Network configuration method and device of equipment, electronic equipment and storage medium

Abstract

Embodiments of the present application provide a network configuration method and device of equipment, electronic equipment and storage medium, and relate to the technical field of equipment management, the method comprises: acquiring environment data collected by a sensor and a voice instruction input by a user; acquiring corresponding network parameters of the smart home equipment in the home network; assigning priority to the smart home equipment according to the voice instruction and / or the environment data and the network parameters, and determining the network configuration priority corresponding to the smart home equipment; in response to detecting an adaptive network configuration instruction for the smart home equipment, sequentially connecting each smart home equipment to the home network according to the network configuration priority, thereby realizing adaptive network configuration while ensuring the overall connection speed and response time of the smart home equipment, ensuring the rationality of network resource allocation, and enabling the smart home system to more flexibly adapt to different use scenarios and demand changes.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, and in particular to a network distribution method for equipment, a network distribution device for equipment, an electronic device, and a computer-readable storage medium. Background Technology

[0002] With the continuous development of smart home technology, more and more smart devices are entering the home environment. However, in smart home systems, how to efficiently configure and connect numerous devices to the network has become a key issue. Currently, the commonly used configuration methods are either following a fixed sequence or requiring manual configuration by the user, lacking flexibility and intelligence. Meanwhile, users not only expect devices to respond quickly but also desire flexible and personalized configurations when using smart homes. Furthermore, in real-world home network environments, network latency often affects device connection speed and response time, leading to a poor user experience. Summary of the Invention

[0003] This invention provides a network configuration method, apparatus, electronic device, and computer-readable storage medium for smart home devices, to solve or partially solve the problems of low network configuration efficiency, unreasonable allocation of network resources, and inability to achieve personalized configuration.

[0004] This invention discloses a network configuration method for a device, applied to a control device in a smart home system. The smart home system further includes smart home devices and sensors. The method includes:

[0005] Acquire environmental data collected by the sensors, as well as voice commands input by the user;

[0006] Obtain the network parameters corresponding to the smart home device in its home network;

[0007] Priority allocation is performed on the smart home devices based on the voice commands and / or the environmental data, as well as the network parameters, to determine the network configuration priority corresponding to the smart home devices;

[0008] In response to the detection of an adaptive network configuration command for the smart home devices, each smart home device is connected to the home network in sequence according to the network configuration priority.

[0009] In some feasible embodiments, the step of responding to the detection of an adaptive network configuration command for the smart home devices and sequentially connecting each smart home device to the home network according to the network configuration priority includes:

[0010] Obtain the command type corresponding to the voice command, the network status corresponding to the home network, and the device status corresponding to the smart home device;

[0011] If the instruction type meets the first preset condition, or the network status meets the second preset condition, or the device status meets the third preset condition, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0012] In some feasible embodiments, if the instruction type meets a first preset condition, then connecting each smart home device to the home network sequentially according to the network allocation priority includes:

[0013] If the instruction type indicates that the voice instruction is an emergency instruction, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0014] In some feasible embodiments, if the network status meets the second preset condition, then connecting each smart home device to the home network sequentially according to the network allocation priority includes:

[0015] If the network status indicates that the home network is undergoing a network upgrade or update, then each of the smart home devices will be connected to the home network in sequence according to the network configuration priority.

[0016] In some feasible embodiments, the step of connecting each smart home device to the home network sequentially according to the network allocation priority if the device status meets the third preset condition includes:

[0017] If the device status indicates that the smart home device has recovered from a fault and reconnected to the home network, then each smart home device will be connected to the home network in sequence according to the network configuration priority.

[0018] In some feasible embodiments, the step of prioritizing the smart home devices based on the voice commands and / or the environmental data, and the network parameters, to determine the network configuration priority corresponding to the smart home devices, includes:

[0019] Identify the target smart home device corresponding to the voice command and / or the environmental data;

[0020] The target smart home device is weighted using the voice command to obtain the target voice command weight value of the target smart home device, and / or the target smart home device is weighted using the environmental data to obtain the target environmental weight value of the target smart home device.

[0021] The target smart home device is weighted according to the network parameters to determine the target network weight value corresponding to the target smart home device.

[0022] The target smart home device's network priority is calculated using the target voice command weight value and / or the target environment weight value, as well as the target network weight value.

[0023] In some feasible embodiments, the target smart home device includes a first smart home device corresponding to the voice command, and the step of assigning weights to the target smart home device using the voice command to obtain a target voice command weight value for the target smart home device includes:

[0024] Recognize the voice command and obtain the command type corresponding to the voice command;

[0025] If the instruction type indicates that the voice instruction is an emergency instruction, then a target voice instruction weight value corresponding to the emergency instruction is configured for the first smart home device, and the target voice instruction weight value is higher than the voice instruction weight values ​​corresponding to other smart home devices.

[0026] In some feasible embodiments, the target smart home device includes a second smart home device corresponding to the environmental data, and the step of assigning weights to the target smart home device using the environmental data to obtain a target environmental weight value for the target smart home device includes:

[0027] If the environmental data meets the preset conditions, then the second smart home device is configured with a target environmental weight value corresponding to the environmental data, and the target environmental weight value is higher than the environmental weight values ​​corresponding to other smart home devices.

[0028] In some feasible embodiments, the environmental data includes at least one of temperature, light intensity, humidity, carbon dioxide concentration, and organic compound concentration; the smart home device includes at least a temperature control device, a humidity control device, an air quality control device, and smart curtains; and if the environmental data meets preset conditions, a target environmental weight value corresponding to the environmental data is configured for the second smart home device, including:

[0029] If the temperature value is greater than or equal to the first preset temperature threshold, then the temperature control device is configured with a first environmental weight value corresponding to the temperature value;

[0030] If the temperature value is less than the second preset temperature threshold, then the temperature control device is configured with a second environmental weight value corresponding to the temperature value, wherein the first preset temperature threshold is greater than the second preset temperature threshold;

[0031] If the humidity value is greater than or equal to the first preset humidity threshold, then the humidity regulating device is configured with a third environmental weight value corresponding to the temperature value;

[0032] If the humidity value is less than the second preset humidity threshold, then the humidity regulating device is configured with a fourth environmental weight value corresponding to the temperature value, and the first preset humidity threshold is greater than the second preset humidity threshold.

[0033] If the light intensity is greater than or equal to the first preset light threshold, then the smart curtain is configured with a fourth environmental weight value corresponding to the temperature value;

[0034] If the light intensity is less than the second preset light threshold, then the smart curtain is configured with a fifth environmental weight value corresponding to the temperature value, and the first preset light threshold is greater than the second preset light threshold.

[0035] If the carbon dioxide concentration is greater than or equal to a first preset concentration threshold, and / or the organic compound concentration is greater than or equal to a second preset concentration threshold, then the air quality control device is configured with a sixth environmental weight value corresponding to the carbon dioxide concentration and / or the organic compound concentration.

[0036] In some feasible embodiments, the target smart home device includes a third smart home device corresponding to the voice command and the environmental data. The step of assigning weights to the target smart home device using the voice command to obtain a target voice command weight value for the target smart home device, and assigning weights to the target smart home device using the environmental data to obtain a target environmental weight value for the target smart home device, includes:

[0037] Recognize the voice command and obtain the command type corresponding to the voice command;

[0038] If the instruction type indicates that the voice instruction is an emergency instruction, then configure a first voice instruction weight value corresponding to the emergency instruction for the third smart home device;

[0039] If the instruction type indicates that the voice instruction is a regular instruction, then a second voice instruction weight value corresponding to the emergency instruction is configured for the third smart home device, and the first voice instruction weight value is greater than the second voice instruction weight value;

[0040] If the environmental data meets the preset conditions, then the third smart home device is configured with a first environmental weight value corresponding to the environmental data;

[0041] If the environmental data does not meet the preset conditions, then the third smart home device is configured with a second environmental weight value corresponding to the environmental data, wherein the first environmental weight value is greater than the second environmental weight value.

[0042] In some feasible embodiments, the network parameters include the network latency corresponding to the smart home device, and the step of weighting the target smart home device according to the network parameters to determine the target network weight value corresponding to the target smart home device includes:

[0043] Obtain the current network weight value corresponding to the target smart home device;

[0044] If the network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0045] In some feasible embodiments, the step of assigning weights to the target smart home device based on the network parameters and determining the target network weight value corresponding to the target smart home device further includes:

[0046] If the target smart home device is accessing the home network for the first time, a test data packet is sent to the target smart home device, and the round-trip time corresponding to the test data packet is obtained;

[0047] Determine the target network latency corresponding to the round-trip time;

[0048] If the target network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0049] In some feasible embodiments, it also includes:

[0050] Continuously detect the current network latency corresponding to the target smart home device;

[0051] If the current network latency corresponding to the target smart home device is less than the preset network latency threshold, then the current network weight value of the target smart home device is increased according to the preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device, or the current network weight value is adjusted to the preset network weight value, which is the network weight value corresponding to the target smart home device when there is no network latency.

[0052] This invention also discloses a network distribution device for a device applied to a control device in a smart home system. The smart home system further includes smart home devices and sensors. The device includes:

[0053] The data acquisition module is used to acquire environmental data collected by the sensor and voice commands input by the user;

[0054] The network parameter acquisition module is used to acquire the network parameters of the smart home device in the home network it is located in;

[0055] The priority determination module is used to allocate priorities to the smart home devices based on the voice commands and / or the environmental data and the network parameters, and to determine the network configuration priority corresponding to the smart home devices.

[0056] The network configuration module is used to respond to the detection of an adaptive network configuration command for the smart home devices and connect each smart home device to the home network in sequence according to the network configuration priority.

[0057] In some feasible embodiments, the distribution network module is specifically used for:

[0058] Obtain the command type corresponding to the voice command, the network status corresponding to the home network, and the device status corresponding to the smart home device;

[0059] If the instruction type meets the first preset condition, or the network status meets the second preset condition, or the device status meets the third preset condition, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0060] In some feasible embodiments, the distribution network module is specifically used for:

[0061] If the instruction type indicates that the voice instruction is an emergency instruction, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0062] In some feasible embodiments, the distribution network module is specifically used for:

[0063] If the network status indicates that the home network is undergoing a network upgrade or update, then each of the smart home devices will be connected to the home network in sequence according to the network configuration priority.

[0064] In some feasible embodiments, the distribution network module is specifically used for:

[0065] If the device status indicates that the smart home device has recovered from a fault and reconnected to the home network, then each smart home device will be connected to the home network in sequence according to the network configuration priority.

[0066] In some feasible embodiments, the priority determination module is specifically used for:

[0067] Identify the target smart home device corresponding to the voice command and / or the environmental data;

[0068] The target smart home device is weighted using the voice command to obtain the target voice command weight value of the target smart home device, and / or the target smart home device is weighted using the environmental data to obtain the target environmental weight value of the target smart home device.

[0069] The target smart home device is weighted according to the network parameters to determine the target network weight value corresponding to the target smart home device.

[0070] The target smart home device's network priority is calculated using the target voice command weight value and / or the target environment weight value, as well as the target network weight value.

[0071] In some feasible embodiments, the target smart home device includes a first smart home device corresponding to the voice command, and the priority determination module is specifically used for:

[0072] Recognize the voice command and obtain the command type corresponding to the voice command;

[0073] If the instruction type indicates that the voice instruction is an emergency instruction, then a target voice instruction weight value corresponding to the emergency instruction is configured for the first smart home device, and the target voice instruction weight value is higher than the voice instruction weight values ​​corresponding to other smart home devices.

[0074] In some feasible embodiments, the target smart home device includes a second smart home device corresponding to the environmental data, and the priority determination module is specifically used for:

[0075] If the environmental data meets the preset conditions, then the second smart home device is configured with a target environmental weight value corresponding to the environmental data, and the target environmental weight value is higher than the environmental weight values ​​corresponding to other smart home devices.

[0076] In some feasible embodiments, the environmental data includes at least one of temperature, light intensity, humidity, carbon dioxide concentration, and organic compound concentration; the smart home devices include at least a temperature control device, a humidity control device, an air quality control device, and smart curtains; and the priority determination module is specifically used for:

[0077] If the temperature value is greater than or equal to the first preset temperature threshold, then the temperature control device is configured with a first environmental weight value corresponding to the temperature value;

[0078] If the temperature value is less than the second preset temperature threshold, then the temperature control device is configured with a second environmental weight value corresponding to the temperature value, wherein the first preset temperature threshold is greater than the second preset temperature threshold;

[0079] If the humidity value is greater than or equal to the first preset humidity threshold, then the humidity regulating device is configured with a third environmental weight value corresponding to the temperature value;

[0080] If the humidity value is less than the second preset humidity threshold, then the humidity regulating device is configured with a fourth environmental weight value corresponding to the temperature value, and the first preset humidity threshold is greater than the second preset humidity threshold.

[0081] If the light intensity is greater than or equal to the first preset light threshold, then the smart curtain is configured with a fourth environmental weight value corresponding to the temperature value;

[0082] If the light intensity is less than the second preset light threshold, then the smart curtain is configured with a fifth environmental weight value corresponding to the temperature value, and the first preset light threshold is greater than the second preset light threshold.

[0083] If the carbon dioxide concentration is greater than or equal to a first preset concentration threshold, and / or the organic compound concentration is greater than or equal to a second preset concentration threshold, then the air quality control device is configured with a sixth environmental weight value corresponding to the carbon dioxide concentration and / or the organic compound concentration.

[0084] In some feasible embodiments, the target smart home device includes a third smart home device corresponding to the voice command and the environmental data, and the priority determination module is specifically used for:

[0085] Recognize the voice command and obtain the command type corresponding to the voice command;

[0086] If the instruction type indicates that the voice instruction is an emergency instruction, then configure a first voice instruction weight value corresponding to the emergency instruction for the third smart home device;

[0087] If the instruction type indicates that the voice instruction is a regular instruction, then a second voice instruction weight value corresponding to the emergency instruction is configured for the third smart home device, and the first voice instruction weight value is greater than the second voice instruction weight value;

[0088] If the environmental data meets the preset conditions, then the third smart home device is configured with a first environmental weight value corresponding to the environmental data;

[0089] If the environmental data does not meet the preset conditions, then the third smart home device is configured with a second environmental weight value corresponding to the environmental data, wherein the first environmental weight value is greater than the second environmental weight value.

[0090] In some feasible embodiments, the network parameters include the network latency corresponding to the smart home device, and the priority determination module is specifically used for:

[0091] Obtain the current network weight value corresponding to the target smart home device;

[0092] If the network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0093] In some feasible embodiments, the priority determination module is further used for:

[0094] If the target smart home device is accessing the home network for the first time, a test data packet is sent to the target smart home device, and the round-trip time corresponding to the test data packet is obtained;

[0095] Determine the target network latency corresponding to the round-trip time;

[0096] If the target network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0097] In some feasible embodiments, it also includes:

[0098] A network latency detection module is used to continuously detect the current network latency corresponding to the target smart home device;

[0099] The weight adjustment module is used to increase the current network weight value of the target smart home device according to a preset adjustment ratio if the current network latency corresponding to the target smart home device is less than the preset network latency threshold, so as to obtain the target network weight value corresponding to the target smart home device, or to adjust the current network weight value to a preset network weight value, wherein the preset network weight value is the network weight value corresponding to the target smart home device when no network latency occurs.

[0100] This invention also discloses an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0101] The memory is used to store computer programs;

[0102] When the processor executes a program stored in the memory, it implements the method described in the embodiments of the present invention.

[0103] This invention also discloses a computer-readable storage medium storing instructions that, when executed by one or more processors, cause the processors to perform the methods described in this invention.

[0104] The embodiments of the present invention have the following advantages:

[0105] In this embodiment of the invention, a control device is applied to a smart home system, which also includes smart home devices and sensors. The control device can acquire environmental data collected by the sensors and voice commands input by the user. Then, it acquires the network parameters corresponding to the smart home devices in the home network. Based on the voice commands and / or environmental data and network parameters, it prioritizes the smart home devices and determines their corresponding network configuration priorities. By combining voice commands, environmental data, and network parameters, a more comprehensive and accurate basis is provided for determining the network configuration priorities of smart home devices. Thus, during the network configuration process, the control device can respond to the detection of adaptive network configuration commands for smart home devices and connect each smart home device to the home network sequentially according to its network configuration priority. By configuring each smart home device according to its network configuration priority, adaptive network configuration is achieved while ensuring the overall connection speed and response time of the smart home devices, ensuring the rationality of network resource allocation, and enabling the smart home system to more flexibly adapt to different usage scenarios and changing needs. Attached Figure Description

[0106] Figure 1 This is a flowchart of the steps of a network distribution method for a device provided in an embodiment of the present invention;

[0107] Figure 2 This is a schematic diagram of the device network distribution process provided in an embodiment of the present invention;

[0108] Figure 3 This is a structural block diagram of a power distribution device provided in an embodiment of the present invention;

[0109] Figure 4 This is a block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0110] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0111] As an example, the commonly used network configuration method involves configuring devices in a fixed sequence or manually by the user, lacking flexibility and intelligence. Meanwhile, when using smart homes, users not only expect devices to respond quickly but also desire flexible, personalized configurations. Furthermore, in a home network environment, network latency often affects device connection speed and response time, leading to a poor user experience.

[0112] In this invention, a control device applied to a smart home system, which also includes smart home devices and sensors, acquires environmental data collected by the sensors and voice commands input by the user. It then obtains the network parameters corresponding to the smart home devices within the home network. Based on the voice commands and / or environmental data, and the network parameters, the control device prioritizes the smart home devices, determining their corresponding network configuration priorities. By combining voice commands, environmental data, and network parameters, a more comprehensive and accurate basis for determining the network configuration priorities of smart home devices is provided. During the network configuration process, the control device can respond to the detection of adaptive network configuration commands for smart home devices, sequentially connecting each smart home device to the home network according to its network configuration priority. By configuring each smart home device based on its priority, adaptive network configuration is achieved while ensuring the overall connection speed and response time of the smart home devices, ensuring the rationality of network resource allocation, and enabling the smart home system to more flexibly adapt to different usage scenarios and changing needs.

[0113] Reference Figure 1 This diagram illustrates a flowchart of a network distribution method for a device provided in an embodiment of the present invention. The method is applied to a control device in a smart home system, which also includes smart home devices and sensors. Specifically, the method may include the following steps:

[0114] Step 101: Obtain the environmental data collected by the sensor and the voice commands input by the user;

[0115] Optionally, a smart home system may include control devices, smart home devices, and corresponding sensors. The control devices are responsible for managing the smart home devices, such as configuring the network for the devices, controlling the devices to perform corresponding operations, and receiving environmental data sent by the sensors. In practice, the smart home system can receive user voice commands through the control devices and, combined with environmental data collected by sensors, use a priority-based adaptive network configuration algorithm to configure and manage various smart home devices, thereby achieving a more intelligent response to user needs and environmental changes, and providing users with convenient and efficient smart home services.

[0116] In the process of managing and controlling smart home devices, sensors can collect environmental data corresponding to the surrounding environment and obtain voice commands input by users. For example, sensors can include temperature sensors, light sensors, humidity sensors, and air quality sensors. Correspondingly, environmental data can include at least one of the following: temperature value, light intensity, humidity value, carbon dioxide concentration, and organic compound concentration. By collecting environmental data, the current state of the home environment can be reflected based on the environmental data. For example, if the indoor temperature is too high, it may mean that the air conditioner needs to be connected first for adjustment. At the same time, continuous monitoring of changes in environmental data is beneficial for adjusting the network priority of smart home devices in real time.

[0117] In addition, the control device can also collect the user's voice commands through microphones and other sound pickup devices, so as to convert the user's voice commands into corresponding text, and perform semantic recognition, emotion recognition and other functions on the text to determine the accent, speech rate, language expression mode and content of the user's voice commands, and then accurately analyze the user's intentions so as to configure the smart home devices according to the user's intentions.

[0118] Step 102: Obtain the network parameters corresponding to the smart home device in its home network;

[0119] During the network configuration process for smart home devices, the control device can also obtain the network parameters corresponding to the smart home devices in their respective home networks. This allows the network's impact on the smart home devices to be considered during the configuration process, providing a more comprehensive and accurate basis for determining the network configuration priority of smart home devices.

[0120] Step 103: Prioritize the smart home devices according to the voice commands and / or the environmental data and the network parameters to determine the network configuration priority corresponding to the smart home devices;

[0121] In this embodiment of the invention, after determining the voice command and / or environmental data, as well as the network parameters, the smart home devices can be prioritized according to the voice command and / or environmental data, as well as the network parameters, to determine the network priority of the smart home devices. By combining the voice command, environmental data, and network parameters, a more comprehensive and accurate basis is provided for determining the network priority of smart home devices. Different network configuration priorities represent the network configuration order and bandwidth allocation for different smart home devices during the network configuration process. For example, assuming the smart home system includes smart home device ①, smart home device ②, and smart home device ③, the control device determines the network configuration priorities of these devices based on relevant data as follows: Smart Home Device ② > Smart Home Device ① > Smart Home Device ③. When configuring network connections for each smart home device, the control device can prioritize connecting smart home device ② to the home network. Then, if smart home device ② is already connected to the home network, it will connect smart home device ① to the home network. If both smart home device ② and smart home device ① are already connected to the home network, it will connect smart home device ③ to the home network. This classification of smart home devices through network configuration priorities ensures that devices with "essential user needs" can quickly connect to the home network and respond, thus ensuring that user needs are met quickly and effectively.

[0122] In some feasible implementations, the control device can first identify the target smart home device corresponding to the voice command and / or environmental data. Then, it uses the voice command to assign weights to the target smart home device, obtaining the target voice command weight value. And / or, it uses environmental data to assign weights to the target smart home device, obtaining the target environmental weight value. Finally, it assigns weights to the target smart home device based on network parameters, determining the target network weight value. Then, it uses the target voice command weight value and / or the target environmental weight value, along with the target network weight value, to calculate the network priority corresponding to the target smart home device. By combining voice commands, environmental data, and network parameters, a more comprehensive and accurate basis is provided for determining the network priority of smart home devices. This allows for the classification of different smart home devices based on network priority, ensuring that smart home devices with "essential user needs" can quickly access the home network and respond, thus ensuring that user needs are met quickly and effectively.

[0123] It should be noted that during the calculation of network configuration priority, the user may not necessarily input the corresponding voice command, and the environmental data collected by the sensors may not necessarily trigger the network configuration of smart home devices. Therefore, during the network configuration process of smart home devices, the control device can determine the corresponding network configuration priority of smart home devices based on voice commands and network parameters, environmental data and network parameters, and voice commands, environmental data and network parameters. Through multi-dimensional data detection, the network configuration strategy of smart home devices can be flexibly adjusted according to the actual situation to ensure that user needs are met quickly and effectively.

[0124] For voice commands, assuming the user inputs a voice command for the first smart home device, the control device can recognize the voice command and obtain the command type corresponding to the voice command. If the command type indicates that the voice command is an emergency command, then the first smart home device is configured with a target voice command weight value corresponding to the emergency command. The target voice command weight value is higher than the voice command weight values ​​corresponding to other smart home devices.

[0125] Voice commands can include both emergency and regular commands. The control device can analyze the user's accent, speech rate, and language style to assess their emotions and determine the command type based on the analysis results. When a voice command is identified as an emergency command, indicating a strong user need for control, a target voice command weight value corresponding to the emergency command can be configured for the first smart home device. This target voice command weight value is set higher than the weight values ​​of voice commands for other smart home devices, ensuring that the first smart home device can be prioritized for network configuration to meet the user's urgent control needs.

[0126] Optionally, the control device can analyze user commands using a corresponding sentiment analysis model to determine the command type corresponding to the voice command. For example, the corresponding sentiment analysis model can be pre-trained by collecting user-input voice commands, ensuring the dataset covers various accents, speech rates, and emotional states, and preprocessing the voice commands (such as noise reduction, framing, and feature extraction) to obtain the corresponding training data. Then, the sentiment analysis model can be trained through processes such as accent analysis, speech rate analysis, and language expression analysis. For example, for accent analysis, an accent recognition model can be trained using machine learning or deep learning models. This involves extracting accent-related features such as phoneme pronunciation and pitch variations, and then classifying accents into different types. For speech rate analysis, the number of frames per second (fps) can be used as a preliminary indicator of speech rate. Then, syllables in the speech are identified, and the number of syllables per second is calculated, thus classifying speech rate into fast, medium, and slow categories based on syllable rate. For language expression analysis, an emotion dictionary can be used to identify emotional words in the speech, calculate the emotional intensity of these words, analyze pitch variations in the speech signal, identify intonation fluctuations, and extract prosodic features. After extracting the corresponding features for accent, speech rate, and language expression based on the aforementioned process, these features can be fused to form a comprehensive feature vector. Then, classification algorithms (such as random forests or deep learning models) can be used to train a sentiment analysis model to identify the user's corresponding emotion. Based on the identified emotion, the model can then determine whether a voice command is an emergency command or a routine command.

[0127] Furthermore, for voice command weight values, different weight values ​​can be set based on the command type. For example, a first weight value corresponds to a regular command, a second weight value corresponds to an emergency command, and the second weight value is greater than the first weight value. In practical applications, assuming the user inputs the voice command "I'm so hot, turn on the air conditioner quickly," recognition can determine that this voice command is an emergency command, and a corresponding target voice command weight value, such as 0.9, can be configured for this voice command to increase its response priority. Conversely, assuming the user inputs the voice command "Turn on the air conditioner," recognition can determine that this voice command is a regular command, and a corresponding target voice command weight value, such as 0.5, can be configured for this voice command. By recognizing the command type corresponding to the voice command, analyzing the user's control intent and the urgency of the control need, the weight value corresponding to the voice command can be determined to ensure that smart home devices can be prioritized for network configuration to meet the user's current urgent control needs.

[0128] For environmental data, assuming the environmental data corresponds to a second smart home device, the control device can determine whether the environmental data meets the corresponding preset conditions. If the environmental data meets the preset conditions, the control device will configure a target environmental weight value corresponding to the environmental data for the second smart home device. The target environmental weight value is higher than the environmental weight values ​​corresponding to other smart home devices.

[0129] In practical implementation, environmental data includes at least one of the following: temperature, light intensity, humidity, carbon dioxide concentration, and organic compound concentration. Smart home devices include at least a temperature controller, a humidity regulator, an air quality control device, and smart curtains. The control device compares the temperature, light intensity, humidity, carbon dioxide concentration, and organic compound concentration with corresponding threshold conditions to determine whether the environmental data meets the corresponding conditions. Specifically, if the temperature is greater than or equal to a first preset temperature threshold, a first environmental weight value corresponding to the temperature is assigned to the temperature controller; if the temperature is less than a second preset temperature threshold, a second environmental weight value corresponding to the temperature is assigned to the temperature controller, where the first preset temperature threshold is greater than the second preset temperature threshold; if the humidity is greater than or equal to a first preset humidity threshold... The first preset humidity threshold is greater than the second preset humidity threshold, which corresponds to the third environmental weight value of the humidity control device configuration and the temperature value. If the humidity value is less than the second preset humidity threshold, the second preset humidity threshold is greater than the second preset humidity threshold. If the light intensity is greater than or equal to the first preset light threshold, the third preset humidity threshold is greater than the second preset light threshold. If the light intensity is less than the second preset light threshold, the fifth preset humidity threshold is greater than the second preset light threshold. If the carbon dioxide concentration is greater than or equal to the first preset concentration threshold, and / or the organic compound concentration is greater than or equal to the second preset concentration threshold, the sixth preset humidity threshold is greater than the carbon dioxide concentration and / or organic compound concentration of the air quality control device configuration.

[0130] It should be noted that, referring to the voice command weight value, when the environmental data meets the preset conditions, a corresponding first weight value can be configured for the environmental data. When the environmental data does not meet the preset conditions, a corresponding second weight value can be configured for the environmental data. The first weight value is greater than the second weight value. Thus, when the environmental data meets the conditions, the corresponding smart home device can be controlled so that the corresponding device operation can be performed through the corresponding smart home device.

[0131] In one example, assume that the environmental data includes at least:

[0132] Temperature value: 25℃;

[0133] Illumination intensity: 1200 lux;

[0134] Humidity level: 60%;

[0135] Carbon dioxide concentration: 1000 ppm;

[0136] Organic compound concentration: 0.5 ppm.

[0137] Meanwhile, the corresponding preset thresholds may include:

[0138] First preset temperature threshold: 24℃;

[0139] Second preset temperature threshold: 20℃;

[0140] First preset humidity threshold: 55%;

[0141] Second preset humidity threshold: 40%;

[0142] First preset illumination threshold: 1000 lux;

[0143] Second preset illumination threshold: 800 lux;

[0144] First preset carbon dioxide concentration threshold: 800 ppm;

[0145] The second preset organic compound concentration threshold is 0.3 ppm.

[0146] Based on the aforementioned data, the control device can compare the corresponding environmental data with preset thresholds to determine the environmental weight value corresponding to the environmental data. Specifically:

[0147] For temperature control equipment: temperature value: 25℃, 25℃≥24℃ (first preset temperature threshold), then the control equipment can be configured with a first environmental weight value, such as 1.0, etc.

[0148] For humidity control equipment: if the humidity value is 60% and 60% ≥ 55% (first preset humidity threshold), the control equipment can be configured with a second environmental weight value, such as 0.8.

[0149] For smart curtains: light intensity: 1200 lux, 1200 lux ≥ 1000 lux (first preset light threshold), then the control device can be configured with a third environmental weight value, such as 1.2, etc.

[0150] For air quality control devices: carbon dioxide concentration: 1000ppm, 1000ppm≥800ppm (first preset carbon dioxide concentration threshold); and organic compound concentration: 0.5ppm, 0.5ppm≥0.3ppm (second preset organic compound concentration threshold). Then, the control device can be configured with a corresponding fourth environmental weight value, such as 1.5, so that the control device can adjust the corresponding environmental weight value of the smart home device according to the current environmental data, so as to determine the network priority of the smart home device based on the environmental weight value.

[0151] Furthermore, assuming that both the voice command and environmental data correspond to the same third smart home device, the control device can first recognize the voice command and obtain the command type corresponding to the voice command. If the command type indicates that the voice command is an emergency command, then a first voice command weight value corresponding to the emergency command is configured for the third smart home device; if the command type indicates that the voice command is a regular command, then a second voice command weight value corresponding to the emergency command is configured for the third smart home device. The first voice command weight value is greater than the second voice command weight value. At the same time, the control device can also analyze the environmental data. If the environmental data meets preset conditions, then a first environmental weight value corresponding to the environmental data is configured for the third smart home device; if the environmental data does not meet preset conditions, then a second environmental weight value corresponding to the environmental data is configured for the third smart home device. The first environmental weight value is greater than the second environmental weight value.

[0152] Through the above process, voice commands and environmental perception data can be combined to provide a more comprehensive and accurate basis for determining the network priority of smart home devices. By analyzing the user's voice commands, the user's needs and intentions can be directly understood; at the same time, combined with environmental perception data, the user's potential needs can be further inferred, improving the intelligence level of the network configuration.

[0153] Furthermore, after determining the network priority corresponding to the smart home device, the control device can also obtain the network parameters corresponding to the smart home device, so as to calculate the network priority corresponding to the smart home device based on the network parameters, environmental weight value, and voice command weight value.

[0154] Among the network parameters, network latency corresponding to smart home devices is considered. The control device first obtains the current network weight value corresponding to the target smart home device. If the network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device. For example, assuming the current network weight value corresponding to the target smart home device is 1.0 and the current network latency is 100ms (i.e., 50ms (preset network latency threshold) ≤ 100ms), the current network weight value can be reduced according to the corresponding adjustment ratio. If the preset adjustment ratio is 0.5, then the target network weight value is: current network weight value × preset adjustment ratio, that is, target network weight value = 1.0 × 0.5 = 0.5. Thus, when determining the network priority of smart home devices, the network latency factor is fully considered, enabling devices with better network conditions to be connected first during the network configuration process, improving the overall connection speed and response time, avoiding some devices from failing to respond in time due to network latency, and improving the user experience.

[0155] In addition, if the target smart home device is accessing the home network for the first time, a test data packet is sent to the target smart home device, and the round-trip time corresponding to the test data packet is obtained. Then, the target network latency corresponding to the round-trip time is determined. If the target network latency is less than or equal to the preset network latency threshold, the current network weight value is reduced according to the preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0156] It's important to note that during the above process, the control device can use network monitoring tools to continuously monitor the status of the entire home network, including metrics such as network latency and bandwidth utilization in the areas where each device is located. For newly added devices, network latency tests can be performed, for example, by sending test data packets and measuring round-trip time to determine the device's network latency. When determining the network priority of smart home devices, if a device's network area has high latency, its priority can be appropriately reduced. Specific adjustments can be made using methods such as setting a network latency threshold; when a device's network latency exceeds this threshold, its priority is reduced proportionally. For example, if a smart speaker's area has high network latency, while other devices such as smart lights and smart curtains have relatively lower priority but lower network latency, the device with lower latency can be connected to the network first. Furthermore, for devices with high network latency requirements, such as video surveillance equipment, excessively high network latency may affect their performance; in this case, their priority can be significantly reduced until the network situation improves.

[0157] Once the voice command weight, environmental weight, and network weight are determined, a weighted summation method can be used to calculate the network priority for each smart home device. The devices are then ranked according to their final values ​​to determine their respective network configuration priorities. For example, the priority score can be calculated using the following formula: Priority Score = Environmental Awareness Weight × Environmental Factor Score + Voice Command Weight × Voice Command Score + Network Latency Weight × Network Latency Score. The environmental factor score, voice command score, and network latency score can be quantified and standardized based on specific circumstances.

[0158] In one example, suppose the calculated weight values ​​are:

[0159] Environmental perception weight: 0.4

[0160] Voice command weight: 0.3

[0161] Network latency weight: 0.3

[0162] For two smart home devices A and B, their scores on different factors are as follows:

[0163] Device A:

[0164] Environmental factor score: 80

[0165] Voice command score: 70

[0166] Network latency score: 60

[0167] Device B:

[0168] Environmental factor score: 70

[0169] Voice command score: 80

[0170] Network latency score: 50

[0171] Therefore, according to the formula, priority score = environmental perception weight × environmental factor score + voice command weight × voice command score + network latency weight × network latency score

[0172] Furthermore, priority scores are assigned to each device:

[0173] For device A: Priority score = 0.4 × 80 + 0.3 × 70 + 0.3 × 60 = 71

[0174] For device B: Priority score = 0.4 × 70 + 0.3 × 80 + 0.3 × 50 = 67

[0175] Based on the calculation results, device A has a priority score of 71, while device B has a priority score of 67. Therefore, device A has a higher distribution network priority than device B.

[0176] Through the above process, the control device can rank devices according to their priority scores to determine the network configuration priority of each smart home device. By combining voice commands and environmental perception data, a more comprehensive and accurate basis for determining the network configuration priority of smart home devices is provided. By analyzing the user's voice commands, the user's needs and intentions can be directly understood; at the same time, combined with environmental perception data, the user's potential needs can be further inferred, improving the intelligence of the network configuration and fully considering network latency factors. This allows devices with better network conditions to be connected first during the network configuration process, improving the overall connection speed and response time, avoiding the inability of some devices to respond in time due to network latency, and improving the user experience.

[0177] Step 104: In response to detecting an adaptive network configuration command for the smart home devices, connect each smart home device to the home network in sequence according to the network configuration priority.

[0178] In this embodiment of the invention, based on the determined network configuration priority, when it is necessary to configure the network for smart home devices, the control device can respond to the detection of the adaptive network configuration command for the smart home devices, and connect each smart home device to the home network in sequence according to the network configuration priority. While realizing adaptive network configuration, it can ensure the overall connection speed and response time of the smart home devices, ensure the rationality of network resource allocation, and enable the smart home system to adapt more flexibly to different usage scenarios and changes in needs.

[0179] In one feasible implementation, the control device can obtain the instruction type corresponding to the voice command, the network status corresponding to the home network, and the device status corresponding to the smart home device. If the instruction type meets the first preset condition, or the network status meets the second preset condition, or the device status meets the third preset condition, then each smart home device is connected to the home network in sequence according to the network configuration priority.

[0180] For example, if the command type indicates that the voice command is an emergency command, then each smart home device will be connected to the home network in sequence according to the network configuration priority. In this way, when the user's voice command is identified as an emergency command, priority network configuration will be triggered for the corresponding smart home devices to ensure that the smart home devices can be configured first to meet the user's current urgent control needs.

[0181] For example, if the network status indicates that the home network is undergoing an upgrade or update, then each smart home device will be connected to the home network in sequence according to the network configuration priority. Thus, when the home network is upgraded or updated, since each smart home device needs to reconnect to the home network, the control device can configure and connect each smart home device according to the determined network configuration priority to ensure that each smart home device can operate normally.

[0182] For example, if the device status indicates that the smart home device has reconnected to the home network after recovering from a fault, then each smart home device will be connected to the home network in sequence according to the network configuration priority. Thus, when the smart home device loses network access due to a fault and recovers, the control device can reconfigure the network according to the network configuration priority to ensure that it can quickly return to its original working state and ensure the stability of the smart home system.

[0183] In some examples, during emergency responses, such as when a user issues an emergency voice command like, "Turn on the smoke alarm, the kitchen is on fire!", the system prioritizes the smoke alarm based on priority calculations. In this case, the control device can use adaptive network configuration to configure smart home devices, prioritizing the connection and configuration of the smoke alarm to ensure a rapid response and timely alarm, thus protecting home safety. Alternatively, in scenarios where a user urgently needs device functionality, such as in cold weather when a user says, "I'm so cold, turn on the heater," the control device, through priority evaluation and calculation, determines that the heater has a high priority. Then, during the adaptive network configuration phase, the control device can connect the heater to the network first, allowing it to quickly start working and provide a warm environment for the user.

[0184] In scenarios involving device reconnection after changes in the network environment, such as when the home network router is upgraded or replaced, all smart home devices need to reconnect to the new network. In this case, the system will prioritize the devices based on previously calculated priorities; for example, smart locks (related to home security) have a higher priority, so the system will first configure and connect the smart locks to the network to ensure that home security functions are restored as quickly as possible.

[0185] In scenarios involving reconnection after device malfunction and repair, assuming a smart camera has failed and been repaired, the system will adaptively configure the network according to priority when reconnecting to the smart home system. If the smart camera has a higher priority in a security monitoring scenario, it will be configured first, allowing it to quickly return to working status and ensuring the continuity of home monitoring.

[0186] In practice, although devices are typically configured with a network upon initial use, subsequent network configurations are still required. For example, regarding network changes: when a home network is upgraded from Wi-Fi 5 to Wi-Fi 6, the network name, password, or security protocol may change. Take a smart refrigerator as an example; it was previously connected to a Wi-Fi 5 network, and now it needs to be reconfigured to connect to the new Wi-Fi 6 network to continue using smart functions such as remotely monitoring the food inside. Another example is device malfunction recovery: if a smart light experiences a software malfunction and the user performs a factory reset, the device's network configuration information is cleared. In this case, the smart light needs to be reconfigured to reconnect to the smart home system and work collaboratively with other devices in the system, such as adjusting brightness based on ambient light and user voice commands.

[0187] Furthermore, during network configuration, control devices can employ appropriate network protocols and technologies to ensure connection stability and reliability. For example, using advanced wireless network technologies such as Wi-Fi 6 can improve network speed and stability, reducing interruptions and errors during configuration. Additionally, for high-priority devices, priority bandwidth allocation can be implemented to ensure rapid connection and normal operation. Simultaneously, for critical devices, backup connection methods, such as Bluetooth or wired connections, can be configured to address network failures; this invention does not impose limitations on these provisions.

[0188] Optionally, during the normal operation of the smart home system, the control device can also dynamically adjust the network priority of each smart home device. Specifically, as the environment changes or new voice commands are received from the user, the control device can continuously adjust the network priority of the devices. For example, when the ambient temperature drops, the priority of the air conditioner may decrease, while the priority of other devices may increase accordingly. Simultaneously, the control device can continuously monitor changes in network status. If network latency improves or worsens, the device priority is adjusted promptly. Specifically, by continuously detecting the current network latency corresponding to the target smart home device, if the current network latency of the target smart home device is less than a preset network latency threshold, the current network weight value of the target smart home device is increased according to a preset adjustment ratio to obtain the target network weight value for the target smart home device. Alternatively, the current network weight value can be adjusted to a preset network weight value, which is the network weight value corresponding to the target smart home device when there is no network latency. For example, if the network latency in a certain area suddenly decreases, the priority of devices in that area can be reassessed, and devices whose priority was reduced due to network latency can be reconsidered for connection.

[0189] In addition, user habits and historical data can be analyzed regularly to further optimize priority evaluation metrics and weights. For example, if it is found that users frequently use a certain device during a specific time period, the device's priority can be appropriately increased during that time period.

[0190] In one example, refer to Figure 2 This diagram illustrates the device network configuration process provided in this embodiment of the invention. During the network configuration process for smart home devices, the smart home system can dynamically collect environmental perception data and collect and recognize user-input voice commands. Then, based on the environmental perception data and voice commands, priority evaluation indicators can be determined, and priority calculations can be performed in conjunction with network latency to obtain the corresponding network configuration priority for each smart home device. The smart home system can then adaptively configure the network for smart home devices based on the network configuration priority. Furthermore, in subsequent processes, as the environment changes or new voice commands emerge, the network configuration priority of the devices is continuously adjusted to ensure the rationality of network resource allocation, enabling the smart home system to more flexibly adapt to different usage scenarios and changing needs.

[0191] It should be noted that the embodiments of the present invention include, but are not limited to, the examples described above. It is understood that those skilled in the art can make further settings according to actual needs under the guidance of the ideas in the embodiments of the present invention, and the present invention does not limit such settings.

[0192] In this embodiment of the invention, a control device is applied to a smart home system, which also includes smart home devices and sensors. The control device can acquire environmental data collected by the sensors and voice commands input by the user. Then, it acquires the network parameters corresponding to the smart home devices in the home network. Based on the voice commands and / or environmental data and network parameters, it prioritizes the smart home devices and determines their corresponding network configuration priorities. By combining voice commands, environmental data, and network parameters, a more comprehensive and accurate basis is provided for determining the network configuration priorities of smart home devices. Thus, during the network configuration process, the control device can respond to the detection of adaptive network configuration commands for smart home devices and connect each smart home device to the home network sequentially according to its network configuration priority. By configuring each smart home device according to its network configuration priority, adaptive network configuration is achieved while ensuring the overall connection speed and response time of the smart home devices, ensuring the rationality of network resource allocation, and enabling the smart home system to more flexibly adapt to different usage scenarios and changing needs.

[0193] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the following examples are provided for illustrative purposes:

[0194] Imagine a smart home scenario where devices such as smart air conditioners, smart lights, smart curtains, smart speakers, and air purifiers are installed. Among them:

[0195] Environmental perception: The current indoor temperature is 30 degrees Celsius, the lighting is strong, and the air quality is average.

[0196] For voice commands: The user says, "It's too hot, turn on the air conditioner." In this embodiment, the temperature sensor first detects that the indoor temperature is high, and simultaneously receives the user's voice command to turn on the air conditioner. According to the priority evaluation index, since the ambient temperature is high and the user has a clear need to turn on the air conditioner, the connection priority of the smart air conditioner is set to the highest. Then, the control device can further consider network latency. Using network monitoring tools, it finds that the network latency in the area where the smart air conditioner is located is 50ms, the network latency in the area where the smart light is located is 30ms, the network latency in the area where the smart curtain is located is 40ms, the network latency in the area where the smart speaker is located is 80ms, and the network latency in the area where the air purifier is located is 60ms. A network latency threshold of 70ms is set, and the priority of devices exceeding this threshold will be appropriately reduced. At this time, the priority evaluation formula is calculated as follows:

[0197] Assume that the weight of environmental awareness is 0.4, the weight of voice commands is 0.5, and the weight of network latency is 0.1.

[0198] For a smart air conditioner, the environmental factor score (temperature factor) is 0.8, the voice command score (matching degree with user command) is 0.9, and the network latency score (score corresponding to 50ms) is 0.8. Therefore, the priority score for the smart air conditioner is: 0.4×0.8 + 0.5×0.9 + 0.1×0.8 = 0.85.

[0199] For smart lights, the environmental factor score (lighting factor) is 0.6, the voice command score (not directly related to user commands, assumed to be 0.3), and the network latency score (score corresponding to 30ms) is 0.9. Therefore, the priority score for smart lights is: 0.4 × 0.6 + 0.5 × 0.3 + 0.1 × 0.9 = 0.48. This process is repeated for other devices. Based on the calculation results, the smart air conditioner has the highest priority, so the algorithm will first connect it to the network to ensure it can respond and start working as quickly as possible to lower the indoor temperature. Then, smart lights, smart curtains, and other devices will be connected to the network in sequence. Smart speakers, due to their higher network latency, have a relatively lower priority and can be connected to the network after other devices have been connected.

[0200] If, after some time, the indoor temperature drops to a comfortable range, and the user issues a voice command to "dim the lights," the algorithm will recalculate the device priorities. Due to the temperature drop, the smart air conditioner's priority decreases, while the smart lights' priority increases. Simultaneously, network latency is considered again, selecting the path with lower latency for connection. If the network status changes at this point—for example, the network latency in the smart speaker's area decreases to 60ms, while the network latency in the smart curtains' area increases to 50ms—then the priority scores for each device will be adjusted accordingly during the recalculation, and network connections will be configured based on the new priorities.

[0201] By combining voice commands, environmental data, and network parameters, a more comprehensive and accurate basis is provided for determining the network configuration priority of smart home devices. During the network configuration process, the control device connects each smart home device to the home network in sequence according to the network configuration priority. By configuring each smart home device according to the network configuration priority, adaptive network configuration can be achieved while ensuring the overall connection speed and response time of smart home devices. This ensures the rational allocation of network resources and enables the smart home system to adapt more flexibly to different usage scenarios and changing needs.

[0202] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0203] Reference Figure 3 This diagram illustrates a structural block diagram of a network distribution device provided in an embodiment of the present invention. This device is applied to a control device in a smart home system, which also includes smart home devices and sensors. Specifically, it may include the following modules:

[0204] The data acquisition module 301 is used to acquire environmental data collected by the sensor and voice commands input by the user;

[0205] The network parameter acquisition module 302 is used to acquire the network parameters corresponding to the smart home device in the home network it is in.

[0206] The priority determination module 303 is used to assign priority to the smart home devices based on the voice command and / or the environmental data and the network parameters, and to determine the network configuration priority corresponding to the smart home devices;

[0207] The network configuration module 304 is used to respond to the detection of an adaptive network configuration command for the smart home devices and connect each of the smart home devices to the home network in sequence according to the network configuration priority.

[0208] In some feasible embodiments, the distribution network module 304 is specifically used for:

[0209] Obtain the command type corresponding to the voice command, the network status corresponding to the home network, and the device status corresponding to the smart home device;

[0210] If the instruction type meets the first preset condition, or the network status meets the second preset condition, or the device status meets the third preset condition, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0211] In some feasible embodiments, the distribution network module 304 is specifically used for:

[0212] If the instruction type indicates that the voice instruction is an emergency instruction, then each of the smart home devices will be connected to the home network in sequence according to the network allocation priority.

[0213] In some feasible embodiments, the distribution network module 304 is specifically used for:

[0214] If the network status indicates that the home network is undergoing a network upgrade or update, then each of the smart home devices will be connected to the home network in sequence according to the network configuration priority.

[0215] In some feasible embodiments, the distribution network module 304 is specifically used for:

[0216] If the device status indicates that the smart home device has recovered from a fault and reconnected to the home network, then each smart home device will be connected to the home network in sequence according to the network configuration priority.

[0217] In some feasible embodiments, the priority determination module 303 is specifically used for:

[0218] Identify the target smart home device corresponding to the voice command and / or the environmental data;

[0219] The target smart home device is weighted using the voice command to obtain the target voice command weight value of the target smart home device, and / or the target smart home device is weighted using the environmental data to obtain the target environmental weight value of the target smart home device.

[0220] The target smart home device is weighted according to the network parameters to determine the target network weight value corresponding to the target smart home device.

[0221] The target smart home device's network priority is calculated using the target voice command weight value and / or the target environment weight value, as well as the target network weight value.

[0222] In some feasible embodiments, the target smart home device includes a first smart home device corresponding to the voice command, and the priority determination module 303 is specifically used for:

[0223] Recognize the voice command and obtain the command type corresponding to the voice command;

[0224] If the instruction type indicates that the voice instruction is an emergency instruction, then a target voice instruction weight value corresponding to the emergency instruction is configured for the first smart home device, and the target voice instruction weight value is higher than the voice instruction weight values ​​corresponding to other smart home devices.

[0225] In some feasible embodiments, the target smart home device includes a second smart home device corresponding to the environmental data, and the priority determination module 303 is specifically used for:

[0226] If the environmental data meets the preset conditions, then the second smart home device is configured with a target environmental weight value corresponding to the environmental data, and the target environmental weight value is higher than the environmental weight values ​​corresponding to other smart home devices.

[0227] In some feasible embodiments, the environmental data includes at least one of temperature, light intensity, humidity, carbon dioxide concentration, and organic compound concentration; the smart home devices include at least a temperature control device, a humidity control device, an air quality control device, and smart curtains; and the priority determination module 303 is specifically used for:

[0228] If the temperature value is greater than or equal to the first preset temperature threshold, then the temperature control device is configured with a first environmental weight value corresponding to the temperature value;

[0229] If the temperature value is less than the second preset temperature threshold, then the temperature control device is configured with a second environmental weight value corresponding to the temperature value, wherein the first preset temperature threshold is greater than the second preset temperature threshold;

[0230] If the humidity value is greater than or equal to the first preset humidity threshold, then the humidity regulating device is configured with a third environmental weight value corresponding to the temperature value;

[0231] If the humidity value is less than the second preset humidity threshold, then the humidity regulating device is configured with a fourth environmental weight value corresponding to the temperature value, and the first preset humidity threshold is greater than the second preset humidity threshold.

[0232] If the light intensity is greater than or equal to the first preset light threshold, then the smart curtain is configured with a fourth environmental weight value corresponding to the temperature value;

[0233] If the light intensity is less than the second preset light threshold, then the smart curtain is configured with a fifth environmental weight value corresponding to the temperature value, and the first preset light threshold is greater than the second preset light threshold.

[0234] If the carbon dioxide concentration is greater than or equal to a first preset concentration threshold, and / or the organic compound concentration is greater than or equal to a second preset concentration threshold, then the air quality control device is configured with a sixth environmental weight value corresponding to the carbon dioxide concentration and / or the organic compound concentration.

[0235] In some feasible embodiments, the target smart home device includes a third smart home device corresponding to the voice command and the environmental data, and the priority determination module 303 is specifically used for:

[0236] Recognize the voice command and obtain the command type corresponding to the voice command;

[0237] If the instruction type indicates that the voice instruction is an emergency instruction, then configure a first voice instruction weight value corresponding to the emergency instruction for the third smart home device;

[0238] If the instruction type indicates that the voice instruction is a regular instruction, then a second voice instruction weight value corresponding to the emergency instruction is configured for the third smart home device, and the first voice instruction weight value is greater than the second voice instruction weight value;

[0239] If the environmental data meets the preset conditions, then the third smart home device is configured with a first environmental weight value corresponding to the environmental data;

[0240] If the environmental data does not meet the preset conditions, then the third smart home device is configured with a second environmental weight value corresponding to the environmental data, wherein the first environmental weight value is greater than the second environmental weight value.

[0241] In some feasible embodiments, the network parameters include the network latency corresponding to the smart home device, and the priority determination module 303 is specifically used for:

[0242] Obtain the current network weight value corresponding to the target smart home device;

[0243] If the network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0244] In some feasible embodiments, the priority determination module 303 is further configured to:

[0245] If the target smart home device is accessing the home network for the first time, a test data packet is sent to the target smart home device, and the round-trip time corresponding to the test data packet is obtained;

[0246] Determine the target network latency corresponding to the round-trip time;

[0247] If the target network latency is less than or equal to a preset network latency threshold, the current network weight value is reduced according to a preset adjustment ratio to obtain the target network weight value corresponding to the target smart home device.

[0248] In some feasible embodiments, it also includes:

[0249] A network latency detection module is used to continuously detect the current network latency corresponding to the target smart home device;

[0250] The weight adjustment module is used to increase the current network weight value of the target smart home device according to a preset adjustment ratio if the current network latency corresponding to the target smart home device is less than the preset network latency threshold, so as to obtain the target network weight value corresponding to the target smart home device, or to adjust the current network weight value to a preset network weight value, wherein the preset network weight value is the network weight value corresponding to the target smart home device when no network latency occurs.

[0251] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0252] In addition, this invention also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above-described network distribution method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0253] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the network distribution method embodiments described above, achieving the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0254] Figure 4 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0255] The electronic device 400 includes, but is not limited to, components such as: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410, and a power supply 411. Those skilled in the art will understand that the electronic device structure involved in the embodiments of the present invention does not constitute a limitation on the electronic device. An electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. In the embodiments of the present invention, the electronic device includes, but is not limited to, mobile phones, tablet computers, laptop computers, PDAs, in-vehicle terminals, wearable devices, and pedometers.

[0256] It should be understood that, in this embodiment of the invention, the radio frequency unit 401 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink data from the base station and processes it with the processor 410; additionally, it transmits uplink data to the base station. Typically, the radio frequency unit 401 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, etc. Furthermore, the radio frequency unit 401 can also communicate with networks and other devices through a wireless communication system.

[0257] The electronic device provides users with wireless broadband internet access through network module 402, such as helping users send and receive emails, browse web pages, and access streaming media.

[0258] The audio output unit 403 can convert audio data received by the radio frequency unit 401 or the network module 402 or stored in the memory 409 into audio signals and output them as sound. Furthermore, the audio output unit 403 can also provide audio output related to specific functions performed by the electronic device 400 (e.g., call signal reception sound, message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, and a receiver, etc.

[0259] Input unit 404 is used to receive audio or video signals. Input unit 404 may include a graphics processing unit (GPU) 4041 and a microphone 4042. The GPU 4041 processes image data of still images or videos acquired by an image capture device (such as a camera) in video capture mode or image capture mode. The processed image frames can be displayed on display unit 406. The image frames processed by GPU 4041 can be stored in memory 409 (or other storage medium) or transmitted via radio frequency unit 401 or network module 402. Microphone 4042 can receive sound and process such sound into audio data. The processed audio data can be converted into a format that can be transmitted to a mobile communication base station via radio frequency unit 401 in telephone call mode.

[0260] The electronic device 400 also includes at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 4061 according to the ambient light level, and the proximity sensor can turn off the display panel 4061 and / or backlight when the electronic device 400 is moved to the ear. As a type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used to identify the posture of the electronic device (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. The sensor 405 may also include a fingerprint sensor, pressure sensor, iris sensor, molecular sensor, gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc., which will not be described in detail here.

[0261] The display unit 406 is used to display information input by the user or information provided to the user. The display unit 406 may include a display panel 4061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0262] User input unit 407 can be used to receive input numerical or character information, and generate key signal inputs related to user settings and function control of electronic devices. Specifically, user input unit 407 includes a touch panel 4071 and other input devices 4072. Touch panel 4071, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near touch panel 4071). Touch panel 4071 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 410, which receives and executes commands from the processor 410. In addition, touch panel 4071 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. Besides touch panel 4071, user input unit 407 may also include other input devices 4072. Specifically, other input devices 4072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here.

[0263] Furthermore, the touch panel 4071 can cover the display panel 4061. When the touch panel 4071 detects a touch operation on or near it, it transmits the information to the processor 410 to determine the type of touch event. Subsequently, the processor 410 provides corresponding visual output on the display panel 4061 according to the type of touch event. It is understood that in one embodiment, the touch panel 4071 and the display panel 4061 are implemented as two independent components to realize the input and output functions of the electronic device. However, in some embodiments, the touch panel 4071 and the display panel 4061 can be integrated to realize the input and output functions of the electronic device. The specific implementation is not limited here.

[0264] Interface unit 408 serves as an interface for connecting external devices to electronic device 400. For example, external devices may include a wired or wireless headphone port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, and so on. Interface unit 408 can be used to receive input from external devices (e.g., data, power, etc.) and transmit the received input to one or more components within electronic device 400, or it can be used to transmit data between electronic device 400 and external devices.

[0265] The memory 409 can be used to store software programs and various data. The memory 409 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback, image playback, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). Furthermore, the memory 409 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0266] The processor 410 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 409, and by calling data stored in the memory 409, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. The processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 410.

[0267] The electronic device 400 may also include a power supply 411 (such as a battery) for supplying power to various components. Preferably, the power supply 411 can be logically connected to the processor 410 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system.

[0268] In addition, the electronic device 400 includes some functional modules not shown, which will not be described in detail here.

[0269] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0270] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0271] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

[0272] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0273] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0274] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0275] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0276] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0277] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0278] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for commissioning a device, the method comprising: The application relates to a control device applied to a smart home system, wherein the smart home system further comprises smart home devices and sensors, and the method comprises the following steps: acquiring environment data collected by the sensors and a voice instruction input by a user; acquiring network parameters corresponding to the smart home devices in a home network; performing priority allocation on the smart home devices according to the voice instruction and / or the environment data and the network parameters, and determining network configuration priorities corresponding to the smart home devices; in response to detecting an adaptive network configuration instruction for the smart home devices, sequentially connecting the smart home devices to the home network according to the network configuration priorities.

2. The method of claim 1, wherein, The step of sequentially connecting the smart home devices to the home network according to the network configuration priorities in response to detecting an adaptive network configuration instruction for the smart home devices comprises the following steps: acquiring an instruction type corresponding to the voice instruction, a network state corresponding to the home network and a device state corresponding to the smart home devices; if the instruction type meets a first preset condition, or the network state meets a second preset condition, or the device state meets a third preset condition, then sequentially connecting the smart home devices to the home network according to the network configuration priorities.

3. The method of claim 2, wherein, The step of sequentially connecting the smart home devices to the home network according to the network configuration priorities if the instruction type meets the first preset condition comprises the following step: if the instruction type represents that the voice instruction belongs to an emergency instruction, then sequentially connecting the smart home devices to the home network according to the network configuration priorities.

4. The method of claim 2, wherein, The step of sequentially connecting the smart home devices to the home network according to the network configuration priorities if the network state meets the second preset condition comprises the following step: if the network state represents that the home network is upgraded or updated, then sequentially connecting the smart home devices to the home network according to the network configuration priorities.

5. The method of claim 2, wherein, The step of sequentially connecting the smart home devices to the home network according to the network configuration priorities if the device state meets the third preset condition comprises the following step: if the device state represents that the smart home device is reconnected to the home network after fault recovery, then sequentially connecting the smart home devices to the home network according to the network configuration priorities.

6. The method of claim 1, wherein, The step of performing priority allocation on the smart home devices according to the voice instruction and / or the environment data and the network parameters, and determining network configuration priorities corresponding to the smart home devices comprises the following steps: determining a target smart home device corresponding to the voice instruction and / or the environment data; performing weight allocation on the target smart home device by using the voice instruction to obtain a target voice instruction weight value of the target smart home device, and / or performing weight allocation on the target smart home device by using the environment data to obtain a target environment weight value of the target smart home device; performing weight allocation on the target smart home device according to the network parameters to determine a target network weight value corresponding to the target smart home device. The target network weight value is used for calculation to obtain a network configuration priority of the target smart home device.

7. The method of claim 6, wherein, The target smart home device includes a first smart home device corresponding to the voice instruction, and the target voice instruction weight value of the first smart home device is obtained by using the voice instruction to perform weight distribution on the target smart home device. The voice instruction is identified to obtain an instruction type corresponding to the voice instruction. If the instruction type represents that the voice instruction is an emergency instruction, a target voice instruction weight value corresponding to the emergency instruction is configured for the first smart home device, and the target voice instruction weight value is higher than a voice instruction weight value corresponding to other smart home devices.

8. The method of claim 6, wherein, The target smart home device includes a second smart home device corresponding to the environment data, and the target environment weight value of the second smart home device is obtained by using the environment data to perform weight distribution on the target smart home device. If the environment data meets a preset condition, a target environment weight value corresponding to the environment data is configured for the second smart home device, and the target environment weight value is higher than an environment weight value corresponding to other smart home devices.

9. The method of claim 8, wherein, The environment data at least includes one of a temperature value, an illumination intensity, a humidity value, a carbon dioxide concentration and an organic compound concentration, and the smart home device at least includes a temperature control device, a humidity adjusting device, an air quality adjusting device and a smart curtain. If the temperature value is greater than or equal to a first preset temperature threshold, a first environment weight value corresponding to the temperature value is configured for the temperature control device. If the temperature value is less than a second preset temperature threshold, a second environment weight value corresponding to the temperature value is configured for the temperature control device, and the first preset temperature threshold is greater than the second preset temperature threshold. If the humidity value is greater than or equal to a first preset humidity threshold, a third environment weight value corresponding to the temperature value is configured for the humidity adjusting device. If the humidity value is less than a second preset humidity threshold, a fourth environment weight value corresponding to the temperature value is configured for the humidity adjusting device, and the first preset humidity threshold is greater than the second preset humidity threshold. If the illumination intensity is greater than or equal to a first preset illumination threshold, a fourth environment weight value corresponding to the temperature value is configured for the smart curtain. If the illumination intensity is less than a second preset illumination threshold, a fifth environment weight value corresponding to the temperature value is configured for the smart curtain, and the first preset illumination threshold is greater than the second preset illumination threshold. If the carbon dioxide concentration is greater than or equal to a first preset concentration threshold and / or the organic compound concentration is greater than or equal to a second preset concentration threshold, a sixth environment weight value corresponding to the carbon dioxide concentration and / or the organic compound concentration is configured for the air quality adjusting device.

10. The method of claim 6, wherein, The target smart home device includes a third smart home device corresponding to the voice instruction and the environment data, the target smart home device is assigned weights by using the voice instruction to obtain a target voice instruction weight value of the target smart home device, and the target smart home device is assigned weights by using the environment data to obtain a target environment weight value of the target smart home device, comprising: identifying the voice instruction to obtain an instruction type corresponding to the voice instruction; if the instruction type represents that the voice instruction is an emergency instruction, a first voice instruction weight value corresponding to the emergency instruction is configured for the third smart home device; if the instruction type represents that the voice instruction is a regular instruction, a second voice instruction weight value corresponding to the emergency instruction is configured for the third smart home device, and the first voice instruction weight value is greater than the second voice instruction weight value; if the environment data meets a preset condition, a first environment weight value corresponding to the environment data is configured for the third smart home device; if the environment data does not meet the preset condition, a second environment weight value corresponding to the environment data is configured for the third smart home device, and the first environment weight value is greater than the second environment weight value.

11. The method of claim 6, wherein, The network parameter includes a network delay corresponding to the smart home device, and the target network weight value corresponding to the target smart home device is determined by assigning weights to the target smart home device according to the network parameter, comprising: obtaining a current network weight value corresponding to the target smart home device; if the network delay is less than or equal to a preset network delay threshold, the current network weight value is reduced by a preset adjustment ratio to obtain a target network weight value corresponding to the target smart home device.

12. The method of claim 11, wherein, The target network weight value corresponding to the target smart home device is determined by assigning weights to the target smart home device according to the network parameter, further comprising: if the target smart home device is accessed to the home network for the first time, a test data packet is sent to the target smart home device, and a round-trip time corresponding to the test data packet is obtained; determining a target network delay corresponding to the round-trip time; if the target network delay is less than or equal to a preset network delay threshold, the current network weight value is reduced by a preset adjustment ratio to obtain a target network weight value corresponding to the target smart home device.

13. The method according to claim 11 or 12, characterized in that, Further comprising: continuously detecting the current network delay corresponding to the target smart home device; if the current network delay corresponding to the target smart home device is less than the preset network delay threshold, the current network weight value of the target smart home device is increased by a preset adjustment ratio to obtain a target network weight value corresponding to the target smart home device, or the current network weight value is adjusted to a preset network weight value, and the preset network weight value is a network weight value corresponding to the target smart home device when no network delay occurs.

14. A commissioning device of a device, the commissioning device comprising: The application relates to a control device applied to an intelligent home system, wherein the intelligent home system further comprises intelligent home devices and sensors, and the device comprises: a data acquisition module for acquiring environmental data collected by the sensors and voice instructions input by a user; a network parameter acquisition module for acquiring network parameters corresponding to the intelligent home devices in a home network; a priority determination module for performing priority allocation on the intelligent home devices according to the voice instructions and / or the environmental data and the network parameters, and determining network configuration priorities corresponding to the intelligent home devices; a network configuration module for sequentially connecting the intelligent home devices to the home network according to the network configuration priorities in response to detecting adaptive network configuration instructions for the intelligent home devices.

15. An electronic device, comprising: The application relates to a control device applied to an intelligent home system, wherein the intelligent home system further comprises intelligent home devices and sensors, and the device comprises: a data acquisition module for acquiring environmental data collected by the sensors and voice instructions input by a user; a network parameter acquisition module for acquiring network parameters corresponding to the intelligent home devices in a home network; a priority determination module for performing priority allocation on the intelligent home devices according to the voice instructions and / or the environmental data and the network parameters, and determining network configuration priorities corresponding to the intelligent home devices; a network configuration module for sequentially connecting the intelligent home devices to the home network according to the network configuration priorities in response to detecting adaptive network configuration instructions for the intelligent home devices. The application relates to a control device applied to an intelligent home system, wherein the intelligent home system further comprises intelligent home devices and sensors, and the device comprises: a data acquisition module for acquiring environmental data collected by the sensors and voice instructions input by a user; a network parameter acquisition module for acquiring network parameters corresponding to the intelligent home devices in a home network; a priority determination module for performing priority allocation on the intelligent home devices according to the voice instructions and / or the environmental data and the network parameters, and determining network configuration priorities corresponding to the intelligent home devices; a network configuration module for sequentially connecting the intelligent home devices to the home network according to the network configuration priorities in response to detecting adaptive network configuration instructions for the intelligent home devices. The application relates to a control device applied to an intelligent home system, wherein the intelligent home system further comprises intelligent home devices and sensors, and the device comprises: a data acquisition module for acquiring environmental data collected by the sensors and voice instructions input by a user; a network parameter acquisition module for acquiring network parameters corresponding to the intelligent home devices in a home network; a priority determination module for performing priority allocation on the intelligent home devices according to the voice instructions and / or the environmental data and the network parameters, and determining network configuration priorities corresponding to the intelligent home devices; a network configuration module for sequentially connecting the intelligent home devices to the home network according to the network configuration priorities in response to detecting adaptive network configuration instructions for the intelligent home devices. The application relates to a control device applied to an intelligent home system, wherein the intelligent home system further comprises intelligent home devices and sensors, and the device comprises: a data acquisition module for acquiring environmental data collected by the sensors and voice instructions input by a user; a network parameter acquisition module for acquiring network parameters corresponding to the intelligent home devices in a home network; a priority determination module for performing priority allocation on the intelligent home devices according to the voice instructions and / or the environmental data and the network parameters, and determining network configuration priorities corresponding

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