Networking method, device and storage medium of internet of things device

Abstract

The application discloses a networking method of an Internet of Things device, a device and a storage medium. The networking method comprises the following steps: determining a target access point device, obtaining device parameters of the target access point device; encoding the device parameters of the target access point device to generate a current device fingerprint of the target access point device; obtaining sample device fingerprints, each sample device fingerprint being associated with a recommended configuration parameter; performing similarity matching between the current device fingerprint and each sample device fingerprint to obtain the recommended configuration parameter corresponding to the sample device fingerprint that succeeds in matching, thereby obtaining a target configuration parameter; and performing parameter configuration processing on the Internet of Things device based on the target configuration parameter, so that the Internet of Things device after parameter configuration can be connected to the target access point device. The recommended configuration parameter can be automatically loaded through device fingerprint matching during network configuration, the network connection establishment time is significantly shortened, and the network configuration compatibility is improved.

Description

Technical Field

[0001] This application relates to the field of network communication technology, and in particular to a networking method, device and storage medium for Internet of Things (IoT) devices. Background Technology

[0002] IoT devices need to connect to a Wireless Fidelity (Wi-Fi) network to enable functions such as remote management, status synchronization, and user authentication.

[0003] Currently, the parameters used by IoT devices to connect to the network are usually factory presets or manually selected by the user. This may lead to problems such as excessively long network connection establishment time, excessive power consumption, and unstable connection due to factors such as the model of the access point (AP) and the actual network environment. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides at least one method, device, and storage medium for connecting IoT devices.

[0005] The first aspect of this application provides a method for connecting an Internet of Things (IoT) device to the network. The method includes: determining a target access point device and obtaining device parameters of the target access point device; encoding the device parameters of the target access point device to generate a current device fingerprint of the target access point device; obtaining sample device fingerprints, each sample device fingerprint being associated with recommended configuration parameters; performing similarity matching between the current device fingerprint and each sample device fingerprint to obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, thereby obtaining target configuration parameters; and performing parameter configuration processing on the IoT device based on the target configuration parameters to enable the parameter-configured IoT device to connect to the target access point device.

[0006] In one embodiment, the device parameters include the identity information and / or status information of the target access point device; obtaining the device parameters of the target access point device includes: obtaining the unique identifier of the target access point device to obtain the identity information of the target access point device; and / or obtaining the beacon frame period value, and / or whether it supports the quality of service standard, and / or the minimum supported communication rate, and / or the actual beacon frame interval, and / or the area information element, and / or the capability information element, and / or the load indication information of the target access point device to obtain the status information of the target access point device.

[0007] In one embodiment, an IoT device stores a local fingerprint set, and a server stores a cloud fingerprint set. The IoT device and the server are communicatively connected. Both the local and cloud fingerprint sets contain sample device fingerprints, and the sample device fingerprints in the local fingerprint set are associated with a record time. The process involves performing a similarity match between the current device fingerprint and each sample device fingerprint to obtain recommended configuration parameters corresponding to the successfully matched sample device fingerprint, thus obtaining the target configuration parameters. This includes: performing a similarity match between the current device fingerprint and each sample device fingerprint in the local fingerprint set; if no successfully matched sample device fingerprint exists in the local fingerprint set, or the record time corresponding to a successfully matched sample device fingerprint in the local fingerprint set has expired, the current device fingerprint is sent to the server so that the server performs a similarity match between the current device fingerprint and each sample device fingerprint in the cloud fingerprint set to obtain recommended configuration parameters corresponding to the successfully matched sample device fingerprint in the cloud fingerprint set, thus obtaining the target configuration parameters; if a successfully matched sample device fingerprint exists in the local fingerprint set, and the record time corresponding to the successfully matched sample device fingerprint in the local fingerprint set has not expired, the recommended configuration parameters corresponding to the successfully matched sample device fingerprint in the local fingerprint set are directly obtained, thus obtaining the target configuration parameters.

[0008] In one embodiment, the sample device fingerprint is associated with multiple levels of recommended configuration parameters, and each level of recommended configuration parameters is set with threshold judgment conditions. The process involves: performing similarity matching between the current device fingerprint and each sample device fingerprint to obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprint, thus obtaining the target configuration parameters. This includes: calculating the similarity between the current device fingerprint and each sample device fingerprint to obtain the fingerprint similarity between the current device fingerprint and each sample device fingerprint; if the highest fingerprint similarity is greater than a preset minimum threshold, selecting the sample device fingerprint corresponding to the highest fingerprint similarity to obtain the successfully matched sample device fingerprint; determining the threshold judgment condition satisfied by the highest fingerprint similarity, obtaining the recommended configuration parameters corresponding to the level of the satisfied threshold judgment condition, and thus obtaining the target configuration parameters.

[0009] In one embodiment, the similarity between the current device fingerprint and each sample device fingerprint is calculated to obtain the fingerprint similarity between the current device fingerprint and each sample device fingerprint, including: comparing the similar fields and the difference fields between the current device fingerprint and the sample device fingerprint; and calculating the fingerprint similarity between the current device fingerprint and the sample device fingerprint based on the field type and / or number of similar fields, and / or the field type and / or number of difference fields.

[0010] In one embodiment, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the IoT device failing to connect to the target access point device, counting the number of connection failures; determining a parameter adjustment strategy based on the number of connection failures; and performing parameter adjustment processing on the IoT device based on the parameter adjustment strategy, so that the IoT device with adjusted parameters can reconnect to the target access point device.

[0011] In one embodiment, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the successful connection of the IoT device to the target access point device, collecting network quality information and / or device status information of the IoT device to obtain environmental information; adjusting the signal transmission power based on the environmental information to obtain the target transmission power, so that the IoT device uses the target transmission power for data transmission.

[0012] In one embodiment, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the successful connection of the IoT device to the target access point device, obtaining the timestamps corresponding to each beacon frame sent by the target access point device to the IoT device; calculating the time difference between adjacent beacon frames based on the timestamps corresponding to each beacon frame to obtain a historical time interval; calculating a predicted time interval based on the historical time interval; and calculating the wake-up time of the IoT device based on the predicted time interval, so that the IoT device enters the active state when the wake-up time is reached, otherwise it remains in the sleep state.

[0013] A second aspect of this application provides a networking device for an Internet of Things (IoT) device. The device includes: a parameter acquisition module for determining a target access point device and acquiring device parameters of the target access point device; a fingerprint generation module for encoding the device parameters of the target access point device to generate a current device fingerprint of the target access point device; and acquiring sample device fingerprints, each sample device fingerprint being associated with recommended configuration parameters; a fingerprint matching module for performing similarity matching between the current device fingerprint and each sample device fingerprint, acquiring the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, and obtaining target configuration parameters; and a networking configuration module for performing parameter configuration processing on the IoT device based on the target configuration parameters, so that the IoT device with the configured parameters can connect to the target access point device.

[0014] A third aspect of this application provides an electronic device, including a memory and a processor, wherein the processor is used to execute program instructions stored in the memory to implement the above-described Internet of Things (IoT) device networking method.

[0015] The fourth aspect of this application provides a computer-readable storage medium having program instructions stored thereon, which, when executed by a processor, implement the above-described method for networking IoT devices.

[0016] The above scheme identifies the target access point device and obtains its device parameters. These parameters are then encoded to generate the current device fingerprint. Sample device fingerprints are also obtained, each associated with recommended configuration parameters. The current device fingerprint is matched with each sample device fingerprint for similarity, and the recommended configuration parameters corresponding to the successfully matched sample device fingerprints are obtained, thus yielding the target configuration parameters. Based on these target configuration parameters, IoT devices are configured to connect to the target access point device. Because sample device fingerprints and corresponding recommended configuration parameters are pre-stored, the recommended configuration parameters can be automatically loaded during network configuration via device fingerprint matching, significantly shortening network connection establishment time. Furthermore, IoT devices can adapt to various network environments, improving compatibility.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0019] Figure 1 This is a schematic diagram illustrating the implementation environment of the solution in an exemplary embodiment of this application; Figure 2 This is a flowchart illustrating a networking method for an Internet of Things (IoT) device, as shown in an exemplary embodiment of this application. Figure 3 This is a flowchart illustrating a networking method for an IoT device, as shown in another exemplary embodiment of this application; Figure 4 This is a schematic diagram illustrating the functional modules of a smart lock and a server in an exemplary embodiment of this application; Figure 5 This is a block diagram illustrating a networking device for an Internet of Things (IoT) device, as shown in an exemplary embodiment of this application. Figure 6 This is a schematic diagram of the structure of an electronic device shown in an exemplary embodiment of this application; Figure 7 This is a schematic diagram illustrating the structure of a computer-readable storage medium, as shown in an exemplary embodiment of this application. Detailed Implementation

[0020] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0021] In the following description, specific details such as particular system architectures, interfaces, and technologies are presented for illustrative purposes rather than for limiting purposes, in order to provide a thorough understanding of this application.

[0022] In this document, the term "and / or" is merely a description of the association information of related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "many" in this document means two or more. Moreover, the term "at least one" in this document means any combination of at least two of any one or more of a plurality of elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0023] The following describes the networking method for IoT devices provided in the embodiments of this application.

[0024] Please refer to Figure 1 , Figure 1 This is a schematic diagram illustrating an implementation environment of the solution in an exemplary embodiment of this application. The implementation environment may include an Internet of Things device 110, a server 120, and a target access point device 130.

[0025] The Internet of Things (IoT) device 110 can be a smart door lock, a smart camera, a smart light bulb, a smart refrigerator, a smart speaker, etc., but is not limited to these.

[0026] Server 120 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0027] In one example, server 120 can determine target configuration parameters based on the device parameters of the target access point device, and perform parameter configuration processing on the IoT device according to the target configuration parameters, so as to establish a communication connection between IoT device 110 and target access point device 130.

[0028] In one example, an IoT device 110 has a client application running a target application installed. This target application can be an application that provides network control functions. The target application determines target configuration parameters based on the device parameters of the target access point device, and performs parameter configuration processing on the IoT device according to the target configuration parameters, so that the IoT device 110 and the target access point device 130 can establish a communication connection. Server 120 can be a backend server for this target application, used to provide backend services for the client of the target application.

[0029] The networking method for IoT devices provided in this application embodiment can be executed by the IoT device 110, such as the client of the target application installed and running in the IoT device 110; it can also be the server 120; or it can be other terminals that are communicatively connected to the IoT device 110, and / or the server 120, and / or the target access point device 130; or it can be executed by at least two of the IoT device 110, the server 120, and other terminals in an interactive and cooperative manner. This application does not limit the executing entity.

[0030] For ease of explanation, the following embodiments will use an IoT device as the execution subject to illustrate the networking method of the IoT device of this application.

[0031] Please see Figure 2 , Figure 2 This is a flowchart illustrating a networking method for an Internet of Things (IoT) device, as shown in an exemplary embodiment of this application. Figure 2 As shown, the method for connecting IoT devices to the network includes at least steps S210 to S240, which are described in detail below: Step S210: Determine the target access point device and obtain the device parameters of the target access point device.

[0032] An access point (AP) is an access point for a wireless network, commonly known as a "hotspot". The target access point device can be a wireless router / gateway, or other electronic devices that serve as a hotspot. This application does not limit the specific device type of the target access point device.

[0033] Initiating the network configuration process for IoT devices, such as smart locks, allows users to initiate the network configuration operation by briefly pressing the setting button on the smart lock or remotely triggering it via a mobile terminal. This puts the smart lock into network configuration mode and initiates the network configuration process.

[0034] After initiating the network configuration process for IoT devices, the IoT devices scan all channels, obtain a list of available APs in the vicinity based on all available APs scanned, and select the target access point device from the list of available APs in the vicinity.

[0035] For example, a list of available access points (APs) in the vicinity can be displayed to the user through a visual interface, and the available AP selected by the user can be used as the target access point device in response to the user's selection.

[0036] For example, it can obtain information such as the type and / or signal strength of each available AP in the surrounding available AP list, and automatically select available APs that meet preset type conditions and / or preset signal strength conditions from the available AP list to obtain the target access point device.

[0037] The specific method for determining the target access point device can be flexibly set according to the actual application scenario, and this application does not limit it in this regard.

[0038] In addition, channel environment assessment can be further conducted to select a network configuration method that better matches the actual wireless environment, thereby improving the initial connection success rate. Specifically, channel environment parameters for each channel are obtained, including noise reduction, channel utilization, and / or the number of overlapping APs, etc., and the network configuration method is determined based on these parameters.

[0039] For example, if the surrounding Bluetooth beacon signal is strong, such as a Received Signal Strength Indicator (RSSI) greater than -70dBm, then Bluetooth Assisted Wi-Fi Provisioning (BLE) will be prioritized for network configuration. If the channel interference is low, such as a Channel Quality Metric (CQM) less than 30%, then SmartConfig will be used for network configuration. Otherwise, SoftAP will be used to ensure a high connection success rate.

[0040] After obtaining the target access point device, acquire the device parameters of the target access point device.

[0041] Device parameters include, but are not limited to, the type of target access point device, and / or its identity, and / or its working status, and / or its working capabilities. The content of device parameters can be flexibly set according to the actual application scenario, and this application does not limit it.

[0042] Step S220: Encode the device parameters of the target access point device to generate the current device fingerprint of the target access point device; and obtain sample device fingerprints, each sample device fingerprint being associated with recommended configuration parameters.

[0043] The device parameters of the target access point device are structured and encoded to represent the device parameters in computer language, thereby obtaining the current device fingerprint of the target access point device.

[0044] Optionally, a unique fingerprint identifier for the current device fingerprint can also be generated, for example, by generating a unique fingerprint identifier for the current device fingerprint using a hash algorithm, so as to facilitate subsequent fingerprint matching queries.

[0045] It should be noted that the same target access point device may generate different device fingerprints under different circumstances. For example, if the target access point device has different working status and network parameters at different times, the corresponding device fingerprints will also be different.

[0046] In addition, sample device fingerprints are obtained, and each sample device fingerprint is associated with recommended configuration parameters.

[0047] The sample device fingerprint can be a device fingerprint generated by one or more access point devices within a historical time period; it can also be a device fingerprint pre-set based on experience, and this application does not limit this. The generation method of the sample device fingerprint is similar to the generation method of the current device fingerprint.

[0048] In addition, the recommended configuration parameters for fingerprint association of sample devices can be the configuration parameters used by the IoT device when one or more access point devices successfully connected to the IoT device within a historical time period; or the configuration parameters after adjusting and modifying the configuration parameters used by the IoT device when successfully connected; or the configuration parameters set in advance based on experience. This application does not limit these.

[0049] Configuration parameters refer to parameters involved in the networking process of IoT devices. For example, configuration parameters include listening interval, minimum allowed data rate, recommended power management model, signal transmission power range, and / or whether fast scan optimization is enabled. This application does not limit the specific parameter types contained in the configuration parameters.

[0050] Step S230: Perform similarity matching between the current device fingerprint and the fingerprints of each sample device, obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, and obtain the target configuration parameters.

[0051] Calculate the similarity between the current device fingerprint and each sample device fingerprint, and determine the sample device fingerprints that match the current device fingerprint based on the similarity.

[0052] For example, you can select sample device fingerprints with a similarity greater than a preset similarity threshold to obtain a successfully matched sample device fingerprint; you can also select sample device fingerprints with the highest similarity to obtain a successfully matched sample device fingerprint; or you can select sample device fingerprints with the highest similarity and a similarity greater than a preset similarity threshold to obtain a successfully matched sample device fingerprint.

[0053] Then, obtain the recommended configuration parameters corresponding to the fingerprints of the successfully matched sample devices, and use them as the target configuration parameters.

[0054] It should be noted that the number of successfully matched sample device fingerprints can be one or more. If the number of successfully matched sample device fingerprints is multiple, multiple recommended configuration parameters can be obtained. Multiple recommended configuration parameters can be merged to obtain the target configuration parameters. For example, the target configuration parameters can be obtained by extracting the same parameter items among multiple recommended configuration parameters, or by deleting the duplicate parameter items among multiple recommended configuration parameters.

[0055] Step S240: Configure the IoT device based on the target configuration parameters so that the configured IoT device can connect to the target access point device.

[0056] After obtaining the target configuration parameters, the IoT device is configured according to the target configuration parameters.

[0057] The parameter configuration can be achieved by filling in the values ​​of the IoT device's parameter items according to the content of the target configuration parameters; or it can be achieved by selecting part of the target configuration parameters and filling in the values ​​of the IoT device's parameter items. The specific parameter configuration method can be flexibly set according to the actual application scenario, and this application does not limit it.

[0058] After parameter configuration, the IoT device attempts to establish a communication connection with the target access point device to achieve network connectivity for the IoT device.

[0059] This application identifies a target access point device and obtains its device parameters. The device parameters are then encoded to generate a current device fingerprint. Sample device fingerprints are also obtained, each associated with recommended configuration parameters. The current device fingerprint is matched with each sample device fingerprint for similarity, and the recommended configuration parameters corresponding to the successfully matched sample device fingerprints are obtained, thus yielding the target configuration parameters. Based on these target configuration parameters, IoT devices are configured to connect to the target access point device. Because sample device fingerprints and corresponding recommended configuration parameters are pre-stored, the recommended configuration parameters can be automatically loaded during network configuration via device fingerprint matching, significantly shortening network connection establishment time. Furthermore, IoT devices can adapt to various network environments, improving compatibility.

[0060] The following describes some embodiments of this application in detail.

[0061] In some implementations, the device parameters include the identity information and / or status information of the target access point device; obtaining the device parameters of the target access point device in step S210 includes: obtaining the unique identifier of the target access point device to obtain the identity information of the target access point device; and / or obtaining the beacon frame period value, and / or whether it supports the quality of service standard, and / or the minimum communication rate supported, and / or the actual beacon frame interval, and / or the area information element, and / or the capability information element, and / or the load indication information of the target access point device to obtain the status information of the target access point device.

[0062] The identity and / or status information of the target access point device can be obtained by analyzing the data content of the received beacon frames, and / or the data content of the Dynamic Host Configuration Protocol (DHCP) messages, and / or the data content of the Probe Response frames.

[0063] For example, the system can obtain the first six bytes of the Beacon frame to get the Organizationally Unique Identifier (OUI), which is used as the unique identifier for the target access point device; and / or, obtain the DTIM (Delivery Traffic Indication Message) period carried in the Beacon frame to get the beacon frame period value, which is used to indicate the broadcast / multicast data scheduling period; and / or, obtain the WMM (Wi-Fi Multimedia) parameter in the Beacon frame to determine whether the target access point device supports the Quality of Service (QoS) standard; and / or, obtain the Basic Rate Set (BRS) declared in the Beacon frame to get the minimum communication rate supported by the target access point device; and / or, obtain the Beacon frame broadcast period declared by the target access point device, which can be measured using the high-precision timestamp of the Beacon frame to obtain the actual beacon interval, and identify whether it is a non-standard value (such as 102ms); and / or, obtain the Country IE (Country Information) in the Beacon frame. The system retrieves the area information element from the Beacon frame, which declares the radio regulations followed by the target access point device to achieve compliant power control; and / or retrieves the HT Capabilities (High Throughput Capabilities) field from the Beacon frame, which includes support for features such as Multiple-Input Multiple-Output (MIMO) and Short Guard Interval (ShortGI), to obtain the capability information element; and / or retrieves the load indication information carried in the Probe Response frame, which includes, but is not limited to, the number of clients currently connected to the target access point device, and / or parameters such as channel utilization.

[0064] The fingerprint of the current device is obtained by combining the above information encoding.

[0065] Optionally, the device fingerprint may also contain device parameters of the IoT device, including the IoT device's identity information and / or status information. For example, the Option 60 field in the Dynamic Host Configuration Protocol (DHCP) message can be obtained to get the IoT device's device type and / or firmware version. The device parameters of the IoT device and the target access point device are encoded to obtain the current device fingerprint, improving matching accuracy.

[0066] By constructing a multi-dimensional, dynamic device fingerprint, we can not only identify information such as device manufacturer and type, but also perceive its working status and capabilities, providing a basis for subsequent precise parameter configuration.

[0067] Then, the current device fingerprint and the sample device fingerprint are matched for similarity, and the successfully matched sample device fingerprints are selected.

[0068] In some implementations, the IoT device stores a local fingerprint set, and the server stores a cloud fingerprint set. The IoT device and the server are connected in communication. Both the local fingerprint set and the cloud fingerprint set contain sample device fingerprints. The sample device fingerprints in the local fingerprint set are associated with the recording time. In step S230, the current device fingerprint is matched with the fingerprints of each sample device to obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, and the target configuration parameters are obtained. This includes the following steps S2311 to S2314.

[0069] Step S2311: Perform similarity matching between the current device fingerprint and the sample device fingerprints in the local fingerprint set.

[0070] The local fingerprint set is stored in the IoT device. It can obtain the connection records of IoT devices within a historical time period. The connection records include the device fingerprints and configuration parameters of each successfully connected access point device. Based on the connection records, sample device fingerprints and recommended configuration parameters are obtained and stored in the local fingerprint set.

[0071] In this local fingerprint set, each sample device fingerprint is also associated with a recording time. This recording time can be obtained by acquiring the last connection time between the IoT device and the access point device corresponding to the sample device fingerprint; or it can be obtained by acquiring the last update time of the sample device fingerprint and / or recommended configuration parameters. This application does not limit the specific type of recording time.

[0072] Obtain the local fingerprint set and perform similarity matching between the current device fingerprint and each sample device fingerprint in the local fingerprint set.

[0073] Step S2312: If there is no successfully matched sample device fingerprint in the local fingerprint set, or the record time corresponding to the successfully matched sample device fingerprint in the local fingerprint set has expired, then proceed to step S2313; if there is a successfully matched sample device fingerprint in the local fingerprint set, and the record time corresponding to the successfully matched sample device fingerprint in the local fingerprint set has not expired, then proceed to step S2314.

[0074] If a matching sample device fingerprint exists in the local fingerprint set, the record time corresponding to the matching sample device fingerprint in the local fingerprint set is obtained, and it is checked whether the record time has exceeded the validity period.

[0075] For example, calculate the time interval between the recorded time and the current time, and check whether the time interval exceeds a preset time interval threshold (such as 6 months). If it does, the validity period has expired; if not, the validity period has not expired. Alternatively, calculate the expiration time based on the recorded time, and check whether the current time has reached the expiration time. If it does, the validity period has expired; if not, the validity period has not expired.

[0076] Step S2313: Send the current device fingerprint to the server so that the server can perform similarity matching between the current device fingerprint and each sample device fingerprint in the cloud fingerprint set, obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprint in the cloud fingerprint set, and obtain the target configuration parameters.

[0077] The server can communicate and connect with multiple IoT devices. Each IoT device reports its detected device fingerprint and the configuration parameters used to connect to that device to the server. For example, IoT devices may report device fingerprints, and / or unique fingerprint identifiers, and / or device model (e.g., smart_lock_v2), and / or geographic location (e.g., province code) to the server via Hypertext Transfer Protocol Secure (HTTPS) or Message Queuing Telemetry Transport (MQTT). The server receives the reported information from multiple IoT devices and constructs a cloud-based fingerprint set.

[0078] If there is no matching sample device fingerprint in the local fingerprint set, or if the record time corresponding to the matching sample device fingerprint in the local fingerprint set has expired, it indicates that the local fingerprint set matching has failed, and the cloud matching process is initiated.

[0079] Specifically, the current device fingerprint is sent to the server, which then performs similarity matching between the current device fingerprint and various sample device fingerprints in the cloud fingerprint set. The server then obtains the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, thus obtaining the target configuration parameters.

[0080] The similarity matching calculation method for the local fingerprint set and the similarity matching calculation method for the cloud fingerprint set can be the same or different. For example, since IoT devices have limited computing resources while servers have more computing resources, a lightweight similarity algorithm or neural network model can be used to perform similarity matching calculation for the local fingerprint set, while a more complex similarity algorithm or neural network model can be used to perform similarity matching calculation for the cloud fingerprint set.

[0081] Step S2314: Directly obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints in the local fingerprint set to obtain the target configuration parameters.

[0082] If a matching sample device fingerprint exists in the local fingerprint set, and the record time corresponding to the matching sample device fingerprint in the local fingerprint set has not expired, it indicates that the local fingerprint set is successfully matched. The recommended configuration parameters corresponding to the matching sample device fingerprint in the local fingerprint set are directly obtained to obtain the target configuration parameters.

[0083] By verifying the timeliness of sample device fingerprints in the local fingerprint set, we can avoid device compatibility degradation caused by long-term use of outdated configurations and improve the connection success rate.

[0084] Of course, in addition to verifying the timeliness of sample device fingerprints in the local fingerprint set, the timeliness of sample device fingerprints in the cloud fingerprint set can also be verified. That is, after obtaining a successfully matched sample device fingerprint from the cloud fingerprint set, it is also checked whether the record time corresponding to the sample device fingerprint has exceeded the validity period. If it has not exceeded the validity period, the recommended configuration parameters corresponding to the sample device fingerprint are used. If it has exceeded the validity period, the matching failure is directly reported, and the default template parameters can be used.

[0085] Optionally, the local fingerprint set and / or cloud fingerprint set may also contain parameters such as a unique fingerprint identifier corresponding to the sample device fingerprint, and / or connection efficiency data, and / or power consumption data. Connection efficiency data refers to data characterizing the efficiency of IoT devices in connecting to the network based on recommended configuration parameters and target docking point devices, including but not limited to connection success rate, and / or connection duration, and / or reconnection rate; power consumption data refers to the power consumption of IoT devices in connecting to the network based on recommended configuration parameters and target docking point devices, including but not limited to the average power consumption, and / or maximum power consumption, and / or minimum power consumption of IoT devices.

[0086] Optionally, connection efficiency data and / or power consumption data can be used to optimize recommended configuration parameters.

[0087] For example, parameter optimization rules are preset, such as: if the connection success rate is lower than the preset success rate threshold, then reduce the Listen Interval; if the average power consumption is higher than the preset power consumption threshold, then reduce the signal transmission power range.

[0088] For example, a parameter optimization model can be pre-trained, which can optimize the recommended configuration parameters based on the input connection efficiency data and / or power consumption data.

[0089] By continuously optimizing recommended configuration parameters and building dynamic local and cloud fingerprint sets, the accuracy of the matched target configuration parameters can be improved. In particular, the cloud fingerprint set is obtained by mining real operating data from multiple IoT devices. Through edge-cloud collaboration, the convergence speed of configuration parameters is accelerated, and the cross-vendor compatibility and first-connection success rate of IoT devices are improved.

[0090] In some implementations, the sample device fingerprint is associated with multiple levels of recommended configuration parameters, and each level of recommended configuration parameters is set with threshold judgment conditions; in step S230, the current device fingerprint is matched with each sample device fingerprint for similarity, and the recommended configuration parameters corresponding to the successfully matched sample device fingerprint are obtained to obtain the target configuration parameters, including the following steps S2321 to S2323.

[0091] Step S2321: Calculate the similarity between the current device fingerprint and the fingerprints of each sample device to obtain the fingerprint similarity between the current device fingerprint and the fingerprints of each sample device.

[0092] The fingerprint similarity between the current device fingerprint and the sample device fingerprint can be calculated directly based on vector similarity calculation methods (such as cosine distance, Euclidean distance, etc.); or the similarity can be calculated field by field to obtain the similarity between each field, and the fingerprint similarity between the current device fingerprint and the sample device fingerprint can be obtained based on the similarity between each field. This application does not limit the specific similarity calculation method.

[0093] For example, the similarity calculation between the current device fingerprint and the fingerprints of each sample device can be performed to obtain the fingerprint similarity between the current device fingerprint and each sample device fingerprint. This includes: comparing the similar and different fields between the current device fingerprint and the sample device fingerprint; and calculating the fingerprint similarity between the current device fingerprint and the sample device fingerprint based on the field type and / or number of similar fields, and the field type and / or number of different fields.

[0094] If the similarity between fields is higher than a preset similarity threshold, then they are considered similar fields; otherwise, they are considered different fields.

[0095] Fingerprint similarity is calculated based on the field type and / or number of similar fields, and / or the field type and / or number of different fields.

[0096] For example, different field types have different levels of importance. If the field type of similar fields has a higher level of importance, the fingerprint similarity will be higher. If the field type of different fields has a higher level of importance, the fingerprint similarity will be lower.

[0097] For example, the greater the number of similar fields, the higher the fingerprint similarity; conversely, the greater the number of different fields, the lower the fingerprint similarity.

[0098] Optionally, a unique fingerprint identifier for the current device fingerprint is generated using a hash algorithm. The unique fingerprint identifier for the current device fingerprint is then matched with the unique fingerprint identifier corresponding to the sample device fingerprint. If the unique fingerprint identifier of a sample device fingerprint matches the unique fingerprint identifier of the current device fingerprint, it indicates that the sample device fingerprint and the current device fingerprint are a perfect match. In this case, the fingerprint similarity can be set to 1 or other preset values ​​(such as 0.95).

[0099] Step S2322: If the highest fingerprint similarity is greater than the preset minimum threshold, then select the sample device fingerprint corresponding to the highest fingerprint similarity to obtain the successfully matched sample device fingerprint.

[0100] The highest fingerprint similarity corresponding to the fingerprints of each sample device is calculated.

[0101] If the highest fingerprint similarity is greater than the preset minimum threshold, then the sample device fingerprint corresponding to the highest fingerprint similarity is taken as the successfully matched sample device fingerprint.

[0102] Step S2323: Determine the threshold judgment condition that the highest fingerprint similarity satisfies, obtain the recommended configuration parameters for the level corresponding to the threshold judgment condition that is satisfied, and obtain the target configuration parameters.

[0103] Each sample device fingerprint is associated with multiple levels of recommended configuration parameters, and each level of recommended configuration parameters has its own threshold judgment conditions.

[0104] The threshold judgment conditions can be the same for fingerprints from different sample devices, or they can be different. The specific settings can be flexibly configured according to the actual scenario.

[0105] Specifically, the recommended configuration parameters for multiple levels of the fingerprint association of successfully matched sample devices are obtained, and the threshold judgment conditions corresponding to the recommended configuration parameters for each level are obtained. The threshold judgment conditions satisfied by the highest fingerprint similarity are detected, and the recommended configuration parameters of the level corresponding to the satisfied threshold judgment conditions are used as the target configuration parameters.

[0106] For example, the recommended configuration parameters for fingerprint association of sample devices and their corresponding threshold judgment conditions include: Level 1 matching: Corresponding recommended configuration parameters: advanced recommended parameters; Corresponding threshold judgment condition: fingerprint similarity greater than 0.95; Second-level matching: corresponding recommended configuration parameters: downgraded recommended parameters; corresponding threshold judgment conditions: fingerprint similarity greater than 0.8 (e.g., the OUI is the same and the DTIM is the same, but the number of other difference fields is greater than or equal to 1). Level 3 matching: Recommended configuration parameters: Default template parameters; Threshold judgment condition: Fingerprint similarity greater than 0.6 (e.g., only OUI is the same).

[0107] The specific parameters in the advanced recommendation parameters, downgraded recommendation parameters, and default template parameters are either preset based on experience or automatically generated by learning from historical connection data; this application does not impose any restrictions on this.

[0108] Optionally, the sample device fingerprint can be associated with only one recommended configuration parameter. The reference parameters from the recommended configuration parameters are determined based on fingerprint similarity, and only these reference parameters are used as the target configuration parameter. For example, higher fingerprint similarity results in more reference parameters, and lower fingerprint similarity results in fewer reference parameters. Based on the number of reference parameters, a corresponding number of reference parameters are selected from the recommended configuration parameters to obtain the target configuration parameter. Alternatively, different similarity threshold ranges correspond to different reference parameters. The reference parameters are determined based on the similarity threshold range in which the fingerprint falls, thus obtaining the target configuration parameter.

[0109] After obtaining the target configuration parameters, configure the parameters of the IoT device.

[0110] For example, set Listen Interval to the recommended value; and / or configure the minimum allowed data rate to the recommended rate to ensure demodulation in weak fields; enable DTIM synchronization power saving mode (dtim_sync) to achieve period alignment with the AP; and set the initial signal transmit power to the recommended intermediate value (e.g., 15dBm).

[0111] After completing the parameter configuration, the IoT device attempts to establish a network connection with the target interface device. Additionally, the IoT device can record the network connection establishment time, and / or authentication results, and / or association results, etc.

[0112] In some implementations, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the IoT device failing to connect to the target access point device, counting the number of connection failures; determining a parameter adjustment strategy based on the number of connection failures; and performing parameter adjustment processing on the IoT device based on the parameter adjustment strategy, so that the IoT device with adjusted parameters can reconnect to the target access point device.

[0113] The parameter adjustment strategy may be used to limit the specific parameter type to be adjusted, and / or to limit the number of parameters to be adjusted, and / or to limit the algorithm used for parameter adjustment, etc. This application does not limit the specific implementation of the parameter adjustment strategy.

[0114] For example, the following parameter adjustment strategies correspond to different numbers of connection failures: First failure: After switching to non-power saving mode, continue to try to establish a connection with the target access point device. In non-power saving mode, Listen Interval=1; Second failure: After switching to Power-Save Poll mode (i.e., power saving mode), continue to try to establish a connection with the target access point device; Third failure: After configuring the IoT device with the default general settings, continue to try to establish a connection with the target access point device.

[0115] The above embodiments improve robustness in abnormal scenarios through multi-level degradation connections.

[0116] In addition, IoT devices can encrypt failure logs and report them to the server, so that the server can continuously optimize the recommended configuration parameters corresponding to the sample device fingerprints.

[0117] In some implementations, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the successful connection of the IoT device to the target access point device, obtaining the timestamps corresponding to each beacon frame sent by the target access point device to the IoT device; calculating the time difference between adjacent beacon frames based on the timestamps corresponding to each beacon frame to obtain a historical time interval; calculating a predicted time interval based on the historical time interval; and calculating the wake-up time of the IoT device based on the predicted time interval, so that the IoT device enters the active state when the wake-up time is reached, otherwise it remains in the sleep state.

[0118] For IoT devices that rely on batteries (such as smart door locks), which are extremely sensitive to power consumption, it is necessary to minimize energy consumption while maintaining network connectivity. Therefore, the wake-up time of the device can be calculated based on the beacon frame period information. The IoT device is only woken up to transmit data after the wake-up time is reached, and remains in sleep mode for the rest of the time, thereby reducing the power consumption of the IoT device.

[0119] For example, an IoT device can enter a low-power mode, in which the IoT device is in a sleep state, shutting down the main central processing unit (CPU) and only keeping the real-time clock (RTC) and Wi-Fi coprocessor running; passively receiving Beacon frames, recording the precise timestamp of each Beacon frame arrival and the DTIM Count field; continuously receiving at least four consecutive Beacon frames to ensure coverage of a complete DTIM cycle; and extracting the timestamp and DTIM Count field of each Beacon frame for subsequent cycle identification.

[0120] At the end of each DTIM cycle, the AP sends a special Beacon frame containing a DTIMCount field set to 0. A DTIM=0 Beacon frame wakes up IoT devices in power-saving mode and informs them that data transmission is required. Each regular Beacon frame contains a DTIM Count that counts down from a certain value to 0. The DTIM Count represents how many Beacon cycles are remaining until the next DTIM cycle (the point in time when data transmission is required).

[0121] Specifically, based on the recorded timestamps, the time difference between adjacent Beacon frames is calculated to obtain the historical time interval; the predicted time interval is calculated based on the historical time interval, and then the wake-up time of the IoT device is calculated based on the predicted time interval.

[0122] For example, a sliding window is used to select a preset number of historical time intervals for weighted calculation to obtain the predicted time interval. The weight of each historical time interval can be preset based on experience, or the weight can be set according to the proximity of the timestamp corresponding to the historical time interval to the current time. For example, the most recent N historical time intervals are weighted by decaying according to their corresponding timestamps to obtain the predicted time interval T (unit: ms). Then, the frame with DTIM Count of zero is found, and the DTIM period length N×T is determined, where N is the number of Beacon periods contained in the DTIM period. The wake-up period of the IoT device is then N×T, and the microcontroller unit (MCU) is triggered to wake up at a preset time (e.g., 500μs) to ensure that initialization is completed and the device enters the active state for data transmission before the next DTIM frame arrives.

[0123] And / or, a bias prediction model is pre-trained. The bias prediction model fits a trend line based on the timestamp corresponding to the Beacon frame, predicts the future time offset corresponding to the Beacon frame based on the trend line, and calculates the prediction time interval and the wake-up time of the IoT device based on the future time offset.

[0124] The above embodiments predict the time of beacon frames based on historical time intervals to avoid clock drift or AP scheduling jitter causing IoT devices to be woken up incorrectly, thereby improving the synchronization accuracy between IoT devices and target access point devices.

[0125] Optionally, each time a Beacon frame is received, its corresponding timestamp is checked to see if it deviates from the predicted time by more than a preset tolerance (e.g., 5ms). If it exceeds the preset tolerance twice in a row, the steps in the above embodiment are triggered to recalculate the predicted time interval and wake-up time to relearn the DTIM cycle. Alternatively, if a change in BSSID is detected, and / or no DTIM frame is received for several consecutive DTIM cycles, and / or RSSI drops by more than 15dBm, and / or the system connects to the same AP for the first time after a restart, and / or every preset time interval, the predicted time interval and wake-up time are recalculated.

[0126] In some implementations, after configuring the IoT device based on the target configuration parameters, the method further includes: in response to the successful connection of the IoT device to the target access point device, collecting network quality information and / or device status information of the IoT device to obtain environmental information; adjusting the signal transmission power based on the environmental information to obtain the target transmission power, so that the IoT device uses the target transmission power for data transmission.

[0127] For example, network quality information can be obtained by collecting parameters such as Received Signal Strength Indication (RSSI), and / or Signal-to-Noise Ratio (SNR), and / or Channel Busy Time (CBT), and / or the number of data transmission failures in the previous data transmission cycle, and / or the average time deviation of the arrival of the most recent 10 Beacon frames.

[0128] For example, by collecting parameters such as battery voltage and / or operating mode of IoT devices, device status information can be obtained. Of course, other types of device status information can also be obtained; for example, if the IoT device is a smart lock, its location information can also be obtained.

[0129] The aforementioned network quality information and / or device status information of IoT devices are considered as environmental information.

[0130] The signal transmission power is dynamically adjusted based on environmental information to obtain the target transmission power.

[0131] For example, if the current RSSI is high (e.g., greater than -65dBm), the signal transmission power is reduced (e.g., reduced by 6dBm); and / or, if channel interference is severe (e.g., CBT>70%), the signal transmission power is reduced to reduce collisions; and / or, if the battery power of the IoT device is below 20%, the signal transmission power is set to an upper limit of 12dBm to extend the battery life of the IoT device; and / or, if the number of consecutive data transmission failures exceeds a threshold, the signal transmission power is temporarily increased (e.g., increased by 2dBm), and then restored to the original signal transmission power after one DTIM cycle; and / or, if the IoT device is a smart lock, and a change in the position of the smart lock is detected, such as movement of the smart lock detected by an accelerometer, the signal transmission power is reset to the default.

[0132] The signal transmission power can be adjusted at preset intervals (e.g., 30 seconds); or it can be adjusted when a significant change in environmental information is detected. This application does not limit the triggering conditions for adjusting the signal transmission power.

[0133] Optionally, the signal transmission power can be adjusted gradually. Specifically, the maximum adjustment value of the signal transmission power can be limited each time, such as the signal transmission power changing by no more than 1dBm each time, so as to complete the target transition in steps and avoid radio frequency oscillation and air interference.

[0134] The target transmit power is written to the WIFI chip through the transmit power control interface so that IoT devices can use the target transmit power for data transmission.

[0135] In some implementations, IoT devices periodically report operational data to a server, such as average RSSI, and / or average power consumption, and / or reconnection count, and / or signal transmission power data. Based on the received operational data from each IoT device, the server optimizes and recommends configuration parameters.

[0136] For example, the server performs comparative tests based on the operational data received from various IoT devices to verify the effects of different configuration combinations, and automatically optimizes and recommends configuration parameters based on the verification results, thereby achieving automatic evolution of the configuration strategy.

[0137] The following example illustrates the networking methods for IoT devices using a specific application scenario. For an example, please refer to [link to example]. Figure 3 , Figure 3 This is a flowchart illustrating a networking method for an IoT device, as shown in another exemplary embodiment of this application. The executing entity is the IoT device, such as... Figure 3 As shown, it includes the following: Step S301: Start the network distribution process and determine the target access point equipment; Step S302: Extract the current device fingerprint corresponding to the target access point device; Step S303: Query whether there is a sample device fingerprint in the local fingerprint set that successfully matches the current device fingerprint. If it exists, proceed to step S304; otherwise, proceed to step S305. Step S304: Obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints in the local fingerprint set, and obtain the target configuration parameters; Step S305: Upload the current device fingerprint to the server, receive the recommended configuration parameters sent by the server, and obtain the target configuration parameters; Step S306: Configure the IoT device parameters based on the target configuration parameters, and establish a connection with the target access point device after configuration; Step S307: Start the DTIM periodic learning process and calculate the wake-up time of the IoT device; Step S308: Enter the operation phase, periodically executing steps S3081 and S3082: Step S3081: Collect environmental information, adjust the signal transmission power based on the environmental information, and use the target transmission power for data transmission; Step S3082: Determine whether the wake-up time needs to be recalibrated. If so, proceed to step S307.

[0138] The following section uses a smart door lock as an example to illustrate the functional modules of IoT devices and servers. For examples, please refer to [link / reference needed]. Figure 4 , Figure 4 This is a schematic diagram illustrating the functional modules of a smart lock and a server, as shown in an exemplary embodiment of this application. Figure 4 As shown, the smart door lock includes a WIFI communication module, an antenna and RF front end, a main control MCU, an environmental sensing module, a transmit power control interface, a device fingerprint extraction module, a local cache module, an energy-saving mode calibration module, and an RTC wake-up timer.

[0139] The WIFI communication module is responsible for sending and receiving data frames, supports the 802.11b / g / n protocol, and has programmable transmit power (8dBm to 20dBm) and Listen Interval configuration capabilities. The WIFI communication module is connected to the main control MCU and is controlled by the transmit power control interface and the power saving mode calibration module.

[0140] The antenna and RF front-end enable RF signal transmission and reception, and support power detection. The antenna and RF front-end are connected to the WIFI communication module, outputting RSSI to the environmental sensing and acquisition module.

[0141] The main control MCU runs the smart lock's main program and includes a low-power coprocessor. This coprocessor performs lightweight tasks (such as time tracking and interrupt wake-up) in sleep mode. A decision engine is deployed in the main control MCU to implement the various embodiments provided in this application, such as querying recommended configuration parameters based on the current device fingerprint, calculating the target transmission power based on environmental information, and dynamically calibrating the wake-up time based on Beacon frames. The main control MCU connects to all modules and coordinates their collaborative operation.

[0142] The environmental sensing module periodically collects environmental information, such as RSSI, SNR, Channel Busy Time, battery voltage, and the number of data transmission failures in the previous data transmission cycle. The environmental sensing module is connected to the Wi-Fi communication module, power management unit, and transmit power control interface.

[0143] The transmit power control interface writes the target transmit power output by the decision engine into the transmit power register of the WIFI chip in the WIFI communication module, supporting fine adjustment (in 1dBm steps). The transmit power control interface connects to both the WIFI communication module and the decision engine.

[0144] During the network configuration phase, the device fingerprint extraction module scans surrounding access points (APs) and extracts device fingerprints from OUI and Beacon frames, including DTIM period, WMM parameters, supported rate sets, and DHCP Option strings. The device fingerprint extraction module connects to the Wi-Fi communication module and stores the extracted device fingerprints as sample device fingerprints in a local cache module and on a server.

[0145] The local caching module stores sample device fingerprints and their recommended configuration parameters. For example, it stores the device fingerprints and recommended configuration parameters of the N most recently successfully connected routers in JSON format, resulting in a local fingerprint set that supports fast lookup. The local caching module connects to the device fingerprint extraction module and the decision engine.

[0146] The energy-saving mode calibration module passively receives Beacon frames, records timestamps and DTIM counts, and identifies the Beacon period and DTIM structure through differential analysis. The energy-saving mode calibration module is connected to the WIFI communication module and the RTC wake-up timer.

[0147] The RTC wake-up timer sets a precise wake-up cycle (e.g., wake-up every 408ms) based on the calibration results of the power-saving mode calibration module, and is implemented using a low-power timer. The RTC wake-up timer is connected to the main control MCU to trigger system wake-up.

[0148] The server is deployed on the vendor's cloud platform and includes: a cloud caching module, a fingerprint matching and recommendation engine, and a feedback learning module. The cloud caching module stores a cloud fingerprint set, which can be implemented using a structured database. Each data record includes the sample device fingerprint, recommended configuration parameters, and known issues. The fingerprint matching and recommendation engine receives device fingerprints reported by the smart lock and returns recommended configuration parameters. The feedback learning module receives connection quality data and communication parameters reported by the smart lock and continuously optimizes the recommended configuration parameters based on the data reported by the smart lock. The server communicates with the smart lock via HTTPS / MQTT protocols and can be activated only during network configuration or reconnection.

[0149] Figure 5 This is a block diagram illustrating a networking device for an Internet of Things (IoT) device, as shown in an exemplary embodiment of this application. Figure 5 As shown, the networking device 500 of this exemplary Internet of Things (IoT) device includes: The parameter acquisition module 510 is used to determine the target access point device and acquire the device parameters of the target access point device. The fingerprint generation module 520 is used to encode the device parameters of the target access point device to generate the current device fingerprint of the target access point device; and to acquire sample device fingerprints, each sample device fingerprint being associated with recommended configuration parameters. The fingerprint matching module 530 is used to perform similarity matching between the current device fingerprint and the fingerprints of various sample devices, obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, and obtain the target configuration parameters. The network configuration module 540 is used to perform parameter configuration processing on IoT devices based on target configuration parameters, so that the IoT devices after parameter configuration can connect to the target access point device.

[0150] It should be noted that the networking device for IoT devices provided in the above embodiments and the networking method for IoT devices provided in the above embodiments belong to the same concept. The specific ways in which each module and unit performs operations have been described in detail in the method embodiments, and will not be repeated here. In practical applications, the networking device for IoT devices provided in the above embodiments can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above. This is not a limitation.

[0151] Please see Figure 6 , Figure 6This is a schematic diagram illustrating the structure of an electronic device in an exemplary embodiment of this application. The electronic device 600 includes a memory 610 and a processor 620. The processor 620 executes program instructions stored in the memory 610 to implement the steps in any of the above-described embodiments of the Internet of Things (IoT) device networking method. In a specific implementation scenario, the electronic device 600 may include, but is not limited to, a microcomputer or a server. Furthermore, the electronic device 600 may also include mobile devices such as laptops and tablets, without limitation.

[0152] Specifically, processor 620 controls itself and memory 610 to implement the steps in any of the above-described IoT device networking method embodiments. Processor 620 may also be referred to as a Central Processing Unit (CPU). Processor 620 may be an integrated circuit chip with signal processing capabilities. Processor 620 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor. Furthermore, processor 620 may be implemented using integrated circuit chips.

[0153] Please see Figure 7 , Figure 7 This is a schematic diagram illustrating the structure of a computer-readable storage medium in an exemplary embodiment of this application. The computer-readable storage medium 700 stores program instructions 710 that can be executed by a processor. The program instructions 710 are used to implement the steps in any of the above-described embodiments of the networking method for IoT devices.

[0154] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0155] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0156] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus implementations described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0157] Furthermore, the functional units in the various embodiments of this application 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. The integrated unit can be implemented in hardware or as a software functional unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, 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. 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.) or processor to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for connecting an Internet of Things (IoT) device to the network, characterized in that, The method includes: Identify the target access point device and obtain the device parameters of the target access point device; Encode the device parameters of the target access point device to generate the current device fingerprint of the target access point device; and obtain sample device fingerprints, each sample device fingerprint being associated with recommended configuration parameters. The current device fingerprint is matched with the fingerprints of each sample device to obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprints, thus obtaining the target configuration parameters; The IoT device is configured based on the target configuration parameters so that the configured IoT device can connect to the target access point device.

2. The method according to claim 1, characterized in that, The device parameters include the identity information and / or status information of the target access point device; obtaining the device parameters of the target access point device includes: Obtain the unique identifier of the target access point device to obtain the identity information of the target access point device; And / or, obtain the beacon frame period value, and / or whether it supports the quality of service standard, and / or the minimum supported communication rate, and / or the actual beacon frame interval, and / or the area information element, and / or the capability information element, and / or the load indication information of the target access point device to obtain the status information of the target access point device.

3. The method according to claim 1, characterized in that, The IoT device stores a local fingerprint set, and the server stores a cloud fingerprint set. The IoT device and the server are communicatively connected. Both the local fingerprint set and the cloud fingerprint set contain sample device fingerprints. The sample device fingerprints in the local fingerprint set are associated with a recording time. The current device fingerprint is matched with each sample device fingerprint for similarity, and the recommended configuration parameters corresponding to the successfully matched sample device fingerprints are obtained to obtain the target configuration parameters, including: Perform similarity matching between the current device fingerprint and each sample device fingerprint in the local fingerprint set; If there is no successfully matched sample device fingerprint in the local fingerprint set, or if the record time corresponding to the successfully matched sample device fingerprint in the local fingerprint set has expired, the current device fingerprint is sent to the server so that the server performs similarity matching between the current device fingerprint and each sample device fingerprint in the cloud fingerprint set, obtains the recommended configuration parameters corresponding to the successfully matched sample device fingerprint in the cloud fingerprint set, and obtains the target configuration parameters. If a matching sample device fingerprint exists in the local fingerprint set, and the record time corresponding to the matching sample device fingerprint in the local fingerprint set has not expired, then the recommended configuration parameters corresponding to the matching sample device fingerprint in the local fingerprint set are directly obtained to obtain the target configuration parameters.

4. The method according to claim 1, characterized in that, The sample device fingerprint is associated with multiple levels of recommended configuration parameters, each level of which has a threshold judgment condition. The process of performing similarity matching between the current device fingerprint and each sample device fingerprint to obtain the recommended configuration parameters corresponding to the successfully matched sample device fingerprint, and thus obtaining the target configuration parameters, includes: The similarity between the current device fingerprint and the fingerprints of each sample device is calculated to obtain the fingerprint similarity between the current device fingerprint and the fingerprints of each sample device. If the highest fingerprint similarity is greater than the preset minimum threshold, then the sample device fingerprint corresponding to the highest fingerprint similarity is selected to obtain the successfully matched sample device fingerprint. Determine the threshold judgment condition that the highest fingerprint similarity satisfies, obtain the recommended configuration parameters for the level corresponding to the satisfied threshold judgment condition, and obtain the target configuration parameters.

5. The method according to claim 4, characterized in that, The step of calculating the similarity between the current device fingerprint and each sample device fingerprint to obtain the fingerprint similarity between the current device fingerprint and each sample device fingerprint includes: Compare the similarity and difference fields between the current device fingerprint and the sample device fingerprint; The fingerprint similarity between the current device fingerprint and the sample device fingerprint is calculated based on the field type and / or number of the similar fields and / or the field type and / or number of the difference fields.

6. The method according to claim 1, characterized in that, After configuring the IoT device based on the target configuration parameters, the method further includes: In response to the failure of the IoT device to connect to the target access point device, the number of connection failures is counted. Determine the parameter adjustment strategy based on the number of connection failures; The IoT device is adjusted according to the parameter adjustment strategy so that the IoT device with adjusted parameters can reconnect to the target access point device.

7. The method according to claim 1, characterized in that, After configuring the IoT device based on the target configuration parameters, the method further includes: In response to the successful connection of the IoT device to the target access point device, network quality information and / or device status information of the IoT device are collected to obtain environmental information; The signal transmission power is adjusted based on the environmental information to obtain the target transmission power, so that the IoT device can use the target transmission power for data transmission.

8. The method according to claim 1, characterized in that, After configuring the IoT device based on the target configuration parameters, the method further includes: In response to the successful connection of the IoT device to the target access point device, the timestamps corresponding to each beacon frame sent by the target access point device to the IoT device are obtained; Based on the timestamps corresponding to each beacon frame, the time difference between adjacent beacon frames is calculated to obtain the historical time interval. The predicted time interval is calculated based on the historical time interval, and the wake-up time of the IoT device is calculated based on the predicted time interval, so that the IoT device enters the active state when the wake-up time is reached, otherwise it remains in the sleep state.

9. An Internet of Things (IoT) device, characterized in that, The Internet of Things (IoT) device includes a memory and a processor, the processor being configured to execute program instructions stored in the memory to implement the steps of the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program instructions that can be executed by a processor to implement the steps of the method as described in any one of claims 1-8.

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