Intelligent internet of everything operating system having built-in ai and control method therefor

Abstract

Disclosed in the present invention are an intelligent Internet of Everything operating system having built-in AI and a control method therefor. The intelligent Internet of Everything operating system comprises: a scheduling module, an API interface, and an interaction description module. An AI algorithm is built in the scheduling module, and the AI algorithm is used for refreshing and synchronizing real-time states of hardware resources and scheduling a corresponding hardware resource on the basis of service requirement information. The API interface is connected to a super terminal, the super terminal comprises a plurality of devices, and each device is arranged according to a usage environment. The interaction description module is used for recording a usage state and the usage environment of each device, a usage habit corresponding to a user of each device, a hardware resource scheduling record of each device, and a human-computer interaction process. The intelligent Internet of Everything operating system of the present invention can implement intelligent scheduling of each device in the super terminal, thereby improving the degree of intelligence of the operating system and facilitating providing better services for users.

Description

AI built-in all things smart operation system and control method thereof TECHNICAL FIELD

[0001] The present application relates to the field of AI intelligent technology, and particularly relates to an AI built-in all things smart operation system and a control method thereof. BACKGROUND

[0002] The existing operation system can be divided into two categories according to the ability of loading devices: one is a single type of operation system, which can only be loaded on a single type of device, such as windows loaded on a computer and Android loaded on a smart phone; the other is represented by the Hongmeng operation system, which can be loaded on various hardware devices by using flexible deployment capability.

[0003] The design concept and implementation architecture of the existing operation system have basically been determined since the birth of OS / 360 in 1964, and there has been no essential change so far, that is, supporting applications on the upper side and scheduling hardware resources on the lower side. The use of computers by users is one-way, that is, users give various inputs to computers through peripherals, and computers give feedback results according to the inputs of users. It can be seen that the current operation system is not intelligent enough to automatically analyze user demand and output the resources that need to be scheduled in time.

[0004] Therefore, the prior art still needs to be improved and improved. SUMMARY

[0005] The technical problem to be solved by the present application is to provide an AI built-in all things smart operation system and a control method thereof, aiming at solving the problem that the existing operation system is not intelligent enough to automatically analyze user demand and output the resources that need to be scheduled in time.

[0006] In order to solve the above technical problems, the technical scheme adopted by the present application is as follows:

[0007] In a first aspect, the present application provides an intelligent control system based on a distributed super terminal, wherein the system comprises:

[0008] A scheduling module, the scheduling module is built-in AI algorithm, the AI algorithm is used for refreshing synchronization of real-time state of hardware resources and scheduling corresponding hardware resources based on service demand information;

[0009] An API interface, the API interface is connected with the super terminal, the super terminal includes a plurality of devices, and each device is arranged according to the use scene;

[0010] An interaction description module is configured to record the usage state of each device, the usage scenario, the usage habit of the user corresponding to each device, the hardware resource scheduling record of each device, and the human-computer interaction process.

[0011] In an implementation manner, the all things intelligent connection operating system further comprises:

[0012] A time control module is connected with the interaction description module and is configured to acquire the historical usage scenario and the historical interaction process of each device.

[0013] In an implementation manner, the time control module is further connected with the scheduling module and is configured to simulate the future scenario and the interaction process of each device.

[0014] In an implementation manner, each device is connected with each other, and the resource pool of each device is shared.

[0015] In an implementation manner, the interaction description module comprises an interaction description information table configured to reflect the usage state of each device, the usage scenario, the usage habit of the user corresponding to each device, and the hardware resource scheduling record of each device.

[0016] In a second aspect, the embodiment of the present application further provides a control method of the all things intelligent connection operating system with built-in AI, wherein the method comprises:

[0017] Acquiring service demand information, determining service scenario information based on the service demand information, and determining a target device matched with the service scenario information based on the service scenario information;

[0018] Acquiring the historical usage scenario and the historical interaction process of the target device, and obtaining resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process;

[0019] Calling the target hardware resource corresponding to the resource scheduling prediction information based on the scheduling module.

[0020] In an implementation manner, the acquiring service demand information and determining service scenario information based on the service demand information comprises:

[0021] Receiving an operation instruction of a user based on any one device in the super terminal, and determining service demand information based on the operation instruction;

[0022] Analyzing the service demand information to obtain user intention information of the service demand information;

[0023] Determining the service scenario information based on the user intention information.

[0024] In an implementation manner, the determining, based on the service scenario information, a target device matched with the service scenario information comprises:

[0025] obtaining, based on the interaction description module, a historical use scenario of each device;

[0026] matching the service scenario information with the historical use scenario of each device to obtain a matching result, wherein the matching result reflects a matching degree between the service scenario information and the historical use scenario of each device;

[0027] taking a device with the highest matching degree between the service scenario information and the historical use scenario in the matching result as the target device.

[0028] In an implementation manner, the obtaining the historical use scenario and the historical interaction process of the target device comprises:

[0029] determining historical time information, and calling an interaction description information table based on the interaction description module, wherein the interaction description information table is used to reflect a use state, a use scenario of each device, a use habit of a user corresponding to each device, and a hardware resource scheduling record of each device;

[0030] obtaining, from the interaction description information table, the historical use scenario and the historical interaction process of the target device corresponding to the historical time information.

[0031] In an implementation manner, the obtaining, based on the historical use scenario and the historical interaction process, the resource scheduling prediction information of the target device comprises:

[0032] determining, based on the historical use scenario and the historical interaction process, historical resource scheduling information of the target device in each historical use scenario and historical interaction process;

[0033] determining resource scheduling preference information based on the historical resource scheduling information;

[0034] determining the resource scheduling prediction information based on the resource scheduling preference information.

[0035] In an implementation manner, the determining, based on the resource scheduling preference information, the resource scheduling prediction information comprises:

[0036] determining, according to the resource scheduling preference information, a target hardware resource with the highest scheduling frequency or the longest scheduling time length of the target device in the historical time information;

[0037] The target hardware resource and a target function corresponding to the target hardware resource are taken as the resource scheduling prediction information.

[0038] In an implementation manner, the resource scheduling prediction information of the target device is obtained based on the historical usage scenario and the historical interaction process.

[0039] The future scenario information and the future interaction process information of the target device are predicted based on the interaction description module and the historical usage scenario and the historical interaction process.

[0040] The target hardware resource is obtained by matching the future scenario information and the future interaction process information with the interaction description information table.

[0041] The target hardware resource and a target function corresponding to the target hardware resource are taken as the resource scheduling prediction information.

[0042] In a third aspect, the application also provides a control device of an AI built-in all things intelligent operation system, and the device comprises:

[0043] A target device determination module is configured to acquire service demand information, determine service scenario information based on the service demand information, and determine a target device matched with the service scenario information based on the service scenario information.

[0044] A resource scheduling prediction module is configured to acquire a historical usage scenario and a historical interaction process of the target device, and obtain resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process.

[0045] A hardware resource calling module is configured to call a target hardware resource corresponding to the resource scheduling prediction information based on the scheduling module.

[0046] In an implementation manner, the target device determination module comprises:

[0047] A demand information determination unit is configured to receive an operation instruction of a user by any one of the super terminals, and determine service demand information based on the operation instruction.

[0048] An intention information determination unit is configured to analyze the service demand information to obtain user intention information of the service demand information.

[0049] A scenario information determination unit is configured to determine the service scenario information based on the user intention information.

[0050] In an implementation manner, the target device determination module further comprises:

[0051] a historical scenario determination unit configured to acquire historical usage scenarios of each device based on the interaction description module;

[0052] a scenario matching unit configured to match the service scenario information with the historical usage scenarios of each device to obtain a matching result, wherein the matching result reflects a matching degree between the service scenario information and the historical usage scenarios of each device;

[0053] a device determination unit configured to determine, as the target device, a device with the highest matching degree between the service scenario information and the historical usage scenarios in the matching result.

[0054] In an implementation manner, the resource scheduling prediction module comprises:

[0055] an information table acquisition unit configured to determine historical time information, and acquire an interaction description information table based on the interaction description module, wherein the interaction description information table is configured to reflect a usage state, a usage scenario of each device, a usage habit of a user corresponding to each device, and a hardware resource scheduling record of each device;

[0056] a historical information acquisition unit configured to acquire, from the interaction description information table, a historical usage scenario and a historical interaction process of the target device corresponding to the historical time information.

[0057] In an implementation manner, the resource scheduling prediction module further comprises:

[0058] a historical scheduling information acquisition unit configured to determine, based on the historical usage scenario and the historical interaction process, historical resource scheduling information of the target device in each historical usage scenario and the historical interaction process;

[0059] a scheduling preference information acquisition unit configured to determine resource scheduling preference information based on the historical resource scheduling information;

[0060] a scheduling prediction information determination unit configured to determine the resource scheduling prediction information based on the resource scheduling preference information.

[0061] In an implementation manner, the scheduling prediction information determination unit comprises:

[0062] a target hardware resource determination sub-unit configured to determine, according to the resource scheduling preference information, a target hardware resource with the highest scheduling frequency or the longest scheduling time length of the target device in the historical time information;

[0063] a resource scheduling prediction determination sub-unit configured to determine, as the resource scheduling prediction information, the target hardware resource and a target function corresponding to the target hardware resource.

[0064] In an implementation manner, the scheduling prediction information determination unit further comprises:

[0065] a future information prediction subunit configured to predict future scene information and future interaction process information of the target device based on the history use scene and the history interaction process according to the interaction description module;

[0066] an information matching subunit configured to match the future scene information and the future interaction process information with the interaction description information table to obtain a target hardware resource;

[0067] a prediction information determination subunit configured to take the target hardware resource and a target function corresponding to the target hardware resource as the resource scheduling prediction information.

[0068] In a fourth aspect, an embodiment of the present application further provides a computer device, wherein the computer device comprises a memory, a processor, and a built-in AI-based everything intelligent connection operating system control program stored in the memory and executable on the processor; and the processor executes the built-in AI-based everything intelligent connection operating system control program to implement the steps of the built-in AI-based everything intelligent connection operating system control method in any of the above solutions.

[0069] In a fifth aspect, an embodiment of the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a built-in AI-based everything intelligent connection operating system control program; and the built-in AI-based everything intelligent connection operating system control program is executed by a processor to implement the steps of the built-in AI-based everything intelligent connection operating system control method in any of the above solutions.

[0070] Advantages: Compared with the prior art, the present application provides a built-in AI-based everything intelligent connection operating system, which comprises a scheduling module, an API interface, and an interaction description module. The scheduling module is built-in with an AI algorithm, and the AI algorithm is used to refresh and synchronize the real-time state of hardware resources and schedule the corresponding hardware resources based on service demand information. The API interface is connected with a super terminal, the super terminal comprises a plurality of devices, and each device is arranged according to a use scene. The interaction description module is used to record the use state of each device, the use scene, the use habit of a user corresponding to each device, the hardware resource scheduling record of each device, and the human-computer interaction process. The everything intelligent connection operating system can intelligently schedule each device in the super terminal, improve the intelligent degree of the operating system, and is beneficial to providing better services for users. BRIEF DESCRIPTION OF DRAWINGS

[0071] Fig. 1 is a schematic diagram of an intelligent control system based on a distributed super terminal according to an embodiment of the present application.

[0072] Fig. 2 is an application environment diagram of the intelligent control method based on the distributed terminal according to an embodiment of the present application.

[0073] Fig. 3 is a flowchart of a preferred embodiment of the intelligent control method based on the distributed terminal according to an embodiment of the present application.

[0074] Fig. 4 is a flowchart of determining a target device in the intelligent control method based on the distributed terminal according to an embodiment of the present application.

[0075] Fig. 5 is a flowchart of resource scheduling prediction in the intelligent control method based on the distributed terminal according to an embodiment of the present application.

[0076] Fig. 6 is a schematic diagram of the architecture of the control device of the AI built-in everything intelligent connection operating system according to an embodiment of the present application.

[0077] Fig. 7 is a schematic diagram of the architecture of the computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0078] To make the objects, technical solutions and effects of the present application clearer and more explicit, the present application is further described in detail below with reference to 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.

[0079] The flowchart shown in the drawings is only an example and does not necessarily include all the contents and operations or steps, nor does it necessarily execute in the order described. For example, some operations or steps can be further divided, combined or partially combined, so the actual execution order may be changed according to the actual situation.

[0080] It should be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0081] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second" and the like are used to distinguish the same or similar items with basically the same function and effect. For example, the first control information and the second control information are only used to distinguish different control information and do not limit the order.

[0082] Those skilled in the art can understand that the terms "first", "second" and the like do not limit the quantity and execution order, and the terms "first", "second" and the like do not necessarily mean different.

[0083] It should also be understood that the term "and / or" as used herein in the specification and in the claims, unless otherwise specified, means any one of the associated listed items or a combination of any of the associated listed items.

[0084] Since the existing single-device-based agent, its perception ability is limited to the hardware richness and spatial position limitation of a single device, and it is difficult to meet the requirements, lacking complete and accurate perception ability, the foundation for the agent to play a role does not exist. And the operation of the existing agent often needs large computing power and other rich hardware resources support, only powerful hardware can become the loading and running object of the agent, the cost is high, and the popularization is limited. In addition, there are problems such as few touch points and small coverage.

[0085] Therefore, the embodiment provides a built-in AI everything intelligent operation system, as shown in Figure 1, which includes a scheduling module, an API interface, and an interaction description module. The scheduling module is built-in AI algorithm, the AI algorithm is used to refresh and synchronize the real-time state of hardware resources and schedule the corresponding hardware resources based on service demand information. In this embodiment, the API interface is connected with the super terminal to realize the connection between the everything intelligent operation system and the super terminal, the super terminal includes a plurality of devices, and each device is arranged according to the use scene, such as device 1, device 2, device 3,..., and device n in Figure 1. For example, in a home environment, it is divided into bedroom use scene, kitchen use scene, bathroom use scene and living room use scene, wherein the bedroom use scene includes intelligent projector, intelligent table lamp, intelligent air conditioner and other devices; the kitchen use scene includes intelligent exhaust hood, intelligent refrigerator, intelligent dishwasher and other devices; the bathroom use scene includes intelligent toilet, intelligent washing machine, intelligent dryer and other devices; the living room use scene includes intelligent television, intelligent air conditioner, intelligent curtain, sweeping robot and other devices. These devices are distributed according to the use scene. The interaction description module of the embodiment is used to record the use state, use scene, user corresponding use habit of each device, hardware resource scheduling record and man-machine interaction process of each device. Therefore, based on the everything intelligent operation system of the embodiment, each device in the super terminal can be intelligently scheduled, the intelligent degree of the operation system is improved, and better service can be provided for the user.

[0086] Further, the all things intelligent connection operating system of the embodiment further comprises a time control module. The time control module is connected with the interaction description module, and is used for acquiring historical use scenes and historical interaction processes of each device. The historical use scenes and the historical interaction processes are recorded by the interaction description module in the process of being used. Further, the time control module of the embodiment is further connected with the scheduling module, and is used for simulating future scenes and interaction processes of each device. As can be seen, the time control mode based on the embodiment can play back the past use scenes and interaction processes of each device, and can also predict future use scenes and interaction processes.

[0087] In addition, the interaction description module of the embodiment can collect and aggregate the use scene records and the interaction process records scattered on each device to form an interaction description information table, and complete trajectory records of past interaction records of the super terminal. The interaction description information table is used to reflect the use state of each device, the use scene, the use habit corresponding to each user of each device, and the hardware resource scheduling record of each device, so as to quickly call the related data of the historical use scene and the historical interaction process of each device.

[0088] Further, all the devices in the embodiment are connected with each other, and the resource pools of all the devices are shared. When the agent needs to use the computing resource or the storage resource, the corresponding computing resource or the storage resource is acquired from the resource pool of any one device. For example, when the hardware resources of the intelligent washing machine are scheduled, it is found that more intelligent actions cannot be performed, such as that the storage resource is insufficient when the recent washing records need to be stored. At this time, the idle storage resource of the intelligent drying machine can be acquired for use by the intelligent washing machine, so as to meet the user demand. As can be seen, the hardware resources of each device constituting the super terminal can be integrated by the embodiment, and the hardware resource sharing problem can be conveniently, flexibly and extremely low-costly realized. Of course, the computing resource or the storage resource of the embodiment can also be assembled on demand, and can be assembled on demand for a single device or for the entire super terminal, so as to meet the computing demand or the storage demand of the user.

[0089] Based on the above embodiment, the application further provides a control method of the all things intelligent connection operating system with built-in AI based on the above scheme. The control method of the all things intelligent connection operating system with built-in AI of the embodiment can be applied to the application environment as shown in FIG. 2. Wherein, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data required to be processed by the server 104. The data storage system can be integrated on the server 104, or can be placed on the cloud or other network servers; the control method of the all things intelligent connection operating system with built-in AI can be executed by the terminal 102 or the server 104, or can be executed by the terminal 102 and the server 104 cooperatively.

[0090] The terminal 102 can be a smartphone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, an Internet of Things device, and a portable wearable device. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc.

[0091] The server 104 can be a standalone physical server, or a service node in a blockchain system, and the service nodes in the blockchain system form a peer-to-peer network.

[0092] In addition, the server 104 can also be a server cluster composed of multiple physical servers, and can be a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms, etc. basic cloud computing services.

[0093] The terminal 102 and the server 104 can be connected through Bluetooth, USB (Universal Serial Bus), or network communication connection methods, which are not limited in the present application.

[0094] In some embodiments, as shown in FIG. 3, a control method of an AI built-in all-thing intelligent operation system is provided, which is executed by the server or the terminal in FIG. 2, or cooperatively executed by the server and the terminal in FIG. 2. Taking the example that the method is executed by the server in FIG. 2, the method includes the following steps:

[0095] In step S100, service requirement information is acquired, service scenario information is determined based on the service requirement information, and a target device matched with the service scenario information is determined based on the service scenario information.

[0096] In this embodiment, service requirement information is first acquired, and then service scenario information is determined based on the service requirement information. The service requirement information reflects the service required by the user, such as using a smart washing machine to wash clothes, etc. The service scenario information reflects the use scenario corresponding to the service required by the user, for example, the service required by the user is to use a smart washing machine to wash clothes, and the corresponding use scenario is the kitchen and bathroom use scenario. It can be seen that the service scenario information reflects the use scenario of the device. Based on this, the corresponding target device can be determined based on the service scenario information.

[0097] Specifically, the embodiment first receives an operation instruction of a user based on any one of the devices in the super terminal, and determines service demand information based on the operation instruction. Since all the devices are interconnected, and all the devices are docked with the operating system of the embodiment, any operation instruction received on any device can be received and analyzed by the operating system. The operation instruction of the embodiment can be an operation instruction issued by touch or key on the device, or a voice instruction issued by the user. When the operation instruction is received, the service demand information can be determined. If the operation instruction is an operation instruction issued by touch or key, the service demand information can be determined based on the function information corresponding to the operation instruction. When the operation instruction is a voice instruction, the voice instruction is converted into text, and the service demand information is determined based on the text information about the function carried in the voice instruction. Further, the embodiment analyzes the determined service demand information to obtain user intention information of the service demand information. Then, the service scene information is determined based on the user intention information. Since the service scene information of the embodiment is matched with the use scene of each device, for example, the use scene of the smart television is the living room scene, and the corresponding service scene information is also the living room scene. Based on this, the embodiment can quickly determine the target device corresponding to the service scene information, as shown in FIG. 4, including the following steps:

[0098] Step S101, based on the interaction description module, obtaining the historical use scene of each device;

[0099] Step S102, matching the service scene information with the historical use scene of each device to obtain a matching result, wherein the matching result reflects the matching degree between the service scene information and the historical use scene of each device;

[0100] Step S103, taking the device with the highest matching degree between the service scene information and the historical use scene in the matching result as the target device.

[0101] Specifically, the interaction description module of the embodiment is used to record the usage state of each device, the usage scenario, the usage habit of the user corresponding to each device, the hardware resource scheduling record of each device and the human-computer interaction process. Therefore, based on the interaction description process, the embodiment can obtain the historical usage scenario of each device. In actual application, the historical usage scenario of each device can be obtained from an interaction description information table, which is used to reflect the usage state of each device, the usage scenario, the usage habit of the user corresponding to each device, the hardware resource scheduling record of each device, so as to quickly call the related data of the historical usage scenario and the historical interaction process of each device. Then, the embodiment matches the service scenario information with the historical usage scenario of each device to obtain a matching result, wherein the matching result reflects the matching degree between the service scenario information and the historical usage scenario of each device. The matching degree can be the coincidence degree between the service scenario information and the historical usage scenario of each device, or the similarity between the service scenario information and the historical usage scenario of each device. Then, the device with the highest matching degree between the service scenario information and the historical usage scenario in the matching result is taken as the target device. Specifically, when the matching degree is the coincidence degree, the embodiment can take the device with the largest coincidence degree between the historical usage scenario and the service scenario information in each device as the target device. When the matching degree is the similarity, the embodiment can take the device with the largest similarity between the historical usage scenario and the service scenario information in each device as the target device. When the target device is determined, the embodiment can realize the calling of the hardware resource of the target device to meet the demand of the user.

[0102] In step S200, the historical usage scenario and the historical interaction process of the target device are obtained, and the resource scheduling prediction information of the target device is obtained based on the historical usage scenario and the historical interaction process.

[0103] Further, the embodiment first acquires the historical use scene and the historical interaction process of the target device, and then predicts the use scene or the interaction process of the target device in the future according to the historical use scene and the historical interaction process, and further obtains the resource scheduling prediction information of the target device. Specifically, when the historical use scene and the historical interaction process of the target device are acquired, the historical time information is first determined, that is, a time interval in the past is first determined, and then the interaction description information table is called based on the interaction description module, where the interaction description information table is used to reflect the use state, the use scene of each device, the use habit of the user corresponding to each device, and the hardware resource scheduling record of each device. Then, the historical use scene and the historical interaction process of the target device corresponding to the historical time information are acquired from the interaction description information table based on the historical time information. The historical use scene and the historical interaction process acquired at this time are all use scenes and all interaction processes of the target device under the time information. Finally, the embodiment can realize the prediction of the resource scheduling based on the acquired historical use scene and the historical interaction process.

[0104] Specifically, when the prediction of the resource scheduling is realized, as shown in FIG. 5, the embodiment includes the following steps:

[0105] Step S201, based on the historical use scene and the historical interaction process, determining the historical resource scheduling information of the target device in each historical use scene and the historical interaction process;

[0106] Step S202, based on the historical resource scheduling information, determining the resource scheduling preference information;

[0107] Step S203, based on the resource scheduling preference information, determining the resource scheduling prediction information.

[0108] Specifically, the embodiment first determines the historical resource scheduling information of the target device in each historical use scene and the historical interaction process based on the historical use scene and the historical interaction process, and the historical resource scheduling information reflects what hardware resource is called for the target device in each historical use scene and the historical interaction process. Then, the resource scheduling preference information is determined based on the historical resource scheduling information, and the resource scheduling preference information reflects what hardware resource is often called for the target device, and further the resource scheduling prediction information is determined based on the resource scheduling preference information.

[0109] In the embodiment, the target device can be determined according to the resource scheduling preference information, and the target hardware resource with the highest scheduling frequency or the longest scheduling time in the historical time information is the hardware resource that is called most frequently by the target device. Therefore, the target hardware resource and the target function corresponding to the target hardware resource can be used as the resource scheduling prediction information. In another implementation, the future scene information and the future interaction process information of the target device can be predicted based on the interaction description module according to the historical use scene and the historical interaction process. Specifically, the historical use scene and the historical interaction process with the highest frequency in the historical use scene and the historical interaction process are used as the future scene information and the future interaction process information. Then, the future scene information and the future interaction process information are matched with the interaction description information table to determine the hardware resource corresponding to the future scene information and the future interaction process information in the interaction description information table, that is, the target hardware resource. Finally, the target hardware resource and the target function corresponding to the target hardware resource are used as the resource scheduling prediction information.

[0110] In step S300, the target hardware resource corresponding to the resource scheduling prediction information is called based on the scheduling module.

[0111] When the resource scheduling prediction information is determined, the target hardware resource corresponding to the resource scheduling prediction information can be called to meet the use demand of the user. It can be seen that the AI of the embodiment is changed from the traditional application level to the full-stack deep integration with the operating system. The operating system is naturally built-in with AI capability, and the operating system is AI. The interaction between the person and the device is changed from one-way delivery to deep integration. The AI-enabled hardware device is integrated with the person. The operating system based on the embodiment can intelligently schedule each device in the super terminal, improve the intelligent degree of the operating system, and is beneficial to providing better service for the user. Moreover, the embodiment adds the time dimension, and the past can be played back to the various interactions and operations that have occurred, and the future can be simulated to the various interactions and operations. The prediction of the resource scheduling is facilitated, and the resource scheduling is more intelligent.

[0112] Based on the above embodiments, the application further provides a control device of an AI built-in all things intelligent operation system, as shown in FIG. 6, the control device of the embodiment comprises: a target device determination module 10, a resource scheduling prediction module 20 and a hardware resource calling module 30. Specifically, the target device determination module 10 is configured to obtain service demand information, determine service scene information based on the service demand information, and determine a target device matched with the service scene information based on the service scene information. The resource scheduling prediction module 20 is configured to obtain a historical use scene and a historical interaction process of the target device, and obtain resource scheduling prediction information of the target device based on the historical use scene and the historical interaction process. The hardware resource calling module 30 is configured to call a target hardware resource corresponding to the resource scheduling prediction information based on the scheduling module.

[0113] In an implementation manner, the target device determination module comprises:

[0114] A demand information determination unit is configured to receive an operation instruction of a user by any one of the super terminals, and determine service demand information based on the operation instruction.

[0115] An intention information determination unit is configured to analyze the service demand information to obtain user intention information of the service demand information.

[0116] A scene information determination unit is configured to determine the service scene information based on the user intention information.

[0117] In an implementation manner, the target device determination module further comprises:

[0118] A historical scene determination unit is configured to obtain historical use scenes of each device based on the interaction description module.

[0119] A scene matching unit is configured to match the service scene information with the historical use scenes of each device to obtain a matching result, wherein the matching result reflects a matching degree between the service scene information and the historical use scenes of each device.

[0120] A device determination unit is configured to take a device with the highest matching degree between the service scene information and the historical use scenes in the matching result as the target device.

[0121] In an implementation manner, the resource scheduling prediction module comprises:

[0122] An information table acquisition unit is configured to determine historical time information and call an interaction description information table based on the interaction description module, wherein the interaction description information table is configured to reflect a usage state of each device, a usage scenario, a usage habit of a user corresponding to each device, and a hardware resource scheduling record of each device.

[0123] A historical information acquisition unit is configured to acquire, from the interaction description information table, a historical usage scenario and a historical interaction process of the target device corresponding to the historical time information.

[0124] In an implementation manner, the resource scheduling prediction module further includes:

[0125] A historical scheduling information acquisition unit is configured to determine historical resource scheduling information of the target device in each historical usage scenario and historical interaction process based on the historical usage scenario and the historical interaction process.

[0126] A scheduling preference information acquisition unit is configured to determine resource scheduling preference information based on the historical resource scheduling information.

[0127] A scheduling prediction information determination unit is configured to determine the resource scheduling prediction information based on the resource scheduling preference information.

[0128] In an implementation manner, the scheduling prediction information determination unit includes:

[0129] A target hardware resource determination sub-unit is configured to determine a target hardware resource with a highest scheduling frequency or a longest scheduling time length of the target device in the historical time information according to the resource scheduling preference information.

[0130] A resource scheduling prediction determination sub-unit is configured to take the target hardware resource and a target function corresponding to the target hardware resource as the resource scheduling prediction information.

[0131] In an implementation manner, the scheduling prediction information determination unit further includes:

[0132] A future information prediction sub-unit is configured to predict future scenario information and future interaction process information of the target device according to the historical usage scenario and the historical interaction process based on the interaction description module.

[0133] An information matching sub-unit is configured to match the future scenario information and the future interaction process information with the interaction description information table to obtain a target hardware resource.

[0134] A prediction information determination sub-unit is configured to take the target hardware resource and a target function corresponding to the target hardware resource as the resource scheduling prediction information.

[0135] The working principles of the various modules in the control device of the built-in AI-based all-thing intelligent connection operating system of this embodiment are the same as those of the various steps in the above method embodiments, and will not be described here.

[0136] The various modules in the control device of the built-in AI-based all-thing intelligent connection operating system described above can be implemented wholly or partially by software, hardware, or a combination thereof. The various modules described above can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the various modules.

[0137] In some embodiments, a computer device, which can be a terminal, is provided, and an internal structure diagram of the computer device can be as shown in FIG. 7. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to perform wired or wireless communication with external terminals, and the wireless communication can be achieved through WIFI, mobile cellular network, NFC (near field communication), or other technologies. The computer program is executed by the processor to implement a control method of a built-in AI-based all-thing intelligent connection operating system. The display unit of the computer device is configured to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or can be a key, a trackball, or a touchpad arranged on the shell of the computer device, or can be an external keyboard, touchpad, or mouse, etc.

[0138] Those skilled in the art can understand that the structure shown in FIG. 7 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. Specifically, the computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0139] In some embodiments, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0140] obtaining service demand information, determining service scenario information based on the service demand information, and determining a target device matched with the service scenario information based on the service scenario information;

[0141] obtaining a historical use scenario and a historical interaction process of the target device, and obtaining resource scheduling prediction information of the target device based on the historical use scenario and the historical interaction process;

[0142] calling, by the scheduling module, a target hardware resource corresponding to the resource scheduling prediction information.

[0143] It should be noted that the user information (including but not limited to user device function information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of the related data need to comply with relevant regulations.

[0144] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0145] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0146] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. An AI built-in everything smart connected operating system, characterized in that, The all things intelligent connection operating system comprises: a scheduling module, wherein an AI algorithm is built in the scheduling module, the AI algorithm is used for refreshing and synchronizing the real-time state of hardware resources and scheduling corresponding hardware resources based on service demand information; an API interface, wherein the API interface is connected with a super terminal, the super terminal comprises a plurality of devices, and each device is arranged according to a use scene; an interaction description module, wherein the interaction description module is used for recording the use state of each device, the use scene, the use habit of a user corresponding to each device, the hardware resource scheduling record of each device and the human-computer interaction process.

2. The built-in AI things intelligent operation system of claim 1, wherein, The all things intelligent connection operating system further comprises: a time control module, wherein the time control module is connected with the interaction description module and is used for obtaining the historical use scene and the historical interaction process of each device.

3. The built-in AI things intelligent operation system of claim 2, wherein, The time control module is also connected with the scheduling module and is used for simulating the future scene and the interaction process of each device.

4. The built-in AI things intelligent operation system of claim 1, wherein, Each device is connected with each other, and the resource pool of each device is shared.

5. The built-in AI things intelligent operation system of claim 1, wherein, The interaction description module comprises an interaction description information table, wherein the interaction description information table is used for reflecting the use state of each device, the use scene, the use habit of a user corresponding to each device and the hardware resource scheduling record of each device.

6. A control method based on the built-in AI-based everything intelligent connection operating system according to any one of claims 1-5, characterized in that, The method comprises: obtaining service demand information, determining service scene information based on the service demand information, and determining a target device matched with the service scene information based on the service scene information; obtaining the historical use scene and the historical interaction process of the target device, and obtaining resource scheduling prediction information of the target device based on the historical use scene and the historical interaction process; calling a target hardware resource corresponding to the resource scheduling prediction information based on a scheduling module.

7. The control method of the built-in AI-based OS for all things according to claim 6, wherein, The obtaining of the service demand information and the determination of the service scene information based on the service demand information comprise: receiving an operation instruction of a user based on any one device in a super terminal, and determining service demand information based on the operation instruction; analyzing the service demand information to obtain user intention information of the service demand information; determining the service scene information based on the user intention information.

8. The control method of the built-in AI-based OS for all things according to claim 6, wherein, The determination of a target device matched with the service scene information based on the service scene information comprises: obtaining the historical use scene of each device based on an interaction description module; matching the service scene information with the historical use scene of each device to obtain a matching result, wherein the matching result reflects the matching degree between the service scene information and the historical use scene of each device; taking the device with the highest matching degree between the service scene information and the historical use scene in the matching result as the target device. 9.The control method of the built-in AI-based OS for intelligent connection of all things according to claim 6, wherein, The obtaining of the historical use scene and the historical interaction process of the target device comprises: determining historical time information, and calling an interaction description information table based on the interaction description module, wherein the interaction description information table is used for reflecting the use state of each device, the use scene, the use habit of a user corresponding to each device and the hardware resource scheduling record of each device; obtain, from the interaction description information table, a historical use scenario and a historical interaction process of the target device corresponding to the historical time information.

10. The control method of the built-in AI-based OS for all things according to claim 9, wherein, The resource scheduling prediction information of the target device is obtained based on the historical use scenario and the historical interaction process, including: determining historical resource scheduling information of the target device in each historical use scenario and historical interaction process based on the historical use scenario and the historical interaction process; determining resource scheduling preference information based on the historical resource scheduling information; determining the resource scheduling prediction information based on the resource scheduling preference information.

11. The control method of the built-in AI-based OS for all things according to claim 10, wherein, The resource scheduling prediction information is determined based on the resource scheduling preference information, including: determining a target hardware resource with the highest scheduling frequency or the longest scheduling time length of the target device in the historical time information according to the resource scheduling preference information; taking the target hardware resource and a target function corresponding to the target hardware resource as the resource scheduling prediction information.

12. The control method of the built-in AI-based OS for everything intelligent connection according to claim 9, wherein The resource scheduling prediction information of the target device is obtained based on the historical use scenario and the historical interaction process, including: predicting future scenario information and future interaction process information of the target device according to the historical use scenario and the historical interaction process based on the interaction description module; matching the future scenario information and the future interaction process information with the interaction description information table to obtain a target hardware resource; taking the target hardware resource and a target function corresponding to the target hardware resource as the resource scheduling prediction information.

13. An AI built-in all things smart connection operating system control device, characterized by, The device includes: a target device determination module configured to obtain service demand information, determine service scenario information based on the service demand information, and determine a target device matched with the service scenario information based on the service scenario information; a resource scheduling prediction module configured to obtain a historical use scenario and a historical interaction process of the target device, and obtain resource scheduling prediction information of the target device based on the historical use scenario and the historical interaction process; a hardware resource calling module configured to call a target hardware resource corresponding to the resource scheduling prediction information based on a scheduling module.

14. A computer device, comprising: The computer device includes a memory, a processor, and a built-in AI-based everything intelligent connection operating system control program stored in the memory and executable on the processor. When the processor executes the built-in AI-based everything intelligent connection operating system control program, the steps of the built-in AI-based everything intelligent connection operating system control method according to any one of claims 6-12 are implemented.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a built-in AI-based everything intelligent connection operating system control program. When the processor executes the built-in AI-based everything intelligent connection operating system control program, the steps of the built-in AI-based everything intelligent connection operating system control method according to any one of claims 6-12 are implemented.

Images