Internet of Things equipment local networking method and system based on working channel automatic distribution

Abstract

The invention discloses an Internet of Things equipment local networking method and system based on working channel automatic allocation, relates to the technical field of Internet of Things, and solves the technical problems that the channel allocation of Internet of Things equipment lacks flexibility and self-adaptive capability, and the network stability and the data transmission reliability are influenced. The method comprises the following steps: a channel monitoring module monitors multiple communication indexes of a current working channel in real time to obtain monitoring data; the central network manager analyzes and decides the monitoring data through an intelligent channel allocation algorithm of machine learning, determines an optimal channel allocation scheme, and automatically allocates channels; automatically switching the Internet of Things equipment to a new working channel, and carrying out the local networking of the Internet of Things equipment; and the channel monitoring module continuously monitors the new working channel in real time. The method is suitable for various scales and types of Internet of Things applications, has flexibility and self-adaptive capability, realizes network stability and data transmission reliability, and improves the communication efficiency of the network.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly to a method and system for local networking of Internet of Things devices based on automatic allocation of working channels. Background Art

[0002] With the rapid development of Internet of Things technology, more and more devices are connected through wireless networks to jointly complete complex tasks. Among these devices, how to effectively manage communication channels has become an important issue. Traditional networking of Internet of Things devices usually relies on manual channel configuration or the use of static channel allocation strategies, which often lead to channel conflicts and low communication efficiency when the number of devices is large or the environment is complex.

[0003] In the prior art, the channel allocation of Internet of Things devices often does not consider real-time network load and interference conditions, lacking flexibility and adaptability, which directly affects the stability of the network and the reliability of data transmission. Therefore, there is an urgent need for a method that can dynamically adjust and optimize channel allocation to improve the communication efficiency and network performance of Internet of Things devices in local networking.

[0004] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:

[0005] The channel allocation of Internet of Things devices lacks flexibility and adaptability, affecting network stability and data transmission reliability. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and system for local networking of Internet of Things devices based on automatic allocation of working channels to solve the technical problem that the channel allocation of Internet of Things devices in the prior art lacks flexibility and adaptability, affecting network stability and data transmission reliability. The numerous technical effects that can be produced by the preferred technical solutions among the numerous technical solutions provided by the present invention are described in detail below.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An Internet of Things device local networking method based on automatic working channel allocation provided by the present invention includes the following steps: S100: In each Internet of Things device, a channel monitoring module monitors multiple communication metrics of the current working channel in real time, obtains monitoring data and sends it to the central network manager; S200: The central network manager analyzes and makes decisions on the monitoring data through an intelligent channel allocation algorithm of machine learning to determine the optimal channel allocation scheme; S300: Based on the optimal channel allocation scheme, the central network manager sends channel adjustment instructions to all the Internet of Things devices for automatic channel allocation; S400: After receiving the channel adjustment instructions, the Internet of Things devices automatically switch to the new working channel for local networking of the Internet of Things devices; S500: The channel monitoring module continues to monitor the working conditions of the switched new working channel in real time.

[0009] Preferably, in the step S100, the multiple communication metrics include at least one of signal strength, noise level, interference situation, and channel utilization rate.

[0010] Preferably, in the step S100, the monitoring data is sent to the central network manager periodically or when there are significant changes in the channel conditions.

[0011] Preferably, in the step S200, the central network manager also dynamically monitors the spectrum usage of available channels through spectrum sensing technology and automatically adjusts channel allocation according to the real-time spectrum occupancy.

[0012] Preferably, in the step S200, the intelligent channel allocation algorithm is obtained through the following steps: S210: Train a machine learning model through historical data so that it can identify various channel usage patterns and interference patterns; S220: Continuously adjust and optimize the channel allocation strategy of the machine learning model through a genetic algorithm, so that the machine learning model gradually learns the optimal decision-making in different environments and adapts to network changes.

[0013] Preferably, the channel allocation strategy preferentially allocates channels with lower interference to Internet of Things devices with higher communication requirements, and allocates channels with lower utilization or higher interference to Internet of Things devices with lower requirements.

[0014] Preferably, in the step S300, the central network manager sends the channel adjustment instructions in stages and regions according to the scale of the Internet of Things devices.

[0015] Preferably, in the step S500, at least one of the stability, data transmission rate, and error rate of the new working channel is monitored.

[0016] Preferably, in step S500, when at least one of the stability, data transmission rate, and error rate of the new working channel exceeds a set threshold, the central network manager reallocates the working channel to the corresponding Internet of Things device.

[0017] An Internet of Things device local networking system based on automatic working channel allocation, which is used to run the Internet of Things device local networking system based on automatic working channel allocation described in any one of the above, includes Internet of Things devices, a channel monitoring module, a central network manager, and a security policy module; the channel monitoring module is arranged in the Internet of Things device and is used to monitor the communication status of the Internet of Things device; the central network manager is communicatively connected to the Internet of Things device and is used to perform automatic channel allocation for multiple Internet of Things devices; the security policy module is arranged in the central network manager and is used to perform data encryption, access control, and data anonymization during the channel allocation and data transmission of the Internet of Things device local networking system, so that the data is not accessed or tampered with without authorization.

[0018] Implementing one of the above technical solutions of the present invention has the following advantages or beneficial effects:

[0019] Through intelligent algorithm prediction and dynamic adjustment, this method effectively avoids channel conflicts and interference, and improves the reliability of data transmission; optimizes channel allocation according to real-time data and prediction algorithms, significantly improving network capacity and throughput; the automation of channel allocation reduces the need for manual intervention, enabling the network to quickly respond to environmental changes and adapt to complex and changing application scenarios. In addition, the optimized channel allocation reduces the energy consumption of the device during repeated signal search and conflict resolution processes, extending the service life and working time of the device. The method of the present invention is applicable to various scales and types of Internet of Things applications, whether it is a home Internet of Things, a small industrial network, or a large-scale smart city infrastructure, with flexibility and adaptability, achieving network stability and data transmission reliability, not only improving the communication efficiency of the network, but also providing strong support for the future expansion and application of the Internet of Things. Description of the Drawings

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings. In the drawings:

[0021] Figure 1 It is a flowchart of the method for local networking of Internet of Things devices based on automatic working channel allocation in Embodiment 1 of the present invention;

[0022] Figure 2 This is the flowchart of step S200 in the local networking method for Internet of Things devices based on automatic working channel allocation in the first embodiment of the present invention. Detailed implementation manners

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, various exemplary embodiments to be described below will refer to the corresponding drawings, which form a part of the exemplary embodiments and describe various exemplary embodiments that may be adopted to implement the present invention. Unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present disclosure. It should be understood that they are merely examples of processes, methods, devices, etc. consistent with some aspects of the present invention disclosed in detail in the appended claims. Other embodiments may also be used, or structural and functional modifications may be made to the embodiments listed herein without departing from the scope and essence of the present invention.

[0024] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", etc. indicate the orientation or positional relationship based on the drawings shown, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the elements referred to must have a specific orientation, be constructed and operated in a specific orientation. The terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. The meaning of the term "plurality" is two or more. The terms "connected" and "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, an integral connection, a mechanical connection, an electrical connection, a communication connection, a direct connection, an indirect connection through an intermediate medium, and may be the internal communication of two elements or the interaction relationship between two elements. The term "and / or" includes any and all combinations of one or more of the related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention may be understood according to specific circumstances.

[0025] In order to illustrate the technical solutions described in the present invention, the following will be described through specific examples, and only the parts related to the embodiments of the present invention are shown.

[0026] Embodiment 1:

[0027] As Figure 1As shown in the figure, the present invention provides a method for local networking of Internet of Things devices based on automatic allocation of working channels, including the following steps: S100: In each Internet of Things device, a channel monitoring module monitors multiple communication metrics of the current working channel in real time, obtains monitoring data and sends it to the central network manager; S200: The central network manager analyzes and makes decisions on the monitoring data through an intelligent channel allocation algorithm of machine learning to determine the optimal channel allocation scheme; S300: Based on the optimal channel allocation scheme, the central network manager sends channel adjustment instructions to all Internet of Things devices for automatic channel allocation; S400: After receiving the channel adjustment instructions, the Internet of Things devices automatically switch to the new working channel; S500: The channel monitoring module continues to monitor the working conditions of the switched new working channel in real time to achieve feedback after channel switching and allocation. If the new channel performs poorly in actual use, the system can quickly identify and reallocate a more suitable channel. This method effectively avoids channel conflicts and interference through intelligent algorithm prediction and dynamic adjustment, improving the reliability of data transmission; optimizing channel allocation according to real-time data and prediction algorithms significantly enhances network capacity and throughput; the automation of channel allocation reduces the need for manual intervention, enabling the network to quickly respond to environmental changes and adapt to complex and changing application scenarios. In addition, the optimized channel allocation reduces the energy consumption of devices during repeated signal search and conflict resolution processes, extending the service life and working time of the devices. The method of the present invention is applicable to various scales and types of Internet of Things applications, whether it is a home Internet of Things, a small industrial network, or a large-scale smart city infrastructure, which can not only improve the communication efficiency of the network, but also provide strong support for the future expansion and application of the Internet of Things.

[0028] As an alternative implementation, in step S100, the multiple communication metrics include at least one of signal strength, noise level, interference situation, and channel utilization rate. Of course, the monitoring metrics of the channel monitoring module can also be increased according to actual needs to further improve the flexibility and adaptability of the automatic allocation of working channels. By monitoring the above metrics, it is convenient to achieve reliable local networking of IoT devices. Signal strength monitoring: Signal strength is an important factor affecting communication quality. By continuously monitoring the signal strength, it can be ensured that the signal in the channel where the IoT device is located is strong enough to support stable data transmission. Noise level detection: The level of noise directly affects the clarity of the channel and the accuracy of data transmission. By monitoring the noise level, interference sources can be identified and channels with severe interference can be avoided. Interference situation analysis: IoT devices will regularly scan the usage of adjacent channels, evaluate possible interference sources and interference intensities, so that high-interference areas can be identified in advance and channels can be avoided from being allocated to these areas. Channel utilization rate evaluation: Real-time evaluation of the channel utilization rate helps to determine which channels are approaching saturation in the current environment and which channels still have available capacity, which is crucial for optimizing the allocation of channel resources. The monitoring data is sent to the central network manager periodically or when there are significant changes in the channel conditions for subsequent channel analysis and decision-making.

[0029] As an alternative implementation, in step S200, the central network manager also dynamically monitors the spectrum usage of available channels through spectrum sensing technology, and automatically adjusts the channel allocation according to the real-time spectrum occupancy, so as to effectively avoid channel conflicts and interference and improve network stability and data transmission reliability.

[0030] As an alternative implementation, as Figure 2 shown, in step S200, the intelligent channel allocation algorithm is obtained through the following steps: S210: Train a machine learning model through historical data so that it can identify various channel usage patterns and interference patterns; S220: Continuously adjust and optimize the channel allocation strategy of the machine learning model through the genetic algorithm, so that the machine learning model gradually learns the optimal decision-making in different environments and adapts to network changes. The channel allocation strategy preferentially allocates channels with lower interference to IoT devices with higher communication requirements, and allocates channels with lower utilization or higher interference to IoT devices with lower requirements.

[0031] As an alternative implementation, in step S300, the central network manager sends channel adjustment instructions in stages and regions according to the scale of IoT devices to avoid instantaneous network congestion caused by a large number of devices switching channels simultaneously in a short period of time and improve the efficiency of IoT device networking.

[0032] As an alternative embodiment, in step S500, at least one of the stability, data transmission rate, and error rate of the new working channel is monitored, realizing the feedback of the monitored data, thereby ensuring that the channel allocation strategy always remains efficient and adaptable. In this embodiment, preferably, the feedback data of the new working channel monitoring is sent back to the central network manager. These feedback data will be used to evaluate the actual effect of the channel allocation. Based on these feedback data, the intelligent channel allocation algorithm can be continuously updated and optimized. Through continuous learning and adjustment, the system can more accurately respond to future network environment changes and device requirements. For example, if a certain channel frequently has problems within a period of time, the intelligent channel allocation algorithm can automatically adjust the weight and reduce the priority of this channel in future allocations. At the same time, over time, it will become more and more adaptable to changes in a specific network environment, such as the increase of devices, the change of environmental interference, etc., so as to maintain the dynamic optimum of the channel allocation.

[0033] As an alternative embodiment, in step S500, when at least one of the stability, data transmission rate, and error rate of the new working channel exceeds a set threshold, which is set as needed, the central network manager reallocates the working channel to the corresponding Internet of Things device.

[0034] The embodiment is only a special case and does not indicate that the present invention has only such an implementation manner.

[0035] Embodiment 2:

[0036] An Internet of Things device local networking system based on automatic working channel allocation, used to run the Internet of Things device local networking system based on automatic working channel allocation in any one of Embodiment 1, includes Internet of Things devices, a channel monitoring module, a central network manager, and a security policy module; the channel monitoring module is set in the Internet of Things device and is used to monitor the communication status of the Internet of Things device; the central network manager is communicatively connected to the Internet of Things device and is used to perform automatic channel allocation for multiple Internet of Things devices; the security policy module is set in the central network manager and is used to perform data encryption, access control, and data anonymization during the channel allocation and data transmission of the Internet of Things device local networking system, so that the data is not accessed or tampered with without authorization. Data encryption: All transmitted data is encrypted to prevent being stolen or tampered with during transmission, which includes channel monitoring data, allocation instructions, and feedback information, etc. Access control: The system adopts a strict access control mechanism internally, and only authorized devices and users can access sensitive data and perform key operations, which effectively prevents potential security threats. Data anonymization: To protect user privacy, the system anonymizes all monitored and feedback data to ensure that the specific information of individuals or devices will not be leaked. At the same time, the system will regularly clean and update the stored data to reduce the risk of data leakage.

[0037] The above are only the preferred embodiments of the present invention. Those skilled in the art will know that various changes or equivalent replacements can be made to these features and embodiments without departing from the spirit and scope of the present invention. Additionally, under the teaching of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application belong to the protection scope of the present invention.

Claims

1. A method for local networking of Internet of Things devices based on automatic allocation of working channels, characterized in that: The following steps are involved: S100: In each IoT device, a channel monitoring module is used to monitor multiple communication indicators of the current working channel in real time, and the monitoring data is obtained and sent to the central network manager; S200: The central network manager analyzes and makes decisions on the monitoring data through a machine learning intelligent channel allocation algorithm to determine an optimal channel allocation solution; S300: Based on the optimal channel allocation scheme, the central network manager sends a channel adjustment instruction to all the IoT devices to automatically allocate channels; S400: After receiving the channel adjustment instruction, the IoT device automatically switches to a new working channel to perform local networking of the IoT device; S500: The channel monitoring module continues to monitor the working status of the new working channel after switching in real time.

2. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1 is characterized in that: In the step S100, the plurality of communication indicators include at least one of signal strength, noise level, interference condition, and channel utilization.

3. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1, characterized in that: In the step S100, the monitoring data is sent to the central network manager periodically or when the channel condition changes significantly.

4. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1, characterized in that: In the step S200, the central network manager also dynamically monitors the spectrum usage of available channels through spectrum sensing technology, and automatically adjusts channel allocation according to real-time spectrum occupancy.

5. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 4 is characterized in that: In step S200, the intelligent channel allocation algorithm is obtained by the following steps: S210: Trains machine learning models using historical data to identify various channel usage patterns and interference patterns; S220: The channel allocation strategy of the machine learning model is continuously adjusted and optimized through the genetic algorithm, so that the machine learning model gradually learns the optimal decision-making in different environments and adapts to network changes.

6. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 5, characterized in that: The channel allocation strategy preferentially allocates channels with lower interference to IoT devices with higher communication demands, and allocates channels with lower utilization or greater interference to IoT devices with lower demands.

7. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1, characterized in that: In the step S300, the central network manager sends the channel adjustment instruction in stages and regions according to the scale of the IoT devices.

8. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1, characterized in that: In the step S500, at least one of the stability, data transmission rate, and error rate of the new working channel is monitored.

9. The method for local networking of Internet of Things devices based on automatic allocation of working channels according to claim 1, characterized in that: In the step S500, when at least one of the stability, data transmission rate, and error rate of the new working channel exceeds a set threshold, the central network manager re-allocates a working channel to the corresponding IoT device.

10. A local networking system for Internet of Things devices based on automatic allocation of working channels, characterized in that: Used to run the local networking system of Internet of Things devices based on automatic allocation of working channels as described in any one of claims 1-9, comprising an Internet of Things device, a channel monitoring module, a central network manager and a security policy module; the channel monitoring module is arranged in the Internet of Things device, and is used to monitor the communication status of the Internet of Things device; the central network manager is communicatively connected with the Internet of Things device, and is used to automatically allocate channels to multiple Internet of Things devices; the security policy module is arranged in the central network manager, and is used to perform channel allocation of the local networking system of the Internet of Things device and data encryption, access control and data anonymization during data transmission, so that the data cannot be accessed or tampered with without authorization.

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