Interaction method and system for cloud platform to manage intelligent terminal

Abstract

The invention provides an interaction method and system for a cloud platform to manage an intelligent terminal, and is applied to the field of communication data processing. According to the invention, through centralized identification and response of the cloud platform to the vehicle interaction request, the problem processing delay caused by personnel departure or shift change in the parking lot service is effectively solved, and through real-time acquisition of information such as the vehicle access record, the parking space number and the charging pile number, whether the request is responded or not can be automatically judged and the terminal calling function is activated; a customer service participated response bridge is constructed, remote instant service support is realized, driving state judgment and congestion information analysis are combined, vehicles are dynamically guided to perform scheduling and path avoidance, in-site congestion or service interruption is avoided, interaction data is generated, closed-loop processing of task execution and user feedback is guaranteed, and the system and the method are suitable for large-scale popularization and application. Therefore, continuous and efficient service support is realized in an unattended period or a personnel empty period, and the operation intelligence level and the user satisfaction degree of the parking lot are improved.

Description

Technical Field

[0001] The present invention relates to the field of communication data processing, and in particular to an interactive method and system for managing smart terminals on a cloud platform. Background Art

[0002] With the development of artificial intelligence technology and the widespread application of Internet of Things technology, the parking and charging industry has begun to enter a refined management model from the traditional shift-based management and operation. It has transitioned from multi-person shifts to smart terminals, freeing up personnel to do other things such as project inspections. At the same time, a 24-hour duty service desk is set up in the background, and multiple projects are managed uniformly in the cloud, which greatly improves the company's cost reduction, efficiency improvement and management level.

[0003] In the existing parking and charging management, when a vehicle needs help entering or exiting a parking lot or charging on site, the staff may be away from their posts or changing shifts and unable to provide timely service. This results in the problem of vehicle entry and exit or charging not being handled in a timely manner, causing congestion. Summary of the Invention

[0004] The present invention aims to solve the problem that when a vehicle needs help entering or exiting a parking lot or charging on site, personnel may be away from their posts or on shift change and unable to provide timely service, resulting in the problem that the vehicle entry and exit or charging problem cannot be handled in a timely manner. The invention provides an interactive method and system for smart terminal management on a cloud platform.

[0005] The present invention adopts the following technical means to solve the technical problem: The present invention provides an interactive method for managing smart terminals on a cloud platform, comprising: Based on the vehicle information collected by the cloud platform at the entrance and exit of the parking lot, the interaction request uploaded by the vehicle through the parking lot terminal is received. The vehicle information specifically includes entry and exit records, parking space number and charging pile number; Determining whether the interaction request receives a response from the cloud platform; If so, the terminal call function preset in the parking terminal is dynamically activated. Based on the terminal call function, a response bridge for short-term interaction with the parking terminal is constructed from the cloud platform. Preset customer service personnel are mobilized on the cloud platform to join the response bridge, and a work order to be served corresponding to the vehicle is generated. The work order to be served specifically includes billing anomalies, equipment failures, and insufficient resources. Determining whether the work order to be serviced can obtain service authorization for the vehicle; If possible, then based on the driving status divided by the customer service based on the vehicle information, the congestion information caused by the vehicle in the parking lot is obtained. Based on the congestion information, the vehicle is guided to perform mobile scheduling in the parking lot through the response bridge, and the vehicle's interaction data is generated in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

[0006] Furthermore, before the step of obtaining the congestion information caused by the vehicle in the parking lot, the method further includes: Identifying location information of the vehicle in the parking lot, and based on the location information, using a preset camera to acquire image data of the vehicle within a preset range; Determining whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; If so, the vehicle's external features are collected through the image data, and the required temporary parking space for the vehicle is constructed based on the external features. Based on the required temporary parking space, the temporary parking position of the vehicle is divided in a preset temporary buffer zone from the cloud platform, wherein the external features specifically include size features, posture features, type features and structural features.

[0007] Furthermore, the step of mobilizing a preset customer service representative on the cloud platform to join the response bridge and generating a work order to be serviced corresponding to the vehicle further includes: Based on the idle customer service resources pre-detected on the cloud platform, randomly assigning the customer service from the idle customer service resources to provide cloud interactive services to the vehicle; Determine whether the cloud interactive service can complete the interactive docking; If so, the interaction progress of the vehicle is generated. According to the interaction progress, the idle customer service resources are restricted from multi-party interaction with the vehicle. The interaction transfer request of the customer service is identified. According to the interaction transfer request, another customer service is reallocated from the idle customer service resources to provide cloud-based interaction services for the vehicle, and the historical interaction information of the vehicle is constructed on the cloud platform.

[0008] Furthermore, the step of dividing the driving status of the vehicle information by the customer service further includes: Based on the image data pre-captured by the cloud platform of the vehicle, combined with the real-time vehicle status uploaded to the cloud platform by the vehicle, identifying the vehicle's status information, wherein the status information specifically includes the location, direction angle, battery level, door and window status, brake status, gear information, whether the vehicle is charging, and whether the vehicle is locked; Determining whether the status information matches a status type preset by the cloud platform, wherein the status types specifically include movable, stationary but recallable, and forced stationary; If so, the vehicle is marked in the virtual map preset by the cloud platform, corresponding marking data is generated, and the navigation direction information in the virtual map is dynamically adjusted according to the marking data.

[0009] Furthermore, the step of determining whether the interaction request receives a response from the cloud platform further includes: Parsing the request content type of the interaction request based on the request source of the interaction request, wherein the request source specifically includes the user app, the vehicle system, and the customer service console, and the request content type specifically includes asking for help, moving the vehicle, reporting charging failure, and voice call; Determine whether the request content type belongs to the conventional question type preset by the cloud platform; If so, a preset question utterance is replied from the cloud platform to the parking lot terminal, the question utterance is used to guide the vehicle to process the interaction request, and the interaction completion result of the vehicle is generated in real time on the cloud platform.

[0010] Furthermore, the step of determining whether the work order to be serviced can obtain service authorization for the vehicle further includes: Based on the service content of the work order to be serviced, obtaining remote control data of the vehicle through the cloud platform; Determining whether the remote control data matches a service level permission preset by the cloud platform, wherein the service level permission specifically includes information viewing only, allowing voice remote communication, and allowing remote control of the vehicle; If so, the service execution parameters of the service content are dynamically adjusted according to the current state of the vehicle, wherein the current state specifically includes the user driving state, the automatic driving state and the power off state, and the service execution parameters specifically include the service duration, service period and service restrictions.

[0011] Furthermore, the step of receiving an interaction request uploaded by a vehicle through a parking lot terminal based on the vehicle information collected at the parking lot entrance and exit by the cloud platform further includes: Based on the interaction request pre-sent by the vehicle through the parking lot terminal, responding to the interaction request to the cloud platform; Determining whether the cloud platform responds to the vehicle; If not, a corresponding interaction failure record is generated from the cloud platform, and the interaction failure record is marked as a priority interaction event. According to the priority interaction event, the customer service resources preset by the cloud platform are dynamically mobilized.

[0012] The present invention also provides an interactive system for managing smart terminals on a cloud platform, comprising: A receiving module is used to receive interaction requests uploaded by vehicles through parking lot terminals based on vehicle information collected at parking lot entrances and exits by the cloud platform, wherein the vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers; A judgment module, configured to judge whether the interaction request has received a response from the cloud platform; an execution module configured to dynamically activate a terminal call function preset in the parking terminal, and, based on the terminal call function, construct a response bridge for short-term interaction with the parking terminal from the cloud platform, mobilize a preset customer service representative on the cloud platform to join the response bridge, and generate a work order to be served corresponding to the vehicle, wherein the work order to be served specifically includes billing anomalies, equipment failures, and insufficient resources; A second judgment module is used to judge whether the work order to be serviced can obtain service authorization for the vehicle; The second execution module is used to, if possible, obtain the congestion information caused by the vehicle in the parking lot according to the driving status divided by the customer service based on the vehicle information; based on the congestion information, guide the vehicle to perform mobile scheduling in the parking lot through the response bridge, and generate the vehicle's interaction data in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

[0013] Furthermore, it also includes: an acquisition module, configured to identify location information of the vehicle in the parking lot, and based on the location information, use a preset camera to acquire image data of the vehicle within a preset range; a third determination module, configured to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; The third execution module is used to, if so, collect the appearance features of the vehicle through the image data, construct the required temporary parking space for the vehicle based on the appearance features, and divide the temporary parking position of the vehicle in a preset temporary buffer zone from the cloud platform based on the required temporary parking space, wherein the appearance features specifically include size features, posture features, type features and structural features.

[0014] Furthermore, the execution module further includes: An allocating unit, configured to randomly allocate the customer service personnel from the idle customer service resources pre-detected on the cloud platform to provide cloud interactive services to the vehicle; A judgment unit, configured to judge whether the cloud interactive service can complete the interactive docking; An execution unit is configured to, if so, generate an interaction progress for the vehicle, limit the idle customer service resources to conduct multi-party interactions with the vehicle based on the interaction progress, identify the customer service's interaction transfer request, and reallocate another customer service from the idle customer service resources to provide cloud-based interaction services for the vehicle based on the interaction transfer request, and construct historical interaction information of the vehicle on the cloud platform.

[0015] The present invention provides an interactive method and system for cloud platform management of intelligent terminals, which has the following beneficial effects: The present invention centrally identifies and responds to vehicle interaction requests through a cloud platform, effectively solving the problem processing delay caused by staff leaving their posts or changing shifts in parking lot services. By collecting information such as vehicle entry and exit records, parking space numbers, and charging pile numbers in real time, it can automatically determine whether the request is responded to and activate the terminal call function, build a response bridge with customer service participation, and realize remote instant service support. Combined with driving status judgment and congestion information analysis, the present invention dynamically guides vehicles for scheduling and path avoidance to avoid congestion or service interruption in the parking lot. At the same time, it generates interactive data to ensure closed-loop processing of task execution and user feedback, thereby realizing continuous and efficient service support during unmanned or staff-unavailable periods, and improving the intelligent level of parking lot operations and user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of an embodiment of an interactive method for managing smart terminals via a cloud platform according to the present invention; Figure 2 This is a structural block diagram of an embodiment of the interactive system for managing smart terminals on a cloud platform of the present invention. DETAILED DESCRIPTION

[0017] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. The implementation, functional features and advantages of the present invention will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] Reference Attachment Figure 1 , is an interactive method for managing smart terminals by a cloud platform in one embodiment of the present invention, comprising: S1: Based on the vehicle information collected by the cloud platform at the entrance and exit of the parking lot, the interaction request uploaded by the vehicle through the parking lot terminal is received. The vehicle information specifically includes entry and exit records, parking space number and charging pile number; S2: Determine whether the interaction request receives a response from the cloud platform; S3: If yes, dynamically activate the terminal call function preset in the parking terminal. Based on the terminal call function, build a response bridge for short-term interaction with the parking terminal from the cloud platform. Mobilize the preset customer service on the cloud platform to join the response bridge, and generate a work order for the vehicle. The work order specifically includes billing anomalies, equipment failures, and insufficient resources. S4: Determine whether the work order to be serviced can obtain service authorization for the vehicle; S5: If yes, then according to the driving status divided by the customer service based on the vehicle information, the congestion information caused by the vehicle in the parking lot is obtained, and based on the congestion information, the vehicle is guided to perform mobile scheduling in the parking lot through the response bridge, and the interaction data of the vehicle is generated in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

[0020] In this embodiment, the system is based on the vehicle information collected and entered by the cloud platform at the entrance and exit of the parking lot. The vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers. When a vehicle is received in the parking lot, the system uploads the user's interaction request to the cloud platform through the parking lot terminals distributed at various locations in the parking lot. The system then determines whether these interaction requests are responded to by the cloud platform to execute the corresponding steps. For example, when the system determines that the user's interaction request to the cloud platform cannot be responded to by the cloud platform, the system will assume that the current customer service of the cloud platform is busy and has not yet found a free time to interact with the user. The system will automatically create a queue record for the unanswered request, assign a queue number and an estimated waiting time, and notify the user of the current queue status through the parking lot terminal or mobile terminal. At the same time, based on the type of user request content (such as "unable to charge"), the FAQ or knowledge base module is called to provide self-service guidance content with intelligent semantic matching, and a voice or text robot is started to guide the user to ask questions, preliminarily identify the type of question, and prepare context information for subsequent manual intervention. For example, when the system determines that the user's interaction request to the cloud platform can be answered, the system will automatically create a queue record for the unanswered request, assign a queue number and an estimated waiting time, and notify the user of the current queue status through the parking lot terminal or mobile terminal. At the same time, based on the type of user request content (such as "unable to charge"), the system will call the FAQ or knowledge base module to provide self-service guidance content with intelligent semantic matching, and start a voice or text robot to guide the user to ask questions, preliminarily identify the type of question, and prepare context information for subsequent manual intervention. Upon receiving a response from the cloud platform, the system deems the cloud platform's customer service representative capable of interacting normally with the user. The system dynamically activates the pre-configured terminal call function at the parking lot terminal, mobilizing pre-configured customer service representatives on the cloud platform to join the response bridge and generate a corresponding pending service ticket for the vehicle. These tickets include billing anomalies, equipment failures, and insufficient resources. By initiating the pre-configured terminal call function, the system effectively establishes a first-line communication channel between the user and the cloud customer service representative, avoiding service interruptions caused by traditional on-call issues such as temporary staff absences and shift changes. The real-time interactive response bridge quickly establishes a one-to-one communication path, ensuring that users receive immediate assistance when encountering issues such as vehicle entry and exit, charging failures, and billing anomalies, significantly improving service response speed and user trust. Furthermore, after responding to user requests, the cloud platform intelligently dispatches matching customer service personnel to the service channel based on their availability and task allocation rules. This process eliminates manual coordination and leverages the platform's resource scheduling engine to automatically dispatch customer service representatives and dynamically build an interactive bridge.After the customer service is transferred to the response bridge, he or she can communicate with the user efficiently through audio and video, visual interface or preset question and answer templates to achieve a quick understanding and preliminary judgment of the background of the problem. After the customer service enters the interaction bridge, the system will intelligently generate a "pending service work order" based on the interaction content between the customer service and the user, and classify it into typical problem types such as "billing anomaly", "equipment failure" or "insufficient resources". Each type of work order will be accompanied by key information such as user vehicle information, terminal location, interaction log, on-site image, etc., to facilitate subsequent automatic transfer or manual review and processing; then the system determines whether these pending service work orders can obtain service authorization for the vehicle to execute the corresponding steps; for example, when the system determines that there is no pending service work order corresponding to the vehicle, If the system cannot obtain service authorization for the user's vehicle, the system will assume that the user has not authorized the cloud center to have partial control over the vehicle, or because the user believes that the pending service ticket cannot solve the problem the user is facing, the system will pop up an authorization confirmation interface through the parking lot terminal, and explain in detail to the user the purpose, scope, and control boundaries of the authorization operation (such as only temporary remote movement, regeneration of parking space tasks, etc.), so as to eliminate user doubts with a transparent mechanism, and provide the service personnel's operating instructions or historical processing success rate to enhance user trust. At the same time, if the user still refuses to authorize, the system should start the "interaction failure guidance mode" and push self-service troubleshooting suggestions, such as "manually drag the vehicle to the buffer zone" and "try to power off and restart the charging pile".It also provides a "problem feedback reclassification" function to guide users to reselect the processing direction of the current work order, such as changing "billing abnormality" to "waiting for family processing" or "try again at an appointment time" to achieve the replacement of problem labels and task buffering. If the user insists on not authorizing, the system will eventually transfer the work order to "manual on-site assistance type", and simultaneously notify the offline inspection or security team, and generate a temporary vehicle label in the system (such as "waiting for human guidance" or "static stop") to prevent the system from trying to automatically dispatch the vehicle again, while prompting surrounding vehicles to avoid and alleviate local congestion risks. For example, when the system determines that the corresponding pending service work order of the vehicle can obtain the service authorization of the user's vehicle, the system will assume that the user has authorized partial control of the vehicle to the cloud center. The system will obtain the possible congestion information in the parking lot of the vehicle based on the driving status divided by the cloud customer service for the vehicle information, which specifically includes normal driving and abnormal driving. Based on different congestion information, when the vehicle is able to move, the vehicle is guided to move and dispatch in the parking lot by responding to the bridge. The mobile dispatch specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data with the vehicle is generated in real time on the cloud platform. The interactive data specifically includes service status, task execution, and user feedback. By identifying the vehicle's driving status and determining whether it is mobile, the system can promptly identify potential sources of congestion. Under the premise of vehicle authorization control, the system can automatically or semi-automatically guide vehicles to avoid critical channels, exit congested areas, or enter temporary buffer zones, thereby relieving hot spots, alleviating traffic pressure, and effectively improving the operating efficiency of the entire parking lot. At the same time, with the help of the "Response Bridge" mechanism, cloud-based customer service can obtain real-time information on vehicle driving status and congestion levels. Combined with system-generated route planning suggestions or dispatch instructions, it provides remote assistance and guidance. This mechanism avoids the judgment delay caused by customer service's lack of scene perception, ensures the timeliness and accuracy of problem handling, and significantly improves the professionalism of customer service assistance. The system also unifies various data during the service process (such as dispatch status, route execution results, user feedback, etc.) into interactive data, forming a traceable digital record. By recording service status, execution results, and user responses, the cloud platform can implement intelligent learning, service evaluation, and problem review, further optimizing dispatch strategies and human-machine collaboration processes, and providing reference and improvement basis for subsequent similar problem handling.

[0021] It should be noted that when a vehicle successfully interacts with the cloud center, but the user is unable to drive the vehicle normally, causing a traffic jam in the parking lot, the cloud platform first uses image recognition and positioning technology to accurately determine the location and occupancy range of the faulty vehicle and dynamically delineate an avoidance zone. The platform then issues avoidance instructions to surrounding connected vehicles, replanning their driving routes and guiding them around the faulty area to alleviate congestion. Simultaneously, the platform provides on-site avoidance prompts to non-connected vehicles through terminal devices such as guidance screens, light signs, and voice broadcasts within the parking lot. Furthermore, the cloud platform combines traffic flow data from the entire parking lot to optimize overall vehicle flow distribution, delaying or adjusting the start and entry timing of some vehicles to avoid further concentration in the congested area. If necessary, customer service personnel will proactively contact the relevant vehicle owners to assist in manually moving their vehicles or adjusting their routes. Through these comprehensive measures, the cloud platform achieves intelligent guidance and decentralized management of traffic flow within the parking lot, effectively alleviating traffic jams caused by faulty vehicles and ensuring smooth operation of the parking lot.

[0022] In this embodiment, before step S3 of obtaining the congestion information caused by the vehicle in the parking lot, the following steps are further included: S301: Identifying location information of the vehicle in the parking lot, and based on the location information, using a preset camera to acquire image data of the vehicle within a preset range; S302: Determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; S303: If so, the appearance features of the vehicle are collected through the image data, and the required temporary parking space of the vehicle is constructed based on the appearance features. Based on the required temporary parking space, the temporary parking position of the vehicle is divided from the cloud platform in a preset temporary buffer zone, wherein the appearance features specifically include size features, posture features, type features and structural features.

[0023] In this embodiment, after the user's vehicle is connected to the smart parking app, the system identifies the vehicle's location information in the parking lot. Based on different location information, the system obtains image data of the vehicle within a pre-set range through the camera in the parking lot. The system then determines whether pre-set congestion characteristics are detected in these image data. Congestion characteristics specifically include vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion, and then executes corresponding steps. For example, when the system determines that the image data of the vehicle within the pre-set range does not detect the pre-set congestion characteristics, the system will consider the traffic status of the area where the vehicle is currently located to be normal. The system will allow or guide the vehicle to continue along the originally planned route, for example, by indicating the route through the app or in-vehicle navigation. At the same time, the traffic status layer in the cloud is synchronously updated, marking the area as "unblocked" or "normal". In addition, according to the system operation logic, congestion handling steps such as emergency diversion and detour suggestions are skipped to improve response efficiency. For example, when the system determines that the image data of the vehicle within the pre-set range detects the pre-set congestion characteristics, the system will consider the traffic status of the area where the vehicle is currently located to be abnormal. The system will collect the vehicle's appearance characteristics through these image data. The appearance characteristics specifically include The system uses the size, posture, type and structure characteristics to construct the required temporary parking space for the vehicle based on different appearance characteristics. Based on the required temporary parking space, the temporary parking position of the vehicle is divided from the temporary buffer zone pre-set in the parking lot by the cloud platform. Based on the detected congestion characteristics, the system determines in real time whether the vehicle is the source of congestion, and further analyzes its appearance characteristics to automatically match the most suitable temporary parking space. This approach can achieve efficient and automated emergency dispatch without relying on manual judgment, and quickly guide abnormal vehicles to the temporary buffer zone that does not affect the main traffic path, thereby reducing traffic pressure in the parking lot. At the same time, after determining the appearance characteristics (such as vehicle length, width, height, posture, and model), the system can intelligently allocate a temporary buffer position that best matches the vehicle's size and structure to ensure that the vehicle will not occupy other lanes or block the camera's field of view when parked, reducing secondary safety risks such as scratches, scrapes, and blind spots caused by improper parking. After the appearance characteristics correspond to the parking position one by one, the cloud platform can generate a complete service record chain based on this, providing key basic data for subsequent customer service access, maintenance scheduling, and abnormality review. With the help of structured information, the trainable model can continuously optimize congestion identification and scheduling strategies, and enhance the system's self-learning and intelligent evolution capabilities.

[0024] In this embodiment, the step S3 of mobilizing a preset customer service on the cloud platform to join the response bridge and generating a service work order corresponding to the vehicle further includes: S31: Based on the idle customer service resources pre-detected on the cloud platform, randomly assigning the customer service from the idle customer service resources to provide cloud interactive services to the vehicle; S32: Determine whether the cloud interactive service can complete the interactive docking; S33: If so, generate the interaction progress of the vehicle, and based on the interaction progress, limit the idle customer service resources to conduct multi-party interaction with the vehicle, identify the interaction transfer request of the customer service, and reallocate another customer service from the idle customer service resources based on the interaction transfer request to provide cloud-based interaction services for the vehicle, and build the historical interaction information of the vehicle on the cloud platform.

[0025] In this embodiment, the system randomly assigns customer service personnel to provide cloud-based interactive services to vehicles based on idle customer service resources pre-detected on the cloud platform. The system then determines whether the cloud-based interactive service can complete the interactive docking to execute the corresponding steps. For example, when the system determines that the cloud-based interactive service cannot complete the interactive docking normally, the system will consider that the communication between the currently assigned customer service resources and the vehicle user has not been successfully established. The system will reclassify the customer service resources that have been assigned but not successfully connected into the idle pool to avoid resource waste, and at the same time reassign available personnel from the remaining idle customer service personnel, supporting up to N consecutive The system can redistribute the information to improve the success rate of docking, and in the scenario where no customer service is available or multiple docking fails, call AI customer service to handle routine problems first, and improve emergency response capabilities. For example, when the system determines that the cloud interactive service can complete the interactive docking normally, the system will consider that the currently allocated customer service resources have successfully established communication with the vehicle user. The system will generate the interaction progress between the vehicle and the customer service on the cloud platform. According to the ongoing interaction progress, it will limit other idle customer service resources from repeating multi-party interactions with the vehicle, identify the interaction transfer request applied by the customer service, and reallocate another customer service from the idle customer service resources to provide cloud interactive services to the vehicle user based on the interaction transfer request, and build the vehicle's historical interaction information on the cloud platform. The system can ensure that only one customer service representative is allowed to interact with the vehicle user at any one time through a unified management mechanism of the interaction progress. Service interactions are carried out with vehicle users to prevent command confusion, response conflicts and information overlap caused by the simultaneous intervention of multiple customer service representatives, ensuring the logical consistency of the interaction process and the accuracy of the processing results. At the same time, when the existing customer service representative needs to transfer services due to work handover, skill mismatch or system arrangement, the system can identify their interaction transfer requests and reallocate matching personnel from idle customer service representatives to continue the service, effectively avoiding the impact of human factors or service interruptions on user experience, maintaining seamless connection and continuous processing of the cloud interaction process, and each cloud interaction is recorded by the system as historical interaction information of the vehicle, including service request type, processing records, customer service instructions, user feedback and other data, providing data support for subsequent personalized service recommendations, rapid problem location, and follow-up of repeated problems, and also helping the platform to conduct interaction quality evaluation and customer service performance analysis.

[0026] In this embodiment, the step S5 of dividing the driving status of the vehicle information by the customer service further includes: S51: Based on the image data pre-captured by the cloud platform of the vehicle and in combination with the real-time vehicle status uploaded to the cloud platform by the vehicle, identifying the vehicle status information, wherein the status information specifically includes the location, direction angle, battery level, door and window status, brake status, gear information, whether the vehicle is being charged, and whether the vehicle is locked; S52: Determine whether the status information matches a status type preset by the cloud platform, wherein the status type specifically includes movable, stationary but recallable, and forced stationary; S53: If yes, mark the vehicle in the virtual map preset by the cloud platform, generate corresponding marking data, and dynamically adjust the navigation direction information in the virtual map according to the marking data.

[0027] In this embodiment, the system identifies the vehicle's status information based on the image data pre-acquired by the cloud platform for the vehicle, combined with the real-time vehicle status uploaded to the cloud platform by the vehicle. The status information specifically includes location, direction angle, power, door and window status, brake status, gear information, whether it is charging and whether it is locked. The system then determines whether these status information match the status types pre-set by the cloud platform. The status types specifically include movable, stationary but recallable and forced stationary, so as to execute the corresponding steps; for example, when the system determines that the vehicle's status information cannot match the status type preset by the cloud platform, the system will consider that the vehicle uploaded If the vehicle's status information is missing, conflicting, or abnormal (such as the direction angle and gear position are inconsistent), the system will mark the vehicle's status as "unknown status" or "pending manual review" and synchronize abnormal prompts to the user and customer service to avoid misoperation and scheduling errors. At the same time, the system will instruct the vehicle to upload a set of status data again and jointly call the surrounding cameras in the parking lot to collect images again. The double comparison reduces the impact of occasional errors or data delay interference, and enables manual review mode, allowing customer service to manually assign a temporary status to the vehicle based on the actual vehicle situation and scene traffic logic, triggering the corresponding scheduling plan to ensure uninterrupted service under abnormal conditions. For example, when the system determines that the vehicle's status information matches the status type preset by the cloud platform, the system will consider that the status information uploaded by the vehicle is normal. The system will mark the vehicle in the virtual map of the parking lot pre-set by the cloud platform and generate corresponding marking data. According to different marking data, the navigation direction information in the virtual map is dynamically adjusted. By promptly marking vehicles in normal status in the virtual map of the cloud platform, the system can dynamically generate navigation directions based on the real position and status, ensuring that the navigation path is highly consistent with the current actual passability of the vehicle, effectively improving the navigation of car owners in the parking lot for behaviors such as finding, leaving, and charging. Efficiency, while the marking data can reflect the real-time behavior of the vehicle (such as whether it is charging, whether it is movable, etc.), and the system dynamically adjusts the navigation direction information in the map accordingly to avoid guiding other vehicles into congestion, obstacles or resource-occupied areas, thereby better completing intelligent scheduling tasks such as path avoidance, parking space recommendation, and buffer zone allocation. In addition, the continuously updated vehicle marking data enables the virtual map to remain highly synchronized with the on-site environment, avoiding navigation errors caused by vehicle changes, position drift or parking status changes, and enhancing the overall perception synchronization and service stability of the system. It is especially suitable for smart parking environments with high traffic and high entry and exit frequencies.

[0028] In this embodiment, the step S2 of determining whether the interaction request receives a response from the cloud platform further includes: S21: parsing the request content type of the interaction request based on the request source of the interaction request, wherein the request source specifically includes a user app, an in-vehicle system, and a customer service console, and the request content type specifically includes a request for help, moving the vehicle, reporting a charging failure, and a voice call; S22: Determine whether the request content type belongs to the conventional question type preset by the cloud platform; S23: If yes, reply a preset question utterance from the cloud platform to the parking lot terminal, guide the vehicle to process the interaction request through the question utterance, and generate the interaction completion result of the vehicle in real time on the cloud platform.

[0029] In this embodiment, the system parses the request content type of the interactive request based on the request source, which specifically includes the user App side, the vehicle system and the customer service console. The request content type specifically includes asking for help, moving the car, reporting charging failure and voice call. The system then determines whether these request content types belong to the conventional problem types pre-set by the cloud platform to execute the corresponding steps; for example, when the system determines that the request content type of the interactive request does not belong to the conventional problem type pre-set by the cloud platform, the system will consider that the request content initiated by the current user or vehicle is unconventional, sudden or complex, and may involve new problems, unclassified scenarios, or special matters that require manual intervention. The system will automatically The unconventional request is marked as a "non-standard request", skipping the regular automated process and giving priority to manual customer service with high processing authority for one-on-one response, ensuring that the user's problem can be quickly identified and processed, avoiding user waiting or service failure due to the inability of the automatic system to identify it. At the same time, the source, content, context interaction data and processing path of the request are fully recorded and uploaded to the cloud data analysis module for subsequent model training and rule library updates, thereby enhancing the system's ability to recognize unconventional scenarios. If the current customer service cannot handle it immediately, the system can send an automatic receipt to the user in the form of voice, text, etc., prompting that it is being processed, and guiding the user to provide additional information (such as pictures, voice descriptions, license plates, etc.) so that the customer service can determine it as soon as possible. For example, when the system determines that the content type of the interactive request belongs to the general question type pre-set by the cloud platform, the system will think that the current interactive request does not need to use customer service resources to assist the user's vehicle to solve the problem. The system will reply with the pre-set question quotations from the cloud platform to the parking lot terminal for the user to solve the problem encountered through the parking lot terminal. The vehicle is guided to process the interactive request through these question quotations, and the interaction completion result of the vehicle is generated in real time on the cloud platform. When the interactive request belongs to the general question type, the system will automatically divert the processing to avoid occupying manual customer service resources for questions that can be answered automatically. This mechanism can effectively improve the scheduling efficiency of customer service resources and give priority to complex or sudden problems. The system can improve the manual response capability of raising questions, thereby improving the service carrying capacity and response speed of the system as a whole. At the same time, structured question quotations are pushed through the parking lot terminal to guide users to handle problems by themselves. This method not only shortens the time required for problem solving, but also improves the user's operational initiative and efficiency in the terminal environment, and enhances the user's trust and satisfaction with the intelligence of the system. After the system automatically handles routine problems, it will still generate "interaction completion results" in real time and synchronize them to the cloud. This process builds a complete link record of interaction data, which not only helps subsequent service quality analysis and problem tracing, but also provides data support for the system to evaluate the effectiveness and coverage of question quotations, and promotes the platform to continuously optimize the routine problem handling mechanism.

[0030] In this embodiment, the step S4 of determining whether the work order to be serviced can obtain service authorization for the vehicle further includes: S41: Based on the service content of the work order to be serviced, obtaining remote control data of the vehicle through the cloud platform; S42: Determine whether the remote control data matches the service level permissions preset by the cloud platform, wherein the service level permissions specifically include information viewing only, allowing voice remote communication, and allowing remote control of the vehicle; S43: If yes, the service execution parameters of the service content are dynamically adjusted according to the current state of the vehicle, wherein the current state specifically includes the user driving state, the automatic driving state and the power off state, and the service execution parameters specifically include the service duration, service period and service restrictions.

[0031] In this embodiment, the system obtains the remote control data of the vehicle through the cloud platform based on the service content of the work order to be serviced, and then the system determines whether the remote control data matches the service level permissions pre-set by the cloud platform. The service level permissions specifically include information viewing only, allowing voice remote communication, and allowing remote control of the vehicle to execute the corresponding steps; for example, when the system determines that the remote control data of the vehicle cannot match the service level permissions pre-set by the cloud platform, the system will consider that the remote operation currently requested exceeds the service permission range authorized by the vehicle user, and it may be that the user has not authorized the cloud platform to control the vehicle at the corresponding level. The system will Attempt to convert the original service operation into an alternative operation that can be executed within the permission level, such as replacing "direct remote control" with "voice remote communication", and at the same time send a permission-inadequate notification to the user App or vehicle terminal through the parking terminal, indicating that the current operation cannot be executed due to insufficient permission level, provide a guidance link for upgrading permissions or modifying authorization settings, and mark the service ticket as "restricted permission" to avoid the system from repeatedly trying invalid control operations and ensure that the service process is clear, closed-loop, and traceable; for example, when the system determines that the vehicle's remote control data can match the service level permissions pre-set by the cloud platform, the system will consider that the remote operation currently requested is in The system will dynamically adjust the service execution parameters of the service content according to the current status of the vehicle, including the user driving status, automatic driving status and power-off status. The service execution parameters include service duration, service period and service restrictions. The system can effectively avoid unauthorized operations by judging whether the remote control data matches the service level authority authorized by the user, ensuring that all control behaviors are carried out within the scope of the user's explicit authorization. A successful match indicates that the user has trusted the cloud platform. The system can perform remote operations without infringing on the user's wishes, thereby improving the credibility and standardization of the service. At the same time, based on the current status of the vehicle (such as Dynamically adjusting service execution parameters (such as service duration, time period, and restrictions) during driving, autonomous driving, and power outages can effectively avoid service conflicts or failures caused by scenario mismatches. For example, automatically shortening service duration or restricting certain control instructions while the user is driving can help reduce interference with driving behavior and improve user experience. Flexible configuration of service execution details through preset service parameters can avoid resource waste caused by unified processing and provide an accurate basis for service scheduling in different scenarios. This on-demand adjustment mechanism not only improves service response efficiency, but also reduces system burden and improves overall operation and maintenance capabilities by reasonably allocating service resources (such as time period restrictions).

[0032] In this embodiment, based on the vehicle information collected by the cloud platform at the entrance and exit of the parking lot, step S1 of receiving the interaction request uploaded by the vehicle through the parking lot terminal also includes: S11: Based on the interaction request pre-sent by the vehicle through the parking lot terminal, respond to the interaction request to the cloud platform; S12: Determine whether the cloud platform responds to the vehicle; S13: If not, a corresponding interaction failure record is generated from the cloud platform, and the interaction failure record is marked as a priority interaction event. According to the priority interaction event, the customer service resources preset by the cloud platform are dynamically mobilized.

[0033] In this embodiment, the system responds to the interaction requests sent in advance by the vehicle through the parking lot terminal to the cloud platform, and then the system determines whether the cloud platform responds to the vehicle to execute the corresponding steps; for example, when the system determines that the cloud platform responds to the vehicle's interaction request, the system will consider that the network link is stable, the vehicle terminal in the parking lot has successfully uploaded the interaction request to the cloud, and has been effectively received and responded to by the cloud platform. The system will formally start the interactive session process, such as loading the corresponding service module (such as customer service interface, automatic answering, intelligent guidance, etc.), pushing response information or operation instructions to the vehicle terminal, and parsing the content of the interaction request. The type (such as asking for help, moving the car, voice call, etc.) is matched with the service strategy preset by the cloud platform, and then different service logic is executed (such as dispatching customer service, pushing common problem guidance, calling remote control instructions, etc.), and the time, request content, response, service results and other information of this interaction are recorded on the cloud platform to provide data support for subsequent tracking of problem solving or user satisfaction evaluation; for example, when the system determines that the cloud platform has not responded to the vehicle's interaction request, the system will consider that the current customer service resources are full and there are no idle resources to reply to the vehicle. The system will generate a corresponding interaction unconnected record from the cloud platform and mark the interaction unconnected record as The next priority interaction event will be based on the priority interaction event, and the customer service resources pre-set on the cloud platform will be dynamically mobilized. When the system detects that the cloud platform fails to respond to the vehicle's interaction request, it believes that the customer service resources are temporarily full, and the system will automatically generate an "interaction unconnected record" and mark it as the next priority event to ensure that vehicles that fail to respond in time will receive a higher response priority in the next round of resource scheduling. This mechanism avoids the risk of service resources being repeatedly allocated to subsequent requesting users, effectively improving the fairness of interactive services and overall scheduling efficiency. At the same time, after identifying the "unconnected record", the system will dynamically mobilize the customer service resources of the cloud platform, such as from the backup customer service By activating new customer services in the pool, reallocating some low-priority tasks, or temporarily suspending some non-critical tasks, the ability to process high-priority interaction requests can be quickly restored. This resource management method can avoid long-term resource overload or idleness, and achieve intelligent and balanced distribution of service loads. Even in extreme cases of high customer service concurrency and high system pressure, the mechanism can still ensure that every unresponded request is recorded, tracked and prioritized, significantly reducing the interaction interruption rate. The system provides a basis for subsequent data analysis by constructing "interaction disconnection records", which helps the platform continuously optimize service capabilities and dynamic capacity planning, and ultimately enhance overall service reliability and user satisfaction.

[0034] Reference Attachment Figure 2 , is an interactive system for managing smart terminals by a cloud platform in one embodiment of the present invention, comprising: The receiving module 10 is used to receive the interaction request uploaded by the vehicle through the parking lot terminal based on the vehicle information collected by the cloud platform at the parking lot entrance and exit, wherein the vehicle information specifically includes the entry and exit record, parking space number and charging pile number; A determination module 20 is configured to determine whether the interaction request has received a response from the cloud platform; Execution module 30 is configured to dynamically activate a terminal call function preset in the parking terminal, and based on the terminal call function, construct a response bridge for short-term interaction with the parking terminal from the cloud platform, mobilize a preset customer service representative on the cloud platform to join the response bridge, and generate a work order to be serviced corresponding to the vehicle, wherein the work order to be serviced specifically includes billing anomalies, equipment failures, and insufficient resources; The second judgment module 40 is used to judge whether the work order to be serviced can obtain the service authorization of the vehicle; The second execution module 50 is used to, if possible, obtain the congestion information caused by the vehicle in the parking lot according to the driving status divided by the customer service based on the vehicle information, guide the vehicle to perform mobile scheduling in the parking lot through the response bridge based on the congestion information, and generate the vehicle's interaction data in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

[0035] In this embodiment, the receiving module 10 is based on the vehicle information collected and recorded by the cloud platform at the entrance and exit of the parking lot. The vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers. When the vehicle is received in the parking lot, the user's interaction request to the cloud platform is uploaded through the parking lot terminals distributed at various locations in the parking lot. The judgment module 20 then judges whether these interaction requests have been responded to by the cloud platform to execute the corresponding steps. For example, when the system determines that the user's interaction request to the cloud platform cannot be responded to by the cloud platform, the system will assume that the customer service of the current cloud platform is busy and has not yet found a free time to interact with the user. The system will automatically create a queue record for the unanswered request, assign a queue number and an estimated waiting time, and notify the user of the current queue status through the parking lot terminal or mobile terminal. At the same time, based on the type of user request content (such as "unable to charge"), the FAQ or knowledge base module is called to provide self-service guidance content with intelligent semantic matching, and a voice or text robot is activated to guide the user to ask questions, preliminarily identify the type of question, and prepare context information for subsequent manual intervention. For example, when the system determines that the user's interaction request to the cloud platform is not responded to, the system will assume that the customer service of the current cloud platform is busy and has not yet found a free time to interact with the user. The system will automatically create a queue record for the unanswered request, assign a queue number and an estimated waiting time, and notify the user of the current queue status through the parking lot terminal or mobile terminal. At the same time, based on the type of user request content (such as "unable to charge"), the system will call the FAQ or knowledge base module to provide self-service guidance content with intelligent semantic matching, and start a voice or text robot to guide the user to ask questions, preliminarily identify the type of question, and prepare context information for subsequent manual intervention. If a response is received from the cloud platform, the execution module 30 will assume that the customer service of the current cloud platform is able to interact normally with the user. The system will dynamically activate the terminal call function pre-set at the parking lot terminal, mobilize the pre-set customer service on the cloud platform to join the response bridge, and generate a corresponding waiting service ticket for the vehicle. The waiting service ticket specifically includes billing anomalies, equipment failures, and insufficient resources. By activating the preset terminal call function, the system effectively opens up a first-time communication channel between the user and the cloud customer service, avoiding service interruptions caused by traditional on-duty issues such as temporary staff absences and shift changes. Through the real-time interactive response bridge, a one-to-one communication path can be quickly established, ensuring that users can immediately obtain manual assistance when encountering problems in scenarios such as vehicle entry and exit, charging failures, and billing anomalies, significantly improving service response speed and user trust. At the same time, after responding to the user request, the cloud platform will intelligently dispatch the matching customer service personnel to the service channel based on the customer service availability and task allocation rules. This process no longer relies on manual allocation, but instead uses the platform's resource scheduling engine to achieve automatic customer service dispatch and dynamic establishment of the interactive bridge.After the customer service is transferred to the response bridge, it can communicate with the user efficiently through audio and video, visual interface or preset question and answer templates to achieve a quick understanding and preliminary judgment of the problem background. After the customer service enters the interactive bridge, the system will intelligently generate a "waiting service work order" based on the interaction content between the customer service and the user, and classify it into typical problem types such as "billing anomaly", "equipment failure" or "insufficient resources". Each type of work order will be accompanied by key information such as user vehicle information, terminal location, interaction log, on-site image, etc., to facilitate subsequent automatic transfer or manual review and processing; then the second judgment module 40 determines whether these waiting service work orders can obtain the service authorization of the vehicle to execute the corresponding steps; for example, when the system determines that the vehicle corresponds to the waiting service work order, When the work order cannot obtain service authorization for the user's vehicle, the system will assume that the user has not authorized the cloud center to have partial control over the vehicle, or because the user believes that the work order to be serviced cannot solve the problem faced by the user, the system will pop up an authorization confirmation interface through the parking lot terminal, explaining in detail to the user the purpose, scope of action, and control boundaries of the authorization operation (such as only temporary remote movement, regeneration of parking space tasks, etc.), using a transparent mechanism to eliminate user concerns, and attaching service personnel's operating instructions or historical processing success rates to enhance user trust. At the same time, if the user still refuses to authorize, the system should start the "interaction failure guidance mode" and push self-service troubleshooting suggestions, such as "manually drag the vehicle to the buffer zone" and "try to power off and restart the charging pile".It also provides a "problem feedback reclassification" function to guide users to reselect the processing direction of the current work order, such as changing "billing exception" to "waiting for family members to handle" or "try again at an appointment time" to achieve the replacement of problem labels and task buffering. If the user insists on not authorizing, the system will eventually transfer the work order to "manual on-site assistance type", and simultaneously notify the offline inspection or security team, and generate a temporary vehicle label in the system (such as "waiting for human guidance" or "static stop") to avoid the system from trying to automatically dispatch the vehicle again, and at the same time prompt surrounding vehicles to avoid and alleviate the risk of local congestion; for example, when the system determines that The service work order corresponding to the vehicle can obtain the service authorization of the user's vehicle. At this time, the second execution module 50 will think that the user has authorized partial control of the vehicle to the cloud center. The system will obtain the possible congestion information in the parking lot of the vehicle based on the driving status divided by the cloud customer service. The driving status specifically includes normal driving and abnormal driving. Based on different congestion information, when the vehicle can move, the vehicle is guided to move in the parking lot by responding to the bridge. The mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points. The cloud platform generates real-time information related to the vehicle. Interaction data, specifically including service status, task execution, and user feedback, can be identified by the system. By identifying a vehicle's driving status and determining whether it is mobile, the system can promptly identify potential sources of congestion. Under authorized vehicle control, the system can automatically or semi-automatically guide vehicles to avoid critical lanes, exit congested areas, or enter temporary buffer zones, thereby relieving hotspots, alleviating traffic pressure, and effectively improving the operational efficiency of the entire parking lot. Furthermore, through the "Response Bridge" mechanism, cloud-based customer service can obtain real-time information on vehicle driving status and congestion levels. Combined with system-generated route planning suggestions or dispatch instructions, it provides remote assistance and guidance. This mechanism avoids delays in customer service decisions caused by a lack of contextual awareness, ensures timely and accurate problem resolution, and significantly enhances the professionalism of customer service assistance. The system also generates interactive data from various service data (such as dispatch status, route execution results, and user feedback) to create a traceable digital record. By recording service status, execution results, and user responses, the cloud platform can implement intelligent learning, service evaluation, and problem analysis, further optimizing dispatch strategies and human-machine collaboration processes, and providing a reference and improvement basis for subsequent handling of similar issues.

[0036] In this embodiment, it also includes: an acquisition module, configured to identify location information of the vehicle in the parking lot, and based on the location information, use a preset camera to acquire image data of the vehicle within a preset range; a third determination module, configured to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; The third execution module is used to, if so, collect the appearance features of the vehicle through the image data, construct the required temporary parking space for the vehicle based on the appearance features, and divide the temporary parking position of the vehicle in a preset temporary buffer zone from the cloud platform based on the required temporary parking space, wherein the appearance features specifically include size features, posture features, type features and structural features.

[0037] In this embodiment, after the user's vehicle is connected to the smart parking app, the system identifies the vehicle's location information in the parking lot. Based on different location information, the system obtains image data of the vehicle within a pre-set range through the camera in the parking lot. The system then determines whether pre-set congestion characteristics are detected in these image data. Congestion characteristics specifically include vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion, and then executes corresponding steps. For example, when the system determines that the image data of the vehicle within the pre-set range does not detect the pre-set congestion characteristics, the system will consider the traffic status of the area where the vehicle is currently located to be normal. The system will allow or guide the vehicle to continue along the originally planned route, for example, by indicating the route through the app or in-vehicle navigation. At the same time, the traffic status layer in the cloud is synchronously updated, marking the area as "unblocked" or "normal". In addition, according to the system operation logic, congestion handling steps such as emergency diversion and detour suggestions are skipped to improve response efficiency. For example, when the system determines that the image data of the vehicle within the pre-set range detects the pre-set congestion characteristics, the system will consider the traffic status of the area where the vehicle is currently located to be abnormal. The system will collect the vehicle's appearance characteristics through these image data. The appearance characteristics specifically include The system uses the size, posture, type and structure characteristics to construct the required temporary parking space for the vehicle based on different appearance characteristics. Based on the required temporary parking space, the temporary parking position of the vehicle is divided from the temporary buffer zone pre-set in the parking lot by the cloud platform. Based on the detected congestion characteristics, the system determines in real time whether the vehicle is the source of congestion, and further analyzes its appearance characteristics to automatically match the most suitable temporary parking space. This approach can achieve efficient and automated emergency dispatch without relying on manual judgment, and quickly guide abnormal vehicles to the temporary buffer zone that does not affect the main traffic path, thereby reducing traffic pressure in the parking lot. At the same time, after determining the appearance characteristics (such as vehicle length, width, height, posture, and model), the system can intelligently allocate a temporary buffer position that best matches the vehicle's size and structure to ensure that the vehicle will not occupy other lanes or block the camera's field of view when parked, reducing secondary safety risks such as scratches, scrapes, and blind spots caused by improper parking. After the appearance characteristics correspond to the parking position one by one, the cloud platform can generate a complete service record chain based on this, providing key basic data for subsequent customer service access, maintenance scheduling, and abnormality review. With the help of structured information, the trainable model can continuously optimize congestion identification and scheduling strategies, and enhance the system's self-learning and intelligent evolution capabilities.

[0038] In this embodiment, the execution module further includes: An allocating unit, configured to randomly allocate the customer service personnel from the idle customer service resources pre-detected on the cloud platform to provide cloud interactive services to the vehicle; A judgment unit, configured to judge whether the cloud interactive service can complete the interactive docking; An execution unit is configured to, if so, generate an interaction progress for the vehicle, limit the idle customer service resources to conduct multi-party interactions with the vehicle based on the interaction progress, identify the customer service's interaction transfer request, and reallocate another customer service from the idle customer service resources to provide cloud-based interaction services for the vehicle based on the interaction transfer request, and construct historical interaction information of the vehicle on the cloud platform.

[0039] In this embodiment, the system randomly assigns customer service personnel to provide cloud-based interactive services to vehicles based on idle customer service resources pre-detected on the cloud platform. The system then determines whether the cloud-based interactive service can complete the interactive docking to execute the corresponding steps. For example, when the system determines that the cloud-based interactive service cannot complete the interactive docking normally, the system will consider that the communication between the currently assigned customer service resources and the vehicle user has not been successfully established. The system will reclassify the customer service resources that have been assigned but not successfully connected into the idle pool to avoid resource waste, and at the same time reassign available personnel from the remaining idle customer service personnel, supporting up to N consecutive The system can redistribute the information to improve the success rate of docking, and in the scenario where no customer service is available or multiple docking fails, call AI customer service to handle routine problems first, and improve emergency response capabilities. For example, when the system determines that the cloud interactive service can complete the interactive docking normally, the system will consider that the currently allocated customer service resources have successfully established communication with the vehicle user. The system will generate the interaction progress between the vehicle and the customer service on the cloud platform. According to the ongoing interaction progress, it will limit other idle customer service resources from repeating multi-party interactions with the vehicle, identify the interaction transfer request applied by the customer service, and reallocate another customer service from the idle customer service resources to provide cloud interactive services to the vehicle user based on the interaction transfer request, and build the vehicle's historical interaction information on the cloud platform. The system can ensure that only one customer service representative is allowed to interact with the vehicle user at any one time through a unified management mechanism of the interaction progress. Service interactions are carried out with vehicle users to prevent command confusion, response conflicts and information overlap caused by the simultaneous intervention of multiple customer service representatives, ensuring the logical consistency of the interaction process and the accuracy of the processing results. At the same time, when the existing customer service representative needs to transfer services due to work handover, skill mismatch or system arrangement, the system can identify their interaction transfer requests and reallocate matching personnel from idle customer service representatives to continue the service, effectively avoiding the impact of human factors or service interruptions on user experience, maintaining seamless connection and continuous processing of the cloud interaction process, and each cloud interaction is recorded by the system as historical interaction information of the vehicle, including service request type, processing records, customer service instructions, user feedback and other data, providing data support for subsequent personalized service recommendations, rapid problem location, and follow-up of repeated problems, and also helping the platform to conduct interaction quality evaluation and customer service performance analysis.

[0040] In this embodiment, the second execution module further includes: an identification unit, configured to identify status information of the vehicle based on image data pre-captured by the cloud platform of the vehicle and in combination with the real-time vehicle status uploaded to the cloud platform by the vehicle, wherein the status information specifically includes position, direction angle, battery level, door and window status, brake status, gear position information, whether the vehicle is charging, and whether the vehicle is locked; A second judgment unit is used to judge whether the state information matches a state type preset by the cloud platform, wherein the state type specifically includes movable, stationary but recallable, and forced stationary; The second execution unit is configured to mark the vehicle in a virtual map preset by the cloud platform, generate corresponding marking data, and dynamically adjust the navigation direction information in the virtual map according to the marking data.

[0041] In this embodiment, the system identifies the vehicle's status information based on the image data pre-acquired by the cloud platform for the vehicle, combined with the real-time vehicle status uploaded to the cloud platform by the vehicle. The status information specifically includes location, direction angle, power, door and window status, brake status, gear information, whether it is charging and whether it is locked. The system then determines whether these status information match the status types pre-set by the cloud platform. The status types specifically include movable, stationary but recallable and forced stationary, so as to execute the corresponding steps; for example, when the system determines that the vehicle's status information cannot match the status type preset by the cloud platform, the system will consider that the vehicle uploaded If the vehicle's status information is missing, conflicting, or abnormal (such as the direction angle and gear position are inconsistent), the system will mark the vehicle's status as "unknown status" or "pending manual review" and synchronize abnormal prompts to the user and customer service to avoid misoperation and scheduling errors. At the same time, the system will instruct the vehicle to upload a set of status data again and jointly call the surrounding cameras in the parking lot to collect images again. The double comparison reduces the impact of occasional errors or data delay interference, and enables manual review mode, allowing customer service to manually assign a temporary status to the vehicle based on the actual vehicle situation and scene traffic logic, triggering the corresponding scheduling plan to ensure uninterrupted service under abnormal conditions. For example, when the system determines that the vehicle's status information matches the status type preset by the cloud platform, the system will consider that the status information uploaded by the vehicle is normal. The system will mark the vehicle in the virtual map of the parking lot pre-set by the cloud platform and generate corresponding marking data. According to different marking data, the navigation direction information in the virtual map is dynamically adjusted. By promptly marking vehicles in normal status in the virtual map of the cloud platform, the system can dynamically generate navigation directions based on the real position and status, ensuring that the navigation path is highly consistent with the current actual passability of the vehicle, effectively improving the navigation of car owners in the parking lot for behaviors such as finding, leaving, and charging. Efficiency, while the marking data can reflect the real-time behavior of the vehicle (such as whether it is charging, whether it is movable, etc.), and the system dynamically adjusts the navigation direction information in the map accordingly to avoid guiding other vehicles into congestion, obstacles or resource-occupied areas, thereby better completing intelligent scheduling tasks such as path avoidance, parking space recommendation, and buffer zone allocation. In addition, the continuously updated vehicle marking data enables the virtual map to remain highly synchronized with the on-site environment, avoiding navigation errors caused by vehicle changes, position drift or parking status changes, and enhancing the overall perception synchronization and service stability of the system. It is especially suitable for smart parking environments with high traffic and high entry and exit frequencies.

[0042] In this embodiment, the judgment module further includes: a parsing unit, configured to parse a request content type of the interaction request based on a request source of the interaction request, wherein the request source specifically includes a user app, an in-vehicle system, and a customer service console, and the request content type specifically includes a request for help, moving the vehicle, reporting a charging failure, and a voice call; A third judgment unit is used to judge whether the request content type belongs to the conventional question type preset by the cloud platform; The third execution unit is used to reply a preset question quotation from the cloud platform to the parking terminal if yes, guide the vehicle to process the interaction request through the question quotation, and generate the interaction completion result of the vehicle in real time on the cloud platform.

[0043] In this embodiment, the system parses the request content type of the interactive request based on the request source, which specifically includes the user App side, the vehicle system and the customer service console. The request content type specifically includes asking for help, moving the car, reporting charging failure and voice call. The system then determines whether these request content types belong to the conventional problem types pre-set by the cloud platform to execute the corresponding steps; for example, when the system determines that the request content type of the interactive request does not belong to the conventional problem type pre-set by the cloud platform, the system will consider that the request content initiated by the current user or vehicle is unconventional, sudden or complex, and may involve new problems, unclassified scenarios, or special matters that require manual intervention. The system will automatically The unconventional request is marked as a "non-standard request", skipping the regular automated process and giving priority to manual customer service with high processing authority for one-on-one response, ensuring that the user's problem can be quickly identified and processed, avoiding user waiting or service failure due to the inability of the automatic system to identify it. At the same time, the source, content, context interaction data and processing path of the request are fully recorded and uploaded to the cloud data analysis module for subsequent model training and rule library updates, thereby enhancing the system's ability to recognize unconventional scenarios. If the current customer service cannot handle it immediately, the system can send an automatic receipt to the user in the form of voice, text, etc., prompting that it is being processed, and guiding the user to provide additional information (such as pictures, voice descriptions, license plates, etc.) so that the customer service can determine it as soon as possible. For example, when the system determines that the content type of the interactive request belongs to the general question type pre-set by the cloud platform, the system will think that the current interactive request does not need to use customer service resources to assist the user's vehicle to solve the problem. The system will reply with the pre-set question quotations from the cloud platform to the parking lot terminal for the user to solve the problem encountered through the parking lot terminal. The vehicle is guided to process the interactive request through these question quotations, and the interaction completion result of the vehicle is generated in real time on the cloud platform. When the interactive request belongs to the general question type, the system will automatically divert the processing to avoid occupying manual customer service resources for questions that can be answered automatically. This mechanism can effectively improve the scheduling efficiency of customer service resources and give priority to complex or sudden problems. The system can improve the manual response capability of raising questions, thereby improving the service carrying capacity and response speed of the system as a whole. At the same time, structured question quotations are pushed through the parking lot terminal to guide users to handle problems by themselves. This method not only shortens the time required for problem solving, but also improves the user's operational initiative and efficiency in the terminal environment, and enhances the user's trust and satisfaction with the intelligence of the system. After the system automatically handles routine problems, it will still generate "interaction completion results" in real time and synchronize them to the cloud. This process builds a complete link record of interaction data, which not only helps subsequent service quality analysis and problem tracing, but also provides data support for the system to evaluate the effectiveness and coverage of question quotations, and promotes the platform to continuously optimize the routine problem handling mechanism.

[0044] In this embodiment, the second judgment module further includes: an acquiring unit, configured to acquire the remote control data of the vehicle through the cloud platform based on the service content of the work order to be serviced; a fourth determination unit, configured to determine whether the remote control data matches a service level permission preset by the cloud platform, wherein the service level permission specifically includes information viewing only, allowing voice remote communication, and allowing remote control of the vehicle; The fourth execution unit is used to dynamically adjust the service execution parameters of the service content according to the current state of the vehicle, wherein the current state specifically includes the user driving state, the automatic driving state and the power off state, and the service execution parameters specifically include the service duration, service period and service restriction.

[0045] In this embodiment, the system obtains the remote control data of the vehicle through the cloud platform based on the service content of the work order to be serviced, and then the system determines whether the remote control data matches the service level permissions pre-set by the cloud platform. The service level permissions specifically include information viewing only, allowing voice remote communication, and allowing remote control of the vehicle to execute the corresponding steps; for example, when the system determines that the remote control data of the vehicle cannot match the service level permissions pre-set by the cloud platform, the system will consider that the remote operation currently requested exceeds the service permission range authorized by the vehicle user, and it may be that the user has not authorized the cloud platform to control the vehicle at the corresponding level. The system will Attempt to convert the original service operation into an alternative operation that can be executed within the permission level, such as replacing "direct remote control" with "voice remote communication", and at the same time send a permission-inadequate notification to the user App or vehicle terminal through the parking terminal, indicating that the current operation cannot be executed due to insufficient permission level, provide a guidance link for upgrading permissions or modifying authorization settings, and mark the service ticket as "restricted permission" to avoid the system from repeatedly trying invalid control operations and ensure that the service process is clear, closed-loop, and traceable; for example, when the system determines that the vehicle's remote control data can match the service level permissions pre-set by the cloud platform, the system will consider that the remote operation currently requested is in The system will dynamically adjust the service execution parameters of the service content according to the current status of the vehicle, including the user driving status, automatic driving status and power-off status. The service execution parameters include service duration, service period and service restrictions. The system can effectively avoid unauthorized operations by judging whether the remote control data matches the service level authority authorized by the user, ensuring that all control behaviors are carried out within the scope of the user's explicit authorization. A successful match indicates that the user has trusted the cloud platform. The system can perform remote operations without infringing on the user's wishes, thereby improving the credibility and standardization of the service. At the same time, based on the current status of the vehicle (such as Dynamically adjusting service execution parameters (such as service duration, time period, and restrictions) during driving, autonomous driving, and power outages can effectively avoid service conflicts or failures caused by scenario mismatches. For example, automatically shortening service duration or restricting certain control instructions while the user is driving can help reduce interference with driving behavior and improve user experience. Flexible configuration of service execution details through preset service parameters can avoid resource waste caused by unified processing and provide an accurate basis for service scheduling in different scenarios. This on-demand adjustment mechanism not only improves service response efficiency, but also reduces system burden and improves overall operation and maintenance capabilities by reasonably allocating service resources (such as time period restrictions).

[0046] In this embodiment, the receiving module further includes: a response unit, configured to respond to the interaction request pre-sent by the vehicle through the parking lot terminal to the cloud platform; a fifth determining unit, configured to determine whether the cloud platform responds to the vehicle; The fifth execution unit is used to generate a corresponding interaction failure record from the cloud platform if not, mark the interaction failure record as a priority interaction event, and dynamically mobilize the customer service resources preset by the cloud platform according to the priority interaction event.

[0047] In this embodiment, the system responds to the interaction requests sent in advance by the vehicle through the parking lot terminal to the cloud platform, and then the system determines whether the cloud platform responds to the vehicle to execute the corresponding steps; for example, when the system determines that the cloud platform responds to the vehicle's interaction request, the system will consider that the network link is stable, the vehicle terminal in the parking lot has successfully uploaded the interaction request to the cloud, and has been effectively received and responded to by the cloud platform. The system will formally start the interactive session process, such as loading the corresponding service module (such as customer service interface, automatic answering, intelligent guidance, etc.), pushing response information or operation instructions to the vehicle terminal, and parsing the content of the interaction request. The type (such as asking for help, moving the car, voice call, etc.) is matched with the service strategy preset by the cloud platform, and then different service logic is executed (such as dispatching customer service, pushing common problem guidance, calling remote control instructions, etc.), and the time, request content, response, service results and other information of this interaction are recorded on the cloud platform to provide data support for subsequent tracking of problem solving or user satisfaction evaluation; for example, when the system determines that the cloud platform has not responded to the vehicle's interaction request, the system will consider that the current customer service resources are full and there are no idle resources to reply to the vehicle. The system will generate a corresponding interaction unconnected record from the cloud platform and mark the interaction unconnected record as The next priority interaction event will be based on the priority interaction event, and the customer service resources pre-set on the cloud platform will be dynamically mobilized. When the system detects that the cloud platform fails to respond to the vehicle's interaction request, it believes that the customer service resources are temporarily full, and the system will automatically generate an "interaction unconnected record" and mark it as the next priority event to ensure that vehicles that fail to respond in time will receive a higher response priority in the next round of resource scheduling. This mechanism avoids the risk of service resources being repeatedly allocated to subsequent requesting users, effectively improving the fairness of interactive services and overall scheduling efficiency. At the same time, after identifying the "unconnected record", the system will dynamically mobilize the customer service resources of the cloud platform, such as from the backup customer service By activating new customer services in the pool, reallocating some low-priority tasks, or temporarily suspending some non-critical tasks, the ability to process high-priority interaction requests can be quickly restored. This resource management method can avoid long-term resource overload or idleness, and achieve intelligent and balanced distribution of service loads. Even in extreme cases of high customer service concurrency and high system pressure, the mechanism can still ensure that every unresponded request is recorded, tracked and prioritized, significantly reducing the interaction interruption rate. The system provides a basis for subsequent data analysis by constructing "interaction disconnection records", which helps the platform continuously optimize service capabilities and dynamic capacity planning, and ultimately enhance overall service reliability and user satisfaction.

[0048] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An interactive method for managing smart terminals on a cloud platform, characterized in that: The following steps are involved: Based on the vehicle information collected by the cloud platform at the entrance and exit of the parking lot, the interaction request uploaded by the vehicle through the parking lot terminal is received. The vehicle information specifically includes entry and exit records, parking space number and charging pile number; Determining whether the interaction request receives a response from the cloud platform; If so, the terminal call function preset in the parking terminal is dynamically activated. Based on the terminal call function, a response bridge for short-term interaction with the parking terminal is constructed from the cloud platform. Preset customer service personnel are mobilized on the cloud platform to join the response bridge, and a work order to be served corresponding to the vehicle is generated. The work order to be served specifically includes billing anomalies, equipment failures, and insufficient resources. Determining whether the work order to be serviced can obtain service authorization for the vehicle; If possible, then based on the driving status divided by the customer service based on the vehicle information, the congestion information caused by the vehicle in the parking lot is obtained. Based on the congestion information, the vehicle is guided to perform mobile scheduling in the parking lot through the response bridge, and the vehicle's interaction data is generated in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

2. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: Before the step of obtaining the congestion information caused by the vehicle in the parking lot, the method further includes: Identifying location information of the vehicle in the parking lot, and based on the location information, using a preset camera to acquire image data of the vehicle within a preset range; Determining whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; If so, the vehicle's external features are collected through the image data, and the required temporary parking space for the vehicle is constructed based on the external features. Based on the required temporary parking space, the temporary parking position of the vehicle is divided in a preset temporary buffer zone from the cloud platform, wherein the external features specifically include size features, posture features, type features and structural features.

3. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: The step of mobilizing a preset customer service representative on the cloud platform to join the response bridge and generating a service order corresponding to the vehicle further includes: Based on the idle customer service resources pre-detected on the cloud platform, randomly assigning the customer service from the idle customer service resources to provide cloud interactive services to the vehicle; Determine whether the cloud interactive service can complete the interactive docking; If so, the interaction progress of the vehicle is generated. According to the interaction progress, the idle customer service resources are restricted from multi-party interaction with the vehicle. The interaction transfer request of the customer service is identified. According to the interaction transfer request, another customer service is reallocated from the idle customer service resources to provide cloud-based interaction services for the vehicle, and the historical interaction information of the vehicle is constructed on the cloud platform.

4. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: The step of determining the driving status based on the vehicle information classified by the customer service further includes: Based on the image data pre-captured by the cloud platform of the vehicle, combined with the real-time vehicle status uploaded to the cloud platform by the vehicle, identifying the vehicle's status information, wherein the status information specifically includes the location, direction angle, battery level, door and window status, brake status, gear information, whether the vehicle is charging, and whether the vehicle is locked; Determining whether the status information matches a status type preset by the cloud platform, wherein the status types specifically include movable, stationary but recallable, and forced stationary; If so, the vehicle is marked in the virtual map preset by the cloud platform, corresponding marking data is generated, and the navigation direction information in the virtual map is dynamically adjusted according to the marking data.

5. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: The step of determining whether the interaction request receives a response from the cloud platform further includes: Parsing the request content type of the interaction request based on the request source of the interaction request, wherein the request source specifically includes the user app, the vehicle system, and the customer service console, and the request content type specifically includes asking for help, moving the vehicle, reporting charging failure, and voice call; Determine whether the request content type belongs to the conventional question type preset by the cloud platform; If so, a preset question utterance is replied from the cloud platform to the parking lot terminal, the question utterance is used to guide the vehicle to process the interaction request, and the interaction completion result of the vehicle is generated in real time on the cloud platform.

6. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: The step of determining whether the work order to be serviced can obtain service authorization for the vehicle further includes: Based on the service content of the work order to be serviced, obtaining remote control data of the vehicle through the cloud platform; Determining whether the remote control data matches a service level permission preset by the cloud platform, wherein the service level permission specifically includes information viewing only, allowing voice remote communication, and allowing remote control of the vehicle; If so, the service execution parameters of the service content are dynamically adjusted according to the current state of the vehicle, wherein the current state specifically includes the user driving state, the automatic driving state and the power off state, and the service execution parameters specifically include the service duration, service period and service restrictions.

7. The interactive method for managing smart terminals using a cloud platform according to claim 1, characterized in that: The step of receiving an interaction request uploaded by a vehicle through a parking lot terminal based on the vehicle information collected at the parking lot entrance and exit by the cloud platform further includes: Based on the interaction request pre-sent by the vehicle through the parking lot terminal, responding to the interaction request to the cloud platform; Determining whether the cloud platform responds to the vehicle; If not, a corresponding interaction failure record is generated from the cloud platform, and the interaction failure record is marked as a priority interaction event. According to the priority interaction event, the customer service resources preset by the cloud platform are dynamically mobilized.

8. An interactive system for managing smart terminals on a cloud platform, characterized in that: include: A receiving module is used to receive interaction requests uploaded by vehicles through parking lot terminals based on vehicle information collected at parking lot entrances and exits by the cloud platform, wherein the vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers; A judgment module, configured to judge whether the interaction request has received a response from the cloud platform; an execution module configured to dynamically activate a terminal call function preset in the parking terminal, and, based on the terminal call function, construct a response bridge for short-term interaction with the parking terminal from the cloud platform, mobilize a preset customer service representative on the cloud platform to join the response bridge, and generate a work order to be served corresponding to the vehicle, wherein the work order to be served specifically includes billing anomalies, equipment failures, and insufficient resources; A second judgment module is used to judge whether the work order to be serviced can obtain service authorization for the vehicle; The second execution module is used to, if possible, obtain the congestion information caused by the vehicle in the parking lot according to the driving status divided by the customer service based on the vehicle information; based on the congestion information, guide the vehicle to perform mobile scheduling in the parking lot through the response bridge, and generate the vehicle's interaction data in real time on the cloud platform, wherein the driving status specifically includes normal driving and abnormal driving, the mobile scheduling specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status class, task execution class and user feedback class.

9. The interactive system for managing smart terminals via a cloud platform according to claim 8, characterized in that: Also includes: an acquisition module, configured to identify location information of the vehicle in the parking lot, and based on the location information, use a preset camera to acquire image data of the vehicle within a preset range; a third determination module, configured to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior congestion, traffic flow state congestion, and non-vehicle obstacle congestion; The third execution module is used to, if so, collect the appearance features of the vehicle through the image data, construct the required temporary parking space for the vehicle based on the appearance features, and divide the temporary parking position of the vehicle in a preset temporary buffer zone from the cloud platform based on the required temporary parking space, wherein the appearance features specifically include size features, posture features, type features and structural features.

10. The interactive system for managing smart terminals via a cloud platform according to claim 8, characterized in that: The execution module also includes: An allocating unit, configured to randomly allocate the customer service personnel from the idle customer service resources pre-detected on the cloud platform to provide cloud interactive services to the vehicle; A judgment unit, configured to judge whether the cloud interactive service can complete the interactive docking; An execution unit is configured to, if so, generate an interaction progress for the vehicle, limit the idle customer service resources to conduct multi-party interactions with the vehicle based on the interaction progress, identify the customer service's interaction transfer request, and reallocate another customer service from the idle customer service resources to provide cloud-based interaction services for the vehicle based on the interaction transfer request, and construct historical interaction information of the vehicle on the cloud platform.

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