Cloud agent allocation method based on parking platform and related device

Abstract

The application discloses a parking platform-based cloud seat allocation method and related device, comprising: judging whether a request instruction belongs to a first type of instruction or a second type of instruction when the request instruction is received from a preset port; generating a request identifier according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction belongs to the first type of instruction; obtaining a preset first type of login strategy, and sending the first type of instruction to a target cloud address corresponding to the first type of login strategy according to the request identifier; obtaining a second type of connection mode corresponding to the second type of instruction when the request instruction belongs to the second type of instruction; obtaining a local interface, entering a local cloud seat through the local interface, and sending the second type of instruction to the local cloud seat; generating a corresponding execution operation according to result information fed back from the local cloud seat or the target cloud address when the result information is received; and improving resource utilization, which can save important data by using a private cloud and improve functional efficiency by using a public cloud.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cloud agents, and in particular to a cloud agent allocation method based on a parking platform and related devices. BACKGROUND

[0002] With the continuous increase of parking lots, the business of cloud agents (a parking lot management system that realizes unattended operation) also expands, and the service of parking lots is more and more, but the cloud agent platform is only one. When the parking problems suddenly increase at a certain moment, the cloud agent cannot serve, resulting in that the problems of the car owners cannot be solved in time, affecting the operation and reputation of the parking lot.

[0003] Therefore, how to distribute the pressure of the agent has become a technical problem to be solved. SUMMARY

[0004] In order to realize the distribution of the pressure of the agent, the present application provides a cloud agent allocation method based on a parking platform and related devices.

[0005] In a first aspect, the present application provides a cloud agent allocation method based on a parking platform, which adopts the following technical scheme:

[0006] A cloud agent allocation method based on a parking platform, comprising:

[0007] When a request instruction is received from a preset port, it is judged whether the request instruction belongs to a first type of instruction or a second type of instruction;

[0008] When the request instruction belongs to the first type of instruction, a request identifier is generated according to a car owner request or a parking lot request in the first type of instruction;

[0009] A first type of login strategy is obtained, and the first type of instruction is sent to a target cloud address corresponding to the first type of login strategy according to the request identifier;

[0010] When the request instruction belongs to the second type of instruction, a second type of connection mode corresponding to the second type of instruction is obtained;

[0011] A local interface is obtained, and the second type of instruction is sent to a local cloud agent through the local interface and enters the local cloud agent;

[0012] When receiving result information fed back from the local cloud agent or the target cloud address, a corresponding execution operation is generated according to the result information.

[0013] Optionally, the step of judging whether the request instruction belongs to the first type of instruction or the second type of instruction when the request instruction is received from the preset port comprises:

[0014] When a request instruction is received from a preset port, the request content in the request instruction is obtained;

[0015] determining whether the request content is valid;

[0016] if yes, determining whether the request instruction belongs to a first type of instruction or a second type of instruction according to the request content.

[0017] Optionally, the step of determining whether the request content is valid comprises:

[0018] obtaining a service set, and determining a target service in the request content;

[0019] traversing the service set according to the target service and obtaining a traversal result;

[0020] matching a corresponding matching range according to the traversal result;

[0021] determining whether the request content is valid according to the matching range and the target service.

[0022] Optionally, the step of generating a request identifier according to the owner request or the parking lot request in the first type of instruction comprises:

[0023] determining whether the first type of instruction belongs to an owner request or a parking lot request according to instruction content in the first type of instruction;

[0024] when the first type of instruction belongs to an owner request, generating a corresponding owner information request identifier;

[0025] when the first type of instruction belongs to a parking lot request, generating a corresponding parking lot information request identifier.

[0026] Optionally, the step of obtaining a preset first type of login strategy and sending the first type of instruction to a target cloud address corresponding to the first type of login strategy according to the request identifier comprises:

[0027] obtaining a preset first type of login strategy, and obtaining remote service content in the first type of login strategy;

[0028] packing the first type of instruction according to the remote service content to generate a packed file;

[0029] sending the packed file to the target cloud address corresponding to the first type of login strategy.

[0030] Optionally, the step of obtaining a local interface, entering a local cloud seat through the local interface, and sending the second type of instruction to the local cloud seat comprises:

[0031] acquire a local interface, determine a local interface type according to specific instruction content of the second type of instruction, the second type of instruction including a passing vehicle instruction, a charging instruction, a coupon instruction, and a parking lot management instruction;

[0032] enter a corresponding local cloud seat through the local interface type and send the second type of instruction to the local cloud seat.

[0033] Optionally, after the step of generating a corresponding execution operation according to the result information when receiving feedback of the result information from the local cloud seat or the target cloud address, the method further includes:

[0034] acquire user information corresponding to the request instruction;

[0035] record a result of the execution operation corresponding to the user information;

[0036] store the result of the execution operation in a processing log corresponding to the user information;

[0037] generate a shortcut processing flow through the processing log when detecting a request operation of the user information.

[0038] In a second aspect, the application provides a cloud seat allocation device based on a parking platform, the cloud seat allocation device based on the parking platform including:

[0039] an instruction judgment module configured to judge whether a request instruction received from a preset port is a first type of instruction or a second type of instruction;

[0040] an identification generation module configured to generate a request identification according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction is the first type of instruction;

[0041] a cloud address module configured to acquire a preset first type of login strategy and send the first type of instruction to a target cloud address corresponding to the first type of login strategy according to the request identification;

[0042] a second type of instruction module configured to acquire a second type of connection mode corresponding to a second type of instruction when the request instruction is the second type of instruction;

[0043] a local cloud seat module configured to acquire a local interface, enter a local cloud seat through the local interface, and send the second type of instruction to the local cloud seat;

[0044] an operation execution module configured to generate a corresponding execution operation according to result information when receiving feedback of the result information from the local cloud seat or the target cloud address.

[0045] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the processor executes the method according to any one of the preceding aspects when running computer instructions stored in the memory.

[0046] In a fourth aspect, the present application provides a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the method according to the preceding aspect.

[0047] In summary, the present application has the following beneficial technical effects:

[0048] The present application judges whether the request instruction belongs to a first type of instruction or a second type of instruction when receiving the request instruction from the preset port; generates a request identifier according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction belongs to the first type of instruction; acquires a preset first login strategy and sends the first type of instruction to a target cloud address corresponding to the first login strategy according to the request identifier; acquires a second connection mode corresponding to the second type of instruction when the request instruction belongs to the second type of instruction; acquires a local interface, enters a local cloud agent through the local interface, and sends the second type of instruction to the local cloud agent; generates a corresponding execution operation according to result information fed back from the local cloud agent or the target cloud address when receiving the result information; and improves resource utilization, which can save important data using a private cloud and improve functional efficiency using a public cloud. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 Fig. 1 is a computer device structure schematic diagram of a hardware running environment related to an embodiment of the present application;

[0050] Figure 2 Fig. 2 is a flow schematic diagram of a first embodiment of a cloud agent distribution method based on a parking platform of the present application;

[0051] Figure 3 Fig. 3 is a basic framework diagram of the first embodiment of the cloud agent distribution method based on the parking platform of the present application;

[0052] Figure 4 Fig. 4 is a flow schematic diagram of a second embodiment of the cloud agent distribution method based on the parking platform of the present application;

[0053] Figure 5 Fig. 5 is a structure block diagram of the first embodiment of the cloud agent distribution device based on the parking platform of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below through the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0055] Referring to Figure 1 , Figure 1 The computer device structure schematic diagram of the hardware running environment involved in the embodiment of the present application.

[0056] As Figure 1 shown, the computer device can include: a processor 1001, for example, a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display screen, an input unit such as a keyboard, and an optional user interface 1003 can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a wireless fidelity (Wi-Fi) interface). The memory 1005 can be a high-speed random access memory (RAM), and can also be a stable non-volatile memory (NVM), such as a disk memory. The memory 1005 can also be an independent storage device from the aforementioned processor 1001.

[0057] Those skilled in the art can understand that Figure 1 the structure shown in the above is not a limitation on the computer device, and can include more or fewer components than the diagram, or combine certain components, or different component arrangements.

[0058] As Figure 1 shown, the memory 1005 as a storage medium can include an operating system, a network communication module, a user interface module, and a cloud-based parking platform-based cloud agent allocation program.

[0059] In Figure 1 the computer device shown, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the computer device of the present application can be provided in the computer device, and the computer device calls the cloud-based parking platform-based cloud agent allocation program stored in the memory 1005 through the processor 1001, and executes the cloud-based parking platform-based cloud agent allocation method provided by the embodiment of the present application.

[0060] The embodiment of the present application provides a cloud-based parking platform-based cloud agent allocation method, referring to Figure 2 , Figure 2A flowchart of a first embodiment of the cloud agent allocation method based on a parking platform according to the present application.

[0061] In this embodiment, the cloud agent allocation method based on a parking platform comprises the following steps:

[0062] Step S10: When a request instruction is received from a preset port, it is determined whether the request instruction belongs to a first type of instruction or a second type of instruction.

[0063] It should be noted that the preset port can be a service input port of a hardware device deployed in a parking lot, or a port for collecting service information in the form of a mobile device software, and the present embodiment does not limit the same.

[0064] It can be understood that in this embodiment, the first type of instruction refers to an instruction for which a service content needs to be acquired by a network request, and the second type of instruction refers to an instruction for which a corresponding policy can be acquired in an intranet. The first type and the second type are only used to distinguish between two different types of instructions, and the naming method is not limited.

[0065] In a specific implementation, the request instruction is determined to belong to the first type of instruction or the second type of instruction by analyzing the instruction content.

[0066] It should be noted that the present embodiment proposes a cloud agent public and private deployment scheme, which hosts the cloud agent to a local customer to decentralize the pressure of the agent and effectively avoid the problem that the cloud agent cannot provide services.

[0067] It can be understood that the cloud agent is deployed in a public manner, and the public deployment system and device must be connected to the network for use, so the system has great limitations. When the network fails, the entry and exit of all parking lots will be affected. All parking lot platforms use a parking system, and the concurrency and pressure resistance of the system will decrease with the increase in the number of parking lots. For data processing, the database is centralized, and the pressure on the database is also increasing, and the security of the data cannot be effectively guaranteed. A lot of traffic and server resources are consumed in the data transmission process, causing a lot of unnecessary waste of resources. Therefore, to solve this problem, unnecessary data needs to be localized, and public data needs to be publicized.

[0068] In a specific implementation, the current cloud attendant is generally deployed on the cloud, and access must be through networking. There is a great limitation in the system. When the network fails, the cloud service of the entire parking lot will be affected. The deployment limitation: it is a headache to want to deploy the cloud attendant in the local intranet, because the intranet cannot be connected to the cloud, and data cannot be synchronized; the concurrency problem of the cloud attendant: with the increase in the number of parking lots, the corresponding parking problem also increases, and the single cloud attendant faces the problems of concurrency and pressure resistance, and the data pressure increases; the problem of processing timeliness: without going through the Internet, the data flow is directly transferred using the intranet, which is fast; it is more flexible, and the property can configure the maximum value of the service according to the demand; solve the situation of network interruption, and the local can still handle the problem of the parking lot.

[0069] In a specific implementation, to achieve this goal, the function modules of the parking platform system need to be modularized and split, and the cloud attendant is matched with the remote service SDK to manage the parking lot. The cloud attendant needs to be connected to the cloud, and the local parking platform needs to be controlled through the remote service SDK. First, the vehicle owner dials the help phone, and according to the phone positioning or the information in the two-dimensional code, it is determined that the vehicle owner needs help in that parking lot on that lane. Then, the system connects the remote service SDK of the parking lot through information to realize connection, thereby realizing management of the access to the parking lot.

[0070] Step S20: When the request instruction belongs to a type of instruction, a request identifier is generated according to a vehicle owner request or a parking lot request in the type of instruction.

[0071] It can be understood that in this embodiment, the payment and the vehicle owner terminal function are separated from the system and deployed on the cloud platform to provide a unified API interface for the local parking lot to call. The vehicle owner terminal is matched with a vehicle owner information library (storing vehicle owner information) and a parking lot library (storing information of all parking lots), so as to realize vehicle group login and payment of a parking order. When the vehicle owner initiates payment, the corresponding parking order payment of the parking lot is found through a network request, and after the payment is successful, the payment record is called back to the payment information library of the local parking platform and the cloud platform, which solves one of the payment problems of the private and public deployment of the parking lot.

[0072] Further, to improve the effectiveness of the identifier generation, the step of generating a request identifier according to a vehicle owner request or a parking lot request in the type of instruction includes: judging whether the type of instruction belongs to a vehicle owner request or a parking lot request according to the instruction content in the type of instruction; generating a corresponding vehicle owner information request identifier when the type of instruction belongs to a vehicle owner request; and generating a corresponding parking lot information request identifier when the type of instruction belongs to a parking lot request.

[0073] Step S30: A preset type of login strategy is obtained, and a type of instruction is sent to a target cloud address corresponding to the type of login strategy according to a request identifier.

[0074] It should be noted that the first type of login strategy refers to the configuration strategy of sending a link request to the cloud agent through the Internet, which is set by the system administrator according to the actual use.

[0075] It can be understood that in the present embodiment, the SDK of remote control is embedded in the cloud agent system to provide open remote service; the operation and maintenance personnel deploy a set of cloud agent system on the cloud, use public deployment, and provide event receiving api interface to the outside; the operation and maintenance personnel can help the customer to deploy the localized cloud agent system through remote assistance, connect well with the cloud agent system on the cloud, realize data interaction, and configure the maximum value of task processing; deploy the local parking management system, debug the connection of the equipment, ensure that the vehicle can normally enter and exit the field, and configure the remote control information.

[0076] Further, in order to improve the work efficiency of the cloud agent in the target cloud address, the step of acquiring the first type of login strategy and sending the first type of instruction to the target cloud address corresponding to the first type of login strategy according to the request identifier comprises: acquiring the first type of login strategy, acquiring the remote service content in the first type of login strategy; packing the first type of instruction according to the remote service content to generate a packed file; and sending the packed file to the target cloud address corresponding to the first type of login strategy.

[0077] Step S40: when the request instruction belongs to the second type of instruction, acquiring the second type of connection mode corresponding to the second type of instruction.

[0078] It can be understood that in the present embodiment, the second type of connection mode belongs to the connection mode of accessing the intranet, and by deploying the cloud agent in the intranet, the user can enjoy part of the parking service in the local area network without connecting to the extranet.

[0079] Step S50: acquiring a local interface, entering a local cloud agent through the local interface, and sending the second type of instruction to the local cloud agent.

[0080] It can be understood that the passing vehicle module, the billing module, the coupon module, the parking lot management module, and the database of parking data can be deployed locally, connected with the equipment using the intranet, and the speed of the network can be greatly improved.

[0081] Further, in order to improve the accuracy of the local cloud agent service, the step of acquiring the local interface, entering the local cloud agent through the local interface and sending the second type of instruction to the local cloud agent, comprises: acquiring the local interface, determining the local interface type according to the specific instruction content of the second type of instruction, the second type of instruction comprising: a passing vehicle instruction, a charging instruction, a coupon instruction and a parking lot management instruction; entering the corresponding local cloud agent through the local interface type and sending the second type of instruction to the local cloud agent.

[0082] Step S60: When receiving the result information fed back from the local cloud agent or the target cloud address, generating a corresponding execution operation according to the result information.

[0083] In a specific implementation, as shown in the infrastructure diagram Figure Three The technical solutions specifically involved in the embodiment are as follows on this basis:

[0084] Interaction between public and private comprehensive deployment of cloud agents is achieved by introducing a remote technology SDK access API solution; a private cloud agent system service processing mechanism. When the service queue exceeds the maximum service value of the local cloud agent, the mechanism automatically pushes events to the public cloud agent system to actively process tasks; solves the problem of increasing number of parking lots, concurrent, pressure resistance and expansion of service processing number faced by cloud agents. Dispersing services and data to the local of customers improves system efficiency and data security; a separation scheme of the parking platform system. Separate functions that need to interact with the external network, and localize parking data to make the parking platform system more flexible and more efficient for entry and exit.

[0085] Further, in order to reduce the waiting time of the same user in multiple use cases, acquiring user information corresponding to the request instruction; recording the result of the execution operation corresponding to the user information; storing the result of the execution operation in the processing log corresponding to the user information; when detecting the request operation of the user information, generating a quick processing flow through the processing log.

[0086] It should be noted that in the embodiment, when the same user requests service in the same parking lot multiple times, the corresponding processing log will be called according to the user's identity information. When the completed entries in the processing log are consistent with the current request content of the user, the processing result will be directly obtained in the processing log and the processing result will be fed back to improve the user's use experience, reduce the user's waiting time and save the system's processing resources.

[0087] The embodiment is based on the parking platform, and the cloud seat allocation method comprises the following steps: when a request instruction is received at a preset port, it is judged whether the request instruction belongs to a first type of instruction or a second type of instruction; when the request instruction belongs to the first type of instruction, a request identifier is generated according to a vehicle owner request or a parking lot request in the first type of instruction; a preset first type of login strategy is acquired, and the first type of instruction is sent to a target cloud address corresponding to the first type of login strategy according to the request identifier; when the request instruction belongs to the second type of instruction, a second type of connection mode corresponding to the second type of instruction is acquired; a local interface is acquired, the local interface is used to enter a local cloud seat, and the second type of instruction is sent to the local cloud seat; when receiving result information fed back from the local cloud seat or the target cloud address, a corresponding execution operation is generated according to the result information; by improving the resource utilization rate, important data can be saved by using a private cloud, and the functional efficiency can be improved by using a public cloud.

[0088] Reference Figure 3 , FIG. 2 is a flowchart of a cloud seat allocation method based on a parking platform according to a second embodiment of the application.

[0089] Based on the first embodiment, the step S10 of the cloud seat allocation method based on the parking platform further comprises the following steps:

[0090] Step S101: When a request instruction is received at a preset port, the request content in the request instruction is acquired.

[0091] Step S102: It is judged whether the request content is valid.

[0092] Further, in order to improve the accuracy of the judgment, the step of judging whether the request content is valid comprises the following steps: acquiring a service set, determining a target service in the request content; traversing the service set according to the target service and acquiring a traversal result; matching a corresponding matching range according to the traversal result; and judging whether the request content is valid according to the matching range and the target service.

[0093] It can be understood that, in the embodiment, whether the request content is valid is judged by judging the target service in the request content, and the invalid request content will be immediately fed back to avoid subsequent calculation.

[0094] Step S103: If yes, it is judged whether the request instruction belongs to a first type of instruction or a second type of instruction according to the request content.

[0095] The embodiment is based on the parking platform, and the cloud seat allocation method comprises the following steps: when a request instruction is received at a preset port, it is judged whether the request instruction belongs to a first type of instruction or a second type of instruction; when the request instruction belongs to the first type of instruction, a request identifier is generated according to a vehicle owner request or a parking lot request in the first type of instruction; a preset first type of login strategy is acquired, and the first type of instruction is sent to a target cloud address corresponding to the first type of login strategy according to the request identifier; when the request instruction belongs to the second type of instruction, a second type of connection mode corresponding to the second type of instruction is acquired; a local interface is acquired, the local interface is used to enter a local cloud seat, and the second type of instruction is sent to the local cloud seat; when receiving result information fed back from the local cloud seat or the target cloud address, a corresponding execution operation is generated according to the result information; by improving the resource utilization rate, important data can be saved by using a private cloud, and the functional efficiency can be improved by using a public cloud.

[0096] In addition, the embodiment of the present application also provides a computer readable storage medium, and the storage medium stores a parking platform based cloud agent allocation program. The parking platform based cloud agent allocation program is executed by a processor to realize the steps of the parking platform based cloud agent allocation method.

[0097] Referring to Figure 4 , Figure 4 FIG. 1 is a structural block diagram of a parking platform based cloud agent allocation device according to an embodiment of the present application.

[0098] As Figure 4 shown, the parking platform based cloud agent allocation device according to the embodiment of the present application comprises:

[0099] An instruction judgment module 10 is configured to judge whether the request instruction belongs to a first type of instruction or a second type of instruction when receiving the request instruction from a preset port;

[0100] An identification generation module 20 is configured to generate a request identification according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction belongs to the first type of instruction;

[0101] A cloud address module 30 is configured to acquire a preset first type of login strategy, and send the first type of instruction to a target cloud address corresponding to the first type of login strategy according to the request identification;

[0102] A second type of instruction module 40 is configured to acquire a second type of connection mode corresponding to the second type of instruction when the request instruction belongs to the second type of instruction;

[0103] A local cloud agent module 50 is configured to acquire a local interface, enter a local cloud agent through the local interface, and send the second type of instruction to the local cloud agent;

[0104] An operation execution module 60 is configured to generate a corresponding execution operation according to result information fed back from the local cloud agent or the target cloud address when receiving the result information.

[0105] It should be understood that the above is only for illustration, and does not constitute any limitation on the technical solutions of the present application. In specific applications, those skilled in the art can set it according to needs, and the present application does not limit it.

[0106] The embodiment is implemented by judging whether the request instruction belongs to a first type of instruction or a second type of instruction when the request instruction is received from a preset port; generating a request identifier according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction belongs to the first type of instruction; obtaining a preset first login strategy, and sending the first type of instruction to a target cloud address corresponding to the first login strategy according to the request identifier; obtaining a second type of connection mode corresponding to the second type of instruction when the request instruction belongs to the second type of instruction; obtaining a local interface, entering a local cloud seat through the local interface, and sending the second type of instruction to the local cloud seat; generating a corresponding execution operation according to result information fed back from the local cloud seat or the target cloud address when the result information is received, thereby improving resource utilization, saving important data by using a private cloud, and improving functional efficiency by using a public cloud.

[0107] In an embodiment, the instruction judgment module 10 is further configured to obtain a request content in the request instruction when the request instruction is received from the preset port; judge whether the request content is valid; if yes, judge whether the request instruction belongs to a first type of instruction or a second type of instruction according to the request content.

[0108] In an embodiment, the instruction judgment module 10 is further configured to obtain a service set, determine a target service in the request content, traverse the service set according to the target service and obtain a traversal result, match a corresponding matching range according to the traversal result, and judge whether the request content is valid according to the matching range and the target service.

[0109] In an embodiment, the identifier generation module 20 is further configured to judge whether the first type of instruction belongs to a vehicle owner request or a parking lot request according to an instruction content in the first type of instruction; generate a corresponding vehicle owner information request identifier when the first type of instruction belongs to the vehicle owner request; and generate a corresponding parking lot information request identifier when the first type of instruction belongs to the parking lot request.

[0110] In an embodiment, the cloud address module 30 is further configured to obtain a preset first login strategy, obtain a remote service content in the first login strategy, pack the first type of instruction according to the remote service content to generate a packed file, and send the packed file to a target cloud address corresponding to the first login strategy.

[0111] In an embodiment, the local cloud seat module 50 is further configured to obtain a local interface, determine a local interface type according to a specific instruction content of the second type of instruction, the second type of instruction including a passing vehicle instruction, a charging instruction, a coupon instruction, and a parking lot management instruction, enter a corresponding local cloud seat through the local interface type, and send the second type of instruction to the local cloud seat.

[0112] In an embodiment, the operation execution module 60 is further configured to acquire user information corresponding to the request instruction; record a result of an execution operation corresponding to the user information; store the result of the execution operation in a processing log corresponding to the user information; and generate a quick processing flow through the processing log when detecting a request operation of the user information.

[0113] It should be noted that the above-described workflow is merely illustrative and does not limit the protection scope of the present application. In actual applications, a person skilled in the art can select part or all of the above-described workflow to achieve the purpose of the embodiment according to actual needs, which is not limited herein.

[0114] In addition, technical details not described in detail in the embodiment can be found in the method for cloud agent allocation based on a parking platform provided by any embodiment of the present application, which will not be described herein.

[0115] In addition, it should be noted that in this document, the terms "comprise", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or system. Without more limitations, the element defined by the statement "comprises a" does not exclude the presence of another identical element in the process, method, article or system that includes the element.

[0116] The above-mentioned embodiment numbers of the present application are only for description, not representing the advantages or disadvantages of the embodiments.

[0117] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and necessary general hardware platforms, of course, they can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, an optical disk), and includes a plurality of instructions for making a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) execute the methods described in various embodiments of the present application.

[0118] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent flow transformation made by using the content of the present application specification and drawings, or directly or indirectly applied to other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A cloud-based agent allocation method based on a parking platform, characterized in that, The application comprises the following steps: When a request instruction is received from a preset port, it is determined whether the request instruction belongs to a first type of instruction or a second type of instruction; When the request instruction belongs to the first type of instruction, a request identifier is generated according to a vehicle owner request or a parking lot request in the first type of instruction; A preset first type of login strategy is obtained, and the first type of instruction is sent to a target cloud address corresponding to the first type of login strategy according to the request identifier; When the request instruction belongs to the second type of instruction, a second type of connection mode corresponding to the second type of instruction is obtained; A local interface is obtained, and a local cloud seat is entered through the local interface, and the second type of instruction is sent to the local cloud seat; When receiving result information fed back from the local cloud seat or the target cloud address, a corresponding execution operation is generated according to the result information; The step of obtaining a local interface, entering a local cloud seat through the local interface, and sending the second type of instruction to the local cloud seat comprises the following steps: A local interface is obtained, and a local interface type is determined according to the specific instruction content of the second type of instruction. The second type of instruction includes a passing vehicle instruction, a charging instruction, a coupon instruction, and a parking lot management instruction; The corresponding local cloud seat is entered through the local interface type, and the second type of instruction is sent to the local cloud seat.

2. The cloud-based platform for parking lot attendant assignment method according to claim 1, wherein, The step of determining whether the request instruction belongs to the first type of instruction or the second type of instruction when the request instruction is received from the preset port comprises the following steps: When a request instruction is received from a preset port, the request content in the request instruction is obtained; It is determined whether the request content is valid; If yes, it is determined whether the request instruction belongs to the first type of instruction or the second type of instruction according to the request content.

3. The cloud-based platform for parking lot attendant assignment method according to claim 2, wherein, The step of determining whether the request content is valid comprises the following steps: A service set is obtained, and a target service is determined in the request content; The target service is traversed in the service set to obtain a traversal result; The traversal result is matched with a corresponding matching range; It is determined whether the request content is valid according to the matching range and the target service.

4. The cloud-based platform for parking lot attendant assignment method according to claim 1, wherein, The step of generating a request identifier according to a vehicle owner request or a parking lot request in the first type of instruction comprises the following steps: It is determined whether the first type of instruction belongs to a vehicle owner request or a parking lot request according to the instruction content in the first type of instruction; When the first type of instruction belongs to a vehicle owner request, a corresponding vehicle owner information request identifier is generated; When the first type of instruction belongs to a parking lot request, a corresponding parking lot information request identifier is generated.

5. The cloud-based platform for parking lot attendant assignment method according to claim 1, wherein, The step of obtaining a preset first type of login strategy and sending the first type of instruction to a target cloud address corresponding to the first type of login strategy according to the request identifier comprises the following steps: A preset first type of login strategy is obtained, and remote service content is obtained in the first type of login strategy; The first type of instruction is packaged to generate a packaged file according to the remote service content; The packaged file is sent to the target cloud address corresponding to the first type of login strategy.

6. The cloud-based platform for parking lot attendant assignment method according to claim 1, wherein, After the step of generating a corresponding execution operation according to the result information when receiving the result information fed back from the local cloud seat or the target cloud address, the following steps are further included: User information corresponding to the request instruction is obtained; record a result of the execution operation corresponding to the user information; store the result of the execution operation into a processing log corresponding to the user information; generate a shortcut processing flow through the processing log when a request operation of the user information is detected.

7. A cloud-based agent allocation device based on a parking platform, characterized in that, The cloud address module is configured to acquire a preset first login strategy and send the first instruction to a target cloud address corresponding to the first login strategy according to the request identifier. The instruction judgment module is configured to judge whether the request instruction belongs to a first type of instruction or a second type of instruction when the request instruction is received from the preset port. The identification generation module is configured to generate a request identifier according to a vehicle owner request or a parking lot request in the first type of instruction when the request instruction belongs to the first type of instruction. The second instruction module is configured to acquire a second connection mode corresponding to the second type of instruction when the request instruction belongs to the second type of instruction. The local cloud agent module is configured to acquire a local interface, enter a local cloud agent through the local interface, and send the second instruction to the local cloud agent. The operation execution module is configured to generate a corresponding execution operation according to result information fed back from the local cloud agent or the target cloud address when the result information is received. The acquisition of the local interface, the entering of the local cloud agent through the local interface, and the sending of the second instruction to the local cloud agent include: The acquisition of the local interface, the entering of the corresponding local cloud agent through the local interface type, and the sending of the second instruction to the local cloud agent include: The device includes a memory and a processor, and the processor executes the method according to any one of claims 1 to 6 when running computer instructions stored in the memory. The instructions, when running on a computer, cause the computer to execute the method according to any one of claims 1 to 6.

8. A computer device, comprising: ​ 9. A computer-readable storage medium, characterized in that, ​

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