type of device	Device attributes	Presetting a collection function A	Presetting a collection function B	Preset acquisition function C
					A	true	1	1	1
B	true	1	0	1
					C	false	0	1	1

A, B, C may represent intelligent devices, such as refrigerators, air conditioners, etc. Version information of each intelligence, such as a fourth generation air conditioner, etc., is also possible. Both 1 and 0 above may represent supported and unsupported. But 1 and 0 cannot be the same. True and false can represent support and non-support of a master function, respectively, but True and false cannot be the same.

In some exemplary embodiments,step 305 may be embodied as: as shown in fig. 4, the following steps may be included:

step 401: inquiring the first networking state of other intelligent equipment supporting the preset acquisition function; the first networking state comprises online and offline;

step 402: and sending a control instruction to at least one intelligent device in other intelligent devices with the first networking state being online, and receiving data collected by the intelligent device.

From this, when the smart machine who is the key center does not support to predetermine the collection function, only need to send control command to other online smart machines that support this to predetermine the collection function, carry out the collection of data through other smart machines promptly to this, make the mode of air quality control in this disclosure more intelligent convenient.

In order to enable normal transmission of control commands in different second network states. In some exemplary embodiments, theaforementioned step 402 can be embodied as: if the second networking state of the intelligent equipment is that a local area network is on-line, sending the control instruction to at least one intelligent equipment in other intelligent equipment of which the first networking state is on-line through the local area network; or if the second networking state of the intelligent device is wide area network online, the control instruction is sent to at least one intelligent device in other intelligent devices of which the first networking state is online through a cloud platform.

For example, as shown in fig. 5A, when thetelevision 501 serving as the key center needs to transmit a control instruction to other smart devices. If it is determined that the second connection status of the television is that the local area network is online, thetelevision 501 needs to send the control instruction to theintelligent device 502, theintelligent device 503, theintelligent device 504, and theintelligent device 505 through the local area network.

If the second connection status of the television is that the wan is online, as shown in fig. 5B, thetelevision 501 needs to forward the control command to theserver 506, and then theserver 506 sends the control command to theintelligent device 502, theintelligent device 503, theintelligent device 504, and theintelligent device 505.

Therefore, the mode of sending the control command by the intelligent device is determined through the second networking state of the intelligent device serving as the master control center, so that the control command can be normally sent.

Step 306: and sending a control instruction to intelligent equipment with an air conditioning function based on the acquired data so as to facilitate the intelligent equipment to adjust the air quality according to the control instruction.

In some exemplary embodiments,step 306 may be embodied as: determining target parameters of each intelligent device with an air conditioning function according to the acquired data; and respectively sending a control instruction to each intelligent device with the first networking state as online and the air conditioning function based on the target parameter, so that each intelligent device can adjust the parameter of each intelligent device to the target parameter according to the received control instruction.

For example, as described above, the first networking status of the smart device B and the smart device D having the air conditioning function is determined to be online. The smart device C is offline. And if the target parameters of the intelligent equipment are determined according to the acquired data. And if the target parameter of the intelligent device B is determined to be B, the target parameter of the intelligent device C is determined to be C, and the target parameter of the intelligent device D is determined to be D. Then a control command is sent to smart device B to adjust the parameter to B (e.g., if smart device B is an air conditioner, the control command may be to adjust the temperature to 28 degrees celsius). A control command is sent to the smart device D, which may be to adjust the parameter to D (for example, if the smart device D is a new fan, the control command may be to adjust the wind speed to a middle gear). And as the first networking state of the intelligent device C is offline, the control instruction is not sent to the intelligent device C. And when the first networking state of the intelligent equipment is determined to be the online state, sending a control instruction to the intelligent equipment C.

Therefore, the control instruction is sent to each intelligent device with the air conditioning function through the determined target parameters, so that each intelligent device can adjust the air quality, and the air conditioning is more convenient and intelligent.

In order to make the determined target parameters more accurate, in some exemplary embodiments, the acquired data is compared with a preset range; and if the acquired data are not in the preset range, inputting the acquired data into a preset algorithm model, and determining target parameters of each intelligent device with an air conditioning function by using the algorithm model.

For example, the target parameters of each smart device may be determined through a pre-trained neural network model. For example, when the acquired data is not within the preset range, the acquired data is input into a pre-trained neural network, and the neural network is used for determining target parameters of each intelligent device with an air conditioning function.

Different algorithm models can be preset in different intelligent device combinations, and the device combinations comprise intelligent devices with air conditioning functions and intelligent devices without air conditioning functions. As shown in table 2:

equipment combination	Algorithm model
		Intelligent device 1, intelligent device 2 and intelligent device 3	A
Intelligent device 1, intelligent device 2, intelligent device 4 and intelligent device 5	B
		Intelligent device 2, intelligent device 3, intelligent device 4 and intelligent device 6	C
…	…

For example, the target parameters of the intelligent devices including the intelligent device 1, the intelligent device 2 and the intelligent device 3 in the room can be determined by the preset algorithm model a.

Therefore, when the collected data are determined to be not in the preset range, the target parameters of the intelligent devices are determined to adjust the air quality according to the preset corresponding relation. The target parameters are determined more accurately.

In some exemplary embodiments, the preset functions further include preset interactive functions; establishing the second corresponding relation between each callback function in the intelligent equipment and each preset interaction function; responding to the triggering operation of any preset interactive function, if the intelligent equipment supports the preset interactive function, determining a callback function corresponding to the preset interactive function according to the second corresponding relation, and calling the determined callback function to judge whether to trigger the operation aiming at the preset acquisition function; and if so, executing the step of responding to the triggering operation of any preset acquisition function.

For example, the preset interaction function may be a voice function, and if the smart device supports the voice function, the user may interact with the smart device through voice. For example, a user may have the smart device collect data via voice input. And the intelligent equipment determines to trigger the operation aiming at the preset acquisition function through voice analysis, and executes the triggering operation corresponding to any preset acquisition function.

Therefore, the preset acquisition function is triggered through the preset interaction function, and the air data can be acquired according to the requirements of the user.

For further understanding of the technical solution of the present disclosure, the following detailed description with reference to fig. 6 may include the following steps:

step 601: determining the equipment attribute of the intelligent equipment according to the equipment type of the intelligent equipment, wherein the equipment attribute comprises a support main control function and a non-support main control function;

step 602: if the device attribute of the intelligent device is determined to be the support main control function, establishing a first corresponding relation between each callback function in the intelligent device and each preset acquisition function;

step 603: responding to the triggering operation of any preset acquisition function, and judging whether the intelligent equipment supports the preset acquisition function; if yes, go to step 604; if not, go to step 605;

step 604: determining a callback function corresponding to the preset acquisition function according to the first corresponding relation, and calling the determined callback function acquisition data;

step 605: inquiring the first networking state of other intelligent equipment supporting the preset acquisition function; the first networking state comprises online and offline; sending a control instruction to at least one intelligent device in other intelligent devices with the first networking state being online, and receiving data collected by the intelligent device;

step 606: determining target parameters of each intelligent device with an air conditioning function according to the acquired data;

step 607: and respectively sending a control instruction to each intelligent device with the first networking state as online and the air conditioning function based on the target parameter, so that each intelligent device can adjust the parameter of each intelligent device to the target parameter according to the received control instruction.

Based on the same inventive concept, the embodiment of the present disclosure further provides a schematic structural diagram of another intelligent device. As shown in fig. 7, theintelligent device 700 includes a device attribute determining module 710, a first corresponding relationship determining module 720, a preset acquisition function triggering operation module 730, and a control instruction sending module 740.

A device attribute determining module 710, configured to determine a device attribute of the intelligent device according to a device type of the intelligent device, where the device attribute includes a support main control function and a non-support main control function;

a first corresponding relationship determining module 720, configured to establish a first corresponding relationship between each callback function in the intelligent device and each preset acquisition function if it is determined that the device attribute of the intelligent device is the support master control function;

a preset acquisition function triggering operation module 730, configured to respond to a triggering operation of any preset acquisition function, determine, according to the first correspondence, a callback function corresponding to the preset acquisition function if the intelligent device supports the preset acquisition function, and call the determined callback function to acquire data; if the intelligent equipment does not support the preset acquisition function, acquiring data through other intelligent equipment supporting the preset acquisition function;

and the control instruction sending module 740 is configured to send a control instruction to the intelligent device with an air conditioning function based on the acquired data, so that the intelligent device adjusts the air quality according to the control instruction.

In some exemplary embodiments, the preset acquisition function triggers the operation module 730 to specifically:

In some exemplary embodiments, the preset collection function operation module 730 is specifically configured to:

In some exemplary embodiments, the control instruction sending module 740 is specifically configured to:

comparing the acquired data with a preset range;

In some exemplary embodiments, the preset functions further include preset interactive functions; the smart device further comprises:

a second corresponding relationship establishing module 750, configured to establish a second corresponding relationship between each callback function in the intelligent device and each preset interaction function after determining that the device attribute of the intelligent device is the support master control function;

a preset interactive function triggering operation module 760, configured to respond to a triggering operation of any preset interactive function, determine, if the smart device supports the preset interactive function, a callback function corresponding to the preset interactive function according to the second correspondence, and call the determined callback function to determine whether to trigger an operation for a preset acquisition function;

the execution response module 770 is configured to execute a step of responding to a trigger operation of any preset acquisition function if the trigger operation is yes.

Embodiments of the present disclosure also provide a computer-readable medium on which a computer program is stored, which when executed by a processor implements the steps of any of the methods described above.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present disclosure may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may be stored in a computer readable storage medium.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.

The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the disclosure are, in whole or in part, generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

The technical solutions provided by the present disclosure are introduced in detail, and the present disclosure applies specific examples to explain the principles and embodiments of the present disclosure, and the descriptions of the above examples are only used to help understanding the method and the core ideas of the present disclosure; meanwhile, for a person skilled in the art, based on the idea of the present disclosure, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present disclosure should not be construed as a limitation to the present disclosure.