An AI-built Internet of Everything Intelligent Operating System and Its Control Method

Abstract

The present invention discloses an AI-built Internet of Everything intelligent operating system and its control method. The Internet of Everything intelligent operating system includes: a scheduling module, an API interface, and the interaction description module. The scheduling module is built with an AI algorithm, and the AI algorithm is used to refresh and synchronize the real-time state of hardware resources and schedule corresponding hardware resources based on service demand information. The API interface is connected to a super terminal, and the super terminal includes several devices, and each device is arranged according to the usage scenario. The interaction description module is used to record the usage status, usage scenario, usage habits corresponding to the users of each device, the hardware resource scheduling record of each device, and the human-computer interaction process. The Internet of Everything intelligent operating system of the present invention can perform intelligent scheduling on each device in the super terminal, improve the intelligence level of the operating system, and is beneficial to providing better services for users.

Description

Technical Field

[0001] The present invention relates to the field of AI intelligent technologies, and in particular, to an AI-built Internet of Everything intelligent operating system and its control method. Background Art

[0002] Existing operating systems can be divided into two categories according to the capabilities of the loading devices: one is the operating system that loads a single type, that is, this type of operating system 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 HarmonyOS, which can be loaded on various hardware devices by using the elastic deployment ability.

[0003] The design concept and implementation architecture of existing operating systems were basically determined after the birth of OS / 360 in 1964 and have not changed essentially so far, that is, supporting applications on the upper layer and scheduling hardware resources on the lower layer. The use of a computer by a user is one-way, that is, the user gives various inputs to the computer through peripherals, and the computer gives feedback results according to the user's inputs. It can be seen that the current operating systems are not intelligent enough to automatically analyze the user's needs and output the resources to be scheduled in a timely manner.

[0004] Therefore, the existing technologies still need to be improved. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an AI-built Internet of Everything intelligent operating system and its control method in view of the above-mentioned defects of the existing technologies, aiming to solve the problems that the existing operating systems are not intelligent enough to automatically analyze the user's needs and output the resources to be scheduled in a timely manner.

[0006] To solve the above technical problems, the technical solutions adopted by the present invention are as follows:

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

[0008] A scheduling module, the scheduling module is built with an AI algorithm, and the AI algorithm is used to refresh and synchronize the real-time state of hardware resources and schedule corresponding hardware resources based on service demand information;

[0009] An API interface, the API interface is connected to the super terminal, the super terminal includes a number of devices, and each device is arranged according to the usage scenario;

[0010] An interaction description module, the interaction description module is used to record the usage status, usage scenario of each device, the usage habits corresponding to the users of each device, the hardware resource scheduling records of each device, and the human-computer interaction process.

[0011] In one implementation, the Internet of Everything intelligent operating system further includes:

[0012] A time control module, which is connected to the interaction description module and is used to obtain the historical usage scenarios and historical interaction processes of each device.

[0013] In one implementation, the time control module is also connected to the scheduling module and is used to simulate the future scenarios and interaction processes of each device.

[0014] In one implementation, each device is interconnected, and the resource pools of each device are shared.

[0015] In one implementation, the interaction description module includes an interaction description information table, and the interaction description information table is used to reflect the usage status, usage scenarios of each device, the usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device.

[0016] In a second aspect, an embodiment of the present invention further provides a control method for an Internet of Everything intelligent operating system with built-in AI. Among them, the method includes:

[0017] Obtain service demand information, determine service scenario information based on the service demand information, and based on the service scenario information, determine a target device that matches the service scenario information;

[0018] Obtain the historical usage scenarios and historical interaction processes of the target device, and based on the historical usage scenarios and the historical interaction processes, obtain the resource scheduling prediction information of the target device;

[0019] Based on the scheduling module, call the target hardware resources corresponding to the resource scheduling prediction information.

[0020] In one implementation, the obtaining of the service demand information and determining the service scenario information based on the service demand information includes:

[0021] Based on any device in the super terminal to receive the user's operation instruction, and determine the service demand information based on the operation instruction;

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

[0023] Based on the user intention information, determine the service scenario information.

[0024] In one implementation, the determining of the target device that matches the service scenario information based on the service scenario information includes:

[0025] Based on the interaction description module, obtain the historical usage scenarios of each device;

[0026] Match the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the matching degree between the service scenario information and the historical usage scenarios of each device;

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

[0028] In one implementation, the obtaining of the historical usage scenario and the historical interaction process of the target device includes:

[0029] Determine the historical time information, and retrieve the interaction description information table based on the interaction description module, where the interaction description information table is used to reflect the usage status, usage scenario, usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device;

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

[0031] In one implementation, the obtaining of the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes:

[0032] Based on the historical usage scenario and the historical interaction process, determine the historical resource scheduling information of the target device in each historical usage scenario and the historical interaction process;

[0033] Based on the historical resource scheduling information, determine the resource scheduling preference information;

[0034] Based on the resource scheduling preference information, determine the resource scheduling prediction information.

[0035] In one implementation, the obtaining of the resource scheduling prediction information based on the resource scheduling preference information includes:

[0036] According to the resource scheduling preference information, determine the target hardware resource with the highest scheduling frequency or the longest scheduling duration of the target device in the historical time information;

[0037] Use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information.

[0038] In one implementation, obtaining the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes:

[0039] Based on the interaction description module, predicting the future scenario information and future interaction process information of the target device according to the historical usage scenario and the historical interaction process;

[0040] Matching the future scenario information and the future interaction process information with the interaction description information table to obtain the target hardware resources;

[0041] Taking the target hardware resources and the target functions corresponding to the target hardware resources as the resource scheduling prediction information.

[0042] In a third aspect, an embodiment of the present invention further provides a control device for an AI-built Internet of Everything intelligent operating system, where the device includes:

[0043] 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 matching the service scenario information based on the service scenario information;

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

[0045] [[ID=2l]]A hardware resource invocation module, configured to invoke the target hardware resources corresponding to the resource scheduling prediction information based on the scheduling module.

[0046] In one implementation, the target device determination module includes:

[0047] A demand information determination unit, configured to receive an operation instruction of a user based on any device in the super terminal, and determine service demand information based on the operation instruction;

[0048] An intention information determination unit, configured to parse the service demand information to obtain the user intention information of the service demand information;

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

[0050] In one implementation, the target device determination module further includes:

[0051] A historical scenario determination unit, configured to obtain the historical usage scenario of each device based on the interaction description module;

[0052] A scene matching unit, configured to match the service scene information with the historical usage scenes of each device to obtain a matching result, where the matching result reflects the matching degree between the service scene information and the historical usage scenes of each device;

[0053] A device determination unit, configured to use the device with the highest matching degree between the service scene information and the historical usage scene in the matching result as the target device.

[0054] In one implementation, the resource scheduling prediction module includes:

[0055] An information table acquisition unit, configured to determine historical time information, and retrieve an interaction description information table based on the interaction description module, where the interaction description information table is used to reflect the usage status, usage scene of each device, the usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device;

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

[0057] In one implementation, the resource scheduling prediction module further includes:

[0058] A historical scheduling information acquisition unit, configured to determine the historical resource scheduling information of the target device in each historical usage scene and the historical interaction process based on the historical usage scene 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 one implementation, the scheduling prediction information determination unit includes:

[0062] A target hardware resource determination subunit, configured to determine the target hardware resource with the highest scheduling frequency or the longest scheduling duration of the target device in the historical time information according to the resource scheduling preference information;

[0063] A resource scheduling prediction determination subunit, configured to use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information.

[0064] In one implementation, the scheduling prediction information determination unit further includes:

[0065] A future information prediction subunit, configured to predict future scenario information and future interaction process information of the target device based on the interaction description module according to the historical usage scenario and the historical interaction process;

[0066] An information matching subunit, configured to match the future scenario information, the future interaction process information with the interaction description information table to obtain target hardware resources; [[ID=,5]]

[0067] A predicted information determination subunit, configured to use the target hardware resources and the target functions corresponding to the target hardware resources as the resource scheduling prediction information.

[0068] In a fourth aspect, an embodiment of the present invention further provides a computer device, where the computer device includes a memory, a processor, and a control program of an AI-built Internet of Everything operating system stored in the memory and executable on the processor. When the processor executes the control program of the AI-built Internet of Everything operating system, the steps of the control method of the AI-built Internet of Everything operating system in any one of the above solutions are implemented.

[0069] In a fifth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a control program of an AI-built Internet of Everything operating system is stored on the computer-readable storage medium. When the control program of the AI-built Internet of Everything operating system is executed by a processor, the steps of the control method of the AI-built Internet of Everything operating system in any one of the above solutions are implemented.

[0070] Advantageous effects: Compared with the prior art, the present invention provides an AI-built Internet of Everything operating system, including: a scheduling module, an API interface, and the interaction description module. The scheduling module is built with an AI algorithm, and the AI algorithm is used to refresh and synchronize the real-time state of hardware resources and schedule corresponding hardware resources based on service demand information. The API interface is connected to a super terminal, the super terminal includes several devices, and each device is arranged according to the usage scenario. The interaction description module is used to record the usage status, usage scenario, usage habits corresponding to the users of each device, the hardware resource scheduling record of each device, and the human-computer interaction process. The Internet of Everything operating system of the present invention can intelligently schedule each device in the super terminal, improve the intelligence level of the operating system, and is beneficial to providing better services for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a schematic diagram of an intelligent control system based on a distributed super terminal provided by an embodiment of the present invention.

[0072] Figure 2It is an application environment diagram of the intelligent control method based on a distributed super terminal provided by an embodiment of the present invention.

[0073] Figure 3 It is a flowchart of a preferred embodiment of the intelligent control method based on a distributed super terminal provided by an embodiment of the present invention.

[0074] Figure 4 It is a flowchart for determining a target device in the intelligent control method based on a distributed super terminal provided by an embodiment of the present invention.

[0075] Figure 5 It is a flowchart for resource scheduling prediction in the intelligent control method based on a distributed super terminal provided by an embodiment of the present invention.

[0076] Figure 6 It is a schematic diagram of the architecture of a control device of an all-scenario intelligent connection operating system with built-in AI provided by an embodiment of the present invention.

[0077] Figure 7 It is a schematic block diagram of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0078] To make the objectives, technical solutions and effects of the present invention clearer and more definite, the following further describes the present invention in detail with reference to the accompanying drawings and by way of examples. It should be understood that the specific examples described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all contents, operations or steps, nor are they necessarily executed in the described order. For example, some operations or steps can also be decomposed, combined or partially merged, so the actual execution order may be changed according to the actual situation.

[0080] It should be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention 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 invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. For example, the first control information and the second control information are only used to distinguish different control information, and do not limit their sequence.

[0082] Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and the terms "first", "second", etc. do not necessarily limit to being different.

[0083] It should also be understood that the term "and / or" used in the specification and appended claims of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0084] Since the perception ability of the existing single-device-based agent is limited by the hardware richness and spatial position limitation of the single device and is difficult to meet the requirements, lacking a complete and accurate perception ability, the basis for the agent to play a role does not exist. Moreover, the operation of the existing agent often requires large computing power and other rich hardware resource support. Only powerful hardware can be the object for the agent to be loaded and run, with high costs and limited popularity. In addition, there are also problems such as few user touchpoints and small coverage.

[0085] Therefore, this embodiment provides an AI-built Internet of Everything operating system, as Figure 1 shown in, the Internet of Everything operating system includes: a scheduling module, an API interface, and the interaction description module. The scheduling module has an AI algorithm built in, and the AI algorithm is used to refresh and synchronize the real-time state of the hardware resources and schedule the corresponding hardware resources based on the service demand information. In this embodiment, the API interface is connected to the super terminal to realize the connection between the Internet of Everything operating system and the super terminal. The super terminal includes several devices, and each device is arranged according to the usage scenario, as Figure 1 the devices 1, 2, 3... n in. For example, in a home environment, it is divided into bedroom usage scenarios, kitchen usage scenarios, bathroom usage scenarios, and living room usage scenarios. Among them, the bedroom usage scenario includes devices such as a smart projector, a smart table lamp, and a smart air conditioner; the kitchen usage scenario includes devices such as a smart range hood, a smart refrigerator, and a smart dishwasher; the bathroom usage scenario includes devices such as a smart toilet, a smart washing machine, and a smart dryer; the living room usage scenario includes devices such as a smart TV, a smart air conditioner, smart curtains, and a floor cleaning robot. These devices are all distributed according to the usage scenario. The interaction description module of this embodiment is used to record the usage status, usage scenario, usage habits corresponding to the users of each device, the hardware resource scheduling record of each device, and the human-computer interaction process. Therefore, based on the Internet of Everything operating system of this embodiment, each device in the super terminal can be intelligently scheduled, improving the intelligence level of the operating system and being beneficial to providing better services for users.

[0086] Furthermore, the Internet of Everything Intelligent Operating System of this embodiment further includes a time control module. The time control module is connected to the interaction description module and is used to obtain the historical usage scenarios and historical interaction processes of each device. These historical usage scenarios and historical interaction processes are all recorded by the interaction description module during the use of the devices. Further, the time control module of this embodiment is also connected to the scheduling module and is used to simulate the future scenarios and interaction processes of each device. Thus, based on the time control mode of this embodiment, the usage scenarios and interaction processes of each device in the past can be played back, and the usage scenarios and interaction processes in the future can also be predicted.

[0087] In addition, the interaction description module of this embodiment can collect and summarize the usage scenario records and interaction process records scattered on each device to form an interaction description information table, and make a complete trajectory record of the past interaction records of the super terminal. The interaction description information table is used to reflect the usage status, usage scenarios of each device, the usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device, so as to quickly call the relevant data of the historical usage scenarios and historical interaction processes of each device.

[0088] Further, all the devices in this embodiment are interconnected, and the resource pools of all the devices are shared. When the intelligent agent needs to use computing power resources or storage resources, it obtains the corresponding computing power resources or storage resources from the resource pool of any device. For example, when scheduling the hardware resources of the intelligent washing machine and finding that it is unable to perform more intelligent actions, such as when there is not enough storage resources to store the recent washing records, the idle storage resources can be obtained from the intelligent dryer for the intelligent washing machine to use, thereby meeting the user's needs. Thus, this embodiment can integrate the hardware resources of each device that makes up the super terminal and conveniently, flexibly, and at extremely low cost realize the problem of hardware resource sharing. Of course, the computing power resources or storage resources of this embodiment can also be assembled on demand, which can be assembled on demand for a single device respectively, or can be assembled on demand for the entire super terminal to meet the user's computing power requirements or storage requirements.

[0089] Based on the above embodiments, the present invention also provides a control method for the Internet of Everything Intelligent Operating System with built-in AI described in the above solution. The control method of the Internet of Everything Intelligent Operating System with built-in AI of this embodiment can be applied to, for example Figure 2In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers; the control method of the Internet of Everything intelligent connection operating system with built-in AI can be executed by the terminal 102 or the server 104, or can be executed collaboratively by the terminal 102 and the server 104.

[0090] Among them, the terminal 102 can be a smart phone, 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 TV, a smart air conditioner, and a smart vehicle-mounted 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 an independent physical server, or a service node in a blockchain system. 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 that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0093] The connection between the terminal 102 and the server 104 can be made through communication connection methods such as Bluetooth, USB (Universal Serial Bus), or the network. This application does not make any restrictions here.

[0094] In some embodiments, as Figure 3 shown, a control method of the Internet of Everything intelligent connection operating system with built-in AI is provided. This method is executed by Figure 2 the server or the terminal in Figure 2 or can be executed collaboratively by the server and the terminal in Figure 2 . Taking the execution by the server in

[0095] as an example, the method includes the following steps:

[0096] In this embodiment, service demand information is first obtained, and then service scenario information is determined based on the service demand information. The service demand information reflects the services required by the user, such as using a smart washing machine to do laundry, etc. The service scenario information reflects the usage scenarios corresponding to the services required by the user. For example, if the service required by the user is to use a smart washing machine to do laundry, the corresponding usage scenario is the kitchen and bathroom usage scenario. It can be seen that the service scenario information reflects the usage scenarios of the devices. Based on this, this embodiment can determine the corresponding target device based on the service scenario information.

[0097] Specifically, in this embodiment, an operation instruction from the user is first received by any one device in the super terminal, and the service demand information is determined based on the operation instruction. Since all devices are interconnected and all devices are docked with the operating system of this embodiment, any operation instruction received on any device can be received and analyzed by the operating system. The operation instruction in this embodiment can be an operation instruction issued by touching or pressing a button 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 touching or pressing a button, 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 therein. Further, this embodiment analyzes the determined service demand information to obtain the user intention information of the service demand information. Then, based on the user intention information, the service scenario information is determined. Since the service scenario information in this embodiment is mutually matched with the usage scenarios of each device, for example, the usage scenario of a smart TV is the living room scenario, and the corresponding service scenario information is also the living room scenario. Based on this, this embodiment can quickly determine the target device corresponding to the service scenario information, specifically as Figure 4 shown below, including the following steps:

[0098] Step S101: Obtain the historical usage scenarios of each device based on the interaction description module;

[0099] Step S102: Match the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the matching degree between the service scenario information and the historical usage scenarios of each device;

[0100] Step S103: Use the device with the highest matching degree between the service scenario information and the historical usage scenario in the matching result as the target device.

[0101] Specifically, since the interaction description module of this embodiment is used to record the usage status, usage scenario, usage habits corresponding to the users of each device, the hardware resource scheduling record of each device, and the human-computer interaction process. Therefore, based on this interaction description process, this embodiment can obtain the historical usage scenarios of each device. In practical applications, the historical usage scenarios of each device can be obtained from the interaction description information table, and the interaction description information table is used to reflect the usage status, usage scenario, usage habits corresponding to the users of each device, and the hardware resource scheduling record of each device, so as to quickly call the historical usage scenarios of each device and the relevant data of the historical interaction process. Then, this embodiment matches the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the matching degree between the service scenario information and the historical usage scenarios of each device. This matching degree can be the coincidence degree between the service scenario information and the historical usage scenarios of each device, or the similarity between the service scenario information and the historical usage scenarios 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 used as the target device. Specifically, when the matching degree is the above-mentioned coincidence degree, this embodiment can use the device with the largest coincidence degree between the historical usage scenario and the service scenario information among each device as the target device. And when the matching degree is the above-mentioned similarity, this embodiment can use the device with the largest similarity between the historical usage scenario and the service scenario information among each device as the target device. After determining the target device, this embodiment can realize the retrieval of the hardware resources of the target device to meet the needs of users.

[0102] Step S200, obtain the historical usage scenario and historical interaction process of the target device, and obtain the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process.

[0103] Further, in this embodiment, the historical usage scenarios and historical interaction processes of the target device are first obtained, and then the future usage scenarios or interaction processes of the target device are predicted based on the historical usage scenarios and historical interaction processes, so as to obtain the resource scheduling prediction information of the target device. Specifically, when obtaining the historical usage scenarios and historical interaction processes of the target device in this embodiment, the historical time information is first determined, that is, a past time interval is first determined, and then the interaction description information table is retrieved based on the interaction description module. The interaction description information table is used to reflect the usage status, usage scenarios of each device, the usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device. Then, based on the historical time information, the historical usage scenarios and historical interaction processes of the target device corresponding to the historical time information are obtained from the interaction description information table. The historical usage scenarios and historical interaction processes obtained at this time are all the usage scenarios and all interaction processes of the target device under this time information. Finally, this embodiment can realize the prediction of resource scheduling based on the obtained historical usage scenarios and historical interaction processes.

[0104] Specifically, when realizing the prediction of resource scheduling in this embodiment, as Figure 5 shown below, the following steps are included:

[0105] Step S201, based on the historical usage scenarios and the historical interaction processes, determine the historical resource scheduling information of the target device in each historical usage scenario and the historical interaction processes;

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

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

[0108] Specifically, in this embodiment, based on the historical usage scenarios and the historical interaction processes, the historical resource scheduling information of the target device in each historical usage scenario and the historical interaction processes is first determined. The historical resource scheduling information reflects what hardware resources are invoked for the target device in each historical usage scenario and the historical interaction processes. Then, based on the historical resource scheduling information, the resource scheduling preference information is determined. The resource scheduling preference information reflects what hardware resources the target device is often invoked, and then the resource scheduling prediction information is determined based on the resource scheduling preference information.

[0109] In this embodiment, according to the resource scheduling preference information, the target hardware resources with the highest scheduling frequency or the longest scheduling duration in the historical time information can be determined for the target device. These target hardware resources are the most frequently invoked hardware resources for the target device. Therefore, the target hardware resources and the target functions corresponding to the target hardware resources can be used as the resource scheduling prediction information. In another implementation, this embodiment can also, based on the interaction description module, predict the future scenario information and future interaction process information of the target device according to the historical usage scenario and the historical interaction process. Specifically, in this embodiment, the historical usage scenario and historical interaction process with the largest number of occurrences in the historical usage scenario and the historical interaction process are used as the future scenario information and future interaction process information. Then, the future scenario information and the future interaction process information are matched with the interaction description information table to determine the hardware resources corresponding to the future scenario information and the future interaction process information in the interaction description information table, and the target hardware resources can be obtained. Finally, the target hardware resources and the target functions corresponding to the target hardware resources are used as the resource scheduling prediction information.

[0110] Step S300: Invoke the target hardware resources corresponding to the resource scheduling prediction information based on the scheduling module.

[0111] After determining the resource scheduling prediction information, this embodiment can invoke the target hardware resources corresponding to the resource scheduling prediction information to meet the user's usage requirements. It can be seen that this embodiment transforms AI from the traditional application level into an in-depth integration with the entire operating system stack. The operating system naturally has built-in AI capabilities to achieve the goal of the operating system being AI, and the relationship between humans and devices changes from one-way delivery to deep integration. The AI-enabled hardware device works in harmony with people and becomes one. Based on the operating system of this embodiment, intelligent scheduling can be performed on each device in the super terminal, improving the intelligence level of the operating system and facilitating the provision of better services for users. Moreover, this embodiment adds a time dimension, allowing playback of various past interactions and operations by going back, and simulation of various future interactions and operations by going forward, facilitating prediction of resource scheduling and achieving more intelligent resource scheduling.

[0112] Based on the above embodiments, the present invention also provides a control device for an AI-built-in all-scenario intelligent operating system, as Figure 6As shown in the figure, the control device of this embodiment includes: a target device determination module 10, a resource scheduling prediction module 20, and a hardware resource invocation module 30. Specifically, the target device determination module 10 is configured to obtain service demand information, determine service scenario information based on the service demand information, and determine a target device that matches the service scenario information based on the service scenario information. The resource scheduling prediction module 20 is configured to obtain the historical usage scenarios and historical interaction processes of the target device, and obtain resource scheduling prediction information of the target device based on the historical usage scenarios and the historical interaction processes. The hardware resource invocation module 30 is configured to invoke the target hardware resources corresponding to the resource scheduling prediction information based on the scheduling module.

[0113] In one implementation, the target device determination module includes:

[0114] A demand information determination unit, configured to receive an operation instruction from any device in the super terminal based on the operation instruction, and determine service demand information;

[0115] An intention information determination unit, configured to parse the service demand information to obtain user intention information of the service demand information;

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

[0117] In one implementation, the target device determination module further includes:

[0118] A historical scenario determination unit, configured to obtain the historical usage scenarios of each device based on the interaction description module;

[0119] A scenario matching unit, configured to match the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the matching degree between the service scenario information and the historical usage scenarios of each device;

[0120] A device determination unit, configured to use the device with the highest matching degree between the service scenario information and the historical usage scenario in the matching result as the target device.

[0121] In one implementation, the resource scheduling prediction module includes:

[0122] An information table acquisition unit, configured to determine historical time information, and retrieve an interaction description information table based on the interaction description module, where the interaction description information table is used to reflect the usage status, usage scenario, usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device;

[0123] 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.

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

[0125] 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;

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

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

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

[0129] A target hardware resource determination subunit, configured to determine, according to the scheduling preference information, a target hardware resource of the target device with the highest scheduling frequency or the longest scheduling duration in the historical time information;

[0130] A resource scheduling prediction determination subunit, configured to use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information.

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

[0132] A future information prediction subunit, configured to predict future scenario information and future interaction process information of the target device based on the interaction description module according to the historical usage scenario and the historical interaction process;

[0133] An information matching subunit, 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 subunit, configured to use the target hardware resource and the 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 Internet of Everything intelligent operating system in this embodiment are the same as those of the various steps in the above method embodiment, and will not be described in detail here.

[0136] Each module in the control device of the above-mentioned Internet of Everything Intelligent Operating System with built-in AI can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor in the computer device in hardware form or independent of the processor, or stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0137] In some embodiments, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as Figure 7 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, 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. Among them, the processor of the computer device is used 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 the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WI FI, a mobile cellular network, NFC (Near Field Communication), or other technologies. The computer program, when executed by the processor, implements a control method for an Internet of Everything Intelligent Operating System with built-in AI. The display unit of the computer device is used 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 covering the display screen, or a button, a trackball, or a touchpad provided on the outer shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0138] Those skilled in the art can understand that Figure 7 the structure shown in

[0139] is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0140] Obtain service demand information, determine service scenario information based on the service demand information, and determine a target device that matches the service scenario information based on the service scenario information;

[0141] Obtain the historical usage scenario and 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;

[0142] Invoke the target hardware resources corresponding to the resource scheduling prediction information based on the scheduling module.

[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 this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0144] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random-access memories (ReRAM), magnetoresistive random-access memories (MRAM), ferroelectric random-access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0145] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0146] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. An AI-built Internet of Everything intelligent operating system, characterized in that, The above-mentioned Internet of Everything Intelligent Operating System includes: A scheduling module, which is built with an AI algorithm. The AI algorithm is used to refresh and synchronize the real-time status of hardware resources and schedule corresponding hardware resources based on service demand information; An API interface, which is connected to a super terminal. The super terminal includes several devices, and each device is arranged according to the usage scenario; An interaction description module, which is used to record the usage status, usage scenario, usage habits corresponding to the users of each device, the hardware resource scheduling records of each device, and the human-computer interaction process; The Internet of Everything Intelligent Operating System further includes: A time control module, which is connected to the interaction description module and is used to obtain the historical usage scenarios and historical interaction processes of each device; The time control module is also connected to the scheduling module and is used to simulate the future scenarios and interaction processes of each device; The interaction description module includes an interaction description information table, which is used to reflect the usage status, usage scenario, usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device; The Internet of Everything Intelligent Operating System is used to achieve: Obtain service demand information, determine service scenario information based on the service demand information, and determine a target device that matches the service scenario information based on the service scenario information; Obtain the historical usage scenarios and historical interaction processes of the target device, and obtain resource scheduling prediction information of the target device based on the historical usage scenarios and the historical interaction processes; Call the target hardware resources corresponding to the resource scheduling prediction information based on the scheduling module; The obtaining of service demand information and the determination of service scenario information based on the service demand information include: Based on any device in the super terminal, receive an operation instruction from the user, and determine service demand information based on the operation instruction. Among them, the operation instruction is an operation instruction issued by touching or pressing a button on the device, or a voice instruction issued by the user. If the operation instruction is an operation instruction issued by touching or pressing a button, determine the service demand information based on the function information corresponding to the operation instruction. If the operation instruction is a voice instruction, perform text conversion on the voice instruction, and determine the service demand information based on the text information about the function carried therein; Analyze the service demand information to obtain the user intention information of the service demand information; Determine the service scenario information based on the user intention information; The determination of a target device that matches the service scenario information based on the service scenario information includes: Based on the interaction description module, obtain the historical usage scenarios of each device; Match the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the degree of matching between the service scenario information and the historical usage scenarios of each device, and the degree of matching is the degree of overlap between the service scenario information and the historical usage scenarios of each device, or the similarity between the service scenario information and the historical usage scenarios of each device; Use the device with the highest degree of matching between the service scenario information and the historical usage scenario in the matching result as the target device; The obtaining of the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes: Based on the historical usage scenario and the historical interaction process, determine the historical resource scheduling information of the target device in each historical usage scenario and the historical interaction process; Based on the historical resource scheduling information, determine the resource scheduling preference information; According to the resource scheduling preference information, determine the target hardware resource with the highest scheduling frequency or the longest scheduling duration in the historical time information for the target device; Use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information; Or, the obtaining of the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes: Based on the interaction description module, predict the future scenario information and future interaction process information of the target device according to the historical usage scenario and the historical interaction process; Match the future scenario information and the future interaction process information with the interaction description information table to obtain the target hardware resource; Use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information.

2. The AI-built Internet of Everything intelligent operating system according to claim 1, wherein Each device is interconnected, and the resource pools of each device are shared.

3. A control method for the built-in AI-powered connected everything operating system based on any one of claims 1-2, characterized in that: The method includes: Obtain service demand information, determine service scenario information based on the service demand information, and determine a target device that matches the service scenario information based on the service scenario information; Obtain the historical usage scenario and historical interaction process of the target device, and obtain the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process; Based on the scheduling module, call the target hardware resource corresponding to the resource scheduling prediction information; The obtaining of the service demand information and determining the service scenario information based on the service demand information includes: Based on any device in the super terminal, receive an operation instruction from the user, and determine the service demand information based on the operation instruction, where the operation instruction is an operation instruction issued by touching or pressing a button on the device, or a voice instruction issued by the user. If the operation instruction is an operation instruction issued by touching or pressing a button, determine the service demand information based on the function information corresponding to the operation instruction. If the operation instruction is a voice instruction, perform text conversion on the voice instruction, and determine the service demand information based on the text information about the function carried therein; Parse the service demand information to obtain the user intention information of the service demand information; Based on the user intention information, determine the service scenario information; The determining the target device matching the service scenario information based on the service scenario information includes: Based on the interaction description module, obtain the historical usage scenarios of each device; Match the service scenario information with the historical usage scenarios of each device to obtain a matching result, where the matching result reflects the matching degree between the service scenario information and the historical usage scenarios of each device, and the matching degree is the coincidence degree between the service scenario information and the historical usage scenarios of each device, or the similarity between the service scenario information and the historical usage scenarios of each device; Use the device with the highest matching degree between the service scenario information and the historical usage scenario in the matching result as the target device; The obtaining the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes: Based on the historical usage scenario and the historical interaction process, determine the historical resource scheduling information of the target device in each historical usage scenario and the historical interaction process; Based on the historical resource scheduling information, determine the resource scheduling preference information; Based on the resource scheduling preference information, determine the resource scheduling prediction information; The determining the resource scheduling prediction information based on the resource scheduling preference information includes: According to the resource scheduling preference information, determine the target hardware resource with the highest scheduling frequency or the longest scheduling duration in the historical time information for the target device; Use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information; The obtaining the resource scheduling prediction information of the target device based on the historical usage scenario and the historical interaction process includes: Based on the interaction description module, predict the future scenario information and future interaction process information of the target device according to the historical usage scenario and the historical interaction process; Match the future scenario information and the future interaction process information with the interaction description information table to obtain the target hardware resource; Use the target hardware resource and the target function corresponding to the target hardware resource as the resource scheduling prediction information.

4. The control method of the AI-powered connected operating system according to claim 3, wherein: The obtaining the historical usage scenario and historical interaction process of the target device includes: Determine the historical time information, and retrieve the interaction description information table based on the interaction description module, where the interaction description information table is used to reflect the usage status, usage scenario of each device, the usage habits corresponding to the users of each device, and the hardware resource scheduling records of each device; Obtain the historical usage scenario and historical interaction process of the target device corresponding to the historical time information from the interaction description information table.

5. A control device for an AI-built Internet of Everything intelligent operating system, characterized in that, The device is used to implement the steps of the control method of the built-in AI Internet of Everything intelligent operating system according to claim 3 or 4, and the device includes: A target device determination module, configured to obtain service requirement information, determine service scenario information based on the service requirement information, and determine a target device that matches the service scenario information based on the service scenario information; A resource scheduling prediction module, configured to obtain the historical usage scenarios and historical interaction processes of the target device, and obtain resource scheduling prediction information of the target device based on the historical usage scenarios and the historical interaction processes; A hardware resource invocation module, configured to invoke target hardware resources corresponding to the resource scheduling prediction information based on a scheduling module.

6. A computer device, characterized in that, The computer device includes a memory, a processor, and a control program of an AI-built Internet of Everything operating system stored in the memory and executable on the processor. When the processor executes the control program of the AI-built Internet of Everything operating system, the steps of the control method of the AI-built Internet of Everything operating system according to claim 3 or 4 are implemented.

7. A computer-readable storage medium, characterized in that, A control program of an AI-built Internet of Everything operating system is stored on the computer-readable storage medium. When the control program of the AI-built Internet of Everything operating system is executed by a processor, the steps of the control method of the AI-built Internet of Everything operating system according to claim 3 or 4 are implemented.

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