AI-based intelligent inspection method and system for shared electric vehicles

Abstract

This invention provides an intelligent inspection method and system for shared electric vehicles based on artificial intelligence, relating to the field of data processing technology. The method includes: a server acquiring attributes of shared electric vehicles in a non-use state within the positioning area of ​​the inspection device; the attributes including location and historical inspection time; if the server determines that the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, it uses the corresponding attribute as the first attribute and obtains the number of other shared electric vehicles within a first preset distance to achieve linkage; if the number of linkages is greater than the preset value, the server sends an inspection signal to the shared electric vehicles and the inspection device, controlling the shared electric vehicles to enter an inspection state and adding an inspection tag; the inspection device performs multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data. This invention automates autonomous intelligent vehicle inspection, improving inspection efficiency and accuracy.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an intelligent inspection method and system for shared electric vehicles based on artificial intelligence. Background Technology

[0002] With the rapid development of the sharing economy, shared electric bikes have become widely used in urban transportation due to their convenience. However, the high frequency of use and wide distribution of shared electric bikes present significant challenges to their daily maintenance and inspection. Shared electric bikes may experience various malfunctions, such as brake failure or body damage. If these are not detected and repaired promptly, they will not only affect the user experience but may also pose safety hazards. Furthermore, shared electric bikes are typically scattered throughout the city, requiring inspection personnel to spend considerable time and effort searching for and inspecting vehicles, resulting in low inspection efficiency and significant resource waste.

[0003] Currently, the inspection of shared electric bikes mainly relies on manual inspections. Inspectors need to search for shared electric bikes throughout the city and then check their condition one by one. This method has several problems. First, the inspection efficiency is low; manual inspection requires a significant amount of time and manpower, making it difficult to conduct a comprehensive inspection of a large number of shared electric bikes in a short period. Second, the accuracy and timeliness of the inspections are difficult to guarantee; inspectors may miss some faulty vehicles or fail to promptly identify potential problems.

[0004] Therefore, how to automate vehicle inspections and improve their efficiency and accuracy has become an urgent problem to be solved. Summary of the Invention

[0005] This invention provides an intelligent inspection method and system for shared electric vehicles based on artificial intelligence, which automates the autonomous intelligent inspection of vehicles, improving inspection efficiency and accuracy.

[0006] A first aspect of this invention provides an intelligent inspection method for shared electric vehicles based on artificial intelligence, comprising:

[0007] The server obtains the attributes of shared electric vehicles in non-use status within the location area where the inspection equipment is located. The attributes include location and historical inspection time.

[0008] If the server determines that the time interval between the historical inspection time and the current time is greater than or equal to the first preset value, it will use the corresponding attribute as the first attribute and obtain the number of other shared electric vehicles within the first preset distance to get the linkage.

[0009] If the number of linkages exceeds the preset value, the server sends an inspection signal to the shared electric vehicle and the inspection equipment, controls the shared electric vehicle to reach the inspection state and adds an inspection tag.

[0010] The inspection equipment performs multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data.

[0011] Optionally, in one possible implementation of the first aspect, the server obtains attributes of shared electric vehicles in a non-use state within the location area where the inspection equipment is located, the attributes including location and historical inspection time, including:

[0012] The server retrieves the location area of ​​the fence corresponding to each inspection device;

[0013] The server obtains the location of the shared electric vehicles in the non-use state within the location area, and retrieves the latest historical inspection time from the historical inspection table of the corresponding shared electric vehicles to obtain the attributes of the shared electric vehicles in the location area obtained by the server this time.

[0014] Optionally, in one possible implementation of the first aspect, if the server determines that the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, it uses the corresponding attribute as the first attribute and obtains the number of other shared electric vehicles within a preset distance of the first location, including:

[0015] The server extracts the first location of the shared electric vehicle based on the first attribute.

[0016] A joint inspection circle is generated with the first position as the center and a preset distance as the radius. The joint inspection circle is overlapped with the fence to obtain the intersection area.

[0017] The number of other shared electric vehicles to be linked is determined based on the aforementioned intersection area.

[0018] Optionally, in one possible implementation of the first aspect, determining the number of other shared electric vehicles to be linked based on the intersection area includes:

[0019] Obtain the second location of other shared electric vehicles located within the intersection area;

[0020] The number of items in the second position is used to determine the number of linked items.

[0021] Optionally, in one possible implementation of the first aspect, the step of sending an inspection signal to the shared electric vehicle and the inspection equipment if the number of linkages exceeds a preset value, controlling the shared electric vehicle to reach the inspection state and adding an inspection tag, includes:

[0022] If the number of linked vehicles exceeds the preset value, the server sends an inspection signal to the shared electric vehicle, and the shared electric vehicle responds to the inspection signal and switches to the inspection state.

[0023] If the server determines that the scanning terminal has extracted the QR code of the shared electric vehicle, it will send inspection information to it and at the same time control the shared electric vehicle to perform inspection reminders.

[0024] The server generates a notification message for the scanning device based on the second location of other shared electric vehicles.

[0025] Optionally, in one possible implementation of the first aspect, the server generates a reminder message for the scanning terminal based on the second location of other shared electric vehicles, including:

[0026] The server obtains the second location and historical inspection time of other shared electric vehicles. If it determines that the time interval between the historical inspection time and the current time is less than a first preset value, it extracts the location to obtain the third location.

[0027] Based on the second and third locations, a guide path is generated and sent as a reminder message to the scanning end.

[0028] Alternatively, in one possible implementation of the first aspect, the processing of the inspection data obtained from the shared electric vehicles includes:

[0029] After determining that the distance between the inspection equipment and the shared electric vehicle is less than or equal to the preset distance, the inspection equipment receives the Bluetooth number configured by the server.

[0030] The inspection equipment sends a Bluetooth pairing request to the shared electric vehicle via Bluetooth. The shared electric vehicle sends the pairing request to the server. After the server verifies the request, it retrieves the control code table corresponding to the shared electric vehicle and sends it back to the inspection equipment, allowing the shared electric vehicle to establish a communication connection with the inspection equipment.

[0031] The inspection equipment performs inspection control on shared electric vehicles based on the control coding table and extracts the corresponding multimodal information to obtain the inspection data of shared electric vehicles.

[0032] Optionally, in one possible implementation of the first aspect, the inspection device performs inspection control on the shared electric vehicle based on a control coding table and extracts corresponding multimodal information to obtain inspection data of the shared electric vehicle, including:

[0033] The inspection equipment categorizes the inspection codes in the control code table to obtain inspection contact group codes, inspection image group codes, and inspection joint group codes. Each inspection code, inspection contact group code, inspection image group code, and inspection joint group code has corresponding completion conditions.

[0034] The inspection equipment sequentially extracts the inspection codes from the inspection contact group codes and interacts with the shared electric vehicles, enabling the inspection equipment to make inspection contact with the shared electric vehicles.

[0035] The inspection equipment sequentially extracts the inspection code from the inspection image group code and interacts with the shared electric vehicle, so that the inspection equipment and the shared electric vehicle meet the image inspection conditions and obtain image inspection information.

[0036] The inspection equipment sequentially extracts the inspection codes within the joint inspection code and interacts with the shared electric vehicles, enabling the inspection equipment and the shared electric vehicles to meet the multimodal inspection conditions and obtain multimodal inspection information.

[0037] Inspection data is obtained by statistically analyzing image inspection information and multimodal inspection information.

[0038] Optionally, in one possible implementation of the first aspect, the inspection device sequentially extracts the inspection code within the inspection contact group code and interacts with the shared electric vehicle, enabling the inspection device to make inspection contact with the shared electric vehicle, including:

[0039] Based on the inspection code control of the shared electric vehicle's audio-visual display, the loudspeaker and image acquisition device of the inspection equipment will control the stop of the audio-visual display after recognizing the shared electric vehicle with the audio-visual display and moving to its preset position.

[0040] The inspection equipment identifies the preset positioning target of the shared electric vehicle and moves towards the preset positioning target at a first preset distance and a first preset angle to achieve the inspection contact condition.

[0041] Optionally, in one possible implementation of the first aspect, the inspection device sequentially extracts the inspection code within the inspection image group code and interacts with the shared electric vehicle, so that the inspection device and the shared electric vehicle meet the image inspection conditions and obtain image inspection information, including:

[0042] The inspection equipment activates the recognition module and moves around the shared electric vehicle 360 ​​degrees along a preset path. During the movement, it sequentially collects images of the vehicle body from different angles and controls the inspection code within the inspection image group code to trigger the shared electric vehicle to respond at different angles.

[0043] The recognition module compares the vehicle image with a preset image to identify damaged equipment and obtain image inspection information.

[0044] The image inspection condition is met after the inspection equipment completes a 360-degree rotation.

[0045] Optionally, in one possible implementation of the first aspect, the inspection device sequentially extracts the inspection code within the joint inspection code and interacts with the shared electric vehicle, enabling the inspection device and the shared electric vehicle to achieve multimodal inspection conditions and obtain multimodal inspection information, including:

[0046] The inspection equipment locates the brake position of the shared electric vehicle and uses a robotic arm to merge and obtain the corresponding linked images of the brake.

[0047] By performing linkage analysis on the linked images, the damaged brakes and combined braking equipment are identified, multimodal inspection information is obtained, and multimodal inspection conditions are met.

[0048] Optionally, in one possible implementation of the first aspect, the inspection device locates the brake position of the shared electric vehicle and, based on a robotic arm, merges and acquires a linked image corresponding to the brake, including:

[0049] The system determines the first position of the first brake of the shared electric vehicle and the first combined braking device corresponding to the first brake. It controls the robotic arm to correspond to the preset position of the first brake and executes the closing operation. At the same time, the camera device extracts images of the first combined braking device.

[0050] The robot arm is controlled to close and tighten for a preset time. The first video of the camera device is extracted within the closing time. If the first video reaches the braking condition, the linked image is correct.

[0051] If the first video does not meet the braking conditions, the linked image will produce an error.

[0052] A second aspect of this invention provides an intelligent inspection system for shared electric vehicles based on artificial intelligence, comprising:

[0053] The acquisition module is used by the server to acquire the attributes of shared electric vehicles in non-use status within the positioning area where the inspection equipment is located. The attributes include location and historical inspection time.

[0054] The linkage module is used by the server to determine that if the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, then the corresponding attribute is used as the first attribute to obtain the number of other shared electric vehicles within the first preset distance.

[0055] The inspection module is used to send an inspection signal to the shared electric vehicle and the inspection equipment if the number of linkages exceeds the preset value, so as to control the shared electric vehicle to reach the inspection state and add an inspection tag.

[0056] The results module is used by the inspection equipment to perform multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data.

[0057] Beneficial effects: This invention improves inspection efficiency and accuracy by intelligently locating, screening, and conducting multimodal interactive inspections of shared electric vehicles. This allows for the timely detection and resolution of vehicle malfunctions and problems, ensuring the normal operation of shared electric vehicles and enhancing the user experience. Simultaneously, by managing and analyzing historical inspection information of shared electric vehicles, inspection strategies are optimized, inspection resources are rationally allocated, and operating costs are reduced.

[0058] This invention utilizes server-based intelligent positioning and screening of shared electric vehicles to automatically identify those requiring inspection, avoiding the blind spots of manual inspections and reducing the time spent by inspection personnel searching for vehicles. Simultaneously, the application of multimodal interaction and image recognition technologies enables the inspection equipment to quickly and comprehensively check the condition of vehicles, significantly improving inspection efficiency.

[0059] This invention utilizes multimodal interaction and image recognition processing to perform comprehensive inspections of shared electric vehicles. It can detect not only obvious problems such as exterior damage but also potential faults in critical components like brakes, improving the accuracy of fault diagnosis. Furthermore, analysis of historical inspection information for shared electric vehicles provides a better understanding of vehicle usage patterns and malfunction patterns, further enhancing inspection accuracy. This invention can promptly identify and resolve faults and problems with shared electric vehicles, ensuring their normal operation, reducing the probability of users encountering malfunctioning vehicles, and improving the user experience. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating an intelligent inspection method for shared electric vehicles based on artificial intelligence, provided in an embodiment of the present invention.

[0061] Figure 2 This is a schematic diagram of the structure of an intelligent inspection system for shared electric vehicles based on artificial intelligence, provided in an embodiment of the present invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 embodiments of the present invention, and not all embodiments. 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.

[0063] See Figure 1 This is a flowchart illustrating an intelligent inspection method for shared electric vehicles based on artificial intelligence, provided in an embodiment of the present invention, including:

[0064] S1, the server obtains the attributes of shared electric vehicles in non-use status within the location area where the inspection equipment is located, including location and historical inspection time.

[0065] In this step, the server uses geofencing technology to define the working area of ​​the inspection equipment and collects real-time location information and historical maintenance records of stationary shared electric vehicles within that area. Specifically, the server accesses a map to obtain the current latitude and longitude coordinates of the inspection equipment and combines this with preset fence boundaries (such as a circular area with a radius of 500 meters or a street area) to determine the target scanning range.

[0066] Simultaneously, onboard sensors (such as GPS modules and accelerometers) determine whether a vehicle is in an unused state. For example, if a vehicle remains stationary for 30 consecutive minutes and its speed sensor displays 0, it is marked as unused. Furthermore, the server retrieves the historical inspection records for each electric vehicle from the cloud database, extracting the most recent valid inspection timestamp as the basis for triggering subsequent linked inspections. This step utilizes dynamic fencing and status filtering to manage only target vehicles requiring priority maintenance.

[0067] In some embodiments, the server obtains attributes of shared electric vehicles in a non-use state within the location area where the inspection device is located. These attributes include location and historical inspection time, including:

[0068] S11, the server retrieves the location area of ​​the fence corresponding to each inspection device.

[0069] In this sub-step, the fence information is stored in the configuration database. After parsing the fence, the server combines it with real-time geographic location data (such as positioning signals from BeiDou satellites) to calculate whether the current location of the inspection equipment is completely within the fence. If it exceeds the boundary, it automatically switches to the backup fence or suspends the task.

[0070] S12, the server obtains the location of the shared electric vehicle in the non-use state within the location area, and retrieves the latest historical inspection time from the historical inspection table of the corresponding shared electric vehicle to obtain the attributes of the shared electric vehicle in the location area obtained by the server this time.

[0071] This step uses multi-source data fusion to filter vehicles. First, the server filters out vehicles currently in use within the fenced area. For vehicles that meet the criteria, the server retrieves their last valid inspection time from the database. If a vehicle's last inspection date was April 1, 2025, and the current date is April 15, 2025, and the preset threshold is 10 days, then the vehicle is marked as a vehicle to be inspected.

[0072] S2, if the server determines that the time interval between the historical inspection time and the current time is greater than or equal to the first preset value, then it will use the corresponding attribute as the first attribute and obtain the number of other shared electric vehicles within the first preset distance to get the linkage.

[0073] This step uses time threshold filtering and spatial range analysis to determine the target vehicles that need to be prioritized for inspection. Specifically, the server calculates the difference between the historical inspection time and the current system time for each shared electric vehicle in non-use mode. If this difference is greater than or equal to a first preset value (e.g., 14 days), the vehicle is marked as having the first attribute and enters the linkage quantity determination stage.

[0074] Subsequently, the server uses its current location (first location) as the center and expands outwards by a preset distance (e.g., 50 meters) to generate a coordinated inspection circle. It then calculates the intersection area based on the fence boundaries and finally counts the number of other shared electric vehicles within the intersection area (coordinated number), which serves as the basis for triggering an inspection task. This mechanism, through dynamic temporal and spatial constraints, ensures both timeliness and avoids resource waste in the inspection strategy.

[0075] In some embodiments, if the server determines that the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, it uses the corresponding attribute as the first attribute to obtain the number of other shared electric vehicles within a preset distance of the first location, including:

[0076] S21, the server extracts the first location of the shared electric vehicle based on the first attribute.

[0077] In this sub-step, the server retrieves the real-time GPS coordinates of the shared electric vehicles already tagged as the first attribute from the cloud database. This step ensures that the generation of the coordinated patrol network is based on the latest and most reliable location data.

[0078] S22, a linkage inspection circle is generated with the first position as the center and a preset distance as the radius, and the linkage inspection circle is overlapped with the fence to obtain an intersection area.

[0079] The server uses the target vehicle's initial location as the center and draws a linked inspection circle at a preset distance (e.g., 10 meters), then calculates the intersection of this circle with the boundary of the corresponding fence. If the linked inspection circle is completely within the fence, the intersection area is the entire circle; if it partially extends beyond the fence, only the overlapping area between the circle and the fence is retained.

[0080] S23, based on the intersection area, determine the number of other shared electric vehicles to be linked.

[0081] The step of determining the number of other shared electric vehicles to be linked based on the intersection area includes:

[0082] S231, obtain the second location of other shared electric vehicles located in the intersection area.

[0083] In this sub-step, the server sends a location query command to other shared electric vehicles in the intersection area and receives their returned real-time GPS coordinates (second location).

[0084] S232, count the number of the second position to get the number of linkages.

[0085] The server deduplicates the obtained second location (e.g., removing duplicate reports of the same vehicle) and counts the number of valid linkages. For example, if there are 6 vehicles in the intersection area (including vehicles with the first attribute), the linkage count is 5. This method allows for the determination of the number of available vehicles, preventing situations where no other vehicles are available during inspections and impacting customer experience.

[0086] S3, if the number of linkages exceeds the preset value, the server sends an inspection signal to the shared electric vehicle and the inspection equipment, controls the shared electric vehicle to reach the inspection state and adds an inspection tag.

[0087] If the number of linked devices exceeds the preset value, it indicates that there are a large number of shared electric bikes gathered in the area. During inspections, the impact on users should be minimized. At this time, the server sends inspection signals to the shared electric bikes and inspection equipment, causing the shared electric bikes to enter a state specifically set for inspection, such as a state where they cannot be started. Inspection tags are also added to these vehicles, which facilitates subsequent identification and management of the vehicle's inspection status.

[0088] In some embodiments, if the number of linkages exceeds a preset value, the server sends an inspection signal to the shared electric vehicle and the inspection equipment, controls the shared electric vehicle to reach the inspection state and adds an inspection tag, including:

[0089] S31, if the number of linkages is greater than the preset value, the server sends an inspection signal to the shared electric vehicle, and the shared electric vehicle responds to the inspection signal and switches to the inspection state.

[0090] When the server determines that the number of linked vehicles exceeds a preset value, it sends an inspection signal to the shared electric vehicles. The shared electric vehicles have an internal signal receiving and processing mechanism. Upon receiving this signal, a series of operations are triggered, thus entering inspection mode. For example, if the vehicle is unusable, specific sensors may be activated, preparing to interact with the inspection equipment. This is the stage where the shared electric vehicle responds to server instructions and prepares for subsequent inspection work.

[0091] S32, if the server determines that the scanning terminal has extracted the QR code of the shared electric vehicle, it will send inspection information to it and control the shared electric vehicle to perform inspection reminders.

[0092] The server continuously monitors the operation of the scanning terminal (held by the user). When the scanning terminal extracts the QR code of the shared electric bike, it indicates that a user wants to use the vehicle. At this time, the server sends an inspection message to the scanning terminal, which could be something like "This vehicle cannot be used." Simultaneously, the server controls the shared electric bike to issue an inspection reminder, such as by making the vehicle emit a sound or flash its lights.

[0093] S33, the server generates a reminder message for the scanning terminal based on the second location of other shared electric vehicles.

[0094] The server generates alerts for the scanning device based on the secondary location information of other shared electric bikes. These alerts can help users navigate to other available vehicles.

[0095] The server generates alert information for the scanning terminal based on the second location of other shared electric vehicles, including:

[0096] S331, the server obtains the second location and historical inspection time of other shared electric vehicles. If it is determined that the time interval between the historical inspection time and the current time is less than the first preset value, then its location is extracted to obtain the third location.

[0097] The server retrieves two key pieces of information from other shared electric bikes: their secondary location and historical inspection time. It then compares the historical inspection time of each bike with the current time to calculate the time interval between the two. If this time interval is less than a first preset value, it means that these bikes have recently been inspected. The server extracts the location of these bikes and defines it as their tertiary location. This location information will be used later to generate more accurate guidance routes.

[0098] S332 generates a guide path based on the second and third positions and sends it as a reminder message to the scanning end.

[0099] Based on the previously obtained second and third location information, the server generates a navigation path. This path is then sent as a notification to the scanning device, allowing users to quickly and accurately locate available vehicles.

[0100] S4, the inspection equipment performs multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data.

[0101] Once the shared electric bikes enter inspection mode, the inspection equipment employs two key methods—multimodal interaction and image recognition processing—to comprehensively understand their condition. Multimodal interaction allows for diverse information exchange between the inspection equipment and the shared electric bikes, such as acquiring physical parameters through sensors. Image recognition processing provides a direct visual inspection of the vehicle's exterior for damage, and whether any components are malfunctioning. The information obtained from both methods is then aggregated to form the shared electric bike's inspection data. This data provides crucial information for subsequent assessments of vehicle malfunctions and the need for repairs.

[0102] In some embodiments, the inspection device performs multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data for the shared electric vehicles, including:

[0103] S41, after the inspection device determines that the distance between the device and the shared electric vehicle is less than or equal to the preset distance, it receives the Bluetooth number configured by the server.

[0104] The inspection device has its own distance detection function, which continuously monitors the distance between it and the shared electric scooter. When the distance is determined to be less than or equal to a preset distance, it indicates that the inspection device has approached within range where it can effectively interact with the shared electric scooter. At this point, the inspection device receives a Bluetooth ID configured for it by the server. This Bluetooth ID is a crucial identifier for establishing a Bluetooth connection with the shared electric scooter; only by obtaining the correct Bluetooth ID can it ensure accurate pairing with the corresponding shared electric scooter.

[0105] S42, the inspection device sends a Bluetooth pairing request to the shared electric vehicle via Bluetooth. The shared electric vehicle sends the pairing request to the server. After the server verifies the request, it retrieves the control code table corresponding to the shared electric vehicle and sends it back to the inspection device, allowing the shared electric vehicle to establish a communication connection with the inspection device.

[0106] After obtaining the Bluetooth ID, the inspection device sends a Bluetooth pairing request to the shared electric vehicle. Upon receiving this request, the shared electric vehicle doesn't immediately pair; instead, it forwards the request to the server. The server verifies the request, checking its validity and compliance with the inspection process. If verification is successful, the server retrieves the control code table corresponding to the shared electric vehicle from its database. This control code table contains instructions for various inspection operations on the vehicle. The server then sends the control code table back to the inspection device, simultaneously allowing the shared electric vehicle to establish a communication connection with it. This enables stable data transmission and command exchange between the inspection device and the shared electric vehicle, preparing for subsequent inspection control.

[0107] S43, the inspection equipment performs inspection control on the shared electric vehicles based on the control coding table and extracts the corresponding multimodal information to obtain the inspection data of the shared electric vehicles.

[0108] After establishing a communication connection with the shared electric vehicle, the inspection equipment will perform inspection control based on the control code table fed back by the server. The instructions in the control code table will guide the inspection equipment to perform a series of operations, such as triggering certain sensors on the vehicle to obtain vehicle status information, or controlling specific components of the vehicle to perform actions to detect its performance. During this process, the inspection equipment will extract relevant multimodal information, which may include the vehicle's electrical parameters, the operating status of mechanical components, and external images. The inspection equipment will then organize and analyze this multimodal information to obtain the inspection data of the shared electric vehicle. This data can comprehensively reflect the current condition of the vehicle, providing strong support for subsequent vehicle maintenance and management.

[0109] The inspection equipment performs inspection control on the shared electric vehicles based on a control coding table and extracts corresponding multimodal information to obtain inspection data for the shared electric vehicles, including:

[0110] S431, the inspection equipment classifies the inspection codes in the control code table to obtain inspection contact group codes, inspection image group codes, and inspection joint group codes. Each inspection code, inspection contact group code, inspection image group code, and inspection joint group code has corresponding completion conditions.

[0111] After receiving the control code table from the server, the inspection equipment categorizes the inspection codes within the table to ensure more orderly and efficient inspection control of shared electric vehicles. These codes are divided into three categories: inspection contact codes, inspection image codes, and inspection combination codes. Different codes correspond to different inspection tasks and methods. For example, inspection contact codes primarily facilitate physical or signal-level contact interaction between the inspection equipment and the shared electric vehicle; inspection image codes focus on acquiring information about the vehicle's appearance through image acquisition and analysis; and inspection combination codes involve the coordinated operation of multiple inspection methods. Furthermore, each inspection code and all three codes are assigned corresponding completion conditions. These conditions serve as the criteria for determining the successful completion of the inspection task, ensuring the accuracy and completeness of the inspection work. Specific implementation examples will follow.

[0112] S432, the inspection equipment sequentially extracts the inspection code from the inspection contact group code and interacts with the shared electric vehicle, so that the inspection equipment and the shared electric vehicle can reach inspection contact.

[0113] After classifying the inspection codes, the inspection equipment first processes the inspection contact group codes. It extracts the inspection codes within the inspection contact group codes in a specific order, and then interacts with the shared electric vehicles based on these codes.

[0114] Through this interactive process, the inspection equipment gradually adjusts its state and position relative to the shared electric bikes, eventually achieving a state of inspection contact. This state is the foundation for subsequent, more in-depth inspection operations; only by successfully achieving inspection contact can the smooth progress of subsequent inspection tasks be guaranteed.

[0115] The inspection equipment sequentially extracts the inspection code from the inspection contact group code and interacts with the shared electric vehicle, enabling the inspection equipment to make inspection contact with the shared electric vehicle, including:

[0116] S4321, based on inspection code control of shared electric vehicle sound and light display, the speaker and image acquisition device of the inspection equipment control to stop the sound and light display after recognizing the shared electric vehicle with sound and light display and moving to its preset position.

[0117] After extracting the inspection code from the inspection contact group code, the inspection equipment controls the shared electric vehicle to activate its audio-visual display according to the coded instructions. The shared electric vehicle may emit specific sound signals (such as a beeping sound), and the lights on the vehicle will flash according to a preset pattern. The inspection equipment itself is equipped with a speaker and an image acquisition device. When these devices detect a shared electric vehicle in audio-visual display mode, the inspection equipment will automatically move to the preset position of the shared electric vehicle. This preset position can be the rear or front of the vehicle. After reaching the preset position, the inspection equipment will control the shared electric vehicle to stop the audio-visual display, and at the same time prepare for the next inspection operation.

[0118] S4322, the inspection equipment identifies the preset positioning target of the shared electric vehicle and moves towards the preset positioning target at a first preset distance and a first preset angle to achieve the inspection contact condition.

[0119] After completing the audio-visual display control and moving to the preset position, the inspection equipment will identify the preset positioning target of the shared electric vehicle. The preset positioning target can be a specific mark, component, etc. on the vehicle, used to help the inspection equipment accurately determine its relative position and orientation with the vehicle. The inspection equipment will adjust its posture to face the preset positioning target and maintain a first preset distance and angle with it. When these distance and angle requirements are met, the inspection contact condition is met. At this point, the inspection equipment and the shared electric vehicle are in a suitable state in terms of spatial position and relative posture for subsequent inspection operations.

[0120] S433, the inspection equipment sequentially extracts the inspection code from the inspection image group code and interacts with the shared electric vehicle, so that the inspection equipment and the shared electric vehicle meet the image inspection conditions and obtain image inspection information.

[0121] After completing the inspection contact code operation, the inspection equipment begins processing the inspection image code. It sequentially extracts the inspection codes within the inspection image code and interacts with the shared electric vehicle based on these codes. Through this interaction, the inspection equipment performs comprehensive image acquisition and analysis of the shared electric vehicle to meet the image inspection requirements. During this process, the inspection equipment acquires image information from various angles of the shared electric vehicle. By processing and analyzing these images, it obtains image inspection information regarding the vehicle's appearance, whether the equipment is damaged, etc. This information is crucial for judging the overall condition of the vehicle.

[0122] The inspection equipment sequentially extracts the inspection code from the inspection image group code and interacts with the shared electric vehicle, enabling the inspection equipment and the shared electric vehicle to meet the image inspection conditions and obtain image inspection information, including:

[0123] S4331, the inspection equipment activates the identification module, and the inspection equipment moves 360 degrees around the shared electric vehicle according to the preset path. During the movement, it sequentially collects vehicle images at different angles, and controls the inspection code in the inspection image group code to trigger the shared electric vehicle to respond at different angles.

[0124] The inspection equipment first activates its recognition module, which has image acquisition and processing capabilities. Then, the equipment moves 360 degrees around the shared electric vehicle along a pre-set path. During this movement, the equipment acquires images of the vehicle from different angles, ensuring complete image information from all sides. Simultaneously, at each acquisition angle, the equipment controls the inspection code within the image group code to trigger a corresponding response from the shared electric vehicle. This response might involve activating certain vehicle components to achieve clearer image acquisition, such as turning on the lights or unfolding the rearview mirrors, thus providing more comprehensive information for subsequent accurate image analysis.

[0125] S4332, the recognition module compares the vehicle image with a preset image to identify damaged equipment and obtain image inspection information.

[0126] After acquiring vehicle images, the recognition module compares these images with pre-stored preset images. These preset images are typically standard images of the vehicle in its normal state. Through comparison, the recognition module can identify differences between the vehicle images and the preset images, thus determining potentially damaged equipment on the vehicle. For example, if the comparison reveals distortion or missing parts in the image of a certain area compared to the preset image, it can be determined that the equipment in that area may be damaged. The recognition module then organizes and records this information about damaged equipment, ultimately obtaining image inspection information that visually reflects the extent of damage to the vehicle's exterior.

[0127] S4333 indicates that the image inspection condition has been met after the inspection equipment has completed a 360-degree rotation.

[0128] After the inspection equipment completes a 360-degree rotation around the shared electric vehicle, it means that images have been captured from all sides of the vehicle. At this point, the image inspection condition is met. This indicates that the inspection equipment has comprehensively acquired image information of the shared electric vehicle's appearance, providing a sufficient image data foundation for subsequent comprehensive assessment of the vehicle's overall condition. Only when this condition is met can the acquired image inspection information be complete and accurate, providing a reliable basis for vehicle maintenance and management.

[0129] S434, the inspection equipment sequentially extracts the inspection codes within the joint inspection code and interacts with the shared electric vehicle, enabling the inspection equipment and the shared electric vehicle to meet the multimodal inspection conditions and obtain multimodal inspection information.

[0130] After completing the operations of the inspection contact group code and inspection image group code, the inspection equipment begins to process the inspection joint group code. It will extract the inspection codes within the group code in sequence and interact with the shared electric vehicle.

[0131] Through this interaction, a variety of detection methods and information acquisition approaches are comprehensively utilized to enable inspection equipment and shared electric vehicles to achieve multimodal inspection conditions. During this process, the inspection equipment will acquire various types of information, such as the working status of the brakes and combined braking devices. This information collectively constitutes multimodal inspection information, which helps to gain a more comprehensive and in-depth understanding of the overall performance and condition of shared electric vehicles.

[0132] The inspection equipment sequentially extracts the inspection codes from the joint inspection code and interacts with the shared electric vehicles, enabling the inspection equipment and the shared electric vehicles to achieve multimodal inspection conditions and obtain multimodal inspection information, including:

[0133] S4341, the inspection equipment locates the brake position of the shared electric vehicle, and uses the robotic arm to merge the brakes and obtain the corresponding linkage image.

[0134] The operational status of the brakes is crucial to the safety of shared electric bikes. The inspection equipment first precisely locates the brake position of the shared electric bike, which is the foundation for subsequent operations. Then, the robotic arm of the inspection equipment performs a merging operation on the brakes. During this process, it simultaneously acquires corresponding linked images of the brakes. These linked images record the status of the brakes and the combined braking device during operation, serving as an important basis for determining whether they are functioning properly.

[0135] Combined braking equipment is a braking device that is linked with the vehicle brake. Taking the most commonly used drum brake as an example, when the vehicle brake is combined, the spring of the drum brake at the rear wheel will be compressed. This solution can collect the linkage image of the corresponding spring position of the drum brake for judgment.

[0136] The inspection equipment locates the brake position of the shared electric vehicle and, based on the robotic arm, merges and acquires the corresponding linked image of the brake, including:

[0137] S43411, determine the first position of the first brake of the shared electric vehicle, and determine the first combined braking device corresponding to the first brake, control the robotic arm to correspond to the preset position of the first brake and perform the closing operation, and at the same time the camera device extracts the image of the first combined braking device.

[0138] The inspection equipment accurately determines the first position of the first brake of the shared electric vehicle and locates the corresponding first combined braking device. Then, the control robotic arm moves to the position corresponding to the preset position of the first brake and performs the closing operation. While the robotic arm is closing the brake, the camera extracts images of the first combined braking device. This allows for real-time recording of the combined braking device's status during brake closing, providing image data for subsequent analysis.

[0139] S43412 controls the robotic arm to close and process for a preset time, extracts the first video from the camera device within the closing time, and if the first video reaches the braking condition, the linked image is correct.

[0140] During the controlled robotic arm's closing operation of the first brake for a preset time, the camera continuously records the status of the first combined braking device, forming the first video. The inspection equipment analyzes this first video to determine whether the braking conditions have been met. If the braking conditions are met, it indicates that the brake and combined braking device can work together normally during the closing operation, and the situation reflected in the linked image is accurate, meaning that the working status of the brake and combined braking device meets expectations.

[0141] One way to determine whether the braking condition has been met is to check whether the spring in the linkage image has been compressed to a certain length. For example, when the brake is fully closed, the spring in the linkage image should be compressed to 2cm, and when the brake is fully released, the spring in the linkage image should be extended to 5cm. Therefore, the length of the spring can be used to determine whether the braking condition has been met.

[0142] S43413, If the first video does not meet the braking conditions, the linked image will have an error.

[0143] If the first video does not meet the braking condition, it indicates that when the brake is closed, the combined braking device fails to work properly as expected. This may mean that there is a fault with the brake itself or a problem with the combined braking device, resulting in an incorrect linked image. In this case, it is necessary to further inspect and repair the brake and the combined braking device.

[0144] S4342, perform a linked analysis on the linked image to determine the damaged brake and combined braking device, obtain multi-modal inspection information, and meet the multi-modal inspection conditions.

[0145] The inspection device will perform a linked analysis on the obtained linked image. By analyzing the states of the brake and the combined braking device in the linked image and combining the previously set standards and judgment conditions, it is determined whether there are damaged brakes and combined braking devices. Once the damaged devices are determined, the relevant information is sorted and recorded to obtain multi-modal inspection information. When this series of analysis and information sorting is completed, the multi-modal inspection conditions are met, and at this time, a more comprehensive and accurate understanding of the working states of the brake and the combined braking device is obtained.

[0146] S435, count the image inspection information and multi-modal inspection information to obtain inspection data.

[0147] After the inspection device completes a series of operations such as inspection contact, image inspection, and multi-modal inspection, it obtains image inspection information and multi-modal inspection information respectively. Finally, the inspection device will statistically summarize these information, integrate the vehicle appearance damage conditions found in the image inspection and the working state information of key components such as the brake and the combined braking device obtained from the multi-modal inspection, and form the final inspection data. These inspection data can comprehensively and comprehensively reflect the overall condition of the shared electric vehicle, providing a strong basis for subsequent vehicle maintenance and repair decisions.

[0148] See Figure 2 , which is a schematic structural diagram of an intelligent inspection system for shared electric vehicles based on artificial intelligence provided by an embodiment of the present invention, including:

[0149] An acquisition module, used for the server to acquire the attributes of the shared electric vehicle in the non-use state within the positioning area where the inspection device is located, and the attributes include position and historical inspection time;

[0150] A linkage module, used for the server to, if it determines that the time period from the historical inspection time to the current time is greater than or equal to the first preset value, use the corresponding attributes as the first attributes, and acquire the linkage quantity of other shared electric vehicles within the first position preset distance;

[0151] An inspection module, used for the server to send an inspection signal to the shared electric vehicle and the inspection device if the linkage quantity is greater than the preset value, control the shared electric vehicle to reach the inspection state and add an inspection label;

[0152] The results module is used by the inspection equipment to perform multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data.

[0153] The present invention also provides a storage medium storing a computer program, which, when executed by a processor, is used to implement the methods provided in the various embodiments described above.

[0154] The storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, the storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be a component of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). This ASIC can also be located within a user device. Alternatively, the processor and storage medium can exist as discrete components in a communication device. Storage media can be read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage devices, etc.

[0155] The present invention also provides a program product including execution instructions stored in a storage medium. At least one processor of the device can read the execution instructions from the storage medium, and the execution instructions by the at least one processor cause the device to implement the methods provided in the various embodiments described above.

[0156] In the above-described terminal or server embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; 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 or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent inspection method for shared electric vehicles based on artificial intelligence, characterized in that, include: The server obtains the attributes of shared electric vehicles in non-use status within the location area where the inspection equipment is located. The attributes include location and historical inspection time. If the server determines that the time interval between the historical inspection time and the current time is greater than or equal to the first preset value, it will use the corresponding attribute as the first attribute and obtain the number of other shared electric vehicles within the first preset distance to get the linkage. If the number of linkages exceeds the preset value, the server sends an inspection signal to the shared electric vehicle and the inspection equipment, controls the shared electric vehicle to reach the inspection state and adds an inspection tag. The inspection equipment performs multimodal interaction and image recognition processing on shared electric vehicles to obtain inspection data, including: After determining that the distance between the inspection equipment and the shared electric vehicle is less than or equal to the preset distance, the inspection equipment receives the Bluetooth number configured by the server. The inspection equipment sends a Bluetooth pairing request to the shared electric vehicle via Bluetooth. The shared electric vehicle sends the pairing request to the server. After the server verifies the request, it retrieves the control code table corresponding to the shared electric vehicle and sends it back to the inspection equipment, allowing the shared electric vehicle to establish a communication connection with the inspection equipment. The inspection equipment performs inspection control on shared electric vehicles based on the control coding table and extracts the corresponding multimodal information to obtain the inspection data of the shared electric vehicles, including: The inspection equipment categorizes the inspection codes in the control code table to obtain inspection contact group codes, inspection image group codes, and inspection joint group codes. Each inspection code, inspection contact group code, inspection image group code, and inspection joint group code has corresponding completion conditions. The inspection equipment sequentially extracts the inspection codes from the inspection contact group codes and interacts with the shared electric vehicles, enabling the inspection equipment to make inspection contact with the shared electric vehicles. The inspection equipment sequentially extracts the inspection code from the inspection image group code and interacts with the shared electric vehicle, so that the inspection equipment and the shared electric vehicle meet the image inspection conditions and obtain image inspection information. The inspection equipment sequentially extracts the inspection codes within the joint inspection code and interacts with the shared electric vehicles, enabling the inspection equipment and the shared electric vehicles to meet the multimodal inspection conditions and obtain multimodal inspection information. Inspection data is obtained by statistically analyzing image inspection information and multimodal inspection information.

2. The method according to claim 1, characterized in that, The server obtains the attributes of shared electric vehicles in non-use status within the location area where the inspection equipment is located. These attributes include location and historical inspection time, including: The server retrieves the location area of ​​the fence corresponding to each inspection device; The server obtains the location of the shared electric vehicles in the non-use state within the location area, and retrieves the latest historical inspection time from the historical inspection table of the corresponding shared electric vehicles to obtain the attributes of the shared electric vehicles in the location area obtained by the server this time.

3. The method according to claim 2, characterized in that, If the server determines that the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, it will use the corresponding attribute as the first attribute and obtain the number of other shared electric vehicles within a preset distance of the first location, including: The server extracts the first location of the shared electric vehicle based on the first attribute. A joint inspection circle is generated with the first position as the center and a preset distance as the radius. The joint inspection circle is overlapped with the fence to obtain the intersection area. The number of other shared electric vehicles to be linked is determined based on the aforementioned intersection area.

4. The method according to claim 3, characterized in that, The determination of the number of other shared electric vehicles to be linked based on the intersection area includes: Obtain the second location of other shared electric vehicles located within the intersection area; The number of items in the second position is used to determine the number of linked items.

5. The method according to claim 1, characterized in that, If the number of linked devices exceeds a preset value, the server sends an inspection signal to the shared electric vehicles and the inspection equipment, controlling the shared electric vehicles to enter the inspection state and adding inspection tags, including: If the number of linked vehicles exceeds the preset value, the server sends an inspection signal to the shared electric vehicle, and the shared electric vehicle responds to the inspection signal and switches to the inspection state. If the server determines that the scanning terminal has extracted the QR code of the shared electric vehicle, it will send inspection information to it and at the same time control the shared electric vehicle to perform inspection reminders. The server generates a notification message for the scanning device based on the second location of other shared electric vehicles.

6. The method according to claim 5, characterized in that, The server generates a reminder message for the scanning terminal based on the second location of other shared electric vehicles, including: The server obtains the second location and historical inspection time of other shared electric vehicles. If it determines that the time interval between the historical inspection time and the current time is less than a first preset value, it extracts the location to obtain the third location. Based on the second and third locations, a guide path is generated and sent as a reminder message to the scanning end.

7. The method according to claim 1, characterized in that, The inspection equipment sequentially extracts the inspection code from the inspection contact group code and interacts with the shared electric vehicle, enabling the inspection equipment to make inspection contact with the shared electric vehicle, including: Based on the inspection code control of the shared electric vehicle's audio-visual display, the loudspeaker and image acquisition device of the inspection equipment will control the stop of the audio-visual display after recognizing the shared electric vehicle with the audio-visual display and moving to its preset position. The inspection equipment identifies the preset positioning target of the shared electric vehicle and moves towards the preset positioning target at a first preset distance and a first preset angle to achieve the inspection contact condition.

8. The method according to claim 1, characterized in that, The inspection device sequentially extracts the inspection code from the inspection image group code and interacts with the shared electric vehicle, enabling the inspection device and the shared electric vehicle to meet the image inspection conditions and obtain image inspection information, including: The inspection equipment activates the recognition module and moves around the shared electric vehicle 360 ​​degrees along a preset path. During the movement, it sequentially collects images of the vehicle body from different angles and controls the inspection code within the inspection image group code to trigger the shared electric vehicle to respond at different angles. The recognition module compares the vehicle image with a preset image to identify damaged equipment and obtain image inspection information. The image inspection condition is met after the inspection equipment completes a 360-degree rotation.

9. The method according to claim 1, characterized in that, The inspection equipment sequentially extracts the inspection codes from the joint inspection code and interacts with the shared electric vehicles, enabling the inspection equipment and the shared electric vehicles to achieve multimodal inspection conditions and obtain multimodal inspection information, including: The inspection equipment locates the brake position of the shared electric vehicle and uses a robotic arm to merge and obtain the corresponding linked images of the brake. By performing linkage analysis on the linked images, the damaged brakes and combined braking equipment are identified, multimodal inspection information is obtained, and multimodal inspection conditions are met.

10. The method according to claim 9, characterized in that, The inspection equipment locates the brake position of the shared electric vehicle and, based on the robotic arm, merges and acquires the corresponding linked images of the brake, including: The system determines the first position of the first brake of the shared electric vehicle and the first combined braking device corresponding to the first brake. It controls the robotic arm to correspond to the preset position of the first brake and executes the closing operation. At the same time, the camera device extracts images of the first combined braking device. The robot arm is controlled to close and tighten for a preset time. The first video of the camera device is extracted within the closing time. If the first video reaches the braking condition, the linked image is correct. If the first video does not meet the braking conditions, the linked image will produce an error.

11. The AI-based intelligent inspection system for shared electric vehicles according to any one of claims 1-10, characterized in that, include: The acquisition module is used by the server to acquire the attributes of shared electric vehicles in non-use status within the positioning area where the inspection equipment is located. The attributes include location and historical inspection time. The linkage module is used by the server to determine that if the time interval between the historical inspection time and the current time is greater than or equal to a first preset value, then the corresponding attribute is used as the first attribute to obtain the number of other shared electric vehicles within the first preset distance. The inspection module is used to send an inspection signal to the shared electric vehicle and the inspection equipment if the number of linkages exceeds the preset value, so as to control the shared electric vehicle to reach the inspection state and add an inspection tag. The results module is used by the inspection equipment to perform multimodal interaction and image recognition processing on the shared electric vehicles to obtain inspection data.

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