Internet of Things terminal intelligent connection system and method based on global operator network

Abstract

The invention relates to the technical field of Internet of Things, and discloses an Internet of Things terminal intelligent connection system and method based on a global operator network, and the method comprises the steps: when equipment is powered on or restarted, automatically executing network environment scanning, detecting a currently available cellular network, and collecting signal intensity, network coverage condition, delay and bandwidth; the equipment identifies an available operator network based on a global network configuration file, and comprehensively evaluates signal strength, network coverage, delay and bandwidth by adopting an optimization algorithm; the equipment continuously monitors a current connection state, collects network quality parameters, analyzes a network fluctuation trend in combination with a machine learning algorithm, and judges whether to switch to other operator networks when monitoring that the network quality is lower than a dynamic threshold value; and when detecting that the current network quality is continuously reduced, the signal is weak or the connection is lost, automatically triggering a network switching mechanism. The method has the advantage of improving the connection efficiency and stability of the Internet of Things terminal.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly to an intelligent connection system and method for Internet of Things terminals based on the global operator network. Background Art

[0002] With the continuous development of the Internet of Things technology, more and more devices are connected to the Internet through various communication methods, forming a huge Internet of Things ecosystem. In this ecosystem, the intelligent connection technology of Internet of Things terminals has become the key to realizing efficient communication and data exchange between devices. However, the existing Internet of Things connection technologies still face some challenges, especially the stable connection problem of Internet of Things terminals in remote areas. Currently, the connection of Internet of Things terminals usually relies on a single operator network, or requires complex network switching and protocol conversion to achieve interconnection between multiple operators. Such solutions not only increase the difficulty of system deployment and maintenance, but also may lead to poor stability of terminal connection, high data transmission delay, and even inability to ensure the continuity and reliability of connection in some remote areas or special scenarios. Therefore, it is necessary to design an intelligent connection system and method for Internet of Things terminals based on the global operator network to improve the connection efficiency and stability of Internet of Things terminals. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides an intelligent connection system and method for Internet of Things terminals based on the global operator network, which has the advantages of improving the connection quality and stability of Internet of Things terminals globally and solving the cross-operator connection problem in the prior art, and solves the problems in the above background art.

[0004] To achieve the above object of improving the connection efficiency and stability of Internet of Things terminals and solving the cross-operator connection problem in the prior art, the present invention provides the following technical solution: An intelligent connection method for Internet of Things terminals based on the global operator network, comprising the following steps:

[0005] S1: When the device is powered on or restarted, automatically perform a network environment scan, detect the currently available cellular networks, and collect signal strength, network coverage, latency, and bandwidth.

[0006] Preferably, the S1 further includes identifying the accessible operator network through the PLMNID, evaluating the network coverage based on the cell information and location area, automatically selecting the optimal network frequency band, adopting an intelligent scanning strategy, dynamically adjusting the communication protocol by the device according to the network conditions, real-time monitoring the network performance, and triggering network switching when the signal quality is poor.

[0007] S2: The device identifies available carrier networks based on the global network profile, and uses an optimization algorithm to comprehensively evaluate signal strength, network coverage, latency, and bandwidth, selects a carrier for initial access, and completes network registration through an intelligent authentication method.

[0008] Preferably, S2 further includes scanning the surrounding environment to identify available carrier networks and collect signal strength, network type, latency, and bandwidth. Based on a comprehensive evaluation including signal strength, network coverage, latency, and bandwidth, the device uses an optimization algorithm to select the most suitable carrier network, completes network access through an intelligent authentication method, automatically selects the authentication process, and provides the access process, supporting signal strength and multi-factor authentication.

[0009] S3: The device continuously monitors the current connection status, collects network quality parameters, and analyzes the network fluctuation trend in combination with a machine learning algorithm to predict the trend of network quality changes. When it detects that the network quality is lower than the dynamic threshold, the device determines whether it needs to switch to another carrier network.

[0010] Preferably, S3 further includes continuously monitoring network quality and combining it with a machine learning algorithm to analyze and predict the fluctuation trend of network quality, predicting network state changes based on historical data, dynamically adjusting the threshold for network quality evaluation. When the network quality drops to the set threshold, the device automatically activates the network switching mechanism and uses an optimization algorithm to comprehensively evaluate multiple network factors.

[0011] Preferably, the prediction of network state changes and the dynamic adjustment of the network quality evaluation threshold further include the device using a machine learning algorithm to adjust the threshold of each network quality parameter according to historical data, and the device adjusts the threshold of each quality parameter according to network environment changes. The formula is:

[0012] T param (t) = T param (t - 1)+α*(NQ(t)-NQ avg )

[0013] In the formula, T param (t) is the parameter threshold at the t-th moment; T param (t - 1) is the parameter threshold at the (t - 1)-th moment; NQ(t) is the network quality score at the t-th moment; NQ avg is the historical average network quality score; α is the learning rate, indicating the sensitivity of threshold adjustment;

[0014] When the network quality score drops to the set threshold, the device triggers the network switching mechanism. The judgment condition is: NQ(t) < T param( t); if the condition is met, the switching mechanism is activated.

[0015] S4: When it is detected that the current network quality continues to decline, the signal is weak, or the connection is lost, the network switching mechanism is automatically triggered. Based on the pre-stored multi-operator access parameters, the device selects an operator network using an optimization algorithm and adopts seamless switching technology to optimize connection stability.

[0016] Preferably, S4 further includes automatically triggering the switching mechanism by real-time monitoring of the network quality. The device pre-stores access parameters of multiple operators, comprehensively evaluates the currently available networks using an optimization algorithm, selects a network for access, and the device adopts seamless switching technology. The switching decision takes into account network load, bandwidth requirements, and user preferences to flexibly respond to different application scenarios and quickly complete network switching.

[0017] Preferably, the optimization algorithm further includes comprehensively evaluating multiple operator networks based on real-time network quality data, calculating the network quality score according to the weight of each evaluation parameter, and selecting the network with the highest score for access. The algorithm makes intelligent decisions based on historical connection data, network switching costs, as well as the user's bandwidth requirements and service quality requirements.

[0018] An intelligent connection system for Internet of Things terminals based on global operator networks, comprising:

[0019] A network environment scanning module that automatically identifies the available cellular networks around and evaluates their quality;

[0020] A network access selection module that selects an operator network according to the network quality parameters obtained by scanning, and completes the authentication and network access process for the selected operator;

[0021] A network quality monitoring and analysis module that obtains the current network status in real time, predicts the future network quality trend based on network quality data and machine learning algorithms, determines whether it meets the network requirements of the current application, and decides whether to switch to other operator networks.

[0022] A network switching and optimization module that automatically switches to a network with a stronger signal when the current network quality cannot meet the requirements.

[0023] Compared with the prior art, the present invention provides an intelligent connection system and method for Internet of Things terminals based on global operator networks, having the following beneficial effects:

[0024] The present invention realizes intelligent network selection and switching by means of real-time scanning and acquisition of network quality parameters, combined with global network profiles, optimization algorithms, and machine learning analysis. This method can comprehensively evaluate multiple factors such as signal strength, coverage, latency, and bandwidth of different operator networks to ensure that the device is always connected to the optimal network. When a decrease in network quality is detected, the device can automatically trigger a switching mechanism to optimize connection stability through seamless switching technology, avoid communication interruption, ensure the continuity and reliability of data transmission, significantly improve the user experience, and reduce device power consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the method of the present invention;

[0026] Figure 2 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment 1

[0029] Please refer to Figure 1 As shown, an intelligent connection method for an Internet of Things terminal based on global operator networks according to an embodiment of the present invention includes the following steps:

[0030] S1: When the device is powered on or restarted, it automatically performs a network environment scan, detects the currently available cellular networks, and collects signal strength, network coverage, latency, and bandwidth.

[0031] The device can support and scan multiple cellular network bands, including but not limited to 2G (GSM), 3G (WCDMA / CDMA), 4G (LTE), 5G (NR), NB-IoT, eMTC, etc. This enables the device to adapt to various network standards globally according to the requirements of different operators and network environments. The supported band scanning includes low-frequency bands (such as 700 MHz), medium-frequency bands (such as 1800 MHz), high-frequency bands (such as 3500 MHz), etc., to adapt to the signal requirements and network coverage characteristics of different scenarios. The device will collect and analyze multiple network quality parameters in real time, such as RSRP (Reference Signal Received Power), RSSI (Received Signal Strength Indicator), SINR (Signal-to-Interference-plus-Noise Ratio), RSRQ (Reference Signal Received Quality), for judging the connection quality of the current network. Delays (such as RTT, Round-Trip Time) and bandwidth (such as throughput, upload / download rate) will also be continuously monitored to evaluate the communication performance of the current network. The device can perform real-time evaluation and make optimized selections under various network conditions (such as signal strength changes, network congestion, latency fluctuations, etc.). Identify the currently accessible operator network through PLMNID, and analyze the network coverage of the current area based on cell information and location area. Automatically determine whether to access different network bands according to the geographical location, and optimize the access strategy of the device. In areas with weak signals, the device will select a network that can provide better coverage, and perform handover or rescan to avoid being in a state of no network or low-quality connection for a long time. The device will conduct network performance tests, such as detecting network latency through PING tests and conducting bandwidth tests through TCP / UDP, to evaluate network stability indicators such as packet loss rate and jitter. The device will dynamically adjust its communication protocol and network access method according to the actual performance of the network (for example, adjust to a lower rate mode to optimize stability). Based on the collected parameters such as signal strength, bandwidth, and delay, the device uses optimization algorithms (such as weighted average method, priority algorithm, etc.) to select the optimal network. When multiple operator networks are available, the device preferentially connects to the network with the best signal quality and optimal bandwidth to reduce the impact of network handover. The device will predict network quality changes based on historical data and environmental changes (such as moving speed, network fluctuations, etc.) and make corresponding handover decisions in advance. The device adopts an intelligent scanning strategy to avoid continuous high-frequency scanning. It scans only when necessary or according to network quality changes to reduce power consumption and extend the battery life of the device. When the network connection is stable, the device can enter the low-power standby mode to reduce unnecessary energy consumption. When the device detects that the current network quality does not meet the preset requirements, it will automatically trigger the network handover mechanism and quickly switch to a network with better signal quality based on the optimization algorithm. During the network handover process, the device will try to avoid interrupting communication and use seamless handover technology to ensure the stability and continuity of the data stream.

[0032] With support for multiple frequency bands and multiple network modes, the device can adapt to the network environments of different operators globally, ensuring that an available cellular network can be found in various scenarios (such as cities, rural areas, and remote regions). The device can perform automatic network selection and optimization in weak signal or remote areas, greatly improving network coverage and access success rate. Through dynamic evaluation and multi-parameter signal quality detection, the device can always connect to the optimal network, avoiding connection interruptions or performance degradation caused by signal attenuation or network quality fluctuations. It evaluates network performance such as latency, bandwidth, and packet loss rate in real time to ensure that the device is always in a stable network environment. Network performance testing and optimization algorithms can significantly reduce the data transmission latency of the device, especially in applications with high real-time requirements (such as telemedicine, vehicle networking, industrial automation, etc.), where it can ensure low-latency and high-bandwidth connections. In the case of packet loss in the network, the device can automatically select a better network, reducing data loss and retransmission during communication and improving transmission efficiency. Through the preferred algorithm and intelligent switching mechanism, the device can quickly switch to a carrier network with better quality, avoiding service interruptions caused by poor connection quality. During the switching process, the device can adopt seamless switching technology to ensure uninterrupted communication and avoid increased latency or data loss caused by network switching. Through intelligent scanning and low-power design, the device can enter the low-power mode when the network environment is stable, reducing power consumption and significantly extending the battery life of the device. It triggers network scanning only when necessary, avoiding the energy waste caused by high-frequency scanning. The device adaptively adjusts network scanning and selection strategies according to different environmental conditions (such as high-speed movement, building obstruction, etc.) to improve network connection stability in complex environments. In different network environments (such as indoors, outdoors, underground garages, etc.), the device can quickly detect and access available networks, reducing connection failures or network instability caused by environmental restrictions.

[0033] S2: Based on the global network profile, the device identifies available carrier networks, comprehensively evaluates signal strength, network coverage, latency, and bandwidth using a preferred algorithm, selects a carrier for initial access, and completes network registration through an intelligent authentication method.

[0034] The device contains a network configuration file that includes operators from around the world. This file contains information such as the PLMN (Public Land Mobile Network) ID, TAC (Tracking Area Code), LAC (Location Area Code), etc. for each region and operator. The network configuration file provides detailed configurations based on information such as operator type, network band, access strategy, etc., supporting adaptation to a global multi-operator network environment. The configuration file can be dynamically updated according to the geographical location and network environment of the device, ensuring that the device can always identify the latest available network. The device scans the surrounding environment to identify the available operator networks in the current area. When the device scans for available networks, it not only identifies the band but also can parse the signal strength, network type, and automatically select the most suitable operator network. During the automated network identification process, the device can collect base station information (such as cell ID, network type, etc.) and signal strength (such as RSRP, RSSI, etc.) in real-time and determine the current network coverage. Based on parameters such as the signal strength, network coverage, latency, and bandwidth collected by the device, the device will use an optimization algorithm to comprehensively evaluate multiple available networks. Signal strength: The optimization algorithm gives priority to RSRP and RSSI to judge the signal quality of each network. Network coverage: The device will analyze the cell coverage in the current area and prefer operators with a wide coverage range and stable signals. Latency: The device will analyze the network latency and prefer networks with lower latency to improve the real-time performance of data transmission. Bandwidth: The device will combine throughput and bandwidth data and prefer operators with a wider network bandwidth to ensure data transmission efficiency. After comprehensive evaluation, the device will select a network as the initial access network to ensure the reliability and performance of the connection. After selecting the optimal operator network, the device conducts network registration through an intelligent authentication method to complete device access. Intelligent authentication refers to user identity verification through methods such as SIM card authentication, USIM authentication, or eSIM authentication, ensuring that the device can successfully access the operator network. The device will automatically select an appropriate authentication process according to the different protocols of the selected operator network, simplifying the authentication process and increasing the access speed. The device can also further enhance the security and stability of the access process through signal strength-based authentication and multi-factor authentication.

[0035] With the support of the global network profile, the device can seamlessly adapt to the network environments of different operators worldwide and automatically identify and connect to available networks. The device can automatically select the appropriate operator according to the real-time environment, ensuring that the device can quickly connect to the network globally, reducing the need for manual settings and enhancing the user experience. Through the comprehensive evaluation of parameters such as signal strength, latency, and bandwidth by the optimization algorithm, the device can select the operator network with the best performance for access, ensuring the stability of the connection and the efficiency of data transmission. This technology ensures that the device can select the optimal network in different environments (such as cities, mountains, remote areas, etc.), reducing connection failures and poor performance caused by poor signal and high latency. When switching networks, the device adopts an intelligent authentication method to quickly complete the access, improving the switching speed and reducing connection interruptions and latency. The intelligent selection of the authentication method and the adaptive algorithm can simplify the process, optimize the access efficiency, and ensure security at the same time, avoiding unnecessary manual intervention. Through the automated operator identification and optimization algorithm, users no longer need to rely on a single operator. The device can automatically select the optimal operator according to the network quality, thereby reducing the user's dependence on a certain operator and enhancing flexibility. Users can automatically switch to the most suitable operator according to the current network conditions without any configuration, optimizing the connection experience. The intelligent authentication method ensures that the access process of the device is more secure, especially in a multi-operator environment, guaranteeing the identity authentication and data security during the device access process. This authentication method can not only automatically select the authentication method according to the protocols of different operators but also improve the network's anti-attack ability and ensure the security of communication content. Through the accurate signal quality evaluation and network coverage analysis, the device can optimize the selection strategy according to environmental changes, ensuring efficient and stable services in different environments. The device can dynamically adjust the configuration according to the network conditions, adapt to complex environments such as high-speed movement and changing signal conditions, and ensure the continuous network connection quality.

[0036] S3: The device continuously monitors the current connection status, collects network quality parameters, and combines machine learning algorithms to analyze the network fluctuation trend and predict the network quality change trend. When it detects that the network quality is lower than the dynamic threshold, the device determines whether it needs to switch to the network of other operators.

[0037] The device continuously monitors the current network connection in real time and regularly collects network quality parameters such as signal strength (e.g., RSRP, RSSI), network latency (e.g., RTT), bandwidth (e.g., throughput), and packet loss rate. Through the network quality collection module, the device continuously records and analyzes the real-time network quality to ensure that network performance changes can be detected in a timely manner. The device introduces machine learning algorithms such as time series analysis, regression analysis, or neural networks to learn long-term data of network quality parameters, analyze and predict the fluctuation trends of network quality. The device trains the machine learning model with historical network quality data so that it can identify and predict the change trends of network quality (such as increased latency, signal attenuation, etc.). The machine learning model can not only analyze real-time data but also predict the network state in the short term in the future based on historical trends, and identify potential trends of network quality degradation or instability in advance. The dynamic threshold is a parameter that is adjusted in real time based on historical network data, environmental conditions, and device usage scenarios. The device automatically adjusts the threshold according to different application requirements and the environment where it is located (such as urban, rural, mountainous areas, etc.) to ensure the evaluation of network quality according to different scenario requirements. The device automatically adjusts the tolerance according to the historical fluctuations of network quality and activates the switching mechanism when the network quality drops to a certain level. The threshold is dynamically adjusted not only considering the current network quality but also combining the network fluctuation trend. The device determines whether to switch to another available operator network by comparing the current network quality with the set dynamic threshold.

[0038] The determination basis includes:

[0039] Signal strength: When the signal strength is lower than the set threshold (e.g., when RSRP or RSSI reaches the set minimum standard).

[0040] Latency: When the latency exceeds the preset threshold (e.g., when RTT is greater than the set maximum value).

[0041] Bandwidth: When the current bandwidth cannot meet the data transmission requirements, it is judged as a trigger condition for switching.

[0042] Packet loss rate: When the packet loss rate is too high (exceeding the preset tolerance range), it indicates that the current network is unstable and a switch is required.

[0043] When these network quality degradations are detected, the device evaluates whether a network switch should be made. The device employs an optimization algorithm that comprehensively considers multiple factors such as signal strength, latency, bandwidth, packet loss rate, etc., to evaluate whether to switch to another network. The device does not rely solely on one carrier network; it also selects the optimal available network according to the optimization algorithm (such as based on network coverage priority, network quality score). The optimization algorithm also incorporates historical connection data and network switching costs (such as switching time consumption, data interruption, etc.) to select the best switching path. Through network access parameter storage, the device can pre-store the access parameters of multiple carriers during the switching process, ensuring that the switching process does not require re-authentication, thereby accelerating the switching speed. The device makes judgments not only based on current network quality parameters but also combines environmental changes (such as moving speed, signal strength changes, etc.) to determine the necessity of switching. The device adopts seamless switching technology, and even when switching to a new carrier network, the device will try to maintain data continuity and reduce the latency and data loss that occur during the switching process.

[0044] By continuously monitoring and analyzing network quality, the device can promptly detect the trend of network quality degradation and make adjustments, thereby reducing connection interruptions or performance degradation caused by network quality issues. The setting of dynamic thresholds and the application of machine learning algorithms ensure that the device can adapt to different network environments and usage scenarios, enhancing the device's adaptability and stability. Through the analysis of machine learning algorithms and the setting of dynamic thresholds, the device can trigger network switching at an appropriate time, avoiding frequent switching, thus reducing unnecessary switching costs and communication interruptions. The intelligent decision-making mechanism can not only accurately determine the necessity of switching but also predict future trends based on network quality, avoiding frequent switching during quality fluctuations and optimizing the user experience. Through seamless switching technology, the device can maintain a stable connection during the switching process, without causing large-scale data loss or communication interruptions, ensuring the continuity of data transmission. Using the preferred algorithm and storing multi-operator access parameters, the device can quickly complete network switching, reducing the latency and overhead during switching and enhancing the user experience. By intelligently determining whether to switch networks, the device can avoid frequent network switching and unnecessary scanning, thereby reducing power consumption and extending the device's battery life. When the device detects that the network quality remains low and triggers the switching mechanism, it will give priority to the energy-saving mode, such as entering the low-power standby state, to minimize energy consumption. The device combines machine learning algorithms, which can not only adjust network strategies according to real-time network quality changes but also dynamically adjust switching judgments according to external environment changes (such as high-speed movement, network congestion, etc.), improving the device's stability in complex environments. The intelligent decision-making mechanism and algorithms ensure that the device can still maintain a reliable connection in high-speed movement environments (such as in vehicles, drones, etc.) and areas with severe signal interference (such as gaps between high-rise buildings in the city, tunnels, underground parking lots, etc.). The device automatically determines and switches to a network with better signal quality to ensure that the user's applications are not interfered with by network problems, guaranteeing high-quality services such as voice calls, video streams, and real-time data transmission. Since the device can make intelligent decisions based on real-time network conditions, users do not need to manually intervene, reducing the user's operation complexity and providing a smooth network experience.

[0045] S4: When it detects that the current network quality continues to decline, the signal is weak, or the connection is lost, it automatically triggers the network switching mechanism. The device selects the operator network using the preferred algorithm based on the pre-stored multi-operator access parameters and adopts seamless switching technology to optimize connection stability.

[0046] The device can detect a continuous decline in network quality (such as signal attenuation, increased latency, or too high packet loss rate), and automatically trigger the switching mechanism when it finds that the network quality cannot meet the requirements. By setting dynamic thresholds, when the network quality is lower than the set value (such as when the signal strength is lower than a certain threshold or the latency is too long), the device determines that the current connection is unstable and then activates the switching mechanism. The device pre-saves the access parameters of multiple carriers in advance, including the network configuration, authentication information, network frequency band, access method, etc. of each carrier. These pre-stored access parameters enable the device to quickly match and select available carrier networks during network switching, reducing the time for re-authentication and re-configuration and improving the switching efficiency. The device can select the most suitable carrier access parameters according to the current network conditions, such as selecting the network with the strongest signal, the lowest latency, the largest bandwidth, etc. to ensure network quality. The device uses an optimization algorithm to comprehensively evaluate multiple currently available carrier networks and selects the most suitable network for access.

[0047] The optimization algorithm takes the following factors into consideration:

[0048] Signal strength: such as RSRP, RSSI, select the network with the strongest signal.

[0049] Network coverage: The device preferentially selects the carrier network with a wider coverage and higher stability.

[0050] Latency: The device will select the network with the lowest latency to optimize the performance of real-time applications (such as video calls, games, etc.).

[0051] Bandwidth: According to the current bandwidth requirements, select the carrier network that can provide sufficient bandwidth.

[0052] The optimized algorithm not only comprehensively evaluates the quality of existing networks, but also takes into account the access costs and service quality of operators, and makes intelligent decisions among multiple networks. The device adopts seamless handover technology to ensure that the existing connection is not interrupted during network handover, and data loss or application interruption will not occur. When performing network handover, the device will maintain the connection with the current network until the handover is completed, ensuring continuous communication for users. During the handover process, the device will establish a connection with the target network in advance, and the handover will be seamless without the user noticing, and the user can hardly perceive the network change. The seamless handover technology can greatly reduce the latency during network handover and ensure stable data transmission, especially in real-time data application scenarios (such as video streaming, voice calls, etc.). When the device detects a decline in network quality, it will immediately activate the fast handover mechanism and quickly switch to a network with stronger signal and better quality through pre-stored operator access parameters. During the handover process, the device will reduce the handover latency through an optimized algorithm to ensure that the data stream is not interrupted. The device can select the nearest available base station and quickly complete network access, avoiding long waiting for the access authentication process. The device can connect to multiple networks simultaneously, and use an intelligent handover strategy to determine whether a handover is needed and whether it can be switched to the network with the best current quality. The handover decision will be made based on real-time network quality and access conditions (such as the load of the current network, the congestion of the used frequency band, etc.) to ensure that the optimal network is selected. The device also supports custom settings based on network load, bandwidth requirements, user preferences, etc. to optimize the handover decision and flexibly respond to different network environments and application requirements.

[0053] By continuously monitoring and automatically switching to a carrier network with stronger signal and better network quality, the device can effectively avoid network quality degradation or disconnection issues and maintain a stable and reliable connection. The seamless switching technology ensures that the device does not lose its connection during the switch and maintains a high-quality communication experience, especially suitable for application scenarios with high requirements for latency and connection stability such as voice calls and video conferences. The seamless network switching avoids any interruptions or disconnections felt by the user and provides a smooth network switching experience. Through an optimization algorithm, the device can intelligently judge and select the most suitable carrier network, making the network switching process transparent and minimizing the user's perceived latency and operation intervention. The device adopts fast switching technology and intelligent switching strategies. When the network quality deteriorates, it can quickly identify and switch to the optimal network, effectively reducing the switching latency. The pre-stored multi-carrier access parameters accelerate the switching process and reduce the power consumption of the device during the switching process, especially extending the battery life of the device in mobile scenarios. The device can automatically switch to a carrier with better signal quality in a complex network environment, not relying on a single carrier, enhancing its adaptability to different network environments. Especially in areas with uneven network coverage (such as remote mountainous areas, high-rise dense areas, underground, etc.), the device can quickly find a suitable carrier network, maintain a continuous connection, and improve its network adaptability in extreme environments. Through intelligent switching, the device can ensure that the user is always connected to the best network, thereby improving the user's application experience. Especially in data-intensive applications (such as video streaming, Internet of Things devices, etc.), it can provide high-quality services and avoid disconnection, latency, and jitter phenomena. The device can also select to preferentially use certain carriers according to actual needs. For example, when a large bandwidth is required, it preferentially selects a 5G-supported network to ensure the service quality of different applications. The device automatically switches according to environmental changes and network quality fluctuations to ensure stable connections in high-mobility scenarios (such as vehicles, airplanes, etc.) and complex network environments (such as cities, high-speed railways, etc.), adapting to different scenarios and usage requirements. This intelligent switching mechanism can maximize the user experience, especially in occasions involving large-scale data transmission, low-latency applications, and high reliability requirements, optimizing the network access strategy.

[0054] Embodiment 2

[0055] Please refer to Figure 2 As shown in the figure, an intelligent connection system for Internet of Things terminals based on global carrier networks according to an embodiment of the present invention includes:

[0056] A network environment scanning module that automatically identifies available cellular networks around and evaluates their quality;

[0057] A network access selection module that selects a carrier network according to the network quality parameters obtained by scanning, completes the authentication of the selected carrier and the network access process;

[0058] The network quality monitoring and analysis module obtains the current network status in real time, predicts the future network quality trend based on network quality data and machine learning algorithms, determines whether the network requirements of the current application are met, and decides whether to switch to the network of other operators.

[0059] The network switching and optimization module automatically switches to a network with stronger signal when the current network quality fails to meet the requirements.

[0060] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0061] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent connection method for Internet of Things terminals based on the global operator network, characterized in that, It includes the following steps: S1: When the device is powered on or restarted, it automatically performs a network environment scan, detects the currently available cellular network, and collects signal strength, network coverage, latency, and bandwidth; S2: Based on the global network profile, the device identifies the available operator networks, comprehensively evaluates the signal strength, network coverage, latency, and bandwidth using an optimization algorithm, selects an operator for initial access, and completes network registration through an intelligent authentication method; S3: The device continuously monitors the current connection status, collects network quality parameters, analyzes the network fluctuation trend in combination with machine learning algorithms, predicts the network quality change trend, and when the monitored network quality is lower than the dynamic threshold, the device determines whether to switch to other operator networks; S4: When it is detected that the current network quality continues to decline, the signal is weak, or the connection is lost, the network switching mechanism is automatically triggered. Based on the pre-stored multi-operator access parameters, the device uses an optimization algorithm to select an operator network and adopts seamless switching technology to optimize connection stability.

2. The intelligent connection method of the Internet of Things terminal based on the global operator network according to claim 1, wherein, S1 further includes identifying the accessible operator network through PLMNID, evaluating network coverage based on cell information and location area, automatically selecting the optimal network band, adopting an intelligent scanning strategy, dynamically adjusting the communication protocol by the device according to network conditions, monitoring network performance in real time, and triggering network switching when the signal quality is poor.

3. The intelligent connection method for an Internet of Things terminal based on a global operator network according to claim 1, wherein S2 further includes scanning the surrounding environment to identify the available operator networks and collecting signal strength, network type, latency, and bandwidth. Based on the comprehensive evaluation, including signal strength, network coverage, latency, and bandwidth, the device uses an optimization algorithm to select the most suitable operator network, completes network access through an intelligent authentication method, automatically selects the authentication process, and provides the access process, supporting signal strength and multi-factor authentication.

4. The intelligent connection method of the Internet of Things terminal based on the global operator network according to claim 1, characterized in that S3 further includes continuously monitoring network quality and analyzing and predicting the network quality fluctuation trend in combination with machine learning algorithms. Based on historical data, predicting network state changes, dynamically adjusting the threshold for network quality evaluation. When the network quality drops to the set threshold, the device automatically activates the network switching mechanism and comprehensively evaluates multiple network factors using an optimization algorithm.

5. The intelligent connection method for an Internet of Things terminal based on a global operator network according to claim 4, characterized in that The prediction of network state changes and the dynamic adjustment of the network quality evaluation threshold further include the device using machine learning algorithms to adjust the threshold of each network quality parameter according to historical data, and the device adjusts the threshold of each quality parameter according to network environment changes. The formula is: T param N(t) = T param N(t - 1)+α*(NQ(t)-NQ avg ) where, T param (t) is the parameter threshold at the t-th moment; T param (t - 1) is the parameter threshold at the (t - 1)-th moment; NQ(t) is the network quality score at the t-th moment; NQ avg is the historical average network quality score; α is the learning rate, indicating the sensitivity of threshold adjustment; When the network quality score drops to the set threshold, the device triggers the network switching mechanism, and the judgment condition is: NQ(t) < T param (t); if the condition is met, the switching mechanism is started.

6. The intelligent connection method of the Internet of Things terminal based on the global operator network according to claim 1, wherein, S4 further includes automatically triggering the switching mechanism when the quality drops by real-time monitoring of network quality. The device pre-stores the access parameters of multiple operators, comprehensively evaluates the currently available networks using an optimization algorithm, selects a network for access, and the device adopts seamless switching technology. The switching decision considers network load, bandwidth requirements, and user preferences, flexibly responds to different application scenarios, and quickly completes network switching.

7. An Internet of Things terminal intelligent connection system and method based on a global operator network according to claim 6, characterized in that, The preferred algorithm further includes comprehensively evaluating multiple carrier networks based on real-time network quality data, calculating a network quality score according to the weight of each evaluation parameter, and selecting the network with the highest score for access. The algorithm makes intelligent decisions based on historical connection data, network switching costs, as well as the user's bandwidth requirements and service quality requirements.

8. An Internet of Things terminal intelligent connection system based on a global operator network, which is applied to an Internet of Things terminal intelligent connection method based on a global operator network as described in claims 1-7, characterized in that, It includes: A network environment scanning module that automatically identifies available cellular networks around and evaluates their quality; A network access selection module that selects a carrier network based on the network quality parameters obtained by scanning, and completes the authentication and network access process for the selected carrier; A network quality monitoring and analysis module that obtains the current network status in real time, predicts the future network quality trend based on network quality data and machine learning algorithms, determines whether it meets the network requirements of the current application, and decides whether to switch to other carrier networks. A network switching and optimization module that automatically switches to a network with a stronger signal when the current network quality cannot meet the requirements.

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