Configuration method of Internet of Things devices based on router and dual-band wireless router

Abstract

The present invention discloses a configuration method for an Internet of Things device based on a router and a dual-band wireless router. The method comprises: firstly receiving a connection request of each Internet of Things device, wherein the connection request carries a preset tag of each Internet of Things device, determining a connectable frequency band of each Internet of Things device according to the preset tag of each Internet of Things device, selecting a network frequency band for each Internet of Things device in at least one connectable frequency band, acquiring a communication path data set between each Internet of Things device, optimizing the communication path data set by using a pre-built communication path configuration model, updating the connection frequency band between each Internet of Things device and the router according to the optimization result, and performing data transmission. By optimizing the communication path data set of the Internet of Things device by using the pre-built communication path configuration model, it is possible to improve the Internet experience of users.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication, and in particular to a configuration method of a router-based Internet of Things device and a dual-band wireless router. Background Art

[0002] Wireless routers, like other wireless products, belong to the radio frequency (RF) system and need to work within a certain frequency range to communicate with other devices. We call this frequency range the working frequency band of wireless routers. However, different products use different network standards, so the working frequency bands are also different. The working frequency bands of wireless routers are generally divided into two frequency bands: 2.4GHz and 5.0GHz. 2.4GHz was the frequency band commonly used by early wireless routers and has continued to this day; with the development of communication technology, 5.0GHz has also begun to be widely used, and combined with 2.4GHz to form a dual-band wireless router.

[0003] For dual-band wireless routers, when the hotspot function is activated, the working frequency band of the wireless access point needs to be set. When users are not clear about the working frequency band of IoT devices, they usually set the working frequency band of the wireless access point to 2.4GHz or 5.0GHz, which will cause the 2.4GHz or 5.0GHz channels to be used in large quantities, resulting in poor Internet experience for users and congestion of the communication path of all IoT devices in a certain frequency band. This has become a problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of the present invention is to provide a configuration method for an Internet of Things device based on a router and a dual-band wireless router to solve the deficiencies in the prior art. By optimizing the communication path data set of the Internet of Things device using a pre-built communication path configuration model, it can improve the user's Internet experience.

[0005] An embodiment of the present application provides a configuration method for an Internet of Things device based on a router, the method comprising:

[0006] Receive a connection request from each IoT device, wherein the connection request carries a preset tag of each IoT device;

[0007] Determine, according to preset tags of each of the IoT devices, a connectable frequency band of each of the IoT devices, wherein the connectable frequency band includes a first frequency band and a second frequency band of a router;

[0008] In at least one connectable frequency band, select a network frequency band for each of the IoT devices, and obtain a communication path data set between each of the IoT devices;

[0009] The communication path data set is optimized using a pre-built communication path configuration model, and according to the optimization result, the connection frequency band between each of the IoT devices and the router is updated, and data transmission is performed.

[0010] Optionally, the preset label of the Internet of Things device includes: a unique identification code of the Internet of Things device and / or a physical address of the Internet of Things device.

[0011] Optionally, the connectable frequency band includes a first frequency band and a second frequency band of a router, wherein the first frequency band is 2.4 GHz and the second frequency band is 5.0 GHz.

[0012] Optionally, selecting a network frequency band for each of the IoT devices respectively and acquiring a communication path data set between each of the IoT devices includes:

[0013] Detect the signal strength of each connectable frequency band, and determine the network frequency band whose signal strength is greater than or equal to a preset threshold as the selectable network frequency band;

[0014] Obtaining the power and power consumption of the selectable network frequency band;

[0015] Determine the signal quality of the IoT device accessing the network frequency band and the corresponding network frequency band according to the corresponding relationship between the power and the power consumption of the selectable network frequency band;

[0016] A communication path data set is generated based on the signal quality of the IoT device and the corresponding network frequency band.

[0017] Optionally, before optimizing the communication path dataset using the pre-built communication path configuration model, the method further includes:

[0018] Using the communication path data set to obtain a plurality of training models for communication path optimization;

[0019] Calculating the difference coefficients between the training models and forming an objective function;

[0020] The multiple training models are processed according to the objective function to obtain a trained communication path configuration model.

[0021] Optionally, the trained communication path configuration model includes: a data pre-processing module, a data feature module, a data post-processing module, and a data fusion module;

[0022] The data pre-processing module is used to extract features from the input feature data of the signal quality of the IoT device and the corresponding network frequency band to obtain a first data feature of the pre-processing;

[0023] The data feature module is used to obtain a second data feature using a network data transmission mechanism for the obtained first data feature of the pre-processing, and to concatenate the second data feature with the corresponding first data feature of the pre-processing to obtain a mixed feature;

[0024] The data post-processing module is used to perform feature extraction on the mixed features to obtain a post-processed third data feature;

[0025] The data fusion module is used to generate a communication path configuration data fusion feature according to the post-processed third data feature.

[0026] Optionally, after updating the connection frequency band between each of the IoT devices and the router according to the optimization result and performing data transmission, the method further includes:

[0027] According to the connection frequency band between each of the IoT devices and the router, the communication path data set is updated and stored in a preset storage space;

[0028] Creating an index corresponding to each of the communication path data sets to form an identifiable path;

[0029] Based on the identifiable path, respond to an access request from a new IoT device and determine an optimal frequency band for connecting to the new IoT device.

[0030] Another embodiment of the present application provides a configuration device for an Internet of Things device based on a router, the device comprising:

[0031] A receiving module, used to receive connection requests from various IoT devices, wherein the connection requests carry preset tags for the various IoT devices;

[0032] A determination module, configured to determine a connectable frequency band of each of the IoT devices according to a preset tag of each of the IoT devices, wherein the connectable frequency band includes a first frequency band and a second frequency band of a router;

[0033] An acquisition module, configured to select a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquire a communication path data set between each of the IoT devices;

[0034] The optimization module is used to optimize the communication path data set using a pre-built communication path configuration model, and according to the optimization result, update the connection frequency band between each of the IoT devices and the router, and perform data transmission.

[0035] Optionally, the acquisition module includes:

[0036] A detection unit, used to detect the signal strength of each connectable frequency band, and determine the network frequency band with a signal strength greater than or equal to a preset threshold as a selectable network frequency band;

[0037] An acquisition unit, used to acquire the power and power consumption of the selectable network frequency band;

[0038] A determination unit, configured to determine the IoT device accessing the network frequency band and the signal quality of the corresponding network frequency band according to the corresponding relationship between the power and the power consumption of the selectable network frequency band;

[0039] A generating unit is used to generate a communication path data set based on the signal quality of the IoT device and the corresponding network frequency band.

[0040] Optionally, the device further comprises:

[0041] A first obtaining module, used for obtaining a plurality of training models for communication path optimization using the communication path data set;

[0042] A calculation module, used to calculate the difference coefficients between the training models and form an objective function;

[0043] The second obtaining module is used to process the multiple training models according to the objective function to obtain a trained communication path configuration model.

[0044] Optionally, after the optimization module, the device further includes:

[0045] An updating module, used to update the communication path data set according to the connection frequency band between each of the IoT devices and the router, and store it in a preset storage space;

[0046] A creation module, used to create an index corresponding to each of the communication path data sets to form an identifiable path;

[0047] A response module is used to respond to an access request of a new IoT device based on the identifiable path and determine an optimal frequency band for connecting to the new IoT device.

[0048] Another embodiment of the present application provides a dual-band wireless router, which includes a central processing unit, a wireless communication module and a chip, wherein the wireless communication module is used to wirelessly communicate with an Internet of Things device, the chip is used to forward communication path data, and the central processing unit is used to process the communication path data to implement any of the methods described above.

[0049] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to execute any of the above methods when running.

[0050] Yet another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the methods described above.

[0051] Compared with the prior art, the present invention first receives connection requests from various Internet of Things devices, wherein the connection requests carry preset tags for each of the Internet of Things devices, and determines connectable frequency bands for each Internet of Things device according to the preset tags for each Internet of Things device, wherein the connectable frequency bands include a first frequency band and a second frequency band of a router, and in at least one connectable frequency band, selects a network frequency band for each Internet of Things device, obtains a communication path data set with each Internet of Things device, optimizes the communication path data set using a pre-built communication path configuration model, updates the connection frequency bands between each Internet of Things device and the router according to the optimization result, and performs data transmission. By optimizing the communication path data set of the Internet of Things device using the pre-built communication path configuration model, it can improve the user's Internet experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A hardware structure block diagram of a computer terminal for a configuration method of an Internet of Things device based on a router provided by an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of a flow chart of a configuration method of an Internet of Things device based on a router provided in an embodiment of the present invention;

[0054] Figure 3 A schematic diagram of the structure of a configuration device for an Internet of Things device based on a router provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0056] The embodiment of the present invention first provides a configuration method for an Internet of Things device based on a router. The method can be applied to electronic devices, such as computer terminals, specifically ordinary computers, quantum computers, etc.

[0057] The following describes it in detail by taking running on a computer terminal as an example. Figure 1 The hardware structure block diagram of a computer terminal of a configuration method of an Internet of Things device based on a router provided by an embodiment of the present invention. Figure 1 As shown, the computer terminal may include one or more ( Figure 1Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the computer terminal may also include a transmission device 106 for communication functions and an input and output device 108. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0058] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / modules corresponding to the configuration method of the Internet of Things device based on the router in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implementing the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0059] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0060] See also Figure 2 , Figure 2 A flowchart of a configuration method for an Internet of Things device based on a router provided in an embodiment of the present invention may include the following steps:

[0061] S201: Receive connection requests from various IoT devices, where the connection requests carry preset tags for the various IoT devices.

[0062] In recent years, with the increasing application of IoT devices, the control and management of IoT devices is an important means to realize intelligent applications in the field of IoT. In order to realize the control function of IoT devices, it is necessary to connect the router and IoT devices first.

[0063] The router receives connection requests from various IoT devices. Its main purpose is to provide users with Internet access and wireless coverage. At the same time, the router itself can be regarded as a repeater, forwarding broadband network signals to nearby IoT devices through antennas. For example, IoT devices can be computers, tablets, smart bracelets, smart watches, etc., or any device that needs to be connected to the network, or all devices with WIFI function.

[0064] It should be noted that the preset tag of the IoT device may include: a unique identification code of the IoT device and / or a physical address of the IoT device. In an application scenario of an IoT device, the IoT device connected in the current application scenario and the connection frequency band supported by the IoT device are first determined by the unique identification code of the IoT device and / or the physical address of the IoT device.

[0065] S202: Determine a connectable frequency band for each of the IoT devices according to a preset tag of each of the IoT devices, where the connectable frequency band includes a first frequency band and a second frequency band of a router.

[0066] Specifically, the connectable frequency band includes a first frequency band and a second frequency band of the router, wherein the first frequency band is 2.4 GHz and the second frequency band is 5.0 GHz.

[0067] Router transmission uses frequency bands to send data. Frequency bands are also called channels. They are data signal transmission channels that use wireless signals as transmission media. Routers can work in single-frequency and dual-frequency. For example, a single-frequency router can use 2.4Ghz or 5.0Ghz to transmit data, and a dual-frequency router uses both 2.4Ghz and 5.0Ghz frequency bands to transmit data. The routers used in this application are all dual-frequency wireless routers.

[0068] S203: Selecting a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquiring a communication path data set between each of the IoT devices.

[0069] Specifically, selecting a network frequency band for each of the IoT devices and acquiring a communication path data set between each of the IoT devices may include:

[0070] Step 1: Detect the signal strength of each connectable frequency band, and determine the network frequency band with a signal strength greater than or equal to a preset threshold as a selectable network frequency band.

[0071] Specifically, each of the several connectable frequency bands is a network frequency band to which the IoT device can connect. In other words, the IoT device can work in each of the several connectable frequency bands. In one implementation of this embodiment, the several connectable frequency bands can be network frequency bands configured by the IoT device when it receives a connection instruction. In practical applications, the signal strength corresponding to each of the connectable frequency bands can be the network signal strength of each connectable frequency band obtained by detecting the signal strength of each connectable frequency band when the router receives the connection instruction. In a specific implementation, the network signal strength of each connectable frequency band can also be obtained and recorded by the router when the connectable frequency band is obtained. It can be understood that in the process of the IoT device connecting to the network, the router will obtain and record the network information strength corresponding to each of the connectable frequency bands in the current network environment, so that when the connection instruction is received, the network signal strength of each connectable frequency band can be quickly determined, and the network frequency band with a signal strength greater than or equal to a preset threshold is determined as a selectable network frequency band.

[0072] Step 2: Obtain the power and power consumption of the selectable network frequency band.

[0073] Step 3: According to the corresponding relationship between the power and power consumption of the selectable network frequency band, determine the IoT devices accessing the network frequency band and the signal quality of the corresponding network frequency band.

[0074] Step 4: Generate a communication path dataset based on the signal quality of the IoT device and the corresponding network frequency band.

[0075] Specifically, the signal loss of the selectable network frequency band will be very different when it passes through different propagation distances. The router uses a common frequency to send or receive signals, so due to the distance, it is easy for the strong signal near the ground to suppress the weak signal far away. The main purpose of determining the signal quality of the IoT devices connected to the network frequency band and the corresponding network frequency band through the power and power consumption of the selectable network frequency band is to find a transmission method with better signal quality and generate a communication path data set.

[0076] For example, for the corresponding strategy of power and power consumption of selectable network frequency bands, a collaborative corresponding algorithm based on threshold judgment or particle swarm optimization can be designed, and a complex computing service can be implemented with a preset model for corresponding analysis and evaluation. And by comprehensively considering the key information corresponding to the currently selectable network frequency band, including not only power and power consumption, but also the status of the wireless channel and the workload of the router, and weighing the latency and energy consumption of the router, the optimal communication path data set based on signal quality is obtained.

[0077] S204: Optimize the communication path data set using a pre-built communication path configuration model, update the connection frequency band between each of the IoT devices and the router according to the optimization result, and perform data transmission.

[0078] Specifically, before optimizing the communication path data set using the pre-built communication path configuration model, the method may further include:

[0079] 1. Using the communication path data set to obtain multiple training models for communication path optimization;

[0080] 2. Calculate the difference coefficient between the training models and form an objective function;

[0081] 3. Process the multiple training models according to the objective function to obtain a trained communication path configuration model.

[0082] In an optional implementation, the communication path data set is discretized to obtain a discretized communication path data set, wherein the discretized communication path data set includes multiple different attributes, each attribute corresponds to multiple feature vectors, wherein the feature vector includes IoT device information, preset label information, and signal quality information of each IoT device connected to the router, etc.; the associated parameters corresponding to each IoT device are obtained by calculating the associated parameters of each attribute feature vector; the multiple associated parameters are mapped using the initial function to obtain the target function; the target function is optimized and trained using the gradient descent algorithm to obtain a trained communication path configuration model, for example, the random gradient descent method is used for optimization, the weight attenuation coefficient is and the initial learning rate is set to a preset value, and a fixed step size attenuation method is used to optimize the parameters of the training model. Among them, the trained communication path configuration model can also be obtained by processing with an intelligent bionic optimization algorithm, because the intelligent bionic optimization algorithm is widely used in the coverage optimization strategy, positioning algorithm, network dynamic deployment, node scheduling, data fusion, reliability, etc. of the router network.

[0083] In another optional embodiment, a communication path data set is obtained, and the communication path data set is used for training to obtain a first training model and a second training model for communication path optimization, and the first training model is higher than the second training model in terms of the dimensions of the following data feature modules for communication path optimization. The feature data output by the data feature module of the first training model is subjected to normalized exponential processing to obtain a first probability distribution, and the feature data output by the data feature module of the second training model is subjected to normalized exponential processing to obtain a second probability distribution Y. The normalized exponential processing here means that the multi-classification output can be converted into a probability by an exponential function and a normalization method, which can be specifically expressed as: the multi-classification result is mapped to zero to positive infinity by an exponential function, and then normalized processing is performed to obtain an approximate probability, and the difference coefficient is calculated according to the first probability distribution X and the second probability distribution Y to form an objective function. Finally, the first training model is processed according to the objective function, and a comparison is made between the first training model and the second training model by processing, and the probability distribution information and communication path optimization information obtained after the comparison are used to train the second training model, and the objective function is used to determine the degree of training of the second training model to the first training model after dimensionality reduction processing. By judging whether the objective function converges, a trained communication path configuration model is obtained.

[0084] Specifically, the trained communication path configuration model may include: a data pre-processing module, a data feature module, a data post-processing module, and a data fusion module; the data pre-processing module is used to perform feature extraction on the feature data of the signal quality of the input IoT device and the corresponding network frequency band to obtain the first data feature of the pre-processing; the data feature module is used to use the network data transmission mechanism to obtain the second data feature for the obtained first data feature of the pre-processing, and to splice the second data feature with the corresponding first data feature of the pre-processing to obtain a mixed feature; the data post-processing module is used to perform feature extraction on the mixed feature to obtain a third data feature of the post-processing; the data fusion module is used to generate a communication path configuration data fusion feature based on the third data feature of the post-processing.

[0085] Exemplarily, the communication path configuration model may include 1 data pre-processing module, 2 data feature modules, 1 data post-processing module and 3 data fusion modules; or it may also be composed of 2 convolutional layer groups, 1 global pooling layer and 1 fully connected layer.

[0086] In an alternative embodiment, assuming that the parameter They are the number of nodes in the input layer of the data pre-processing module, the number of nodes in the middle layer of the data post-processing module, and the number of nodes in the output layer of the data fusion module of the communication path configuration model. For example, the number of nodes in the input layer of the data pre-processing module of the communication path configuration model is As well as preset weights and correction values wait. As the objective function, the communication path configuration model can be expressed mathematically as follows:

[0087]

[0088] in, Represents the data pre-processing module input layer and the The input weight vector of the intermediate layer node of the data post-processing module, Represents the middle layer node of the data post-processing module and the The output weight vector of the output layer nodes of the data fusion module, Represents the output value of the communication path configuration model.

[0089] After updating the connection frequency band between each of the IoT devices and the router according to the optimization result and performing data transmission, the method may further include:

[0090] According to the connection frequency band between each of the IoT devices and the router, the communication path data set is updated and stored in a preset storage space; an index corresponding to each of the communication path data sets is created to form an identifiable path; based on the identifiable path, an access request of a new IoT device is responded to, and the optimal frequency band for connecting to the new IoT device is determined.

[0091] Specifically, after obtaining the optimal connection frequency band of the current IoT device through the above method, the IoT device and frequency band information can be stored in the preset storage space. The purpose of this is to enable the IoT device to be directly paired and connected when it is no longer within the network coverage of the current router and needs to re-search and configure the optimal frequency band, without the need for re-verification and optimization; and it can quickly identify access requests from new IoT devices and repeat the above steps to determine the optimal frequency band for the new IoT device connection.

[0092] In an optional implementation, if the connection result of the new IoT device is abnormal, the router device can prompt the user of the connection abnormality by flashing or other means; if the connection result of the new IoT device is normal, the connection frequency band between the IoT device and the router is recorded, the communication path data set is updated and stored in the preset storage space, and the trained communication path configuration model is input to verify whether the connection frequency band of the newly connected IoT device is optimal.

[0093] Compared with the prior art, the present invention first receives connection requests from various Internet of Things devices, wherein the connection requests carry preset tags for each of the Internet of Things devices, and determines connectable frequency bands for each Internet of Things device according to the preset tags for each Internet of Things device, wherein the connectable frequency bands include a first frequency band and a second frequency band of a router, and in at least one connectable frequency band, selects a network frequency band for each Internet of Things device, obtains a communication path data set with each Internet of Things device, optimizes the communication path data set using a pre-built communication path configuration model, updates the connection frequency bands between each Internet of Things device and the router according to the optimization result, and performs data transmission. By optimizing the communication path data set of the Internet of Things device using the pre-built communication path configuration model, it can improve the user's Internet experience.

[0094] Another embodiment of the present application provides a configuration device for an Internet of Things device based on a router, which is applied to any of the above-mentioned configuration methods for an Internet of Things device based on a router, such as Figure 3 A schematic diagram of a configuration device for an Internet of Things device based on a router is shown, the device comprising:

[0095] The receiving module 301 is used to receive connection requests from various IoT devices, where the connection requests carry preset tags for the various IoT devices;

[0096] A determination module 302 is used to determine a connectable frequency band of each of the IoT devices according to a preset tag of each of the IoT devices, wherein the connectable frequency band includes a first frequency band and a second frequency band of a router;

[0097] An acquisition module 303 is used to select a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquire a communication path data set between each of the IoT devices;

[0098] The optimization module 304 is used to optimize the communication path data set using a pre-built communication path configuration model, and update the connection frequency band between each of the IoT devices and the router according to the optimization result, and perform data transmission.

[0099] Specifically, the acquisition module includes:

[0100] A detection unit, used to detect the signal strength of each connectable frequency band, and determine the network frequency band with a signal strength greater than or equal to a preset threshold as a selectable network frequency band;

[0101] An acquisition unit, used to acquire the power and power consumption of the selectable network frequency band;

[0102] A determination unit, configured to determine the IoT device accessing the network frequency band and the signal quality of the corresponding network frequency band according to the corresponding relationship between the power and the power consumption of the selectable network frequency band;

[0103] A generating unit is used to generate a communication path data set based on the signal quality of the IoT device and the corresponding network frequency band.

[0104] Specifically, the device further includes:

[0105] A first obtaining module, used for obtaining a plurality of training models for communication path optimization using the communication path data set;

[0106] A calculation module, used to calculate the difference coefficients between the training models and form an objective function;

[0107] The second obtaining module is used to process the multiple training models according to the objective function to obtain a trained communication path configuration model.

[0108] Specifically, after the optimization module, the device further includes:

[0109] An updating module, used to update the communication path data set according to the connection frequency band between each of the IoT devices and the router, and store it in a preset storage space;

[0110] A creation module, used to create an index corresponding to each of the communication path data sets to form an identifiable path;

[0111] A response module is used to respond to an access request of a new IoT device based on the identifiable path and determine an optimal frequency band for connecting to the new IoT device.

[0112] Compared with the prior art, the present invention first receives connection requests from various Internet of Things devices, wherein the connection requests carry preset tags for each of the Internet of Things devices, and determines connectable frequency bands for each Internet of Things device according to the preset tags for each Internet of Things device, wherein the connectable frequency bands include a first frequency band and a second frequency band of a router, and in at least one connectable frequency band, selects a network frequency band for each Internet of Things device, obtains a communication path data set with each Internet of Things device, optimizes the communication path data set using a pre-built communication path configuration model, updates the connection frequency bands between each Internet of Things device and the router according to the optimization result, and performs data transmission. By optimizing the communication path data set of the Internet of Things device using the pre-built communication path configuration model, it can improve the user's Internet experience.

[0113] Another embodiment of the present application provides a dual-band wireless router, which includes a central processing unit, a wireless communication module and a chip, wherein the wireless communication module is used to wirelessly communicate with an Internet of Things device, the chip is used to forward communication path data, and the central processing unit is used to process the communication path data to implement any of the methods described above.

[0114] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0115] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps:

[0116] S201: receiving connection requests from various IoT devices, wherein the connection requests carry preset tags for the various IoT devices;

[0117] S202: Determine, according to preset tags of each of the IoT devices, a connectable frequency band of each of the IoT devices, where the connectable frequency band includes a first frequency band and a second frequency band of a router;

[0118] S203: Selecting a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquiring a communication path data set between each of the IoT devices;

[0119] S204: Optimize the communication path data set using a pre-built communication path configuration model, update the connection frequency band between each of the IoT devices and the router according to the optimization result, and perform data transmission.

[0120] Specifically, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0121] Compared with the prior art, the present invention first receives connection requests from various Internet of Things devices, wherein the connection requests carry preset tags for each of the Internet of Things devices, and determines connectable frequency bands for each Internet of Things device according to the preset tags for each Internet of Things device, wherein the connectable frequency bands include a first frequency band and a second frequency band of a router, and in at least one connectable frequency band, selects a network frequency band for each Internet of Things device, obtains a communication path data set with each Internet of Things device, optimizes the communication path data set using a pre-built communication path configuration model, updates the connection frequency bands between each Internet of Things device and the router according to the optimization result, and performs data transmission. By optimizing the communication path data set of the Internet of Things device using the pre-built communication path configuration model, it can improve the user's Internet experience.

[0122] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0123] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0124] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0125] S201: receiving connection requests from various IoT devices, wherein the connection requests carry preset tags for the various IoT devices;

[0126] S202: Determine, according to preset tags of each of the IoT devices, a connectable frequency band of each of the IoT devices, where the connectable frequency band includes a first frequency band and a second frequency band of a router;

[0127] S203: Selecting a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquiring a communication path data set between each of the IoT devices;

[0128] S204: Optimize the communication path data set using a pre-built communication path configuration model, update the connection frequency band between each of the IoT devices and the router according to the optimization result, and perform data transmission.

[0129] Compared with the prior art, the present invention first receives connection requests from various Internet of Things devices, wherein the connection requests carry preset tags for each of the Internet of Things devices, and determines connectable frequency bands for each Internet of Things device according to the preset tags for each Internet of Things device, wherein the connectable frequency bands include a first frequency band and a second frequency band of a router, and in at least one connectable frequency band, selects a network frequency band for each Internet of Things device, obtains a communication path data set with each Internet of Things device, optimizes the communication path data set using a pre-built communication path configuration model, updates the connection frequency bands between each Internet of Things device and the router according to the optimization result, and performs data transmission. By optimizing the communication path data set of the Internet of Things device using the pre-built communication path configuration model, it can improve the user's Internet experience.

[0130] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0131] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0132] In the several embodiments provided by the present invention, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0133] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0134] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0135] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0136] The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A configuration method for an Internet of Things device based on a router, characterized in that: The method comprises: Receive a connection request from each IoT device, wherein the connection request carries a preset tag of each IoT device; Determine, according to preset tags of each of the IoT devices, a connectable frequency band of each of the IoT devices, wherein the connectable frequency band includes a first frequency band and a second frequency band of a router; In at least one connectable frequency band, select a network frequency band for each of the IoT devices, and obtain a communication path data set between each of the IoT devices; Optimizing the communication path data set using a pre-built communication path configuration model, updating the connection frequency band between each of the IoT devices and the router according to the optimization result, and performing data transmission; The selecting a network frequency band for each of the IoT devices respectively and obtaining a communication path data set between each of the IoT devices includes: Detect the signal strength of each connectable frequency band, and determine the network frequency band whose signal strength is greater than or equal to a preset threshold as the selectable network frequency band; Obtaining the power and power consumption of the selectable network frequency band; Determine the signal quality of the IoT device accessing the network frequency band and the corresponding network frequency band according to the corresponding relationship between the power and the power consumption of the selectable network frequency band; Generate a communication path data set based on the signal quality of the IoT device and the corresponding network frequency band; The method further comprises: Using the communication path data set to obtain a plurality of training models for communication path optimization; Calculating the difference coefficients between the training models and forming an objective function; Processing the multiple training models according to the objective function to obtain a trained communication path configuration model; The trained communication path configuration model includes: a data pre-processing module, a data feature module, a data post-processing module, and a data fusion module; The data pre-processing module is used to extract features from the input feature data of the signal quality of the IoT device and the corresponding network frequency band to obtain a first data feature of the pre-processing; The data feature module is used to obtain a second data feature using a network data transmission mechanism for the obtained first data feature of the pre-processing, and to concatenate the second data feature with the corresponding first data feature of the pre-processing to obtain a mixed feature; The data post-processing module is used to perform feature extraction on the mixed features to obtain a post-processed third data feature; The data fusion module is used to generate a communication path configuration data fusion feature according to the post-processed third data feature.

2. The method according to claim 1, characterized in that The preset label of the Internet of Things device includes: a unique identification code of the Internet of Things device and / or a physical address of the Internet of Things device.

3. The method according to claim 1, characterized in that The connectable frequency band includes a first frequency band and a second frequency band of the router, wherein the first frequency band is 2.4 GHz and the second frequency band is 5.0 GHz.

4. The method according to claim 1, characterized in that: After updating the connection frequency band between each of the IoT devices and the router according to the optimization result and performing data transmission, the method further includes: According to the connection frequency band between each of the IoT devices and the router, the communication path data set is updated and stored in a preset storage space; Creating an index corresponding to each of the communication path data sets to form an identifiable path; Based on the identifiable path, respond to an access request from a new IoT device and determine an optimal frequency band for connecting to the new IoT device.

5. A configuration device for an Internet of Things device based on a router, characterized in that: The device comprises: A receiving module, used to receive connection requests from various IoT devices, wherein the connection requests carry preset tags for the various IoT devices; A determination module, configured to determine a connectable frequency band of each of the IoT devices according to a preset tag of each of the IoT devices, wherein the connectable frequency band includes a first frequency band and a second frequency band of a router; An acquisition module, configured to select a network frequency band for each of the IoT devices in at least one connectable frequency band, and acquire a communication path data set between each of the IoT devices; An optimization module, used to optimize the communication path data set using a pre-built communication path configuration model, and update the connection frequency band between each of the IoT devices and the router according to the optimization result, and perform data transmission; The acquisition module is used to detect the signal strength of each connectable frequency band, determine the network frequency band with a signal strength greater than or equal to a preset threshold as a selectable network frequency band; obtain the power and power consumption of the selectable network frequency band; determine the signal quality of the Internet of Things device connected to the network frequency band and the corresponding network frequency band according to the corresponding relationship between the power and power consumption of the selectable network frequency band; generate a communication path data set based on the signal quality of the Internet of Things device and the corresponding network frequency band; A first obtaining module, used for obtaining a plurality of training models for communication path optimization using the communication path data set; A calculation module, used to calculate the difference coefficients between the training models and form an objective function; A second obtaining module is used to process the multiple training models according to the objective function to obtain a trained communication path configuration model; The trained communication path configuration model includes: a data pre-processing module, a data feature module, a data post-processing module, and a data fusion module; The data pre-processing module is used to extract features from the input feature data of the signal quality of the IoT device and the corresponding network frequency band to obtain a first data feature of the pre-processing; The data feature module is used to obtain a second data feature using a network data transmission mechanism for the obtained first data feature of the pre-processing, and to concatenate the second data feature with the corresponding first data feature of the pre-processing to obtain a mixed feature; The data post-processing module is used to perform feature extraction on the mixed features to obtain a post-processed third data feature; The data fusion module is used to generate a communication path configuration data fusion feature according to the post-processed third data feature.

6. A dual-band wireless router, characterized in that: The dual-band wireless router includes a central processing unit, a wireless communication module and a chip, wherein the wireless communication module is used to wirelessly communicate with an IoT device, the chip is used to forward communication path data, and the central processing unit is used to process the communication path data to implement the method described in any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

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