CN113671844A - Intelligent device control method and device, intelligent control device and storage medium - Google Patents
Intelligent device control method and device, intelligent control device and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides an intelligent device control method, an intelligent device control device, an intelligent control device and a storage medium, wherein the intelligent device control method is applied to the intelligent control device and comprises the steps of establishing local area network communication with other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task. The intelligent device control method provided by the embodiment of the application can control all intelligent devices in the contextual model in time when the contextual model is triggered.
Description
Technical Field
The application relates to the technical field of smart home, in particular to a method and a device for controlling smart equipment, the smart control equipment and a storage medium.
Background
With the continuous development of science and technology and the continuous improvement of the living standard of people, modern people are not more and more satisfied with the current living situation, and instead, the urgent pursuit of more comfortable high-grade living environment is adopted, so that smart homes (home automation) also come with the urgent pursuit, so-called smart homes take homes as platforms, facilities related to home life are integrated by utilizing a comprehensive wiring technology, a network communication technology, a safety precaution technology, an automatic control technology and an audio and video technology, a high-efficiency management system of home facilities and home schedule affairs is constructed, the home safety, convenience, comfortableness and artistry are improved, and the environment-friendly and energy-saving living environment is realized.
The intelligent home scene mode is a home mode which is made by means of intelligent home equipment, is adjustable, has strong flexibility and supports multiple application scenes and is a combination of a series of home functions in order to fully meet various requirements in life. In the existing smart home system, if too many smart home devices are bound to a contextual model, when the contextual model is triggered, some smart home devices may fail to be controlled due to the problem that the processing performance of a single smart control device is limited.
Disclosure of Invention
In view of the above problems, embodiments of the present application provide an intelligent device control method, apparatus, intelligent control device, and storage medium to solve the above technical problems.
The embodiment of the application is realized by adopting the following technical scheme:
in a first aspect, some embodiments of the present application provide an intelligent device control method, which is applied to an intelligent control device, and includes establishing local area network communication with other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task.
In a second aspect, an intelligent device control apparatus according to some embodiments of the present application is applied to an intelligent control device, and the apparatus includes a communication establishing module, a context determining module, a task obtaining module, and an assisting module; the communication establishing module is used for establishing local area network communication with other intelligent control equipment; the scene determining module is used for determining a target scene mode according to the scene triggering instruction; the task obtaining module is used for obtaining the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; the assistance module is configured to send an assistance control instruction to at least one other intelligent control device in the local area network if the number of tasks is greater than or equal to a preset number, where the assistance control instruction is used to instruct the at least one other intelligent control device to assist in processing the at least one task.
In a third aspect, an embodiment of the present application further provides an intelligent control device, which includes a processor and a memory, where the memory stores computer program instructions, and the computer program instructions, when called by the processor, execute the intelligent device control method.
In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which a program code is stored, where the above-mentioned intelligent device control method is executed when the program code is executed by a processor.
According to the intelligent device control method, the intelligent device control device, the intelligent control device and the storage medium, local area network communication is established between the intelligent device control method and other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task, so that when the contextual model is triggered, the intelligent control device can timely control all the intelligent devices in the contextual model.
These and other aspects of the present application will be more readily apparent from the following description of the embodiments.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a schematic diagram of an intelligent home system provided by an embodiment of the present application.
Fig. 2 shows a flowchart of an intelligent device control method provided in an embodiment of the present application.
Fig. 3 shows a flowchart of another intelligent device control method provided in an embodiment of the present application.
Fig. 4 shows a schematic flowchart of steps S281 to S284 provided in an embodiment of the present application.
Fig. 5 shows a schematic flowchart of steps S285 to S86 provided in an embodiment of the present application.
Fig. 6 shows a block diagram of a smart device control apparatus according to an embodiment of the present application.
Fig. 7 shows a block diagram of modules of an intelligent control device according to an embodiment of the present application.
FIG. 8 illustrates a block diagram of a computer storage medium provided by an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
With the continuous development of science and technology and the continuous improvement of the living standard of people, modern people are not more and more satisfied with the current living situation, and instead, the urgent pursuit of more comfortable high-grade living environment is adopted, so that smart homes (home automation) also come with the urgent pursuit, so-called smart homes take homes as platforms, facilities related to home life are integrated by utilizing a comprehensive wiring technology, a network communication technology, a safety precaution technology, an automatic control technology and an audio and video technology, a high-efficiency management system of home facilities and home schedule affairs is constructed, the home safety, convenience, comfortableness and artistry are improved, and the environment-friendly and energy-saving living environment is realized.
The intelligent home scene mode is a home mode which is made by means of intelligent home equipment, is adjustable, has strong flexibility and supports multiple application scenes and is a combination of a series of home functions in order to fully meet various requirements in life. In the existing smart home system, if too many smart home devices are bound to a contextual model, part of the smart home devices may fail to be controlled when the contextual model is triggered.
The inventor provides an intelligent device control method, an intelligent device control device, intelligent control equipment and a storage medium through long-term research, wherein the intelligent device control method establishes local area network communication with other intelligent control equipment; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task, so that when the contextual model is triggered, the intelligent control device can timely control all the intelligent devices in the contextual model.
As shown in fig. 1, fig. 1 is an intelligent home system 10 provided in an embodiment of the present application, where the intelligent home system 10 includes a mobile terminal 11, a server 12, a plurality of intelligent control devices 13, and a plurality of intelligent devices 14. The mobile terminal 11 may be any device having communication and storage functions, for example, a smart phone, a desktop computer, a notebook computer, a tablet computer, or other smart communication devices having a network connection function, and a client (which may be an application client, such as a mobile phone APP; or a web page client) for managing the sub-devices and a user account that can be logged in at the client are stored in the mobile terminal 11. The server 12 may be a network access server, a database server, a cloud server, or the like. The mobile terminal 11 and the server 12 may be connected via a network.
The smart control device 13 may be a smart home control panel. In the smart home system 10, the smart control device 13 may include a plurality of smart control devices 13, and the plurality of smart control devices 13 may control and manage the smart device 14. Further, the smart control device 13 may be built based on, but not limited to, at least one of bluetooth, ZigBee (ZigBee) and Wi-Fi protocols. The plurality of smart devices 14 may establish network connections with the smart control device 13 based on a bluetooth protocol or a ZigBee protocol or a Wi-Fi protocol.
As shown in fig. 2, fig. 2 shows an intelligent device control method 100 provided in the embodiment of the present application, where the intelligent device control method 100 may be applied to the intelligent home system 10, and specifically, may be applied to the intelligent control device 13. In this embodiment, the intelligent device control method 100 may include the following steps S110 to S140.
Step S110: and establishing local area network communication with other intelligent control equipment.
In this embodiment, the current intelligent control device may establish local area network communication with other intelligent control devices in the intelligent home system. After the local area network is established, communication between the intelligent control devices joined in the local area network may not pass through the server.
Specifically, in each intelligent control device, a network node may be built in, and the intelligent control device may join in a local area network environment of other intelligent control devices through the network node. For example, the intelligent control device B and the intelligent control device C may join the local area network environment of the intelligent control device a through their built-in network nodes.
In this embodiment, the current intelligent control device may enable other intelligent control devices to join in the local area network environment of the current intelligent control device. The LAN network environment may be, but is not limited to, a Bluetooth network environment, a ZigBee network environment, a Wi-Fi network environment. It is worth mentioning that a plurality of intelligent control devices in the same lan network environment can be considered to be associated with each other.
Step S120: and determining a target contextual model according to the contextual trigger instruction.
The context trigger instruction may be issued by a user. As one mode, the context trigger instruction may be an operation instruction issued by a user, that is, the intelligent control device may determine the target context mode through the operation instruction. The user may directly select the target contextual model through an operation interface, which may be an operation interface of the mobile terminal or an operation interface of the intelligent control device, and is not limited.
As another mode, the context trigger instruction may be a voice instruction issued by the user, that is, the intelligent control device may determine the target context mode through a voice command. Specifically, it may be identified whether the voice information of the user contains specific information, and if so, a target contextual model associated with the specific information may be determined, where each contextual model may be associated with a plurality of specific information. For example, in the voice message "turn on sleep mode" of the user, the specific information "sleep mode" is recognized, and it may be determined that the target contextual model that needs to be started currently is "sleep mode"; for another example, in the voice information "i want to rest" of the user, it is also determined that the target profile that needs to be started at present is the "sleep mode" by recognizing the specific information "rest".
In some embodiments, the context trigger instruction may not be issued by the user, but is automatically triggered, that is, the intelligent control device may automatically determine the target context mode according to the specific context information. Specifically, a target contextual model corresponding to a certain piece of specific context information that needs to be started at this time may be automatically determined triggered by the certain piece of specific context information, where the specific context information includes, but is not limited to, a contextual model, a time, and an action of the smart device. For example, when the time reaches 22.00, it is automatically determined that the target profile that needs to be started currently is the "sleep mode"; or when the door lock is closed, automatically determining that the current target contextual model needing to be started is the 'away mode'; or when the 'away-from-home mode' is triggered, automatically determining that the current target contextual model needing to be started is the 'security mode'.
In this embodiment, the current intelligent control device may determine the corresponding target contextual model according to the contextual trigger instruction.
Step S130: and acquiring the number of tasks corresponding to the target contextual model.
Specifically, in the context mode, one or more intelligent devices need to be controlled to be in a predetermined state, and therefore, the intelligent control device may divide the control of the context mode on the one or more intelligent devices into one or more tasks, and each task may correspondingly control at least one intelligent device.
As one way, one task may correspond to controlling one smart device. For example, in the scenario mode a, if the smart device 1, the smart device 2, and the smart device 3 need to be controlled to be in a predetermined state, the control of the smart device by the scenario mode a may be divided into 3 tasks, where the task 1 controls the smart device 1 correspondingly, the task 2 controls the smart device 2 correspondingly, and the task 3 controls the smart device 3 correspondingly.
Alternatively, one task may control a plurality of intelligent devices correspondingly. For example, in the scenario mode B, the smart device 1, the smart device 2, and the scenario mode C need to be controlled to be in a predetermined state, the smart control device may also divide the control of the scenario mode B on the smart device into 3 tasks, where the task 1 controls the smart device 1, the task 2 controls the smart device 2, and the task 3 controls the scenario mode C, where in the scenario mode C, the smart device 4 and the smart device 5 need to be controlled to be in a predetermined state, that is, the task 3 controls the smart device 4 and the smart device 5.
In this embodiment, after the target contextual model is determined, the current intelligent control device may directly obtain the number of tasks corresponding to the target contextual model.
Step S140: and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network.
The preset number of tasks may be a critical value that can be smoothly and timely processed by the current intelligent control device, and if the number of tasks corresponding to the target contextual model is greater than or equal to the preset number, when the current intelligent control device starts the target contextual model, a situation that all the intelligent devices in the target contextual model cannot be timely controlled may occur.
In this embodiment, if the number of tasks corresponding to the target contextual model determined by the current intelligent control device is greater than or equal to the preset number, the current intelligent control device may send an assistance control instruction to at least one other intelligent control device added to the local area network of the current intelligent control device, where the assistance control instruction is used to instruct the at least one other intelligent control device to assist in processing the at least one task.
In other words, when it is determined that the number of tasks corresponding to the target contextual model is greater than or equal to the preset number, the current intelligent control device may request all or part of other intelligent control devices associated with the current intelligent control device in the local area network to request assistance, so that all or part of other intelligent control devices in the local area network assist the current intelligent control device in processing the tasks in the target contextual model, and thus all intelligent devices required to be controlled in the target contextual model can be smoothly and timely controlled when the target contextual model is triggered.
It should be noted that, as one mode, the preset number may be a fixed value set in advance; as another mode, the preset number may also be determined according to the current processing capability of the current intelligent control device, that is, the preset number may be variable, for example, if the current network condition of the current intelligent control device is good, it indicates that the current processing capability of the current intelligent control device is strong, and at this time, the preset number may be increased correspondingly; if the current network condition of the current intelligent control equipment is poor, the current processing capability of the current intelligent control equipment is weak, and at the moment, the preset number can be correspondingly reduced.
The intelligent device control method provided by the embodiment of the application establishes local area network communication with other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task, so that when the contextual model is triggered, the intelligent control device can timely control all the intelligent devices in the contextual model.
As shown in fig. 3, an embodiment of the present application further provides an intelligent device control method 200. The smart device control method 200 may also be applied to the smart home system 10, and in particular, to the smart control device 13. In this embodiment, the intelligent device control method 200 may include the following steps S210 to S280.
Step S210: and establishing local area network communication with other intelligent control equipment.
In this embodiment, the step S210 may refer to the step S110, which is not described herein.
Step S220: and determining a target contextual model according to the contextual trigger instruction.
In this embodiment, the step S220 may refer to the step S120, which is not described herein.
Step S230: and acquiring the number of tasks corresponding to the target contextual model.
In this embodiment, the step S220 may refer to the step S130, which is not described herein.
Step S240: and if the number of the tasks is greater than or equal to the preset number, generating a task set to be assisted by the tasks exceeding the preset number and sending an assistance request to other intelligent control equipment in the local area network.
In this embodiment, if the number of tasks in the target contextual model is greater than or equal to the preset number, the current intelligent control device may generate a set of tasks to be assisted from other tasks exceeding the preset number in the tasks in the target contextual model, where the set of tasks to be assisted is a set of tasks that need to be assisted by other intelligent control devices in the tasks in the target contextual model. For example, assuming that the preset number is 2, if the tasks of the target contextual model include task 1, task 2, task 3, task 4, and task 5, the current intelligent control device may generate a set of tasks to be assisted from task 3, task 4, and task 5, where the set of tasks to be assisted is a set of task 3, task 4, and task 5.
In some embodiments, the current intelligent control device may further generate a set of tasks to be assisted according to the maximum bearer control amount and a preset number of the current intelligent control device, and the preset number may be determined according to the current maximum bearer control amount of the current intelligent control device and the number of the intelligent devices controlled by the tasks of the target contextual model. It should be noted that the maximum bearer control amount may be determined in real time according to the current network condition of the current intelligent control device.
For example, suppose that the maximum bearer control amount of the current intelligent control device is to control 2 intelligent devices, the tasks of the scenario mode a include task 1, task 2, task 3, and task 4, and task 1 correspondingly controls one intelligent device, task 2 correspondingly controls one intelligent device, task 3 correspondingly controls one intelligent device, and task 4 correspondingly controls one intelligent device, so that the current intelligent control device can process task 1 and task 2 at the maximum, that is, the preset number can be 2 tasks, and at this time, the current intelligent control device can generate a task set to be assisted by task 3 and task 4.
For another example, assume that the maximum bearer control amount of the current intelligent control device is to control 2 intelligent devices, the task of the scenario B includes task 1, task 2, task 3, and task 4, and task 1 controls 2 intelligent devices correspondingly, task 2 controls 1 intelligent device correspondingly, task 3 controls one intelligent device correspondingly, and task 4 controls one intelligent device correspondingly, so that the current intelligent control device can process task 1 at maximum, that is, the preset number can be 1 task, and at this time, the current intelligent control device can generate a task set to be assisted with task 2, task 3, and task 4.
In some embodiments, if the number of tasks of the target contextual model in the preset time period is greater than the preset number, the current intelligent control device may generate a task set to be assisted by the tasks exceeding the preset number.
In this embodiment, if the number of tasks of the target contextual model is greater than or equal to the preset number, the current intelligent control device may also send an assistance request to other intelligent control devices in the local area network of the current intelligent control device. Wherein the request for assistance is used to query the current status of the other intelligent control devices. Specifically, the current intelligent control device may broadcast a request for assistance to all other intelligent control devices within the local area network.
Further, the current state of the intelligent control device includes an idle state and a busy state. The idle state may be used to indicate that the current work task of the intelligent control device is smaller than the preset work task, and the busy state may be used to indicate that the current work task of the intelligent control device is greater than or equal to the preset work task.
Step S250: and receiving the assistance response sent by other intelligent control equipment.
In this embodiment, after the current intelligent control device sends the assistance request to other intelligent control devices in the local area network, the other intelligent control devices may send the assistance response to the current intelligent control device according to the current state of the other intelligent control devices.
Step S260: and determining the current state of the corresponding other intelligent control equipment according to the assistance response.
In this embodiment, the assistance response sent by the other intelligent control device may indicate the current state of the other intelligent control device to the current intelligent control device, and thus the current intelligent control device may determine the current state of the corresponding other intelligent control device according to the assistance response.
In a specific implementation scenario, the current intelligent control device may broadcast an assistance request to all other intelligent control devices a, B, and C in the lan to inquire about the current state of the intelligent control device a, B, and C, and if the current state of the intelligent control device a is in an idle state, may send an assistance response to the current intelligent control device to indicate to the current intelligent control device that the current state of the intelligent control device a is in an idle state; if the current state of the intelligent control device B is the idle state, an assistance response can be sent to the current intelligent control device to indicate that the current state of the intelligent control device B is the idle state to the current intelligent control device; if the current state of the intelligent control device C is the busy state, an assistance response may be sent to the current intelligent control device to indicate to the current intelligent control device that the current state of the intelligent control device C is the busy state. Therefore, the current intelligent control device can respectively determine that the current state of the intelligent control device A is an idle state, determine that the current state of the intelligent control device B is an idle state and determine that the current state of the intelligent control device C is a busy state according to the assistance responses sent by the intelligent control device A, the intelligent control device B and the intelligent control device C respectively.
Step S270: and determining the intelligent control equipment in an idle state in other intelligent control equipment as target intelligent control equipment.
In this embodiment, the idle state indicates that the intelligent control device has redundant processing capacity to process additional work. Therefore, the current intelligent control device may determine an intelligent control device in an idle state among other intelligent control devices as a target intelligent control device, and the target intelligent control device may serve as a target for assisting a task in which the current intelligent control device is in the target contextual model.
Step S280: and sending an assistance task instruction to the target intelligent control equipment.
The assistance control instruction is used for instructing the target intelligent control device to assist the current intelligent control device in processing at least one task in the task set to be assisted of the target contextual model.
As shown in fig. 4, in some embodiments, step S280 may be implemented by the following steps S281 to S284.
Step S281: and acquiring the equipment information of the target intelligent control equipment.
In this embodiment, the current intelligent control device may obtain device information of the target intelligent control device.
As one mode, the current intelligent control device may obtain device information of the target intelligent control device through local area network communication or wide area network communication.
As another mode, when the current state of other intelligent control devices in the local area network is the idle state, the assistance response sent by the intelligent control device may indicate that the current state of the intelligent control device is the idle state to the current intelligent control device, and may also carry device information of the intelligent control device. When the current intelligent control device determines the intelligent control device in the idle state as the target intelligent control device, the current intelligent control device can directly acquire the device information of the target intelligent control device through the assistance response previously sent by the target intelligent control device. Thereby, the data transmission time of the device information can be saved.
Further, the device information may include load information of the target intelligent control device, wherein the load information may include, but is not limited to, a device identification, a device address, and a current device control number of the target intelligent control device.
Further, the current intelligent control device may determine the first task allocation information of each target intelligent control device according to the device information. Specifically, the first task allocation information of each target intelligent control device may be determined through steps S282 to S283.
Step S282: and acquiring a task set to be assisted.
In this embodiment, the current intelligent control device may directly obtain the generated task set to be assisted of the target contextual model.
Step S283: and generating first task allocation information corresponding to each target intelligent control device according to the task set to be assisted and the load information.
In this embodiment, the current intelligent control device may generate first task allocation information corresponding to each target intelligent control device according to the set of tasks to be assisted of the target contextual model and the load information of the target intelligent control device.
As one way, the current intelligent control device may evenly distribute the tasks in the task set to be assisted to each target intelligent control device according to the number of the target intelligent control devices. For example, the target intelligent control device includes an intelligent control device a, an intelligent control device B, and an intelligent control device C, and the task to be assisted collectively includes a task 1, a task 2, and a task 3, then the current intelligent control device may allocate the task 1 to the intelligent control device a, the task 2 to the intelligent control device B, and the task 3 to the intelligent control device C.
As another way, the current intelligent control device may averagely distribute the control of the intelligent devices to each target intelligent control device according to the number of target intelligent control devices and the total control amount of the intelligent devices in the task set to be assisted. For example, the target intelligent control device includes an intelligent control device a and an intelligent control device B, the task to be assisted includes a task 1, a task 2, and a task 3, where the task 1 controls 1 intelligent device correspondingly, the task 2 controls 1 intelligent device correspondingly, and the task 3 controls 2 intelligent devices correspondingly, and then the current intelligent control device may allocate the task 1 and the task 2 to the intelligent control device a, and allocate the task 3 to the intelligent control device.
As another way, the current intelligent control device may determine an idle level of each target intelligent control device according to the load information of the target intelligent control device, and allocate the task in the task set to be assisted to the target intelligent control device according to the idle level and the total control amount of the intelligent devices in the task set to be assisted. For example, the target intelligent control device includes an intelligent control device a, an intelligent control device B, and an intelligent control device C, where the size relationship of the load information of the intelligent control device a, the intelligent control device B, and the intelligent control device C is that the intelligent control device a is smaller than the intelligent control device B and smaller than the intelligent control device C, and at this time, it may be determined that the size relationship of the idle levels of the intelligent control device a, the intelligent control device B, and the intelligent control device C is that the intelligent control device a is larger than the intelligent control device B and larger than the intelligent control device C. The task set to be assisted comprises a task 1, a task 2, a task 3, a task 4 and a task 5, wherein the task 1 correspondingly controls 3 intelligent devices, the task 2 correspondingly controls 1 intelligent device, the task 3 correspondingly controls 1 intelligent device, and the task 4 correspondingly controls 1 intelligent device, so that the current intelligent control device can allocate the task 1 to the intelligent control device A, allocate the task 2 and the task 3 to the intelligent control device B, and allocate the task 4 to the intelligent control device C.
As another way, the current intelligent control device may determine the maximum idle control amount of each target intelligent control device according to the load information of the target intelligent control device, and allocate the task in the task set to be assisted to the target intelligent control device according to the maximum idle control amount of the target intelligent control device and the total control amount of the intelligent devices in the task set to be assisted, where the number of intelligent devices correspondingly controlled by the total task allocated by each target intelligent control device is less than or equal to the maximum idle control amount of the target intelligent control device. For example, the target intelligent control device includes an intelligent control device a, an intelligent control device B, and an intelligent control device C, wherein it is determined according to the load information that the maximum idle control amounts of the intelligent control device a, the intelligent control device B, and the intelligent control device C are all 2 intelligent devices. The task set to be assisted comprises a task 1, a task 2 and a task 3, wherein the task 1 correspondingly controls 1 intelligent device, the task 2 correspondingly controls 1 intelligent device, and the task 3 correspondingly controls 1 intelligent device, so that the current intelligent control device can allocate the task 1 to the intelligent control device A, allocate the task 2 to the intelligent control device B, and allocate the task 3 to the intelligent control device C.
Step S284: and respectively sending an assistance control instruction carrying the first task allocation information to each target intelligent control device.
In this embodiment, after determining the first task allocation information of each target intelligent control device, the current intelligent control device may send an assistance control instruction carrying the first task allocation information to each target intelligent control device, where the assistance control instruction may instruct the target intelligent control device to perform control of a predetermined state on the corresponding intelligent device according to the first task allocation information.
For example, the current intelligent control device allocates the task 1 to the intelligent control device a, where the task 1 controls the intelligent device and the intelligent device 2 correspondingly, the current intelligent control device sends an assistance control instruction carrying first task allocation information corresponding to the intelligent control device a, and after receiving the assistance control instruction, the intelligent control device a can control the intelligent device 1 and the intelligent device 2 to be in a predetermined state according to the first task allocation information.
In this embodiment, the current intelligent control device actively allocates task information of each target intelligent control device, and can accurately perform control on allocation of tasks, so as to improve accuracy of assisting control of the target intelligent control device on the target contextual model, thereby timely and accurately controlling all intelligent devices in the target contextual model.
As shown in fig. 5, in some embodiments, step S280 may be implemented by the following steps S285 to S286.
Step S285: and acquiring a task set to be assisted and generating an assistance control instruction carrying the task set to be assisted.
In this embodiment, the current intelligent control device may directly obtain the to-be-assisted task set of the generated target contextual model, and generate an assistance control instruction carrying the to-be-assisted task set.
Step S286: and sending an assistance control instruction carrying the set of tasks to be assisted to at least one target intelligent control device.
In this embodiment, the current intelligent control device may send the assistance control instruction carrying the task set to be assisted to at least one target intelligent control device, where the assistance control instruction is used to instruct the at least one target intelligent control device to determine second task allocation information corresponding to each target intelligent control device according to the task set to be assisted, and assist in processing at least one task according to the second task allocation information.
In this embodiment, after receiving the assistance control instruction, the target intelligent control device may automatically allocate the task corresponding to each target intelligent control device according to the number of tasks in the set of tasks to be assisted and the number of target intelligent control devices.
As another mode, when the number of the intelligent devices to be controlled in each task is the same, the target intelligent control device may perform allocation according to the total number of tasks in the task set to be assisted, and averagely allocate the tasks in the task set to be assisted to each target intelligent control device.
As another mode, when the number of intelligent devices to be controlled in each task is different, the target intelligent control device may only allocate the tasks in the task set to be assisted according to the total number of the tasks in the task set to be assisted, and averagely allocate the tasks in the task set to be assisted to each target intelligent control device.
As another way, when the number of the intelligent devices to be controlled in each task is different, the target intelligent control device may perform allocation according to the number of the target intelligent control devices and the total control amount of the intelligent devices to be controlled in the task set to be assisted, and averagely allocate the total control amount of the intelligent devices to be controlled in the task set to be assisted to each target intelligent control device.
As another way, the target intelligent control device may determine an idle level of each target intelligent control device according to the respective load information of the target intelligent control device, and allocate the task in the task set to be assisted to each target intelligent control device according to the idle level and the total control amount of the intelligent devices in the task set to be assisted.
As another way, the target intelligent control device may determine the maximum idle control amount corresponding to each target intelligent control device according to the load information corresponding to the target intelligent control device, and allocate the task amount to be performed in the task set to be assisted according to the maximum idle control amount and the total control amount of the intelligent devices in the task set to be assisted. And the number of intelligent devices correspondingly controlled by the total task distributed by each target intelligent control device is less than or equal to the maximum idle control quantity of the target intelligent control device.
Furthermore, after each target intelligent control device obtains the respective second task allocation information, the corresponding intelligent device can be controlled in the preset state according to the second task allocation information.
In this embodiment, the current intelligent control device sends an assistance control instruction carrying a set of tasks to be assisted to each target intelligent control device, so that the target intelligent control devices determine respective second task allocation information and control the corresponding intelligent devices, thereby saving processing resources of the current intelligent control device and greatly reducing response time of the current intelligent control device, and not being able to control all intelligent devices in the target contextual model in time.
The intelligent device control method provided by the embodiment of the application establishes local area network communication with other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task, so that when the contextual model is triggered, the intelligent control device can timely control all the intelligent devices in the contextual model.
As shown in fig. 6, fig. 6 shows a block diagram of an intelligent device control apparatus 300 according to an embodiment of the present application. The smart device control apparatus 300 may include a communication establishing module 310, a context determining module 320, a task obtaining module 330, and a transmitting module 340. The communication establishing module 310 is configured to establish local area network communication with other intelligent control devices; the context determination module 320 is configured to establish local area network communication with other intelligent control devices; the task obtaining module 330 is configured to obtain a number of tasks corresponding to the target contextual model; the sending module 340 is configured to send an assistance control instruction to at least one other intelligent control device in the local area network if the number of tasks is greater than or equal to the preset number.
In some embodiments, the transmitting module 340 may include a first generating unit 341, an acknowledgement receiving unit 342, a status determining unit 343, a target determining unit 344, and a transmitting unit 345. The first generating unit 341 is configured to, if the number of tasks is greater than or equal to the preset number, generate a set of tasks to be assisted for the tasks exceeding the preset number, and send an assistance request to other intelligent control devices in the local area network; the response receiving unit 342 is configured to receive an assistance response sent by another intelligent control device; the state determining unit 343 is configured to determine, according to the assistance response, a current state of the corresponding other intelligent control device; the target determination unit 344 is configured to determine an intelligent control device in an idle state from among other intelligent control devices as a target intelligent control device; the sending unit 345 is configured to send an instruction of the assistance task to the target intelligent control device.
In some embodiments, the sending unit 345 may include an information obtaining unit 3451, a task set obtaining unit 3452, a task allocating unit 3453, a first sending unit 3454, a second generating unit 3455, and a second sending unit 3456. The information acquiring unit 3451 is configured to acquire device information of a target intelligent control device; the task set obtaining unit 3452 is configured to obtain a task set to be assisted; the task allocation unit 3453 is configured to generate first task allocation information corresponding to each target intelligent control device according to the set of tasks to be assisted and the load information; the first sending unit 3454 is configured to send an assistance control instruction carrying the first task allocation information to each target intelligent control device; the second generating unit 3455 is configured to obtain a task set to be assisted and generate an assistance control instruction carrying the task set to be assisted; the second sending unit 3456 is configured to send an assistance control instruction carrying a set of tasks to be assisted to at least one target intelligent control device.
The intelligent device control device provided by the embodiment of the application establishes local area network communication with other intelligent control devices; determining a target contextual model according to the contextual trigger instruction; acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and if the number of the tasks is larger than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task, so that when the contextual model is triggered, the intelligent control device can timely control all the intelligent devices in the contextual model.
As shown in fig. 7, fig. 7 illustrates a block diagram of an intelligent control device 400 provided in an embodiment of the present application, where the intelligent control device 400 includes a processor 410 and a memory 420, and the memory 420 stores program instructions, and the program instructions, when executed by the processor 410, implement the above-mentioned multimedia intelligent playing method.
The Memory 420 may include a Random Access Memory (RAM) 420 or a Read-Only Memory (Read-Only Memory) 420. The memory 420 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 420 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The storage data area can also store data (such as a phone book, audio and video data, chatting record data) created by the electronic device map in use and the like.
As shown in fig. 8, an embodiment of the present application further provides a computer-readable storage medium 500, in which computer program instructions 510 are stored in the computer-readable storage medium 500, and the computer program instructions 510 can be called by a processor to execute the method described in the above embodiment.
The computer-readable storage medium may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium includes a non-volatile computer-readable storage medium. The computer-readable storage medium 600 has storage space for program code for performing any of the method steps described above. The program code can be read from or written to one or more computer program products. The program code may be compressed, for example, in a suitable form.
Although the present application has been described with reference to the preferred embodiments, it is to be understood that the present application is not limited to the disclosed embodiments, but rather, the present application is intended to cover various modifications, equivalents and alternatives falling within the spirit and scope of the present application.
Claims (9)
1. An intelligent device control method is applied to an intelligent control device, and comprises the following steps:
establishing local area network communication with other intelligent control equipment;
determining a target contextual model according to the contextual trigger instruction;
acquiring the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and
and if the number of the tasks is greater than or equal to the preset number, sending an assistance control instruction to at least one other intelligent control device in the local area network, wherein the assistance control instruction is used for instructing the at least one other intelligent control device to assist in processing the at least one task.
2. The intelligent device control method according to claim 1, wherein if the number of tasks is greater than or equal to a preset number, sending an assistance control instruction to at least one other intelligent control device in a local area network includes:
if the number of the tasks is larger than or equal to the preset number, generating a task set to be assisted by the tasks exceeding the preset number, and sending an assistance request to other intelligent control equipment in the local area network;
determining target intelligent control equipment in other intelligent control equipment according to an assistance response, wherein the assistance response is sent by other intelligent control equipment according to the assistance request; and
and sending the assistance control instruction to the target intelligent control device, wherein the assistance control instruction is used for instructing the target intelligent control device to assist in processing at least one task in the task set to be assisted.
3. The intelligent device control method according to claim 2, wherein the assistance request is used to query current states of other intelligent control devices, the current states including an idle state and a busy state; the determining of the target intelligent control device among the other intelligent control devices according to the assistance response includes:
receiving the assistance response sent by other intelligent control equipment;
determining the current state of the corresponding other intelligent control equipment according to the assistance response; and
and determining the intelligent control equipment in the idle state in the other intelligent control equipment as the target intelligent control equipment.
4. The intelligent device control method according to claim 2, wherein the sending of the assist control instruction to the target intelligent control device comprises:
acquiring equipment information of the target intelligent control equipment;
determining first task allocation information of each target intelligent control device according to the device information;
and respectively sending the assistance control instruction carrying the first task allocation information to each target intelligent control device.
5. The intelligent device control method of claim 4, wherein the device information includes load information of the target intelligent control devices, and the determining the first task allocation information of each of the target intelligent control devices according to the device information includes:
acquiring the task set to be assisted; and
and generating first task allocation information corresponding to each target intelligent control device according to the task set to be assisted and the load information.
6. The intelligent device control method according to claim 2, wherein the sending of the assist control instruction to the target intelligent control device comprises:
acquiring the task set to be assisted and generating the assistance control instruction carrying the task set to be assisted; and
and sending the assistance control instruction carrying the task set to be assisted to at least one target intelligent control device, wherein the assistance control instruction is used for instructing the at least one target intelligent control device to determine second task allocation information corresponding to each target intelligent control device according to the task set to be assisted, and assisting in processing at least one task according to the second task allocation information.
7. The intelligent equipment control device is characterized by being applied to intelligent control equipment and comprising:
the communication establishing module is used for establishing local area network communication with other intelligent control equipment;
the scene determining module is used for determining a target scene mode according to the scene triggering instruction;
the task obtaining module is used for obtaining the number of tasks corresponding to the target contextual model, wherein each task correspondingly controls at least one intelligent device; and
and the assistance module is used for sending an assistance control instruction to at least one other intelligent control device in the local area network if the number of the tasks is greater than or equal to a preset number, wherein the assistance control instruction is used for indicating the at least one other intelligent control device to assist in processing the at least one task.
8. An intelligent control device comprising a processor and a memory, the memory storing computer program instructions which, when invoked by the processor, perform the intelligent device control method of any one of claims 1 to 7.
9. A computer-readable storage medium storing a program code, wherein the program code is executed by a processor to perform the smart device control method according to any one of claims 1 to 7.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103576633A (en) * | 2012-08-09 | 2014-02-12 | 海尔集团公司 | Method and system for conducting power supply control on intelligent home systems in community micro grid |
| CN105827695A (en) * | 2016-03-11 | 2016-08-03 | 中国联合网络通信集团有限公司 | Sharing method and apparatus of bandwidth resources |
| CN106708050A (en) * | 2016-12-30 | 2017-05-24 | 四川九洲电器集团有限责任公司 | Image acquisition method and equipment capable of autonomously moving |
| CN107070980A (en) * | 2017-01-22 | 2017-08-18 | 微鲸科技有限公司 | Remote assistance method, the apparatus and system of intelligent terminal |
| CN108510984A (en) * | 2017-02-24 | 2018-09-07 | 九阳股份有限公司 | A kind of voice cooperative control method of intelligent appliance equipment |
| CN110673645A (en) * | 2019-11-06 | 2020-01-10 | 中国人民解放军国防科技大学 | Automatic flight control method, system and storage medium for unmanned aerial vehicle group |
| CN110971289A (en) * | 2018-09-29 | 2020-04-07 | 比亚迪股份有限公司 | Unmanned aerial vehicle control method and device, storage medium and electronic equipment |
| CN111371819A (en) * | 2018-12-25 | 2020-07-03 | 美的集团股份有限公司 | Multi-device cooperation processing method and device, intelligent device and electronic device |
| CN111766798A (en) * | 2019-04-02 | 2020-10-13 | 青岛海信智慧家居系统股份有限公司 | Intelligent household equipment control method and device |
| CN112015200A (en) * | 2020-07-31 | 2020-12-01 | 湖南省西瓜甜瓜研究所 | Agricultural unmanned aerial vehicle group cooperative operation system, cooperative operation method and unmanned aerial vehicle |
| WO2020248626A1 (en) * | 2019-06-10 | 2020-12-17 | 北京达佳互联信息技术有限公司 | Task execution method, apparatus, device and system, and storage medium |
| CN112231075A (en) * | 2020-09-07 | 2021-01-15 | 武汉市九格合众科技有限责任公司 | Server cluster load balancing control method and system based on cloud service |
| CN112596406A (en) * | 2020-12-18 | 2021-04-02 | 深圳市欧瑞博科技股份有限公司 | Control method and device of intelligent equipment, control panel and storage medium |
-
2021
- 2021-08-06 CN CN202110902576.7A patent/CN113671844A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103576633A (en) * | 2012-08-09 | 2014-02-12 | 海尔集团公司 | Method and system for conducting power supply control on intelligent home systems in community micro grid |
| CN105827695A (en) * | 2016-03-11 | 2016-08-03 | 中国联合网络通信集团有限公司 | Sharing method and apparatus of bandwidth resources |
| CN106708050A (en) * | 2016-12-30 | 2017-05-24 | 四川九洲电器集团有限责任公司 | Image acquisition method and equipment capable of autonomously moving |
| CN107070980A (en) * | 2017-01-22 | 2017-08-18 | 微鲸科技有限公司 | Remote assistance method, the apparatus and system of intelligent terminal |
| CN108510984A (en) * | 2017-02-24 | 2018-09-07 | 九阳股份有限公司 | A kind of voice cooperative control method of intelligent appliance equipment |
| CN110971289A (en) * | 2018-09-29 | 2020-04-07 | 比亚迪股份有限公司 | Unmanned aerial vehicle control method and device, storage medium and electronic equipment |
| CN111371819A (en) * | 2018-12-25 | 2020-07-03 | 美的集团股份有限公司 | Multi-device cooperation processing method and device, intelligent device and electronic device |
| CN111766798A (en) * | 2019-04-02 | 2020-10-13 | 青岛海信智慧家居系统股份有限公司 | Intelligent household equipment control method and device |
| WO2020248626A1 (en) * | 2019-06-10 | 2020-12-17 | 北京达佳互联信息技术有限公司 | Task execution method, apparatus, device and system, and storage medium |
| CN110673645A (en) * | 2019-11-06 | 2020-01-10 | 中国人民解放军国防科技大学 | Automatic flight control method, system and storage medium for unmanned aerial vehicle group |
| CN112015200A (en) * | 2020-07-31 | 2020-12-01 | 湖南省西瓜甜瓜研究所 | Agricultural unmanned aerial vehicle group cooperative operation system, cooperative operation method and unmanned aerial vehicle |
| CN112231075A (en) * | 2020-09-07 | 2021-01-15 | 武汉市九格合众科技有限责任公司 | Server cluster load balancing control method and system based on cloud service |
| CN112596406A (en) * | 2020-12-18 | 2021-04-02 | 深圳市欧瑞博科技股份有限公司 | Control method and device of intelligent equipment, control panel and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 么刚 等: "基于分级代理的智能家庭网络模型研究", 高技术通讯, vol. 19, no. 09, pages 919 - 925 * |
| 张勇 等: "网络化制造中车间层分布式数字控制系统信息集成框架研究", 计算机集成制造系统, vol. 14, no. 04, pages 704 - 711 * |
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