based on the cushion load weight data and it is determined that the electric switch is in the no-output state based on the electric switch state data, it is determined that there is a behavior of pushing the electric vehicle by the user.
Generally, in a normal running process of an electric vehicle, since stored electric energy is required to be continuously consumed to provide power, an electric door of the electric vehicle is always in an output state.
However, when the user pushes, the electric door of the electric vehicle is in a non-output state because of the electric energy which is not consumed.
Therefore, it is possible to determine whether or not there is a behavior of pushing the electric vehicle by the user based on both the magnitude of the decrease in the cushion load magnitude and the state of the electric door.
Judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data, including: if the auxiliary pushing system is determined to be in the starting state based on the auxiliary pushing system state data, determining that the user has the action of pushing the electric vehicle.
And part of electric vehicles are provided with auxiliary pushing systems, so that whether a user is pushing or not can be directly detected.
If the auxiliary pushing system is in a starting state, the user is indicated to be pushing; if the auxiliary pushing system is in a closed state, the user is not pushing.
According to the electric vehicle monitoring method, whether the user has the action of pushing the electric vehicle is judged based on the data acquired by the sensor, and the detection result is accurate.
In some embodiments, the first monitoring data includes valve status data and speed data.
Judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data, including: and if the driving speed value is lower than the second preset threshold value based on the driving speed data and the electric door is in the no-output state based on the electric door state data, determining that the behavior of pushing the electric vehicle exists for the user.
In order to ensure driving safety, all electric vehicles have the function of detecting driving speed or acceleration.
If the electric vehicle is not provided with the required sensor, whether the user has the action of pushing the electric vehicle or not can be judged based on the electric door state data and the driving speed data.
Generally, the running speed of an electric vehicle during normal running is faster than the running speed of the electric vehicle when the user pushes the electric vehicle, so that it is possible to determine whether the user has a behavior of pushing the electric vehicle based on a change in the running speed value.
It is understood that in order to exclude the possibility that the electric vehicle keeps running normally at a low speed, it is also necessary to cooperatively judge based on the electric door state data.
Specifically, if the driving speed value is determined to be lower than the second preset threshold value based on the driving speed data, and the electric door is determined to be in the no-output state based on the electric door state data, the user is determined to have the behavior of pushing the electric vehicle.
According to the electric vehicle monitoring method, under the condition that the electric vehicle is not provided with the required sensor, whether the user acts to push the electric vehicle or not can be judged directly based on the electric door state data and the driving speed data, no additional equipment is required to be installed, and the electric vehicle monitoring method is low in cost and high in practicability.
In some embodiments, determining whether the electric vehicle user has an offence according to the second monitoring data includes: inputting the gesture data into a gesture detection model; the gesture detection model is obtained by training based on gesture data samples and corresponding sample detection results; and acquiring a first judging result which is output by the gesture detection model and is used for judging whether the user of the electric vehicle has illegal behaviors.
Because the gesture data can reflect the illegal behaviors of the electric vehicle user, the association between the gesture data and the illegal behaviors of the user can be mined, and a corresponding gesture detection model is trained to realize automatic identification and judgment.
Specifically, the gesture detection model is trained based on the gesture data sample and the corresponding sample detection result, and after gesture data is input into the trained gesture detection model, a first discrimination result output by the gesture detection model can be obtained.
The first discrimination result may be that the user has a violation or that the user does not have a violation.
In some embodiments, determining whether the electric vehicle user has an offence according to the second monitoring data includes: inputting the image data into an image recognition model; the image recognition model is obtained based on elevator environment samples, indoor environment samples, outdoor environment samples and corresponding sample labels; and acquiring a second judging result which is output by the image recognition model and is used for judging whether the electric vehicle user has illegal behaviors or not.
The image data shot by the vehicle-mounted camera comprises a video or an image of the environment where the electric vehicle is located, and whether the electric vehicle user has illegal behaviors can be judged based on the environment where the electric vehicle is located in the image data shot by the vehicle-mounted camera.
Generally, the environment in which an electric vehicle is located can be divided into three types: elevator environment, indoor environment, and outdoor environment. Because the characteristics of the three environments are different, whether the electric vehicle enters a building or an elevator can be judged based on the difference of the environmental characteristics.
Specifically, the image recognition model is trained based on the elevator environment sample, the indoor environment sample, the outdoor environment sample and the corresponding sample discrimination results, and after the image data shot by the vehicle-mounted camera is input into the trained image recognition model, a second discrimination result output by the image recognition model can be obtained.
The second judging result can be the recognition result of the situation that the user has the illegal action or the user does not have the illegal action and the environment where the electric vehicle is located.
Specifically, for the input image data, the image recognition model may first determine whether the environment in which the electric vehicle is located is an outdoor environment; if the environment where the electric vehicle is located is not the outdoor environment, further judging whether the environment where the electric vehicle is located is the indoor environment or not; if the environment of the electric vehicle is not the indoor environment, further judging whether the environment of the electric vehicle is the elevator environment or not.
Optionally, the data shot by the camera is cut and screened, and the video or the image needing to be identified and judged is determined, so that the operation amount of image identification is reduced.
Preferably, the data after determining that the user has the action of pushing the electric vehicle is cut and screened out from the image data shot by the vehicle-mounted camera and used as the input data of the image recognition model, so that the number of videos or images acquired and stored by the electric vehicle is reduced, the operation amount of image recognition is reduced, and the detection computational power requirement is reduced.
Alternatively, for an electric vehicle with high hardware performance, the image recognition model may be provided on the electric vehicle.
Optionally, a plurality of cameras can be arranged to shoot and acquire all-round video or images of the environment where the electric vehicle is located, so that the accuracy of the result of the subsequent judgment based on the data shot by the cameras is ensured.
Alternatively, the camera may take a photograph based on a preset period.
After determining that the user has the action of pushing the electric vehicle, judging whether the electric vehicle enters the elevator through the image recognition model, and not needing to judge in real time through the image recognition model, the pressure of local detection can be reduced, and the local rapid detection is realized.
In some embodiments, the image recognition model is disposed at a backend server.
For electric vehicles with low hardware performance, the image recognition model is arranged on a back-end server.
Inputting image data into an image recognition model, comprising: uploading the image data to a back-end server; the back-end server inputs the image data to the image recognition model.
The image recognition model is arranged on the rear end server, the image data shot by the vehicle-mounted camera is uploaded to the rear end server, the rear end server inputs the image data shot by the vehicle-mounted camera into the image recognition model for recognition and judgment, a second judgment result is obtained, and the rear end server returns the second judgment result to the electric vehicle, so that the flow required by local detection can be reduced while the performance requirement on the electric vehicle is reduced.
The present invention also provides an electric vehicle monitoring device, referring to fig. 2, fig. 2 is a schematic structural diagram of the electric vehicle monitoring device provided by the present invention, in this embodiment, the electric vehicle monitoring device includes an obtaining module 210, a first judging module 220 and a second judging module 230.
The acquiring module 210 is configured to acquire first monitoring data of the electric vehicle.
The first determining module 220 is configured to determine whether the user has a behavior of pushing the electric vehicle based on the first monitoring data.
The second determining module 230 is configured to obtain second monitoring data of the electric vehicle if it is determined that the user has a behavior of pushing the electric vehicle, and determine whether the user of the electric vehicle has an illegal behavior according to the second monitoring data.
The second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
In some embodiments, the first monitoring data includes door status data, cushion load weight data acquired based on the sensor, and auxiliary propulsion system status data.
The first determining module 220 is configured to determine that the user has a behavior of pushing the electric vehicle if it is determined that the magnitude of the drop in the cushion load magnitude exceeds the first preset threshold based on the cushion load weight data and the electric door is in the no-output state based on the electric door state data, or the auxiliary pushing system is in the start state based on the auxiliary pushing system state data.
In some embodiments, the first monitoring data includes valve status data and speed data.
The first determining module 220 is configured to determine that the user has a behavior of pushing the electric vehicle if it is determined that the driving speed value is lower than the second preset threshold based on the driving speed data and it is determined that the electric switch is in the no-output state based on the electric switch state data.
In some embodiments, the second determining module 230 is configured to input gesture data to the gesture detection model; the gesture detection model is obtained by training based on gesture data samples and corresponding sample detection results; and acquiring a first judging result which is output by the gesture detection model and is used for judging whether the user of the electric vehicle has illegal behaviors.
In some embodiments, the second determining module 230 is configured to input the image data into the image recognition model; the image recognition model is obtained based on elevator environment samples, indoor environment samples, outdoor environment samples and corresponding sample labels; and acquiring a second judging result which is output by the image recognition model and is used for judging whether the electric vehicle user has illegal behaviors or not.
In some embodiments, the image recognition model is disposed at a backend server.
A second judging module 230, configured to upload the image data to a backend server; the back-end server inputs the image data to the image recognition model.
The present invention also provides an electronic device, and fig. 3 is a schematic structural diagram of the electronic device provided by the present invention, as shown in fig. 3, the electronic device may include: processor 310, communication interface (Communications Interface) 320, memory 330 and communication bus 340, wherein processor 310, communication interface 320, memory 330 accomplish communication with each other through communication bus 340. The processor 310 may invoke logic instructions in the memory 330 to perform an electric vehicle monitoring method comprising: acquiring first monitoring data of the electric vehicle; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
Further, the logic instructions in the memory 330 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which when executed by a processor is implemented to perform the electric vehicle monitoring method provided by the above methods, the method comprising: acquiring first monitoring data of the electric vehicle; judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data; if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors or not is judged according to the second monitoring data; the second monitoring data includes gesture data or image data captured by the vehicle-mounted camera.
The invention also provides a shared electric vehicle system, comprising: the plurality of shared electric vehicles are provided with identification marks; the user terminal is used for requesting to use the shared electric vehicle by scanning the identification mark; the server issues a command to start the shared electric vehicle requested to be used by the user terminal according to the request and payment information of the user terminal; the shared electric vehicle is also used for executing the electric vehicle monitoring method according to any one of the above alone or in combination with the server.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An electric vehicle monitoring method, comprising:
acquiring first monitoring data of the electric vehicle;
judging whether the user has the action of pushing the electric vehicle or not based on the first monitoring data;
if the fact that the user pushes the electric vehicle is determined, second monitoring data of the electric vehicle are obtained, and whether the electric vehicle user has illegal behaviors is judged according to the second monitoring data;
the second monitoring data comprises attitude data or image data shot by an on-board camera.
2. The electric vehicle monitoring method of claim 1, wherein the first monitoring data includes door status data, cushion load data acquired based on a sensor, and auxiliary propulsion system status data;
the determining whether the user has a behavior of pushing the electric vehicle based on the first monitoring data includes:
and if the descending amplitude of the cushion bearing weight value exceeds a first preset threshold value based on the cushion bearing weight data and the electric valve is in a non-output state based on the electric valve state data or the auxiliary pushing system is in a starting state based on the auxiliary pushing system state data, determining that the user has the action of pushing the electric vehicle.
3. The electric vehicle monitoring method of claim 1, wherein the first monitoring data includes door state data and speed data;
the determining whether the user has a behavior of pushing the electric vehicle based on the first monitoring data includes:
and if the driving speed value is lower than a second preset threshold value based on the driving speed data and the electric door is in the no-output state based on the electric door state data, determining that the behavior of pushing the electric vehicle exists for the user.
4. The method for monitoring an electric vehicle according to claim 1, wherein the determining whether the electric vehicle user has a violation according to the second monitoring data includes:
inputting the gesture data to a gesture detection model; the gesture detection model is obtained by training based on gesture data samples and corresponding sample detection results;
and acquiring a first judging result which is output by the gesture detection model and is used for judging whether the user of the electric vehicle has illegal behaviors.
5. The method for monitoring an electric vehicle according to claim 1, wherein the determining whether the electric vehicle user has a violation according to the second monitoring data includes:
inputting the image data into an image recognition model; the image recognition model is obtained based on elevator environment samples, indoor environment samples, outdoor environment samples and corresponding sample labels through training;
and acquiring a second judging result which is output by the image recognition model and used for judging whether the electric vehicle user has illegal behaviors or not.
6. The method for monitoring an electric vehicle according to claim 5, wherein the image recognition model is provided at a back-end server;
the inputting the image data into an image recognition model includes:
uploading the image data to the backend server;
the backend server inputs the image data to the image recognition model.
7. An electric vehicle monitoring device, comprising:
the acquisition module is used for acquiring first monitoring data of the electric vehicle;
the first judging module is used for judging whether the behavior of pushing the electric vehicle exists or not according to the first monitoring data;
the second judging module is used for acquiring second monitoring data of the electric vehicle if the user is determined to have the behavior of pushing the electric vehicle, and judging whether the user of the electric vehicle has illegal behaviors according to the second monitoring data;
the second monitoring data comprises attitude data or image data shot by an on-board camera.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the electric vehicle monitoring method of any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the electric vehicle monitoring method according to any one of claims 1 to 6.
10. A shared electric vehicle system, comprising:
the system comprises a plurality of shared electric vehicles, wherein identification marks are arranged on the shared electric vehicles;
the user terminal is used for requesting to use the shared electric vehicle by scanning the identification mark;
the server issues a command to start the shared electric vehicle requested to be used by the user terminal according to the request and payment information of the user terminal;
wherein the shared electric vehicle is further configured to perform the electric vehicle monitoring method according to any one of claims 1 to 6 alone or in combination with a server.
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| CN202311246526.3A CN117011803A (en) | 2023-09-26 | 2023-09-26 | Electric vehicle monitoring method, device, equipment, medium and shared electric vehicle system |
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| CN202311246526.3A CN117011803A (en) | 2023-09-26 | 2023-09-26 | Electric vehicle monitoring method, device, equipment, medium and shared electric vehicle system |
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