An interaction method and system for cloud platform to manage intelligent terminal

Abstract

The application provides an interaction method and system for cloud platform to manage intelligent terminals, which is applied to the field of communication data processing; the application effectively solves the problem processing delay caused by personnel off-duty or shift change in parking lot service through centralized identification and response of vehicle interaction request by the cloud platform, can automatically judge whether the request is responded and activate the terminal call function, build a response bridge for customer service participation, realize remote instant service support, dynamically guide the vehicle for scheduling and path avoidance combined with driving state judgment and congestion information analysis, avoid congestion or service interruption in the field, and generate interaction data at the same time to guarantee the closed-loop processing of task execution and user feedback, so as to realize continuous and efficient service support during unattended or personnel off-duty period, improve the intelligent level of parking lot operation and user satisfaction.

Description

Technical Field

[0001] This 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 Technology

[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 move from the traditional shift-based operation and management to a refined management model. It has transitioned from multiple shifts to intelligent terminal monitoring, freeing up personnel to perform other tasks such as project inspections. At the same time, a 24-hour duty service desk has been built in the background, enabling unified management of multiple projects online in the cloud, which has greatly improved the company's cost reduction, efficiency improvement and management level.

[0003] In the existing parking and charging management system, when vehicles need assistance entering or leaving the parking lot or charging within the lot, staff may be absent or change shifts and unable to provide timely service. This results in problems with vehicle entry, exit, or charging not being handled promptly, leading to congestion. Summary of the Invention

[0004] This invention aims to solve the problem that when vehicles need assistance entering or leaving the parking lot or charging in the parking area, staff may be absent or change shifts and unable to provide timely service, resulting in the inability to handle vehicle entry, exit, or charging issues in a timely manner. The invention provides an interactive method and system for managing smart terminals through a cloud platform.

[0005] The present invention employs the following technical means to solve the technical problem:

[0006] This invention provides an interactive method for managing smart terminals on a cloud platform, comprising:

[0007] Based on vehicle information collected at the entrance and exit of the parking lot by the cloud platform, the system receives interactive requests uploaded by vehicles through the parking lot terminal. The vehicle information specifically includes entry and exit records, parking space number, and charging pile number.

[0008] Determine whether the interaction request receives a response from the cloud platform;

[0009] If so, the preset terminal call function of the parking lot terminal is dynamically activated. Based on the terminal call function, a response bridge for short-term interaction with the parking lot terminal is built from the cloud platform. The preset customer service is mobilized to join the response bridge on the cloud platform, and a service order corresponding to the vehicle is generated. The service order specifically includes billing anomalies, equipment failures, and insufficient resources.

[0010] Determine whether the pending service order can obtain service authorization for the vehicle.

[0011] If possible, based on the driving status classification of the vehicle information by the customer service representative, the congestion information caused by the vehicle in the parking lot is obtained. Based on the congestion information, the vehicle is guided to move and be dispatched in the parking lot through the response bridge. The vehicle's interaction data is generated in real time on the cloud platform. The driving status specifically includes normal driving and abnormal driving. The movement and dispatch specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points. The interaction data specifically includes service status, task execution, and user feedback.

[0012] Furthermore, before the step of obtaining the congestion information caused by the vehicle in the parking lot, the method further includes:

[0013] The location information of the vehicle in the parking lot is identified, and based on the location information, a preset camera is used to acquire image data of the vehicle within a preset range;

[0014] Determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion;

[0015] If so, the vehicle's shape features are collected through the image data. Based on the shape features, the required temporary parking space for the vehicle is constructed. Based on the required temporary parking space, the temporary parking position of the vehicle is divided in a preset temporary buffer from the cloud platform. The shape features specifically include size features, posture features, type features, and structural features.

[0016] Furthermore, the step of mobilizing preset customer service representatives on the cloud platform to join the response bridge and generate a service order corresponding to the vehicle also includes:

[0017] Based on the pre-detected idle customer service resources on the cloud platform, customer service representatives are randomly assigned from the idle customer service resources to provide cloud-based interactive services to the vehicle.

[0018] Determine whether the cloud-based interactive service can complete the interactive connection;

[0019] If so, the interaction progress of the vehicle is generated. Based on the interaction progress, the multi-party interaction between the idle customer service resources and the vehicle is restricted. The interaction transfer request of the customer service is identified. Based on the interaction transfer request, another customer service representative is reallocated from the idle customer service resources to provide cloud interaction services for the vehicle. The historical interaction information of the vehicle is constructed on the cloud platform.

[0020] Furthermore, the step of classifying the driving status based on the vehicle information by the customer service representative also includes:

[0021] Based on the image data of the vehicle pre-acquired by the cloud platform, and combined with the real-time vehicle status uploaded by the vehicle to the cloud platform, the status information of the vehicle is identified. The status information specifically includes position, direction angle, battery level, door and window status, brake status, gear information, whether it is charging, and whether it is locked.

[0022] Determine whether the status information matches the preset status type of the cloud platform, wherein the status type specifically includes movable, stationary but recallable, and forced stationary;

[0023] If so, the vehicle will be marked in the virtual map preset on the cloud platform to generate corresponding marking data, and the navigation direction information in the virtual map will be dynamically adjusted according to the marking data.

[0024] Furthermore, the step of determining whether the interaction request receives a response from the cloud platform also includes:

[0025] Based on the request source of the interaction request, the request content type of the interaction request is parsed. The request source specifically includes the user's App, the vehicle system, and the customer service console. The request content type specifically includes requests for help, vehicle relocation, charging failure reporting, and voice calls.

[0026] Determine whether the type of the requested content belongs to the common question types preset by the cloud platform;

[0027] If so, a preset question quote is sent from the cloud platform to the parking lot terminal, guiding the vehicle to process the interaction request through the question quote, and generating the vehicle's interaction completion result in real time on the cloud platform.

[0028] Furthermore, the step of determining whether the pending service order can obtain service authorization for the vehicle also includes:

[0029] Based on the service content of the work order to be serviced, the remote control data of the vehicle is obtained through the cloud platform;

[0030] Determine whether the remote control data matches the preset service level permissions of the cloud platform, wherein the service level permissions specifically include viewing information only, allowing remote voice communication, and allowing remote vehicle control;

[0031] If so, the service execution parameters of the service content are dynamically adjusted according to the current state of the vehicle. The current state specifically includes the user driving state, the autonomous driving state, and the power outage state. The service execution parameters specifically include the service duration, the service time period, and the service restrictions.

[0032] Furthermore, the step of receiving interactive requests uploaded by vehicles through parking lot terminals based on vehicle information collected at parking lot entrances and exits via a cloud platform also includes:

[0033] Based on the interaction request pre-sent by the vehicle through the parking lot terminal, the interaction request is responded to by the cloud platform;

[0034] Determine whether the cloud platform responds to the vehicle;

[0035] If not, a corresponding failed interaction record is generated from the cloud platform, and the failed interaction record is marked as a priority interaction event. Based on the priority interaction event, the customer service resources preset by the cloud platform are dynamically mobilized.

[0036] This invention also provides an interactive system for managing smart terminals via a cloud platform, comprising:

[0037] The receiving module is used to receive vehicle information collected at the entrance and exit of the parking lot based on the cloud platform, and to receive interactive requests uploaded by vehicles through the parking lot terminal. The vehicle information specifically includes entry and exit records, parking space number and charging pile number.

[0038] The judgment module is used to determine whether the interaction request has received a response from the cloud platform;

[0039] The execution module is used to dynamically activate the preset terminal call function of the parking lot terminal if the condition is met, construct a response bridge from the cloud platform to interact with the parking lot terminal based on the terminal call function, mobilize preset customer service personnel on the cloud platform to join the response bridge, and generate a service order corresponding to the vehicle. The service order specifically includes billing anomalies, equipment failures, and insufficient resources.

[0040] The second judgment module is used to determine whether the work order to be served can obtain service authorization for the vehicle.

[0041] The second execution module is used to, if possible, obtain congestion information caused by the vehicle in the parking lot based on the driving status classified by the customer service representative, guide the vehicle to move and be dispatched 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. The driving status specifically includes normal driving and abnormal driving, the movement and dispatching specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interaction data specifically includes service status, task execution, and user feedback.

[0042] Furthermore, it also includes:

[0043] The acquisition module is used to identify the location information of the vehicle in the parking lot, and based on the location information, to acquire image data of the vehicle within a preset range using a preset camera;

[0044] The third judgment module is used to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion.

[0045] The third execution module is used to, if so, acquire the vehicle's shape features through the image data, construct the required temporary parking space for the vehicle based on the shape features, and divide the vehicle's temporary parking position from the cloud platform in a preset temporary buffer based on the required temporary parking space. The shape features specifically include size features, posture features, type features, and structural features.

[0046] Furthermore, the execution module also includes:

[0047] The allocation unit is used to randomly allocate customer service representatives to provide cloud-based interactive services to the vehicle from the idle customer service resources pre-detected on the cloud platform.

[0048] The judgment unit is used to determine whether the cloud-based interactive service can complete the interactive connection.

[0049] An execution unit is configured to, if so, generate the interaction progress of the vehicle, restrict the idle customer service resources from engaging in multi-party interactions with the vehicle based on the interaction progress, identify the customer service representative's interaction transfer request, reallocate another customer service representative from the idle customer service resources to provide cloud interaction services for the vehicle based on the interaction transfer request, and construct the vehicle's historical interaction information on the cloud platform.

[0050] This invention provides an interactive method and system for managing smart terminals on a cloud platform, which has the following beneficial effects:

[0051] This invention effectively solves the problem of delayed problem handling caused by staff absence or shift changes in parking lot services by centrally identifying and responding to vehicle interaction requests through a cloud platform. 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 a request should be responded to and activate the terminal call function, building a response bridge with customer service participation, and realizing remote instant service support. Combined with driving status judgment and congestion information analysis, it dynamically guides vehicles to schedule and avoid routes, avoiding congestion or service interruptions in the parking lot. At the same time, it generates interactive data to ensure closed-loop processing of task execution and user feedback, thereby achieving continuous and efficient service support during periods of no staff or staff absence, improving the level of intelligent operation of parking lots and user satisfaction. Attached Figure Description

[0052] Figure 1 This is a flowchart illustrating an embodiment of the interactive method for managing smart terminals on a cloud platform according to the present invention.

[0053] Figure 2 This is a structural block diagram of an embodiment of the interactive system for managing smart terminals on the cloud platform of the present invention. Detailed Implementation

[0054] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The realization of the purpose, functional features, and advantages of the invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings.

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Reference Appendix Figure 1 The present invention provides an interactive method for managing smart terminals via a cloud platform, comprising:

[0057] S1: Based on vehicle information collected at the entrance and exit of the parking lot by the cloud platform, receive interactive requests uploaded by vehicles through the parking lot terminal, wherein the vehicle information specifically includes entry and exit records, parking space number and charging pile number;

[0058] S2: Determine whether the interaction request has received a response from the cloud platform;

[0059] S3: If so, the preset terminal call function of the parking lot terminal is dynamically activated. According to the terminal call function, a response bridge for short-term interaction with the parking lot terminal is built from the cloud platform. The preset customer service is mobilized to join the response bridge on the cloud platform to generate a service order corresponding to the vehicle. The service order specifically includes billing abnormality, equipment failure and insufficient resources.

[0060] S4: Determine whether the pending service order can obtain service authorization for the vehicle;

[0061] S5: If possible, based on the driving status classification of the vehicle information by the customer service representative, obtain the congestion information caused by the vehicle in the parking lot. Based on the congestion information, guide the vehicle to move and be dispatched in the parking lot through the response bridge. Generate the vehicle's interaction data in real time on the cloud platform. The driving status specifically includes normal driving and abnormal driving. The movement and dispatch specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points. The interaction data specifically includes service status, task execution, and user feedback.

[0062] In this embodiment, the system collects and records vehicle information at the parking lot entrance and exit via a cloud platform. This vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers. When a vehicle is in the parking lot, it receives user interaction requests to the cloud platform via parking lot terminals located at various locations within the parking lot. The system then determines whether these interaction requests receive a response from the cloud platform to execute corresponding steps. For example, if the system determines that a user's interaction request to the cloud platform cannot receive a response, it assumes that the cloud platform's customer service is currently busy and has not yet made time to interact with the user. The system automatically creates a queue record for the unresponsive request, assigns a queue number and estimated waiting time, and notifies the user of the current queue status via parking lot terminals or mobile devices. Simultaneously, based on the type of the user's request (e.g., "cannot charge"), it calls the FAQ or knowledge base module to provide intelligent semantic matching self-guided content and activates a voice or text robot to guide the user with questions, initially identifying the problem type and preparing contextual information for subsequent human intervention. For example, if the system determines that a user's interaction request to the cloud platform can receive a response, it determines that the user's interaction request to the cloud platform can receive a response. Upon receiving a response from the cloud platform, the system assumes that the customer service representatives on the cloud platform are capable of interacting normally with the user. The system then dynamically activates the pre-set terminal call function on the parking lot terminal, mobilizing pre-set customer service representatives on the cloud platform to join the response bridge and generating a service order for the corresponding vehicle. The service order specifically includes billing anomalies, equipment malfunctions, and resource shortages. By activating the pre-set terminal call function, this mechanism effectively establishes a first-time communication channel between the user and cloud customer service, avoiding service interruptions caused by traditional on-duty issues such as temporary staff absences or 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 human assistance when encountering problems such as vehicle entry and exit from the parking lot, charging malfunctions, or billing anomalies. This significantly improves service response speed and user trust. Simultaneously, after responding to the user's request, the cloud platform intelligently dispatches and matches customer service personnel to the service channel based on the customer service representative's availability and task allocation rules. This process no longer relies on manual allocation but instead utilizes the platform's resource scheduling engine to achieve automatic customer service assignment and dynamic construction of the interactive bridge.Once customer service representatives are connected to the response bridge, they can communicate efficiently with users through audio / video, visual interfaces, or pre-set Q&A templates to quickly understand and make initial judgments about the problem's background. After a customer service representative enters the interaction bridge, the system intelligently generates "service requests" based on the interaction content between the representative and the user, categorizing them into typical problem types such as "billing anomaly," "equipment malfunction," or "insufficient resources." Each service request includes key information such as user vehicle information, terminal location, interaction logs, and on-site images, facilitating subsequent automatic dispatch or manual review. The system then determines whether these service requests can obtain vehicle service authorization to execute the corresponding steps. For example, if the system determines that a service request corresponding to a vehicle is not authorized, the system will proceed accordingly. When the system obtains service authorization for a user's vehicle, it will assume that the user has not authorized partial control of the vehicle to the cloud center, or that the user believes the pending service order cannot resolve the problem. The system will then display an authorization confirmation interface through the parking lot terminal, explaining in detail the purpose, scope, and control boundaries of the authorized operation (such as temporary remote movement or regenerating parking space tasks) to eliminate user doubts through transparency. The system will also include the service personnel's operation instructions or historical success rates to enhance user trust. If the user still refuses authorization, the system should activate the "interaction failure guidance mode" and push self-troubleshooting suggestions, such as "manually drag the vehicle to the buffer zone" or "try powering off and restarting the charging station."The system also provides a "problem feedback reclassification" function, guiding users to re-select the processing direction of the current work order. For example, "billing anomaly" can be changed to "waiting for family members to handle" or "try again at an appointment time," enabling the replacement of problem labels and task buffering. If the user insists on not authorizing, the system will eventually convert the work order to "human on-site assistance," simultaneously notifying the offline inspection or security team and generating a temporary vehicle label in the system (such as "waiting for human guidance" or "static stop") to prevent the system from attempting to automatically dispatch the vehicle again. At the same time, it prompts surrounding vehicles to give way and alleviate the risk of local congestion. For example, when the system determines that the work order corresponding to a vehicle can obtain service authorization from the user's vehicle, the system will consider that the user has authorized partial control of the vehicle to the cloud center. The system will then obtain the potential congestion information in the parking lot based on the driving status classified by the cloud customer service, which includes normal driving and abnormal driving. Based on different congestion information, when the vehicle can move, it will guide the vehicle to move and be dispatched in the parking lot through the response bridge. The movement and dispatching specifically includes path planning, pointing to temporary buffer zones, and avoiding congestion points. The system will generate real-time interaction data with the vehicle on the cloud platform. According to reports, the interactive data specifically includes service status, task execution, and user feedback. By identifying the driving status of vehicles and determining whether they are mobile, the system can promptly identify potential congestion sources. Under authorized vehicle control, the system can automatically or semi-automatically guide vehicles to avoid key lanes, exit congested areas, or enter temporary buffer zones, thereby alleviating congestion and improving the overall parking lot's operational efficiency. Simultaneously, through a "response bridge" mechanism, cloud-based customer service can obtain real-time vehicle driving status and congestion level information. Combined with system-generated route planning suggestions or dispatch instructions, it provides remote assistance and guidance. This mechanism avoids delays in judgment due to a lack of scenario awareness among customer service personnel, ensuring the timeliness and accuracy of problem handling and significantly improving the professionalism of customer service assistance. Furthermore, the system unifies various data during the service process (such as dispatch status, route execution results, and user feedback) into interactive data, forming a traceable digital record. By recording service status, execution results, and user responses, the cloud platform can achieve intelligent learning, service evaluation, and problem review, further optimizing dispatch strategies and human-machine collaboration processes, providing reference and improvement for handling similar problems in the future.

[0063] It's important to note that when a vehicle successfully interacts with the cloud center but the user is unable to drive it, causing traffic congestion in the parking lot, the cloud platform first uses image recognition and positioning technology to accurately determine the location and occupied area of ​​the malfunctioning vehicle, dynamically defining an avoidance zone. Then, the platform issues avoidance instructions to nearby vehicles with network connectivity, replanning their routes and guiding them around the malfunctioning area to alleviate congestion. Simultaneously, it provides on-site avoidance prompts to non-networked vehicles through parking lot guidance screens, light signs, and voice announcements. Furthermore, the cloud platform combines overall traffic flow data to optimize the overall vehicle flow distribution, delaying or adjusting the start and entry times of some vehicles to prevent further concentrated flow into the congested area. If necessary, customer service personnel will proactively contact the relevant vehicle owners to assist in manually moving vehicles or adjusting routes. Through these comprehensive measures, the cloud platform achieves intelligent guidance and decentralized management of traffic flow within the parking lot, effectively alleviating traffic congestion caused by malfunctioning vehicles and ensuring the smooth operation of the parking lot.

[0064] In this embodiment, before step S3 of obtaining congestion information caused by the vehicle in the parking lot, the method further includes:

[0065] S301: Identify the 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;

[0066] S302: Determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion;

[0067] S303: If so, the vehicle's shape features are collected through the image data, and the required temporary parking space for the vehicle is constructed based on the shape 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. The shape features specifically include size features, posture features, type features, and structural features.

[0068] In this embodiment, after a user's vehicle connects to the smart parking app, the system identifies the vehicle's location information within the parking lot. Based on different location information, it acquires image data of the vehicle within a pre-defined range using cameras within the parking lot. The system then determines whether pre-defined congestion features are detected in these image data. These congestion features specifically include vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion, and executes corresponding steps accordingly. For example, if the system determines that no pre-defined congestion features are detected in the image data of the vehicle within the pre-defined range, the system considers the traffic flow in the area where the vehicle is located to be normal. The system will allow or guide the vehicle to continue along the original planned path, for example, by providing route guidance through the app or in-vehicle navigation. Simultaneously, the system updates the traffic flow status layer in the cloud, marking the area as "smooth" or "no abnormality," and skips congestion handling steps such as emergency diversion and detour suggestions according to the system's operating logic, improving response efficiency. Conversely, if the system determines that pre-defined congestion features are detected in the image data of the vehicle within the pre-defined range, the system considers the traffic flow in the area where the vehicle is located to be abnormal. The system will then collect the vehicle's external features through these image data. These external features specifically include... This system incorporates size, posture, type, and structural characteristics. Based on these characteristics, it constructs the required temporary parking space for each vehicle. Then, using this required space, it allocates a parking location for the vehicle from pre-defined temporary buffer zones within the parking lot via a cloud platform. Based on detected congestion features, the system determines in real-time whether a vehicle is a source of congestion and further analyzes its shape characteristics to automatically match the most suitable temporary parking space. This approach enables efficient and automated emergency dispatching without relying on manual judgment, quickly guiding abnormal vehicles to temporary buffer zones that do not obstruct the main traffic path, thereby alleviating traffic pressure within the parking lot. Meanwhile, after determining the vehicle's external characteristics (such as length, width, height, posture, and model), the system can intelligently allocate a temporary buffer space that best matches the vehicle's size and structure, ensuring that the vehicle does not occupy other lanes or obstruct the camera's view when parked. This reduces secondary safety risks such as scratches, scrapes, and blind spots caused by improper temporary parking. Furthermore, once the external characteristics and temporary parking locations are matched one-to-one, the cloud platform can generate a complete service record chain, providing key basic data for subsequent customer service access, maintenance scheduling, and anomaly review. With the help of structured information, the system can train models to continuously optimize congestion identification and scheduling strategies, thereby enhancing the system's self-learning and intelligent evolution capabilities.

[0069] In this embodiment, step S3, which involves mobilizing preset customer service representatives to join the response bridge on the cloud platform and generating a service order for the vehicle, further includes:

[0070] S31: Based on the pre-detected idle customer service resources on the cloud platform, randomly assign a customer service representative from the idle customer service resources to provide cloud-based interactive services to the vehicle;

[0071] S32: Determine whether the cloud-based interactive service can complete the interactive connection;

[0072] S33: If so, generate the interaction progress of the vehicle, restrict the idle customer service resources from interacting with the vehicle in multiple ways according to the interaction progress, identify the interaction transfer request of the customer service, reallocate another customer service from the idle customer service resources to provide cloud interaction services for the vehicle according to the interaction transfer request, and build the historical interaction information of the vehicle on the cloud platform.

[0073] In this embodiment, the system randomly assigns customer service representatives to provide cloud-based interactive services to vehicles based on pre-detected idle customer service resources on the cloud platform. The system then determines whether the cloud-based interactive service can complete the interaction and executes the corresponding steps accordingly. For example, if the system determines that the cloud-based interactive service cannot complete the interaction, it considers that the communication between the currently assigned customer service resource and the vehicle user has not been successfully established. The system will then return the assigned but unsuccessfully connected customer service resource to the idle pool to avoid resource waste. Simultaneously, it will reassign available personnel from the remaining idle customer service representatives, supporting up to N consecutive interactions. This secondary redistribution improves the success rate of connections and, in scenarios where no customer service is available or multiple connections fail, invokes AI customer service to handle routine issues first, enhancing emergency response capabilities. For example, when the system determines that the cloud-based interactive service can complete the interaction connection normally, it considers the currently allocated customer service resource to have successfully established communication with the vehicle user. The system generates the interaction progress between the vehicle and the customer service representative on the cloud platform. Based on the ongoing interaction progress, it restricts other idle customer service resources from repeatedly engaging in multi-party interactions with the vehicle. It identifies interaction transfer requests submitted by customer service representatives and, based on these requests, reallocates another customer service representative from idle resources to provide cloud-based interactive services to the vehicle user. It also builds the vehicle's historical interaction information on the cloud platform. Through a unified management mechanism for interaction progress, the system ensures that only one customer service representative is allowed at any given time. By interacting with vehicle users, the system prevents confusion, conflicting responses, and overlapping information caused by multiple customer service representatives intervening simultaneously. This ensures the logical coherence of the interaction process and the accuracy of the results. Furthermore, when existing customer service representatives need to be transferred due to handover, skill mismatch, or system scheduling, the system can identify the transfer request and reassign a qualified representative from available slots. This effectively avoids user experience disruptions caused by human error or service interruptions, maintaining seamless and continuous cloud-based interaction. Each cloud interaction is recorded as historical interaction information for the vehicle, including service request type, processing records, customer service instructions, and user feedback. This data supports subsequent personalized service recommendations, rapid problem identification, and follow-up on recurring issues. It also helps the platform conduct interaction quality assessments and customer service performance analysis.

[0074] In this embodiment, step S5, which involves classifying the driving state based on the vehicle information by the customer service representative, further includes:

[0075] S51: Based on the image data of the vehicle pre-acquired by the cloud platform, and combined with the real-time vehicle status uploaded by the vehicle to the cloud platform, identify the status information of the vehicle, wherein the status information specifically includes position, direction angle, battery level, door and window status, brake status, gear information, whether it is charging and whether it is locked.

[0076] S52: Determine whether the status information matches the preset status type of the cloud platform, wherein the status type specifically includes movable, stationary but recallable, and forced stationary;

[0077] S53: If so, the vehicle is marked in the virtual map preset on the cloud platform to generate corresponding marking data, and the navigation direction information in the virtual map is dynamically adjusted according to the marking data.

[0078] In this embodiment, the system identifies vehicle status information based on pre-acquired image data of the vehicle on the cloud platform, combined with real-time vehicle status uploaded to the cloud platform. This status information specifically includes position, steering angle, battery level, door and window status, brake status, gear position, whether charging is in progress, and whether the vehicle is locked. The system then determines whether this status information matches a pre-defined status type on the cloud platform. These status types include movable, stationary but retrievable, and forced stationary, and executes corresponding steps accordingly. For example, if the system determines that the vehicle's status information does not match a pre-defined status type on the cloud platform, the system will consider the vehicle's uploaded data as invalid. If the vehicle's status information is missing, conflicting, or abnormal (such as inconsistency between steering angle and gear position), the system will mark the vehicle's status as "unknown" or "awaiting manual review," and simultaneously send an error message to both the user and customer service terminals to prevent misoperation and scheduling errors. At the same time, the system will instruct the vehicle to re-upload a set of status data and jointly call upon surrounding cameras in the parking lot to re-collect images. This double comparison reduces the impact of occasional errors or data delays. A manual review mode is also enabled, allowing customer service representatives to manually assign a temporary status to the vehicle based on its actual condition and the scenario's traffic logic, triggering a corresponding scheduling plan to ensure uninterrupted service even in abnormal situations. For example, if the system determines that the vehicle's status information matches a preset status type on the cloud platform, it considers the uploaded status information normal. The system will then mark the vehicle on a pre-defined virtual map of the parking lot on the cloud platform, generating corresponding marker data. Based on different marker data, the system will dynamically adjust the navigation direction information in the virtual map. By promptly marking vehicles with normal status on the cloud platform's virtual map, the system can dynamically generate navigation directions based on the real location and status, ensuring a high degree of consistency between the navigation path and the vehicle's current actual accessibility. This effectively improves navigation for drivers searching for their vehicles, leaving the parking lot, and charging their vehicles. Efficiency is enhanced, and the labeled data reflects the real-time behavior of vehicles (such as whether they are charging or movable). Based on this, the system dynamically adjusts the navigation direction information in the map to avoid guiding other vehicles into congested, obstructed, or resource-occupied areas. This allows for better completion of intelligent scheduling tasks such as path avoidance, parking space recommendation, and buffer zone allocation. Furthermore, the continuously updated vehicle labeled data ensures that the virtual map remains highly synchronized with the on-site environment, avoiding navigation errors caused by vehicle changes, location drift, or changes in parking status. This enhances the overall perception synchronization and service stability of the system, making it particularly suitable for intelligent parking environments with high traffic and frequent entry and exit.

[0079] In this embodiment, step S2, which determines whether the interaction request receives a response from the cloud platform, further includes:

[0080] S21: Based on the request source of the interaction request, parse the request content type 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 help request, vehicle relocation request, charging failure report and voice call.

[0081] S22: Determine whether the type of the requested content belongs to the common question type preset by the cloud platform;

[0082] S23: If so, then the preset question quote is replied from the cloud platform to the parking lot terminal, and the vehicle is guided to process the interaction request through the question quote, and the interaction completion result of the vehicle is generated in real time on the cloud platform.

[0083] In this embodiment, the system analyzes the request content type of the interaction request based on its source, which specifically includes the user's app, the vehicle system, and the customer service console. Specific request content types include requests for assistance, vehicle relocation, charging failure reporting, and voice calls. The system then determines whether these request content types belong to the pre-defined routine question types on the cloud platform and executes the corresponding steps accordingly. For example, if the system determines that the request content type does not belong to the pre-defined routine question types on the cloud platform, the system considers the request initiated by the user or vehicle to be unconventional, sudden, or complex, potentially involving newly emerging problems, unclassified scenarios, or special matters requiring manual intervention. The system will automatically... This unconventional request is marked as a "non-standard request," skipping the regular automated process and prioritizing a human customer service representative with high processing authority for a one-on-one response. This ensures the user's problem is quickly identified and resolved, preventing user wait times or service failures due to the automated system's inability to recognize the issue. Simultaneously, the request's source, content, contextual interaction data, and processing path are fully recorded and uploaded to the cloud-based data analysis module for subsequent model training and rule base updates. This enhances the system's ability to identify unconventional scenarios. Furthermore, if the current customer service representative cannot handle the request immediately, the system can send an automated receipt to the user via voice, text, or images, indicating that the request is being processed and guiding the user to provide supplementary information (such as images, voice descriptions, license plates, etc.) so that customer service can respond as quickly as possible. To address specific issues and improve processing efficiency, for example, when the system determines that the content of an interaction request belongs to a pre-defined routine question type on the cloud platform, the system will consider that the current interaction request does not require customer service resources to assist the user's vehicle in resolving the problem. The system will then reply with pre-set question prompts from the cloud platform to the parking lot terminal, allowing the user to resolve the problem through the parking lot terminal. These question prompts guide the vehicle in processing the interaction request, and the interaction completion result is generated in real time on the cloud platform. When the interaction request belongs to a routine question type, the system will automatically triage the processing, avoiding the consumption of human customer service resources for questions that could be answered automatically. This mechanism can effectively improve the scheduling efficiency of customer service resources, prioritizing complex or sudden issues. The system enhances its human response capabilities for issues, thereby improving its overall service capacity and response speed. Simultaneously, by pushing structured problem quotes to parking lot terminals, users are guided to handle issues independently. This approach not only shortens the time required for problem resolution but also increases user initiative and efficiency in the terminal environment, enhancing user trust and satisfaction with the system's intelligence. Furthermore, after automatically handling routine issues, the system generates "interaction completion results" in real time and synchronizes them to the cloud. This process constructs a complete record of the interaction data, which not only aids in subsequent service quality analysis and problem tracing but also provides data support for the system to evaluate the effectiveness and coverage of problem quotes, promoting continuous optimization of the platform's routine problem handling mechanism.

[0084] In this embodiment, step S4, which determines whether the pending service order can obtain service authorization for the vehicle, further includes:

[0085] S41: Based on the service content of the work order to be served, obtain the remote control data of the vehicle through the cloud platform;

[0086] S42: Determine whether the remote control data matches the service level permissions preset by the cloud platform, wherein the service level permissions specifically include viewing information only, allowing remote voice communication, and allowing remote vehicle control;

[0087] S43: If so, then 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 autonomous driving state, and the power failure state, and the service execution parameters specifically include the service duration, the service time period, and the service restrictions.

[0088] In this embodiment, the system obtains remote control data of the vehicle through the cloud platform based on the service content of the work order to be serviced. The system then determines whether this remote control data matches the service level permissions pre-set by the cloud platform. These service level permissions specifically include information viewing only, allowing remote voice communication, and allowing remote vehicle control, in order to execute the corresponding steps. For example, if the system determines that the vehicle's remote control data does not match the pre-set service level permissions by the cloud platform, the system will consider that the currently requested remote operation exceeds the scope of the service permissions authorized by the vehicle user. This may be because the user has not authorized the cloud platform to control the vehicle at the corresponding level. The system will then proceed according to the current permissions... To address the limited access level, the system attempts to convert the original service operation into an alternative that is executable within the specified permissions. For example, it could replace "direct remote control" with "voice remote communication." Simultaneously, it sends an insufficient permissions notification to the user's app or vehicle terminal via the parking lot terminal, explaining that the current operation cannot be executed due to insufficient permissions. It provides a link to upgrade permissions or modify authorization settings and marks the service ticket as "restricted permissions" to prevent the system from repeatedly attempting invalid control operations, ensuring a clear, closed-loop, and traceable service process. For instance, when the system determines that the vehicle's remote control data matches the service level permissions pre-set on the cloud platform, the system considers the currently requested remote operation to be within the permitted permissions range. The system dynamically adjusts service execution parameters based on the vehicle's current status, including whether the user is driving, in autonomous driving mode, or experiencing a power outage. These parameters include service duration, service time period, and service restrictions. By determining whether remote control data matches the user's authorized service level, the system effectively prevents unauthorized operations, ensuring all control actions are performed within the user's explicit authorization. A successful match indicates the user trusts the cloud platform, allowing the system to perform remote operations without infringing on the user's wishes, thus enhancing service credibility and standardization. This is further enhanced by considering the vehicle's current status (e.g., driving mode, autonomous driving mode, and power outage). 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 the service duration or restricting certain control commands when the user is driving helps reduce interference with driving behavior, improves user experience, and flexibly configuring service execution details through preset service parameters can avoid resource waste caused by uniform processing. It also provides 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).

[0089] In this embodiment, step S1, which involves receiving an interaction request uploaded by a vehicle through a parking lot terminal based on vehicle information collected by the cloud platform at the parking lot entrance and exit, further includes:

[0090] 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;

[0091] S12: Determine whether the cloud platform responds to the vehicle;

[0092] S13: If not, generate a corresponding failed interaction record from the cloud platform, mark the failed interaction record as a priority interaction event, and dynamically mobilize the customer service resources preset by the cloud platform according to the priority interaction event.

[0093] In this embodiment, the system responds to the interaction requests pre-sent by the vehicle through the parking lot terminal by sending these interaction requests to the cloud platform. The system then determines whether the cloud platform has responded to the vehicle and executes the corresponding steps accordingly. For example, when the system determines that the cloud platform has responded to the vehicle's interaction request, it considers the network link stable, the vehicle's terminal in the parking lot has successfully uploaded the interaction request to the cloud, and it has been effectively received and responded to by the cloud platform. The system then formally initiates the interaction session process, such as loading the corresponding service modules (e.g., customer service interface, automatic response, intelligent guidance), pushing response information or operation instructions to the vehicle terminal, and simultaneously parsing the content of the interaction request. The system matches the type of request (e.g., assistance request, vehicle relocation request, voice call) with the service strategy preset by the cloud platform, and then executes different service logics (e.g., dispatching customer service, pushing frequently asked questions, retrieving remote control commands, etc.). The system also records the time, request content, response status, and service result of this interaction on the cloud platform, providing data support for subsequent tracking of problem resolution or user satisfaction evaluation. For example, if the system determines that the cloud platform has not responded to the vehicle's interaction request, it assumes that current customer service resources are full and there are no available resources to respond to the vehicle. The system will then generate a corresponding missed interaction record from the cloud platform and mark this missed interaction record as... The next priority interaction event will be dynamically allocated based on the pre-set customer service resources on the cloud platform. When the system detects that the cloud platform fails to respond to a vehicle's interaction request, it considers the customer service resources temporarily full and automatically generates an "interaction not connected record," marking it as the next priority event. This ensures that vehicles that do not respond in time 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 interaction services and overall scheduling efficiency. Simultaneously, after identifying the "not connected record," the system will dynamically allocate customer service resources from the cloud platform, such as from backup customer service. By activating new customer service representatives in the pool, reallocating some low-priority tasks, or temporarily suspending some non-critical tasks, the system can quickly restore its ability to process high-priority interaction requests. This resource management approach avoids long-term resource overload or idleness, achieving intelligent and balanced distribution of service load. Even under extreme conditions of high customer service concurrency and high system pressure, this mechanism ensures that every unresponsive request is recorded, tracked, and prioritized, significantly reducing the interaction interruption rate. By constructing an "interaction unconnection record," the system provides a basis for subsequent data analysis, helping the platform to continuously optimize service capabilities and dynamic capacity planning, ultimately enhancing overall service reliability and user satisfaction.

[0094] Reference Appendix Figure 2 An interactive system for managing smart terminals via a cloud platform, as described in one embodiment of the present invention, includes:

[0095] The receiving module 10 is used to receive vehicle information collected at the entrance and exit of the parking lot based on the cloud platform, and to receive interactive requests uploaded by vehicles through the parking lot terminal. The vehicle information specifically includes entry and exit records, parking space number and charging pile number.

[0096] The judgment module 20 is used to determine whether the interaction request has received a response from the cloud platform;

[0097] The execution module 30 is used to dynamically activate the preset terminal call function of the parking lot terminal if the condition is met, construct a response bridge from the cloud platform to interact with the parking lot terminal based on the terminal call function, mobilize preset customer service personnel on the cloud platform to join the response bridge, and generate a service order corresponding to the vehicle. The service order specifically includes billing anomalies, equipment failures, and insufficient resources.

[0098] The second judgment module 40 is used to determine whether the work order to be served can obtain service authorization from the vehicle.

[0099] The second execution module 50 is used to, if possible, obtain congestion information caused by the vehicle in the parking lot based on the driving status classified by the customer service representative, guide the vehicle to move and be dispatched in the parking lot through the response bridge based on the congestion information, and generate interactive data of the vehicle in real time on the cloud platform. The driving status specifically includes normal driving and abnormal driving, the movement and dispatching specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points, and the interactive data specifically includes service status, task execution and user feedback.

[0100] In this embodiment, the receiving module 10 receives vehicle information collected and entered at the parking lot entrance and exit by the cloud platform. This vehicle information specifically includes entry and exit records, parking space numbers, and charging pile numbers. When a vehicle is in the parking lot, it uploads the user's interaction requests to the cloud platform through parking lot terminals located at various locations within the parking lot. The judging module 20 then determines whether these interaction requests receive a response from the cloud platform and executes the corresponding steps accordingly. For example, when the system determines that the user's interaction request to the cloud platform cannot receive a response, the system assumes that the cloud platform's customer service is currently busy and has not yet made time to interact with the user. The system automatically creates a queue record for the unresponsive request, assigns a queue number and estimated waiting time, and notifies the user of the current queue status through the parking lot terminal or mobile device. Simultaneously, based on the type of the user's request (e.g., "cannot charge"), the system calls the FAQ or knowledge base module to provide intelligent semantic matching self-guided content and initiates a voice or text robot to guide the user with questions, initially identifying the problem type and preparing contextual information for subsequent human intervention. For example, when the system determines that the user's interaction request to the cloud platform... Upon receiving a response from the cloud platform, the execution module 30 assumes that the customer service on the cloud platform can interact normally with the user. The system dynamically activates the pre-set terminal call function of the parking lot terminal, mobilizes the pre-set customer service personnel on the cloud platform to join the response bridge, and generates a service order for the vehicle. The service order specifically includes billing anomalies, equipment failures, and insufficient resources. By activating the preset terminal call function, the system effectively opens up a first-time contact channel between the user and the cloud customer service, avoiding service interruptions caused by traditional on-duty issues such as temporary staff absences or 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 human assistance when encountering problems such as vehicle entry and exit from the parking lot, charging failures, and billing anomalies. This significantly improves the service response speed and user trust. At the same time, after responding to the user's request, the cloud platform intelligently dispatches and matches customer service personnel to access the service channel based on the customer service personnel's idle status and task allocation rules. This process no longer relies on manual allocation but uses the platform's resource scheduling engine to achieve automatic customer service assignment and dynamic construction of the interactive bridge.After customer service representatives are transferred to the response bridge, they can communicate efficiently with users through audio / video, visual interfaces, or preset Q&A templates to quickly understand and make initial judgments about the problem background. Once a customer service representative enters the interaction bridge, the system intelligently generates "service pending orders" based on the interaction content between the representative and the user, categorizing them into typical problem types such as "billing anomaly," "equipment failure," or "insufficient resources." Each service order includes key information such as user vehicle information, terminal location, interaction logs, and on-site images, facilitating subsequent automatic assignment or manual review. The second judgment module 40 then determines whether these service pending orders can obtain vehicle service authorization to execute the corresponding steps. For example, when the system determines that a vehicle has a service pending order... If a service order cannot obtain service authorization for the user's vehicle, the system will assume that the user has not authorized partial control of the vehicle to the cloud center, or that the user believes the service order cannot solve the problem they face. The system will then display an authorization confirmation interface through the parking lot terminal, explaining in detail the purpose, scope, and control boundaries of the authorized operation (such as temporary remote movement, regenerating parking space tasks, etc.) to eliminate user doubts through transparency. The system will also include the service personnel's operation instructions or historical success rates to enhance user trust. If the user still refuses authorization, the system should activate the "interaction failure guidance mode" and push self-troubleshooting suggestions, such as "manually drag the vehicle to the buffer zone" or "try powering off and restarting the charging station".It also provides a "problem feedback reclassification" function, guiding users to reselect the processing direction of the current work order. For example, changing "billing anomaly" to "waiting for family to handle" or "schedule a time to try again" allows for changing the problem label and buffering the task. If the user insists on not authorizing, the system will eventually convert the work order to "human on-site assistance," simultaneously notifying the offline inspection or security team and generating 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. At the same time, it prompts surrounding vehicles to give way and alleviates the risk of local congestion. For example, when the system determines... Once the service order corresponding to the vehicle is received, the user's vehicle service authorization is obtained. At this point, the second execution module 50 assumes that the user has authorized partial control of the vehicle to the cloud center. The system will then determine the vehicle's driving status based on the cloud customer service's classification of the vehicle information. The driving status specifically includes normal driving and abnormal driving. It will also obtain information on potential congestion within the parking lot caused by the vehicle. Based on this congestion information, when the vehicle is movable, it will guide the vehicle's movement within the parking lot via a response bridge. This movement scheduling includes path planning, pointing to temporary buffer zones, and avoiding congestion points. The system will generate real-time updates for the vehicle on the cloud platform. Interactive data includes service status, task execution, and user feedback. By identifying vehicle driving status and determining whether it is mobile, the system can promptly detect potential congestion sources. Under authorized vehicle control, the system can automatically or semi-automatically guide vehicles to avoid key lanes, exit congested areas, or enter temporary buffer zones, thereby alleviating congestion and improving the overall parking lot's operational efficiency. Simultaneously, through a "response bridge" mechanism, cloud-based customer service can obtain real-time vehicle driving status and congestion level information. Combined with system-generated route planning suggestions or dispatch instructions, remote assistance and guidance are provided. This mechanism avoids delays in judgment due to a lack of scenario awareness among customer service personnel, ensuring the timeliness and accuracy of problem handling and significantly improving the professionalism of customer service assistance. Furthermore, the system unifies various data during the service process (such as dispatch status, route execution results, and user feedback) into interactive data, forming a traceable digital record. By recording service status, execution results, and user responses, the cloud platform can achieve intelligent learning, service evaluation, and problem review, further optimizing dispatch strategies and human-machine collaboration processes, providing reference and improvement for handling similar problems in the future.

[0101] In this embodiment, it also includes:

[0102] The acquisition module is used to identify the location information of the vehicle in the parking lot, and based on the location information, to acquire image data of the vehicle within a preset range using a preset camera;

[0103] The third judgment module is used to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion.

[0104] The third execution module is used to, if so, acquire the vehicle's shape features through the image data, construct the required temporary parking space for the vehicle based on the shape features, and divide the vehicle's temporary parking position from the cloud platform in a preset temporary buffer based on the required temporary parking space. The shape features specifically include size features, posture features, type features, and structural features.

[0105] In this embodiment, after a user's vehicle connects to the smart parking app, the system identifies the vehicle's location information within the parking lot. Based on different location information, it acquires image data of the vehicle within a pre-defined range using cameras within the parking lot. The system then determines whether pre-defined congestion features are detected in these image data. These congestion features specifically include vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion, and executes corresponding steps accordingly. For example, if the system determines that no pre-defined congestion features are detected in the image data of the vehicle within the pre-defined range, the system considers the traffic flow in the area where the vehicle is located to be normal. The system will allow or guide the vehicle to continue along the original planned path, for example, by providing route guidance through the app or in-vehicle navigation. Simultaneously, the system updates the traffic flow status layer in the cloud, marking the area as "smooth" or "no abnormality," and skips congestion handling steps such as emergency diversion and detour suggestions according to the system's operating logic, improving response efficiency. Conversely, if the system determines that pre-defined congestion features are detected in the image data of the vehicle within the pre-defined range, the system considers the traffic flow in the area where the vehicle is located to be abnormal. The system will then collect the vehicle's external features through these image data. These external features specifically include... This system incorporates size, posture, type, and structural characteristics. Based on these characteristics, it constructs the required temporary parking space for each vehicle. Then, using this required space, it allocates a parking location for the vehicle from pre-defined temporary buffer zones within the parking lot via a cloud platform. Based on detected congestion features, the system determines in real-time whether a vehicle is a source of congestion and further analyzes its shape characteristics to automatically match the most suitable temporary parking space. This approach enables efficient and automated emergency dispatching without relying on manual judgment, quickly guiding abnormal vehicles to temporary buffer zones that do not obstruct the main traffic path, thereby alleviating traffic pressure within the parking lot. Meanwhile, after determining the vehicle's external characteristics (such as length, width, height, posture, and model), the system can intelligently allocate a temporary buffer space that best matches the vehicle's size and structure, ensuring that the vehicle does not occupy other lanes or obstruct the camera's view when parked. This reduces secondary safety risks such as scratches, scrapes, and blind spots caused by improper temporary parking. Furthermore, once the external characteristics and temporary parking locations are matched one-to-one, the cloud platform can generate a complete service record chain, providing key basic data for subsequent customer service access, maintenance scheduling, and anomaly review. With the help of structured information, the system can train models to continuously optimize congestion identification and scheduling strategies, thereby enhancing the system's self-learning and intelligent evolution capabilities.

[0106] In this embodiment, the execution module further includes:

[0107] The allocation unit is used to randomly allocate customer service representatives to provide cloud-based interactive services to the vehicle from the idle customer service resources pre-detected on the cloud platform.

[0108] The judgment unit is used to determine whether the cloud-based interactive service can complete the interactive connection.

[0109] An execution unit is configured to, if so, generate the interaction progress of the vehicle, restrict the idle customer service resources from engaging in multi-party interactions with the vehicle based on the interaction progress, identify the customer service representative's interaction transfer request, reallocate another customer service representative from the idle customer service resources to provide cloud interaction services for the vehicle based on the interaction transfer request, and construct the vehicle's historical interaction information on the cloud platform.

[0110] In this embodiment, the system randomly assigns customer service representatives to provide cloud-based interactive services to vehicles based on pre-detected idle customer service resources on the cloud platform. The system then determines whether the cloud-based interactive service can complete the interaction and executes the corresponding steps accordingly. For example, if the system determines that the cloud-based interactive service cannot complete the interaction, it considers that the communication between the currently assigned customer service resource and the vehicle user has not been successfully established. The system will then return the assigned but unsuccessfully connected customer service resource to the idle pool to avoid resource waste. Simultaneously, it will reassign available personnel from the remaining idle customer service representatives, supporting up to N consecutive interactions. This secondary redistribution improves the success rate of connections and, in scenarios where no customer service is available or multiple connections fail, invokes AI customer service to handle routine issues first, enhancing emergency response capabilities. For example, when the system determines that the cloud-based interactive service can complete the interaction connection normally, it considers the currently allocated customer service resource to have successfully established communication with the vehicle user. The system generates the interaction progress between the vehicle and the customer service representative on the cloud platform. Based on the ongoing interaction progress, it restricts other idle customer service resources from repeatedly engaging in multi-party interactions with the vehicle. It identifies interaction transfer requests submitted by customer service representatives and, based on these requests, reallocates another customer service representative from idle resources to provide cloud-based interactive services to the vehicle user. It also builds the vehicle's historical interaction information on the cloud platform. Through a unified management mechanism for interaction progress, the system ensures that only one customer service representative is allowed at any given time. By interacting with vehicle users, the system prevents confusion, conflicting responses, and overlapping information caused by multiple customer service representatives intervening simultaneously. This ensures the logical coherence of the interaction process and the accuracy of the results. Furthermore, when existing customer service representatives need to be transferred due to handover, skill mismatch, or system scheduling, the system can identify the transfer request and reassign a qualified representative from available slots. This effectively avoids user experience disruptions caused by human error or service interruptions, maintaining seamless and continuous cloud-based interaction. Each cloud interaction is recorded as historical interaction information for the vehicle, including service request type, processing records, customer service instructions, and user feedback. This data supports subsequent personalized service recommendations, rapid problem identification, and follow-up on recurring issues. It also helps the platform conduct interaction quality assessments and customer service performance analysis.

[0111] In this embodiment, the second execution module further includes:

[0112] The identification unit is used to identify the vehicle's status information based on the image data pre-acquired by the cloud platform and the real-time vehicle status uploaded to the cloud platform. The status information specifically includes position, direction angle, battery level, door and window status, brake status, gear information, whether it is charging, and whether it is locked.

[0113] The second judgment unit is used to determine whether the status information matches the preset status type of the cloud platform, wherein the status type specifically includes movable, stationary but recallable, and forced stationary.

[0114] The second execution unit is used to mark the vehicle in a preset virtual map on the cloud platform if the condition is met, generate corresponding marking data, and dynamically adjust the navigation direction information in the virtual map according to the marking data.

[0115] In this embodiment, the system identifies vehicle status information based on pre-acquired image data of the vehicle on the cloud platform, combined with real-time vehicle status uploaded to the cloud platform. This status information specifically includes position, steering angle, battery level, door and window status, brake status, gear position, whether charging is in progress, and whether the vehicle is locked. The system then determines whether this status information matches a pre-defined status type on the cloud platform. These status types include movable, stationary but retrievable, and forced stationary, and executes corresponding steps accordingly. For example, if the system determines that the vehicle's status information does not match a pre-defined status type on the cloud platform, the system will consider the vehicle's uploaded data as invalid. If the vehicle's status information is missing, conflicting, or abnormal (such as inconsistency between steering angle and gear position), the system will mark the vehicle's status as "unknown" or "awaiting manual review," and simultaneously send an error message to both the user and customer service terminals to prevent misoperation and scheduling errors. At the same time, the system will instruct the vehicle to re-upload a set of status data and jointly call upon surrounding cameras in the parking lot to re-collect images. This double comparison reduces the impact of occasional errors or data delays. A manual review mode is also enabled, allowing customer service representatives to manually assign a temporary status to the vehicle based on its actual condition and the scenario's traffic logic, triggering a corresponding scheduling plan to ensure uninterrupted service even in abnormal situations. For example, if the system determines that the vehicle's status information matches a preset status type on the cloud platform, it considers the uploaded status information normal. The system will then mark the vehicle on a pre-defined virtual map of the parking lot on the cloud platform, generating corresponding marker data. Based on different marker data, the system will dynamically adjust the navigation direction information in the virtual map. By promptly marking vehicles with normal status on the cloud platform's virtual map, the system can dynamically generate navigation directions based on the real location and status, ensuring a high degree of consistency between the navigation path and the vehicle's current actual accessibility. This effectively improves navigation for drivers searching for their vehicles, leaving the parking lot, and charging their vehicles. Efficiency is enhanced, and the labeled data reflects the real-time behavior of vehicles (such as whether they are charging or movable). Based on this, the system dynamically adjusts the navigation direction information in the map to avoid guiding other vehicles into congested, obstructed, or resource-occupied areas. This allows for better completion of intelligent scheduling tasks such as path avoidance, parking space recommendation, and buffer zone allocation. Furthermore, the continuously updated vehicle labeled data ensures that the virtual map remains highly synchronized with the on-site environment, avoiding navigation errors caused by vehicle changes, location drift, or changes in parking status. This enhances the overall perception synchronization and service stability of the system, making it particularly suitable for intelligent parking environments with high traffic and frequent entry and exit.

[0116] In this embodiment, the determination module further includes:

[0117] The parsing unit is used to parse 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 requests for help, vehicle relocation, charging failure reporting and voice call;

[0118] The third judgment unit is used to determine whether the type of the requested content belongs to the conventional question type preset by the cloud platform;

[0119] The third execution unit is used to reply with a preset question quote from the cloud platform to the parking lot terminal if the condition is met, guide the vehicle to process the interaction request through the question quote, and generate the interaction completion result of the vehicle in real time on the cloud platform.

[0120] In this embodiment, the system analyzes the request content type of the interaction request based on its source, which specifically includes the user's app, the vehicle system, and the customer service console. Specific request content types include requests for assistance, vehicle relocation, charging failure reporting, and voice calls. The system then determines whether these request content types belong to the pre-defined routine question types on the cloud platform and executes the corresponding steps accordingly. For example, if the system determines that the request content type does not belong to the pre-defined routine question types on the cloud platform, the system considers the request initiated by the user or vehicle to be unconventional, sudden, or complex, potentially involving newly emerging problems, unclassified scenarios, or special matters requiring manual intervention. The system will automatically... This unconventional request is marked as a "non-standard request," skipping the regular automated process and prioritizing a human customer service representative with high processing authority for a one-on-one response. This ensures the user's problem is quickly identified and resolved, preventing user wait times or service failures due to the automated system's inability to recognize the issue. Simultaneously, the request's source, content, contextual interaction data, and processing path are fully recorded and uploaded to the cloud-based data analysis module for subsequent model training and rule base updates. This enhances the system's ability to identify unconventional scenarios. Furthermore, if the current customer service representative cannot handle the request immediately, the system can send an automated receipt to the user via voice, text, or images, indicating that the request is being processed and guiding the user to provide supplementary information (such as images, voice descriptions, license plates, etc.) so that customer service can respond as quickly as possible. To address specific issues and improve processing efficiency, for example, when the system determines that the content of an interaction request belongs to a pre-defined routine question type on the cloud platform, the system will consider that the current interaction request does not require customer service resources to assist the user's vehicle in resolving the problem. The system will then reply with pre-set question prompts from the cloud platform to the parking lot terminal, allowing the user to resolve the problem through the parking lot terminal. These question prompts guide the vehicle in processing the interaction request, and the interaction completion result is generated in real time on the cloud platform. When the interaction request belongs to a routine question type, the system will automatically triage the processing, avoiding the consumption of human customer service resources for questions that could be answered automatically. This mechanism can effectively improve the scheduling efficiency of customer service resources, prioritizing complex or sudden issues. The system enhances its human response capabilities for issues, thereby improving its overall service capacity and response speed. Simultaneously, by pushing structured problem quotes to parking lot terminals, users are guided to handle issues independently. This approach not only shortens the time required for problem resolution but also increases user initiative and efficiency in the terminal environment, enhancing user trust and satisfaction with the system's intelligence. Furthermore, after automatically handling routine issues, the system generates "interaction completion results" in real time and synchronizes them to the cloud. This process constructs a complete record of the interaction data, which not only aids in subsequent service quality analysis and problem tracing but also provides data support for the system to evaluate the effectiveness and coverage of problem quotes, promoting continuous optimization of the platform's routine problem handling mechanism.

[0121] In this embodiment, the second determination module further includes:

[0122] The acquisition unit is used to acquire remote control data of the vehicle through the cloud platform based on the service content of the work order to be served.

[0123] The fourth judgment unit is used to determine whether the remote control data matches the service level permissions preset by the cloud platform, wherein the service level permissions specifically include viewing information only, allowing remote voice communication, and allowing remote vehicle control;

[0124] 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 if the current state is true. The current state specifically includes the user driving state, the autonomous driving state, and the power failure state. The service execution parameters specifically include the service duration, the service time period, and the service restrictions.

[0125] In this embodiment, the system obtains remote control data of the vehicle through the cloud platform based on the service content of the work order to be serviced. The system then determines whether this remote control data matches the service level permissions pre-set by the cloud platform. These service level permissions specifically include information viewing only, allowing remote voice communication, and allowing remote vehicle control, in order to execute the corresponding steps. For example, if the system determines that the vehicle's remote control data does not match the pre-set service level permissions by the cloud platform, the system will consider that the currently requested remote operation exceeds the scope of the service permissions authorized by the vehicle user. This may be because the user has not authorized the cloud platform to control the vehicle at the corresponding level. The system will then proceed according to the current permissions... To address the limited access level, the system attempts to convert the original service operation into an alternative that is executable within the specified permissions. For example, it could replace "direct remote control" with "voice remote communication." Simultaneously, it sends an insufficient permissions notification to the user's app or vehicle terminal via the parking lot terminal, explaining that the current operation cannot be executed due to insufficient permissions. It provides a link to upgrade permissions or modify authorization settings and marks the service ticket as "restricted permissions" to prevent the system from repeatedly attempting invalid control operations, ensuring a clear, closed-loop, and traceable service process. For instance, when the system determines that the vehicle's remote control data matches the service level permissions pre-set on the cloud platform, the system considers the currently requested remote operation to be within the permitted permissions range. The system dynamically adjusts service execution parameters based on the vehicle's current status, including whether the user is driving, in autonomous driving mode, or experiencing a power outage. These parameters include service duration, service time period, and service restrictions. By determining whether remote control data matches the user's authorized service level, the system effectively prevents unauthorized operations, ensuring all control actions are performed within the user's explicit authorization. A successful match indicates the user trusts the cloud platform, allowing the system to perform remote operations without infringing on the user's wishes, thus enhancing service credibility and standardization. This is further enhanced by considering the vehicle's current status (e.g., driving mode, autonomous driving mode, and power outage). 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 the service duration or restricting certain control commands when the user is driving helps reduce interference with driving behavior, improves user experience, and flexibly configuring service execution details through preset service parameters can avoid resource waste caused by uniform processing. It also provides 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).

[0126] In this embodiment, the receiving module further includes:

[0127] The response unit is used to respond to the interaction request to the cloud platform based on the interaction request pre-sent by the vehicle through the parking lot terminal;

[0128] The fifth judgment unit is used to determine whether the cloud platform responds to the vehicle;

[0129] The fifth execution unit is used to generate a corresponding failed interaction record from the cloud platform if no, mark the failed interaction record as a priority interaction event, and dynamically mobilize the customer service resources preset by the cloud platform according to the priority interaction event.

[0130] In this embodiment, the system responds to the interaction requests pre-sent by the vehicle through the parking lot terminal by sending these interaction requests to the cloud platform. The system then determines whether the cloud platform has responded to the vehicle and executes the corresponding steps accordingly. For example, when the system determines that the cloud platform has responded to the vehicle's interaction request, it considers the network link stable, the vehicle's terminal in the parking lot has successfully uploaded the interaction request to the cloud, and it has been effectively received and responded to by the cloud platform. The system then formally initiates the interaction session process, such as loading the corresponding service modules (e.g., customer service interface, automatic response, intelligent guidance), pushing response information or operation instructions to the vehicle terminal, and simultaneously parsing the content of the interaction request. The system matches the type of request (e.g., assistance request, vehicle relocation request, voice call) with the service strategy preset by the cloud platform, and then executes different service logics (e.g., dispatching customer service, pushing frequently asked questions, retrieving remote control commands, etc.). The system also records the time, request content, response status, and service result of this interaction on the cloud platform, providing data support for subsequent tracking of problem resolution or user satisfaction evaluation. For example, if the system determines that the cloud platform has not responded to the vehicle's interaction request, it assumes that current customer service resources are full and there are no available resources to respond to the vehicle. The system will then generate a corresponding missed interaction record from the cloud platform and mark this missed interaction record as... The next priority interaction event will be dynamically allocated based on the pre-set customer service resources on the cloud platform. When the system detects that the cloud platform fails to respond to a vehicle's interaction request, it considers the customer service resources temporarily full and automatically generates an "interaction not connected record," marking it as the next priority event. This ensures that vehicles that do not respond in time 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 interaction services and overall scheduling efficiency. Simultaneously, after identifying the "not connected record," the system will dynamically allocate customer service resources from the cloud platform, such as from backup customer service. By activating new customer service representatives in the pool, reallocating some low-priority tasks, or temporarily suspending some non-critical tasks, the system can quickly restore its ability to process high-priority interaction requests. This resource management approach avoids long-term resource overload or idleness, achieving intelligent and balanced distribution of service load. Even under extreme conditions of high customer service concurrency and high system pressure, this mechanism ensures that every unresponsive request is recorded, tracked, and prioritized, significantly reducing the interaction interruption rate. By constructing an "interaction unconnection record," the system provides a basis for subsequent data analysis, helping the platform to continuously optimize service capabilities and dynamic capacity planning, ultimately enhancing overall service reliability and user satisfaction.

[0131] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which 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, Includes the following steps: Based on vehicle information collected at the entrance and exit of the parking lot by the cloud platform, the system receives interactive requests uploaded by vehicles through the parking lot terminal. The vehicle information specifically includes entry and exit records, parking space number, and charging pile number. Determine whether the interaction request receives a response from the cloud platform; If so, the preset terminal call function of the parking lot terminal is dynamically activated. Based on the terminal call function, a response bridge for short-term interaction with the parking lot terminal is built from the cloud platform. The preset customer service is mobilized to join the response bridge on the cloud platform, and a service order corresponding to the vehicle is generated. The service order specifically includes billing anomalies, equipment failures, and insufficient resources. Determine whether the pending service order can obtain service authorization for the vehicle. If possible, the driving status of the vehicle information is collected by the customer service representative, the congestion information caused by the vehicle in the parking lot is obtained, and based on the congestion information, the vehicle is guided to move and be dispatched in the parking lot through the response bridge. The interaction data of the vehicle is generated in real time on the cloud platform. The driving status specifically includes normal driving and abnormal driving, and the movement and dispatching specifically includes path planning, pointing to temporary buffer zones and avoiding congestion points. The step of determining whether the pending service order can obtain service authorization for the vehicle further includes: Based on the service content of the work order to be serviced, the remote control data of the vehicle is obtained through the cloud platform; Determine whether the remote control data matches the preset service level permissions of the cloud platform, wherein the service level permissions specifically include viewing information only, allowing remote voice communication, and allowing remote vehicle control; If so, the service execution parameters of the service content are dynamically adjusted according to the current state of the vehicle. The current state specifically includes the user driving state, the autonomous driving state, and the power outage state. The service execution parameters specifically include the service duration, the service time period, and the service restrictions.

2. The interactive method for managing smart terminals on 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: The location information of the vehicle in the parking lot is identified, and based on the location information, a preset camera is used to acquire image data of the vehicle within a preset range; Determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion; If so, the vehicle's shape features are collected through the image data. Based on the shape features, the required temporary parking space for the vehicle is constructed. Based on the required temporary parking space, the temporary parking position of the vehicle is divided in a preset temporary buffer from the cloud platform. The shape features specifically include size features, posture features, type features, and structural features.

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

4. The interactive method for managing smart terminals on a cloud platform according to claim 1, characterized in that, The step of classifying the driving status based on the vehicle information by the customer service representative also includes: Based on the image data of the vehicle pre-acquired by the cloud platform, and combined with the real-time vehicle status uploaded by the vehicle to the cloud platform, the status information of the vehicle is identified. The status information specifically includes position, direction angle, battery level, door and window status, brake status, gear information, whether it is charging, and whether it is locked. Determine whether the status information matches the preset status type of the cloud platform, wherein the status type specifically includes movable, stationary but recallable, and forced stationary; If so, the vehicle will be marked in the virtual map preset on the cloud platform to generate corresponding marking data, and the navigation direction information in the virtual map will be dynamically adjusted according to the marking data.

5. The interactive method for managing smart terminals on 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: Based on the request source of the interaction request, the request content type of the interaction request is parsed. The request source specifically includes the user's App, the vehicle system, and the customer service console. The request content type specifically includes requests for help, vehicle relocation, charging failure reporting, and voice calls. Determine whether the type of the requested content belongs to the common question types preset by the cloud platform; If so, a preset question quote is sent from the cloud platform to the parking lot terminal, guiding the vehicle to process the interaction request through the question quote, and generating the vehicle's interaction completion result in real time on the cloud platform.

6. The interactive method for managing smart terminals on a cloud platform according to claim 1, characterized in that, The step of receiving interactive requests uploaded by vehicles through parking lot terminals based on vehicle information collected at parking lot entrances and exits via a cloud platform further includes: Based on the interaction request pre-sent by the vehicle through the parking lot terminal, the interaction request is responded to by the cloud platform; Determine whether the cloud platform responds to the vehicle; If not, a corresponding failed interaction record is generated from the cloud platform, and the failed interaction record is marked as a priority interaction event. Based on the priority interaction event, the customer service resources preset by the cloud platform are dynamically mobilized.

7. An interactive system for managing smart terminals via a cloud platform, characterized in that, include: The receiving module is used to receive vehicle information collected at the entrance and exit of the parking lot based on the cloud platform, and to receive interactive requests uploaded by vehicles through the parking lot terminal. The vehicle information specifically includes entry and exit records, parking space number and charging pile number. The judgment module is used to determine whether the interaction request has received a response from the cloud platform; The execution module is used to dynamically activate the preset terminal call function of the parking lot terminal if the condition is met, construct a response bridge from the cloud platform to interact with the parking lot terminal based on the terminal call function, mobilize preset customer service personnel on the cloud platform to join the response bridge, and generate a service order corresponding to the vehicle. The service order specifically includes billing anomalies, equipment failures, and insufficient resources. The second judgment module is used to determine whether the work order to be served can obtain service authorization for the vehicle. The second execution module is used to, if possible, collect the driving status of the vehicle information as classified by the customer service, obtain the congestion information caused by the vehicle in the parking lot, guide the vehicle to move and be dispatched 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. The driving status specifically includes driving normally and driving abnormally, and the movement and dispatching specifically includes path planning, pointing to temporary buffer zones, and avoiding congestion points. The second judgment module also includes: The acquisition unit is used to acquire remote control data of the vehicle through the cloud platform based on the service content of the work order to be served. The fourth judgment unit is used to determine whether the remote control data matches the service level permissions preset by the cloud platform, wherein the service level permissions specifically include viewing information only, allowing remote voice communication, and allowing remote vehicle control; 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 if the current state is true. The current state specifically includes the user driving state, the autonomous driving state, and the power failure state. The service execution parameters specifically include the service duration, the service time period, and the service restrictions.

8. The interactive system for managing smart terminals via a cloud platform according to claim 7, characterized in that, Also includes: The acquisition module is used to identify the location information of the vehicle in the parking lot, and based on the location information, to acquire image data of the vehicle within a preset range using a preset camera; The third judgment module is used to determine whether a preset congestion feature is detected in the image data, wherein the congestion feature specifically includes vehicle behavior-related congestion, traffic flow status-related congestion, and non-vehicle obstacle-related congestion. The third execution module is used to, if so, acquire the vehicle's shape features through the image data, construct the required temporary parking space for the vehicle based on the shape features, and divide the vehicle's temporary parking position from the cloud platform in a preset temporary buffer based on the required temporary parking space. The shape features specifically include size features, posture features, type features, and structural features.

9. The interactive system for managing smart terminals via a cloud platform according to claim 7, characterized in that, The execution module further includes: The allocation unit is used to randomly allocate customer service representatives to provide cloud-based interactive services to the vehicle from the idle customer service resources pre-detected on the cloud platform. The judgment unit is used to determine whether the cloud-based interactive service can complete the interactive connection. An execution unit is configured to, if so, generate the interaction progress of the vehicle, restrict the idle customer service resources from engaging in multi-party interactions with the vehicle based on the interaction progress, identify the customer service representative's interaction transfer request, reallocate another customer service representative from the idle customer service resources to provide cloud interaction services for the vehicle based on the interaction transfer request, and construct the vehicle's historical interaction information on the cloud platform.

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