A multi-protocol smart internet of things gateway device

Abstract

This invention provides a multi-protocol smart IoT gateway device, solving the problems of traditional gateways such as limited functionality and protocol support. It utilizes a MIPS 1004Kc dual-core chip for computing and integrates WiFi 6E, LoRa, and 5G modules to achieve multi-protocol convergence. The software is based on OpenWRT, featuring intelligent adaptive protocol stack dynamic parameter adjustment, encryption and authentication for security, and intelligent channel and power adjustment to optimize communication and energy consumption. It is suitable for smart cities, industrial IoT, and smart homes, providing a stable and reliable communication solution.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) communication devices, and more specifically to a multi-protocol smart gateway device. Background Technology

[0002] With the rapid development of IoT technology, the number of smart devices is growing exponentially, and various application scenarios are placing higher demands on the performance and functionality of gateway devices. In smart city construction, there is a need for unified access and data integration of widely distributed traffic sensors, environmental monitoring equipment, and other devices; in industrial IoT scenarios, a large number of automated production equipment have extremely high requirements for the real-time performance and stability of data transmission; in the field of smart agriculture, various sensors in vast farmlands urgently need long-distance, low-power communication; and in smart home environments, many home appliances rely on convenient local area network connections. These diverse application scenarios present new challenges to the communication capabilities, processing performance, and adaptability of smart gateways.

[0003] Currently, there are various IoT gateway products on the market. CN111131012A discloses a control circuit for an IoT gateway, which includes a main control chip, a memory chip, a flash memory chip and a MINI PCI-E interface socket. The MINI PCI-E interface socket enables hot-swapping of the IoT communication module and the cellular backhaul module, and supports multiple communication standards [2]. CN210693980U provides a similar IoT gateway control circuit, which also uses a MINI PCI-E interface socket to connect the IoT communication module and the cellular backhaul module to achieve flexible plugging and unplugging of the module [3]. CN111077839A discloses a multi-interface intelligent IoT data gateway, which includes a power module, a main control chip, a sensor interface module, a communication module, a microcontroller data preprocessing module and a display interface module. It solves the problem of multi-source heterogeneity of sensor data by customizing the data frame format structure [4]. CN118764499A proposes a method for IoT cloud 5G gateway to be compatible with multiple protocols. Through multi-protocol compatibility design, efficient data processing architecture and energy management optimization, it supports multiple communication protocols including ZigBee, Wi-Fi, Bluetooth, LoRa and 5G[5].

[0004] However, existing technologies still have the following shortcomings: First, the main control chips of existing gateways have limited performance, mostly using a single-core architecture. This leads to performance bottlenecks in scenarios involving multitasking, data encryption / decryption, and network protocol parsing, making it difficult to meet the demands for high throughput and fast response. Second, while existing Wi-Fi modules mostly support protocols such as 802.11a / b / g / n / ac, they lack support for the latest 802.11ax (Wi-Fi 6) and 802.11be standards, and their antenna designs are generally simple, limiting coverage and the number of connectable devices. Third, existing LoRa modules typically have a communication range of 8-10 kilometers, and their power consumption control is not precise enough, making it difficult to meet the needs of long-distance, low-power applications. Fourth, the 5G modules in existing gateways are mostly early versions, failing to support the latest 3GPP Release 16 standard, and thus unable to fully utilize advanced technologies such as carrier aggregation and Massive MIMO, resulting in poor uplink and downlink speeds and latency. Fifth, the power module design of existing gateways is relatively simple, lacking support for multiple power inputs and energy recovery functions, resulting in low energy efficiency. Finally, the existing gateway software system lacks in-depth optimization, has low task scheduling efficiency, poor driver-hardware coordination, and cannot fully realize the hardware performance potential.

[0005] Therefore, there is an urgent need to develop a high-performance smart gateway that integrates advanced hardware architecture and optimized software systems to meet the growing demands of IoT applications. This gateway should possess powerful data processing capabilities, multi-protocol support, long-distance communication capabilities, and high energy efficiency to adapt to various complex application scenarios and provide a solid foundation for the continued development of the IoT industry. Summary of the Invention

[0006] To address the technical challenges of traditional smart gateways in the context of rapid development of IoT technology, such as limited functionality, support for only a limited number of communication protocols, and significant performance bottlenecks, and to achieve comprehensive compatibility with various communication protocol devices while endowing the gateway with multiple superior characteristics such as high speed, low latency, long range, and low power consumption, this invention provides a smart gateway integrating WiFi, LoRa, and 5G modules.

[0007] The technical solution adopted by the present invention to solve its technical problem is: to provide a smart gateway integrating WiFi, LoRa and 5G modules, including a main control chip, WiFi module, LoRa module, 5G module, power module, storage module and interface circuit, as well as corresponding software design and communication process.

[0008] Preferably, the main control chip is a new type of processor designed specifically for high-performance computing in the Internet of Things. It is based on the MIPS1004Kc dual-core architecture with a main frequency of up to 880MHz, and its computing power is improved by more than 100% compared with the traditional single-core MIPS architecture chip. Its memory management unit has been deeply optimized and has a more efficient memory allocation and reclamation mechanism. The chip integrates rich and high-speed interface resources, including multiple high-speed UARTs, SPI 4.0, I2C 3.0 and USB 3.1 interfaces.

[0009] Preferably, the WiFi module adopts a WiFi module with an innovative antenna design, supporting multiple WiFi protocol standards such as 802.11a / b / g / n / ac / ax and the latest 802.11be, with MediaTek's high-end WiFi 6E module MT7921 as a representative example. This module adds 6GHz band support to the existing 2.4GHz and 5GHz dual-band architecture. Through intelligent antenna beamforming technology, the effective coverage range can reach 50 meters in complex indoor environments, and the signal transmission distance can reach over 200 meters in open outdoor environments. The maximum number of connections can be expanded to 256. The module connects to the main control chip via a high-speed SPI 4.0 or SDIO 4.0 interface.

[0010] Preferably, the LoRa module is based on a new LoRa spread spectrum algorithm and uses the new generation LoRa chip module SX1268 launched by Semtech. Through optimized encoding and decoding algorithms, the communication distance can be extended to up to 15 kilometers under ideal conditions, which is about 50% higher than that of traditional LoRa modules. It adopts dynamic power consumption adjustment technology, and in deep sleep mode, the power consumption can be reduced to less than 30% of that of traditional LoRa modules. It supports 64 LoRa channels and is equipped with an intelligent channel selection algorithm. The module is connected to the main control chip through a high-speed UART interface.

[0011] Preferably, the 5G module adopts the SIMComSIM8200G-M2 5G module compliant with the latest 3GPP Release 16 standard, supporting 5G NSA / SA dual-mode and the latest advanced technologies such as carrier aggregation and Massive MIMO; the theoretical peak downlink speed can reach 3.6Gbps, the uplink speed can reach 640Mbps, and the air interface latency is as low as less than 10ms; it supports the Sub-6GHz band and millimeter wave band of 5G network; the module is connected to the main control chip through a high-speed Mini PCIe 5.0 interface and is equipped with a high-performance 5G antenna with adaptive adjustment direction.

[0012] Preferably, the power module adopts TI's TPS62130 solution, which supports multiple power inputs and has energy recovery function; it supports AC 220V mains input and DC 12V / 5V DC power input, and can also be connected to renewable energy sources such as solar and wind power; the conversion efficiency is up to 95%; it has overvoltage, overcurrent, short circuit protection and undervoltage protection functions; and it can recover some of the excess energy generated by the circuit and reuse it.

[0013] Preferably, the storage module is equipped with 4Gbit DDR3 memory, which improves read and write speed by 50% compared to traditional memory; it uses a new 512Mbit SPI Flash memory chip, which improves storage speed by 30% and has data encryption storage function.

[0014] Preferably, the interface circuit is equipped with two RJ45 Ethernet interfaces, supporting adaptive rates of 10 / 100 / 1000Mbps and high-speed rates of 2.5Gbps and 10Gbps; it provides multiple UART serial ports with automatic identification function, including RS232 and RS485 interfaces; it is equipped with two USB interfaces, supporting USB 2.0 / 3.0 / 3.1 protocols; and it is also equipped with GPIO interfaces and I2C interfaces with high-speed data transmission capabilities.

[0015] Preferably, the software design includes an operating system, drivers, a communication protocol stack, and applications.

[0016] Preferably, the operating system is an embedded operating system based on OpenWRT that has been deeply optimized and has undergone kernel simplification, real-time enhancement, and power consumption optimization for the application scenarios of smart gateways; it has a more efficient task scheduling algorithm and reduces response time by 40%.

[0017] Preferably, the driver includes a WiFi module driver, a LoRa module driver, a 5G module driver, and other peripheral interface drivers; the WiFi module driver has intelligent connection management functions and supports intelligent switching of multiple WiFi working modes; the LoRa module driver can automatically adjust the working parameters of the LoRa module according to factors such as data volume and communication distance; the 5G module driver supports a variety of advanced features of 5G networks, such as intelligent carrier aggregation and dynamic MIMO technology adjustment.

[0018] Preferably, the communication protocol stack includes an intelligent adaptive WiFi protocol stack, an intelligent LoRa communication protocol stack, and an intelligent 5G communication protocol stack; the WiFi protocol stack supports the IEEE 802.11 series of standard protocols and has intelligent protocol switching function; the LoRa communication protocol stack realizes functions such as intelligent node management, dynamic channel allocation, efficient data transmission, and reliability assurance of LoRa networks; the 5G communication protocol stack integrates intelligent network slicing management function and supports a variety of innovative features of 5G networks.

[0019] Preferably, the application includes intelligent data acquisition and processing functions, intelligent device management functions, intelligent network management functions, security mechanisms, and remote intelligent management and monitoring functions; the intelligent data acquisition and processing functions improve data accuracy to over 99.5%; the intelligent device management functions improve device management efficiency to over 99%; the intelligent network management functions include real-time network status monitoring, intelligent network configuration management, and dynamic traffic control; the security mechanisms include encrypted data transmission, user authentication and authorization, and access control; and the remote intelligent management and monitoring functions support remote intelligent configuration, automatic upgrades, and accurate fault diagnosis.

[0020] Preferably, the communication process includes a WiFi communication process, a LoRa communication process, and a 5G communication process; the WiFi communication process adopts intelligent signal enhancement technology and advanced multi-factor authentication methods, which shortens the authentication time by more than 50% and reduces the latency of the entire data transmission process by more than 40%; the LoRa communication process adopts a blockchain-based identity verification and network access permission mechanism, which improves the reliability of the entire communication process by more than 30%; the 5G communication process adopts an intelligent base station search algorithm, which shortens the registration time by more than 40%.

[0021] The beneficial effects of this invention are as follows: By integrating three advanced communication technologies—WiFi, LoRa, and 5G—it achieves comprehensive compatibility with various communication protocol devices, adapting to the needs of complex application scenarios such as smart cities, industrial IoT, smart agriculture, and smart homes; by adopting a high-performance main control chip and optimized software design, it significantly enhances data processing capabilities and response speed, effectively solving the performance bottleneck problem of traditional gateways in high-load scenarios; by leveraging WiFi 6E technology and intelligent antenna beamforming technology, it greatly expands the WiFi signal coverage and increases the capacity of connected devices, meeting the needs of dense device access scenarios; the optimized LoRa module extends the communication distance to 15 kilometers and reduces power consumption to less than 30% of traditional modules, effectively solving the long-distance low-power communication needs in scenarios such as remote area monitoring and large-scale surveillance; the integrated 5G module achieves a downlink speed of 3.6Gbps and a latency of less than 10ms, perfectly adapting to application scenarios with stringent real-time requirements such as industrial control, intelligent driving, and virtual reality; through intelligent software design and communication process optimization, it further improves system stability, security, and ease of use, providing solid and powerful technical support for the sustainable development of the IoT industry. Attached Figure Description Figure 1 Hardware topology diagram; Figure 2 Main control chip block diagram; Figure 3 Schematic diagram of 2.4G / 5.8G WIFI module; Figure 4 Schematic diagram of 5G network communication module; Figure 5 LoRa module schematic diagram. Detailed Implementation

[0022] The present application will be further described in detail below with reference to the accompanying drawings, so that those skilled in the art can better understand and implement the present invention, but the embodiments described are not intended to limit the present invention. Example 1

[0023] This embodiment provides an intelligent IoT gateway device, which adopts an innovative hardware architecture design, including a main control chip, a WiFi module, a LoRa module, a 5G module, and a power module.

[0024] The main control chip of the smart IoT gateway device adopts a new processor designed specifically for high-performance computing in the IoT field. Based on the advanced MIPS 1004Kc dual-core architecture, this processor boasts a clock speed of up to 880 MHz, offering over 100% improved computing power compared to traditional single-core MIPS architecture chips (such as the common MT7620). This high-performance processor demonstrates significant performance advantages in scenarios such as multitasking, data encryption / decryption, and network protocol parsing, effectively improving the device's throughput and response speed. The main control chip's memory management unit has been deeply optimized, featuring a more efficient memory allocation and reclamation mechanism, supporting more advanced memory management features, significantly reducing memory fragmentation, and improving overall system stability. Simultaneously, the chip integrates rich and high-speed interface resources, including multiple high-speed UARTs, SPI 4.0, I2C 3.0, and USB 3.1 interfaces, providing high-speed and stable data channels for connecting other functional modules. This ensures efficient handling of concurrent processing of multi-protocol data in complex data processing scenarios, meeting the extreme requirements of smart gateways for data processing speed and stability.

[0025] High-end WiFi modules featuring innovative antenna designs are exemplified by MediaTek's MT7921 high-end WiFi 6E module. This module supports multiple WiFi protocol standards, including 802.11a / b / g / n / ac / ax and the latest 802.11be. Building upon the 2.4GHz and 5GHz dual-band design, it adds 6GHz band support, complying with the WiFi 6E standard and avoiding congestion issues associated with traditional bands. In the 6GHz band, thanks to WiFi 6E's Orthogonal Frequency Division Multiple Access (OFDMA) and 1024QAM modulation technologies, the maximum transmission rate can soar to 2400 Mbps (theoretical single-stream rate), with further improvements possible in multi-stream configurations. Through intelligent antenna beamforming technology, the effective coverage range remains at 50 meters even in complex indoor environments (such as those with multiple walls); in open outdoor environments, the signal transmission distance exceeds 200 meters, significantly outperforming traditional WiFi modules and greatly expanding coverage. This module achieves a significant breakthrough in the number of connected terminal devices, with a maximum connection capacity of up to 256, effectively meeting the needs of scenarios with dense device access. The module connects to the main control chip via a high-speed SPI 4.0 or SDIO 4.0 interface, further improving data transmission bandwidth and efficiency, and enabling ultra-high-speed data transmission and interaction.

[0026] The LoRa module incorporates the new generation LoRa chip module SX1268 from Semtech, based on a novel LoRa spread spectrum algorithm. Building upon the advantages of traditional LoRa technology, such as low power consumption, long range, and strong anti-interference capabilities, this module optimizes encoding and decoding algorithms, extending the communication distance to up to 15 kilometers under ideal conditions. This represents an improvement of approximately 50% compared to traditional LoRa modules (typically 8-10 kilometers), further meeting the needs of applications requiring long-distance communication, such as remote areas and large-scale monitoring. In terms of power consumption control, the module innovatively employs dynamic power adjustment technology, automatically adjusting the transmit power and operating mode based on the communication load (such as data transmission frequency and distance). In deep sleep mode, power consumption can be reduced to less than 30% of traditional LoRa modules (such as the SX1278), significantly extending the lifespan of battery-powered devices. Furthermore, the module supports more LoRa channels, reaching 64, and is equipped with an intelligent channel selection algorithm that monitors channel status in real time, automatically selecting the optimal channel to effectively avoid channel interference and improve communication reliability. The module connects to the main control chip via a high-speed UART interface, ensuring fast transmission and reception of LoRa data and efficient interaction of control commands.

[0027] The 5G module adopts the SIMCom SIM8200G-M2, which complies with the latest 3GPP Release 16 standard. It supports 5G NSA / SA dual-mode and the latest advanced technologies such as carrier aggregation and Massive MIMO. Its theoretical peak downlink speed can exceed 3.6Gbps, uplink speed can reach 640Mbps, and air interface latency is as low as less than 10ms, perfectly meeting the near-demanding real-time response requirements of applications such as industrial control, intelligent driving, and virtual reality. The module supports both the Sub-6GHz and millimeter-wave bands of 5G networks and can intelligently switch bands according to the signal environment, effectively covering various complex scenarios such as urban areas, suburbs, and indoor / outdoor environments, ensuring network signal stability and continuity. The module connects to the main control chip via a high-speed Mini PCIe 5.0 interface and is equipped with a high-performance, adaptively adjustable 5G antenna to ensure excellent signal reception and transmission.

[0028] The power module adopts TI's TPS62130 solution, featuring an innovative design that supports multiple power inputs and incorporates energy recovery. This module supports not only AC 220V mains input and DC 12V / 5V input, but also renewable energy sources such as solar and wind power. Employing advanced power conversion chips with a conversion efficiency of up to 95%, it accurately converts the input power to the different voltage levels required by each module, such as 3.3V and 1.8V. Multi-stage voltage regulation and filtering ensure stable and reliable operation of each module. Furthermore, it features overvoltage, overcurrent, short-circuit protection, and undervoltage protection, comprehensively preventing power failures from damaging the equipment.

[0029] Through the innovative design of the aforementioned hardware architecture, this intelligent IoT gateway device can simultaneously support multiple communication protocols, achieving efficient data processing and transmission to meet the needs of various complex application scenarios. The high-performance computing capabilities of the main control chip, combined with the advanced features of each communication module, enable the device to achieve industry-leading levels in data throughput, response speed, coverage, and connection stability. Meanwhile, an innovative power management solution ensures reliable operation of the device under various working environments, providing a powerful hardware support platform for IoT applications.

[0030] Example 2 This embodiment provides a software design method, including the following steps: Step 1: Operating System Design Design an embedded operating system based on OpenWRT with deep optimization, focusing on kernel simplification, real-time performance enhancement, and power consumption optimization for smart gateway applications. Specific implementation includes:

[0031] 1) Kernel simplification: Unnecessary kernel modules and functions of the smart gateway are removed, while core functional modules are retained, reducing system footprint and system startup time. The simplified kernel size is 35% smaller than the original OpenWRT kernel, and system startup time is reduced from 45 seconds to 28 seconds.

[0032] 2) Enhanced Real-Time Performance: The task scheduling algorithm was redesigned, adopting a priority-based preemptive scheduling mechanism to allocate higher priority to critical tasks, ensuring their timely execution even under multi-task concurrency. The interrupt handling mechanism was optimized to reduce interrupt latency and improve system response speed. Testing showed that the system response time was reduced by 40% compared to the standard OpenWRT system, from an average of 12 milliseconds to 7.2 milliseconds.

[0033] 3) Power Consumption Optimization: Intelligent dynamic frequency adjustment is implemented, automatically adjusting the CPU frequency based on system load; a deep sleep mode is introduced, automatically entering a low-power state when the system is idle; peripheral power management is optimized, automatically shutting down unused peripheral modules. Testing shows that under the same workload, system power consumption is reduced by 25%.

[0034] 4) Driver framework optimization: Refactor the driver framework to achieve plug-and-play functionality for driver modules, simplify the driver development process, and improve the reliability and stability of driver programs.

[0035] Step 2: WiFi Module Driver Development Develop a WiFi module driver with intelligent connection management capabilities, implementing the following functions: 1) Fast initialization: The WiFi module initialization process has been optimized and parallel initialization technology has been adopted to reduce the initialization time from the standard 2.5 seconds to 0.8 seconds.

[0036] 2) Intelligent configuration: Automatically selects the best working channel based on the surrounding network environment to avoid interference sources; dynamically adjusts the transmission power and transmission rate according to the number of connected devices and data transmission requirements.

[0037] 3) Stable connection management: Real-time monitoring of connection quality; when signal quality deteriorates, automatically adjust antenna direction or switch to backup channel; implement an automatic reconnection mechanism to ensure network connection stability.

[0038] 4) Ultra-high-speed data transmission and reception: Optimize data transmission and reception buffer management to reduce the number of data copies; implement zero-copy technology to directly transfer data between the hardware and application layers, thereby improving data transmission efficiency.

[0039] 5) Multi-mode intelligent switching: An automatic mode switching algorithm is implemented, intelligently switching between AP mode, Station mode, and AP+Station hybrid mode based on the surrounding network environment and device requirements. When an external network access requirement is detected, it automatically switches to Station mode; when a device needs to connect to the gateway, it automatically switches to AP mode; when both external network access and access service provision are required simultaneously, it switches to hybrid mode. Mode switching time is controlled within 200 milliseconds to ensure uninterrupted network service.

[0040] Step 3: LoRa Module Driver Development Develop a smart driver for the LoRa module to achieve the following functions: 1) Fast initialization: The LoRa module initialization process has been optimized by adopting configuration preloading technology, which reduces the initialization time from the standard 1.8 seconds to 0.6 seconds.

[0041] 2) Intelligent parameter configuration: Based on factors such as communication distance, data volume, and environmental interference, the system automatically adjusts parameters such as spreading factor, bandwidth, and coding rate to optimize communication performance. For example, in short-distance communication, it automatically lowers the spreading factor to increase the data transmission rate; in long-distance communication, it automatically increases the spreading factor to ensure communication reliability.

[0042] 3) High-efficiency data transmission and reception: Automatic data packet fragmentation and reassembly are implemented to support large data volume transmission; adaptive data rate is implemented to automatically adjust the data transmission rate according to signal quality; forward error correction coding is implemented to improve data transmission reliability.

[0043] 4) Precise interrupt handling: Optimize the interrupt handling mechanism, reduce interrupt handling delay, and improve system response speed; implement interrupt priority management to ensure that important interrupts can be handled in a timely manner.

[0044] 5) Intelligent parameter adjustment: Through an intelligent interface with the upper-layer protocol stack, the operating parameters of the LoRa module are automatically adjusted based on factors such as data volume and communication distance. For example, when a large amount of data needs to be transmitted, a high-speed, low-spreading-factor configuration is automatically selected; when long-distance communication is required, a low-speed, high-spreading-factor configuration is automatically selected.

[0045] Step 4: 5G Module Driver Development Develop a 5G module driver with intelligent signal optimization capabilities to achieve the following functions:

[0046] 1) Fast initialization: The 5G module initialization process has been optimized by adopting parallel initialization and configuration preloading technology, which reduces the initialization time from the standard 3.5 seconds to 1.2 seconds.

[0047] 2) Fast Network Registration: Optimize the network registration process to enable fast network search and registration; support automatic identification and switching of multiple carrier networks, and select the network with the strongest signal for connection.

[0048] 3) Efficient data transmission: Implement data compression and optimized transmission strategies to reduce data transmission volume; implement packet priority management to ensure that important data is transmitted first; implement dynamic bandwidth allocation to allocate appropriate bandwidth resources according to application needs.

[0049] 4) Intelligent signal monitoring: Real-time monitoring of signal strength and quality; when signal quality deteriorates, automatic adjustment of antenna direction or switching to backup frequency band; signal quality prediction; advance preparation for network switching; and reduction of network interruption time.

[0050] 5) Advanced feature support: Enables intelligent carrier aggregation, dynamically adjusting the number of aggregated carriers according to data transmission requirements; supports dynamic MIMO technology adjustment, automatically adjusting MIMO antenna configuration according to signal environment; supports network slicing technology, allocating independent network resources for different types of services to ensure the quality of service for critical services.

[0051] Step 5: Peripheral Interface Driver Development For various peripheral interfaces of the main control chip, such as UART, SPI, I2C, and USB, develop drivers with automatic detection and adaptive functions:

[0052] 1) UART driver: Supports automatic baud rate detection and adjustment to adapt to the communication needs of different devices; implements data flow control to prevent data loss; supports multiple parity check methods to improve communication reliability.

[0053] 2) SPI driver: Supports automatic identification and switching of multiple SPI modes; enables high-speed data transmission with a maximum clock frequency of 50MHz; supports DMA transfer mode to reduce CPU load.

[0054] 3) I2C driver: Supports automatic switching between standard mode (100kHz), fast mode (400kHz) and high-speed mode (3.4MHz); implements bus conflict detection and recovery mechanism to improve communication reliability; supports multi-master mode to realize complex bus topologies.

[0055] 4) USB driver: Supports USB 2.0 and USB 3.0 standards, automatically identifies device types; enables plug-and-play functionality without manual driver installation; supports USB power management to control the power supply status of USB ports.

[0056] Step Six: Power Management Driver Development Develop a smart power management driver to implement the following functions:

[0057] 1) Dynamic voltage regulation: Dynamically adjusts the operating voltage of the CPU and peripherals according to the system load to reduce power consumption.

[0058] 2) Intelligent sleep control: Monitors system activity status and automatically enters an appropriate sleep state when the system is idle; supports multi-level sleep modes, allowing selection of different depths of sleep mode based on the length of idle time.

[0059] 3) Temperature monitoring and regulation: Real-time monitoring of system temperature; when the temperature is too high, automatic reduction of system performance to prevent overheating; intelligent fan control, automatically adjusting fan speed according to temperature.

[0060] 4) Battery Management: For battery-powered devices, it enables accurate monitoring of battery power and prediction of remaining usage time; it also provides battery charge and discharge protection to extend battery life.

[0061] Step 7: Storage Management Driver Development Develop an intelligent storage management driver to implement the following functions:

[0062] 1) File system optimization: Optimize the file system structure to reduce write cycles and extend flash memory lifespan, taking into account the characteristics of flash memory; implement a journaling file system to prevent data loss due to sudden power outages.

[0063] 2) Cache Management: Implement intelligent caching strategies, preload potentially needed data based on access patterns to improve access speed; implement automatic cache adjustment, dynamically adjust cache size based on system memory usage.

[0064] 3) Data compression: Achieve transparent data compression to reduce storage space usage; automatically select the most suitable compression algorithm based on data type.

[0065] 4) Bad block management: Implement bad block detection and marking to avoid using bad blocks; implement automatic data migration, and automatically migrate data to good blocks when a block is detected to be about to be corrupted.

[0066] Step 8: Communication Protocol Stack Development Innovative integration of a smart adaptive WiFi protocol stack into the operating system kernel:

[0067] 1) Supports IEEE 802.11 series standard protocols, including 802.11a / b / g / n / ac / ax, etc., and is compatible with various WiFi devices.

[0068] 2) Implement intelligent protocol switching functionality, automatically switching between different protocol standards based on network environment and device requirements. For example, in environments with high interference, automatically switch to a protocol with strong anti-interference capabilities; when high-speed transmission is required, automatically switch to a high-speed protocol.

[0069] 3) Optimize the protocol stack structure to reduce protocol processing latency and improve data transmission efficiency. Protocol processing latency was reduced from 5 milliseconds in the standard implementation to 1.8 milliseconds, an improvement of 64%.

[0070] 4) Implement adaptive adjustment of protocol parameters. Based on network conditions, automatically adjust parameters such as retransmission count and timeout time to improve communication reliability.

[0071] 5) Supports multiple security encryption protocols, including WEP, WPA, WPA2, WPA3, etc., to ensure communication security.

[0072] Through the above steps, a complete intelligent gateway software design scheme has been completed. This scheme is characterized by high efficiency, stability, and intelligence, and can meet the communication needs of various complex network environments.

[0073] Example 3 This embodiment provides a multi-protocol intelligent communication device that can automatically select the optimal communication protocol for data transmission based on the network environment and device requirements. The device mainly includes a WiFi communication module, a LoRa communication module, a 5G communication module, a central processing unit, a storage unit, and a power management unit.

[0074] The central processing unit (CPU), as the core control component of the device, is responsible for coordinating the work of various communication modules and intelligently selecting the optimal communication method based on the current network environment and application requirements. The storage unit stores device configuration information, communication protocol stacks, and application data. The power management unit is responsible for providing stable power to all functional modules and implementing low-power management.

[0075] The WiFi communication module integrates an intelligent WiFi protocol stack, which automatically selects the optimal WiFi protocol version for data transmission based on the network environment and device requirements. The WiFi communication module includes a WiFi radio frequency unit, a WiFi baseband processing unit, and a WiFi protocol processing unit. The WiFi radio frequency unit is responsible for transmitting and receiving WiFi signals, supporting dual-band operation at 2.4GHz and 5GHz. The WiFi baseband processing unit is responsible for signal modulation and demodulation and baseband processing. The WiFi protocol processing unit implements the WiFi protocol stack functions, including fast connection establishment, enhanced authentication and encryption, ultra-high-speed data transmission, and intelligent roaming switching.

[0076] The WiFi protocol processing unit, through deep interaction with the WiFi driver, encapsulates and sends application layer data in the optimal WiFi protocol format, and efficiently parses and processes received data packets, quickly delivering valid data to the application layer. This unit can dynamically adjust the WiFi operating mode based on current network congestion, signal strength, and application requirements, optimizing power consumption while ensuring communication quality. The WiFi protocol processing unit also implements intelligent roaming, enabling seamless switching between multiple WiFi access points to ensure communication continuity.

[0077] In a preferred embodiment, the WiFi protocol processing unit also integrates an intelligent channel selection algorithm, which can automatically scan the surrounding environment and select the channel with the least interference for communication, thereby improving communication quality and speed. This algorithm predicts the congestion level of each channel by real-time monitoring of the surrounding WiFi signal distribution and combining historical data analysis, and then selects the optimal channel for communication.

[0078] The LoRa communication module integrates a proprietary intelligent LoRa communication protocol stack, enabling intelligent node management, dynamic channel allocation, efficient data transmission, and reliability assurance in the LoRa network. The LoRa communication module comprises a LoRa radio frequency unit, a LoRa baseband processing unit, and a LoRa protocol processing unit. The LoRa radio frequency unit is responsible for transmitting and receiving LoRa signals and supports multi-band operation. The LoRa baseband processing unit is responsible for modulation and demodulation of LoRa signals and baseband processing. The LoRa protocol processing unit implements the LoRa protocol stack functionality.

[0079] The LoRa protocol processing unit works in conjunction with the LoRa driver to intelligently adjust data transmission strategies based on factors such as node distribution and signal strength. It is responsible for encoding and modulating application layer data according to the optimized LoRa protocol before transmission, and for precisely demodulating, decoding, and verifying received LoRa data to ensure accuracy and integrity. This unit implements adaptive spreading factor adjustment, automatically selecting the optimal spreading factor based on communication distance and environmental conditions, improving transmission efficiency while ensuring communication reliability. The LoRa protocol processing unit also implements intelligent power control, dynamically adjusting the transmit power based on communication distance and channel quality to extend device battery life.

[0080] In a preferred embodiment, the LoRa protocol processing unit also integrates a network topology self-organizing function, which can automatically discover surrounding LoRa nodes, construct an optimal network topology, achieve multi-hop communication, and expand communication coverage. This function maintains network topology information through periodic neighbor discovery and routing information exchange, and selects the optimal communication path based on link quality and node energy status.

[0081] The 5G communication module is based on the latest 3GPP standard and integrates a 5G communication protocol stack with intelligent network slicing management capabilities. This enables rapid 5G network access, accurate registration, intelligent session management, efficient mobility management, and ultra-high-speed data transmission. The 5G communication module includes a 5G radio frequency (RF) unit, a 5G baseband processing unit, and a 5G protocol processing unit. The 5G RF unit is responsible for transmitting and receiving 5G signals, supporting both Sub-6GHz and millimeter-wave bands. The 5G baseband processing unit is responsible for 5G signal modulation / demodulation and baseband processing. The 5G protocol processing unit implements the 5G protocol stack functionality.

[0082] The 5G protocol processing unit, working closely with the 5G driver, enables intelligent communication and interaction with 5G base stations, facilitating ultra-efficient transmission of application layer data within the 5G network. It also supports various innovative 5G network features, such as intelligent slice management and edge computing collaboration, to meet the diverse and demanding requirements of different application scenarios. This unit implements intelligent network slice selection, automatically choosing the most suitable network slice for communication based on application type and quality of service requirements, ensuring the quality of service for critical businesses. The 5G protocol processing unit also implements multi-connection management, enabling the simultaneous maintenance of multiple 5G connections, improving communication reliability and throughput.

[0083] In a preferred embodiment, the 5G protocol processing unit also integrates edge computing collaboration functionality, enabling it to work collaboratively with network edge computing nodes to offload computationally intensive tasks to edge nodes, reducing the burden on terminal devices and improving application response speed. This functionality intelligently decides whether to process tasks locally or offload them to edge nodes by real-time assessment of local computing resources and network conditions.

[0084] This device also integrates a multi-protocol fusion management unit, responsible for coordinating the collaborative operation of WiFi, LoRa, and 5G communication methods. This unit dynamically selects the optimal communication method or combines multiple methods based on application requirements, network environment, and energy consumption requirements, achieving optimal utilization of communication resources. The multi-protocol fusion management unit implements intelligent protocol switching, enabling seamless switching between different communication protocols to ensure communication continuity. This unit also implements multi-protocol parallel transmission, allowing simultaneous data transmission using multiple communication methods, improving communication throughput and reliability.

[0085] In practical applications, when a device is within WiFi coverage and requires high-speed data transmission, the multi-protocol fusion management unit will prioritize WiFi communication mode; when the device is in a wide area far from the base station and the data volume is small, it will choose LoRa communication mode; when the device needs mobile communication and has high requirements for speed and latency, it will choose 5G communication mode. In certain special scenarios, the multi-protocol fusion management unit can also enable multiple communication modes simultaneously, such as transmitting large amounts of data via WiFi while simultaneously transmitting control signals via LoRa, achieving optimal allocation of communication resources.

[0086] Through the above design, this multi-protocol intelligent communication device can adapt to various complex network environments, provide optimal communication solutions for different application scenarios, and achieve efficient, reliable, and low-power data transmission.

[0087] Example 4

[0088] This embodiment provides an application with intelligent data acquisition and processing capabilities. This application can collect data from various devices connected to the gateway in real time and accurately, including WiFi devices, LoRa devices, and data from devices accessed through serial ports and other interfaces.

[0089] The application's overall architecture includes a data acquisition module, a data preprocessing module, a data classification, storage and forwarding module, a communication link selection module, and a device management module. These modules work together to realize the complete process from data acquisition to data processing and data transmission.

[0090] The data acquisition module is responsible for real-time data acquisition from various devices connected to the gateway. This module employs multi-threaded parallel acquisition technology, enabling simultaneous monitoring of multiple communication interfaces, including WiFi, LoRa, and serial ports. For WiFi devices, it uses the standard 802.11 protocol stack for data interaction, supporting both 2.4GHz and 5GHz dual-band. For LoRa devices, it uses the LoRaWAN protocol for communication, supporting multi-channel parallel reception. For serial port devices, it supports multiple level standards such as RS232 / RS485 / TTL, with a configurable baud rate range of 1200bps to 115200bps. This module also implements an automatic device discovery function, automatically identifying the device type and establishing a communication connection when a new device connects to the network.

[0091] The data preprocessing module performs intelligent preprocessing on the collected raw data. First, it intelligently converts data from different devices and protocols into a unified standard JSON format. Then, it performs multiple data verifications, including CRC checksums, checksum verification, and data integrity checks, to ensure data accuracy. Next, it performs intelligent data filtering, using algorithms such as threshold setting, rate of change detection, and outlier identification to filter out obviously erroneous or redundant data. After these preprocessing steps, the data accuracy can be improved to over 99.5%. In a preferred embodiment, the data accuracy can reach 99.8% by introducing machine learning algorithms to analyze historical data and automatically optimize the filtering rules.

[0092] The data classification, storage, and forwarding module classifies, stores, and forwards pre-processed data according to intelligent configuration strategies. Data classification is based on a preset rule engine, which can divide data into different categories such as real-time data, historical data, alarm data, and configuration data. Real-time data goes directly into the forwarding queue; historical data is first stored in a local database and then uploaded in batches according to set time intervals; alarm data is set to high priority and forwarded immediately; configuration data is stored in a local configuration database and synchronized periodically. Local storage uses a lightweight SQLite database, supports data compression and encryption, and can automatically adjust data retention strategies according to storage space. Before forwarding, data is efficiently packaged and encapsulated, using binary compression format to reduce data transmission volume, and adding metadata such as timestamps and device identifiers.

[0093] The communication link selection module uses intelligent algorithms to choose the optimal communication link for data transmission. This module monitors the status of WiFi, LoRa, and 5G communication links in real time, including parameters such as signal strength, bandwidth, latency, and stability. Based on these parameters, combined with data priority and size, it dynamically selects the most suitable transmission channel. For high-priority small data packets, low-latency links are prioritized; for large-capacity data transmission, high-bandwidth links are prioritized; when an unstable link is detected, it automatically switches to a backup link to ensure continuous data transmission. This module also implements link aggregation, allowing multiple communication links to be used simultaneously for parallel data transmission when high bandwidth transmission is required, improving overall transmission efficiency.

[0094] The device management module enables comprehensive and intelligent centralized management of various devices connected to the gateway. This module provides intelligent device registration, supporting both self-registration and manual registration by the administrator. Each device is assigned a unique identifier and its basic parameters, such as device type, communication protocol, and location information, are recorded. The automatic discovery function periodically scans the network and listens for broadcast messages to discover newly connected devices and add them to the management scope. The real-time status monitoring function periodically checks the device's online status, battery level, signal strength, and other operating parameters, automatically triggering alarms when anomalies are detected. The remote parameter configuration function allows administrators to remotely adjust device operating parameters, such as sampling frequency, alarm thresholds, and communication modes, through the application interface. This module also provides device group management and access control functions, allowing devices to be grouped according to type, location, or purpose, and different device management permissions can be assigned to different users.

[0095] In practical applications, this application can be deployed on edge gateway devices and work in conjunction with a cloud management platform. When device data needs to be uploaded to the cloud, the application will select the most appropriate time and communication link for transmission based on the data type and network conditions. For critical business data, end-to-end encryption technology is used to ensure data transmission security; for non-critical data, a differential transmission strategy can be used to transmit only the changing data portion, reducing bandwidth consumption.

[0096] This intelligent data acquisition and processing application can effectively solve problems such as inaccurate data acquisition, low transmission efficiency, and complex device management in IoT systems, providing a reliable data foundation and device management capabilities for various IoT applications.

[0097] Example 5 This device is a remote intelligent device management system that enables real-time monitoring, remote control, and intelligent maintenance of equipment.

[0098] The remote intelligent device management system mainly includes a terminal monitoring module, a data transmission module, a cloud processing platform, an intelligent analysis engine, a remote control module, and a maintenance early warning module.

[0099] The terminal monitoring module is installed on the managed equipment and consists of various sensors, including temperature sensors, vibration sensors, current sensors, pressure sensors, and displacement sensors. These sensors are distributed in key parts of the equipment, collecting various parameter data in real time during equipment operation. The temperature sensor uses a high-precision thermocouple with a measurement range of -50℃ to 350℃ and an accuracy of ±0.1℃; the vibration sensor uses a piezoelectric accelerometer with a measurement frequency range of 0.5Hz to 10kHz; the current sensor uses a Hall effect sensor with a measurement range of 0 to 100A; the pressure sensor has a measurement range of 0 to 20MPa; and the displacement sensor uses a linear variable differential transformer with a measurement accuracy of 0.01mm. These sensors preprocess data through a miniature data acquisition unit, and the sampling frequency can be automatically adjusted according to the equipment's operating status, at 10 times per second under normal conditions and increasing to 100 times per second under abnormal conditions to ensure the capture of instantaneous abnormal data.

[0100] The data transmission module is responsible for securely and efficiently transmitting the data collected by the terminal monitoring module to the cloud processing platform. This module employs a dual-channel transmission architecture: the primary channel uses a 5G wireless network with a transmission rate of up to 1Gbps, while the backup channel uses NB-IoT technology. Although the backup channel has a lower transmission rate, it ensures the transmission of core data in the event of a primary channel failure. Before data transmission, the system performs AES-256-bit encryption and uses data compression algorithms to reduce the data volume by 40% to 60%, lowering the transmission load. The data transmission module also features local caching, capable of storing up to 72 hours of monitoring data in the event of a network outage. Once the network is restored, the data is automatically uploaded to the cloud, ensuring data integrity.

[0101] The cloud processing platform is the core of the entire system, employing a distributed architecture comprised of a data storage layer, a computing processing layer, and an application service layer. The data storage layer uses a combination of time-series and relational databases. The time-series database specifically stores real-time parameter data of the devices, while the relational database stores basic device information, maintenance records, and user information. The computing processing layer is equipped with a high-performance server cluster, whose processing capacity can dynamically scale according to the data volume, supporting the processing of millions of data points per second. The application service layer provides API interfaces, supporting seamless integration with existing enterprise ERP, MES, and other systems to achieve data sharing and business collaboration.

[0102] The intelligent analysis engine, based on machine learning and deep learning algorithms, performs real-time analysis and processing of equipment operation data. This engine includes multiple specialized models, such as an equipment status identification model, a fault diagnosis model, a lifespan prediction model, and an energy efficiency optimization model. The equipment status identification model, by learning from normal equipment operation data, establishes a baseline model for equipment operation, capable of identifying minute abnormal fluctuations. The fault diagnosis model, based on historical fault data and an expert knowledge base, can accurately determine the type and cause of faults, with a diagnostic accuracy rate exceeding 95%. The lifespan prediction model, by analyzing equipment wear trends and the operating environment, predicts the remaining lifespan of key components with a prediction accuracy of 90%. The energy efficiency optimization model, by analyzing the relationship between equipment operating parameters and energy consumption, provides optimal operating parameter recommendations, which can reduce energy consumption by 15% to 30%.

[0103] The remote control module allows administrators to remotely operate and adjust equipment via PC or mobile devices. This module provides an intuitive graphical user interface that visually presents complex equipment parameters and statuses. The interface is divided into three parts: a monitoring area, a control area, and an information area. The monitoring area displays real-time operating parameters and status indicators of the equipment and supports customized monitoring panels; the control area provides operation buttons for equipment start / stop, parameter adjustment, and mode switching; the information area displays basic equipment information, historical data, and alarm records. The remote control module employs a three-level access control mechanism, with different levels of users having different operating permissions to ensure system security. All remote operation commands undergo legality and security verification before execution to prevent misoperation and malicious attacks. Furthermore, the module supports operation recording and playback functions, facilitating the tracing of operation history and the training of new personnel.

[0104] The maintenance early warning module provides equipment maintenance suggestions and fault warnings based on the analysis results of the intelligent analysis engine. This module employs a three-level early warning mechanism: Level 1 is a prompt message indicating minor anomalies in certain equipment parameters that do not affect normal operation; Level 2 is a warning message indicating potential equipment failure risks and recommending inspection; Level 3 is an emergency alarm indicating a serious equipment anomaly requiring immediate attention. Warning information can be sent to relevant personnel through various methods, including the system interface, SMS, email, and mobile application push notifications. The maintenance early warning module also includes an intelligent maintenance scheduling system that can automatically generate the optimal maintenance plan based on equipment status, maintenance personnel capabilities, and spare parts inventory, and provide detailed maintenance guidance, including maintenance steps, required tools, and precautions.

[0105] In a preferred embodiment, the system also integrates augmented reality (AR) technology, allowing maintenance personnel to access real-time equipment data and repair guidance through AR glasses, significantly improving repair efficiency. The AR system can overlay information such as the internal structure of the equipment, pipeline routing, and the location of key components onto the actual equipment, and provide interactive repair guidance, enabling maintenance personnel to accurately complete complex repair tasks even without extensive experience.

[0106] In another preferred embodiment, the system is also equipped with digital twin technology to build a virtual model of the device in the cloud, enabling real-time data synchronization between the physical device and the virtual model. Through the digital twin model, managers can simulate and optimize device performance, predict device performance under different operating conditions, and provide a scientific basis for device management decisions.

[0107] During operation, this remote intelligent device management system first continuously collects equipment operation data through the terminal monitoring module. After preprocessing, the data is securely transmitted to the cloud processing platform via the data transmission module. The cloud processing platform stores and performs initial processing on the data, followed by in-depth analysis by the intelligent analysis engine to identify equipment status, diagnose potential problems, and predict future trends. Based on the analysis results, the system allows administrators to perform necessary remote operations and parameter adjustments through the remote control module. Simultaneously, the maintenance early warning module promptly issues warnings and provides maintenance suggestions when anomalies are detected or potential faults are predicted.

[0108] By applying this system, enterprises can achieve digital transformation of equipment management, shifting from traditional reactive maintenance to proactive predictive maintenance. This results in an 85% reduction in equipment failure rates, a 90% reduction in unplanned downtime, a 40% reduction in maintenance costs, a 30% extension of equipment lifespan, and an overall improvement in equipment management efficiency of over 99%. Simultaneously, the system helps enterprises establish complete equipment health records, providing data support and decision-making basis for full lifecycle equipment management.

[0109] Example 6 This embodiment provides an intelligent network management gateway device that can realize intelligent network management functions, including real-time network status monitoring, intelligent network configuration management, and dynamic traffic control.

[0110] The intelligent network management gateway device mainly includes a main control unit, a network interface module, an intelligent monitoring module, a network configuration management module, a traffic control module, a security protection module, and a remote management module.

[0111] The main control unit, as the core processing center of the entire gateway device, employs a high-performance processor chip and is equipped with sufficient RAM and storage space. It is responsible for coordinating the work of various functional modules, processing data flow, and executing intelligent decision-making algorithms. The main control unit has a built-in real-time operating system that supports multi-task parallel processing, ensuring the gateway device operates efficiently and stably.

[0112] The network interface module integrates three network communication interfaces: WiFi, LoRa, and 5G. The WiFi interface supports multiple protocol standards such as IEEE 802.11a / b / g / n / ac / ax, operating in 2.4GHz and 5GHz frequency bands, with a maximum transmission rate of 3Gbps. The LoRa interface employs low-power, long-range communication technology, operating in 433MHz / 868MHz / 915MHz frequency bands, with a communication distance of up to 15 kilometers. The 5G interface supports Sub-6GHz and millimeter-wave bands, with a maximum downlink rate of 10Gbps. The network interface module connects to the main control unit via a dedicated bus, enabling high-speed data exchange.

[0113] The intelligent monitoring module is responsible for real-time and accurate monitoring of parameters such as signal strength, connection status, and data transmission rate of WiFi, LoRa, and 5G networks. This module employs a distributed sensor architecture, deploying dedicated signal monitoring units at each network interface to collect network parameter data in real time. For WiFi networks, the monitoring module can detect parameters such as signal strength (RSSI), signal-to-noise ratio (SNR), channel congestion, and the number of connected devices; for LoRa networks, it can detect parameters such as signal strength, spreading factor, bandwidth utilization, and transmission success rate; for 5G networks, it can detect parameters such as signal quality (SINR), reference signal received power (RSRP), reference signal received quality (RSRQ), and network latency. The intelligent monitoring module transmits the collected data to the main control unit for analysis and processing, and performs intelligent dynamic adjustments and optimizations based on network conditions.

[0114] The network configuration management module supports intelligent configuration of network parameters. This module includes a parameter configuration engine and an intelligent optimization algorithm library. For WiFi networks, the module can intelligently set parameters such as hotspot name, password, channel, and transmit power, automatically selecting the optimal channel through environmental scanning to avoid interference. For LoRa networks, the module can adaptively adjust parameters such as spreading factor, bandwidth, and coding rate based on communication distance and data volume requirements, balancing transmission distance and data rate. For 5G networks, the module can intelligently match access parameters, such as frequency band selection and network switching thresholds, to ensure optimal connection quality. The network configuration management module analyzes historical data and the current network environment through intelligent algorithms to automatically optimize configuration parameters, meeting the complex network needs of different application scenarios.

[0115] The traffic control module, through its intelligent traffic control function, rationally allocates network bandwidth based on data type and service priority. Employing Deep Packet Inspection (DPI) technology, this module can identify different types of network traffic, such as video streams, voice calls, file transfers, and control commands. The module incorporates a multi-level priority queue management system, which prioritizes different types of data streams, granting higher-priority data priority transmission rights and more bandwidth resources. Simultaneously, the traffic control module implements a dynamic bandwidth allocation algorithm, dynamically adjusting the bandwidth allocation ratio for each service stream based on real-time network load conditions. This ensures priority and high-speed transmission of critical business data, effectively preventing network congestion.

[0116] The security protection module employs multiple advanced security mechanisms to ensure the security of the gateway and its data. First, it implements encrypted data transmission, performing multiple encryption processes on data transmitted over WiFi, LoRa, and 5G networks. WiFi data transmission uses the WPA3 encryption protocol, supporting 128-bit and 192-bit encryption strengths; LoRa data transmission uses the AES-128 encryption algorithm; and 5G data transmission utilizes a dual encryption mechanism at both the network and application layers. Second, the security protection module provides user authentication and authorization functions, employing multi-factor authentication to strictly verify the identity of users logging into the gateway. Authentication methods include username and password, digital certificates, fingerprint recognition, etc., and support two-factor authentication. Fine-grained operation permissions are assigned based on user roles; administrators, ordinary users, and visitors have different permission ranges, ensuring that only legitimate users can manage and operate the gateway. Furthermore, the security protection module implements access control functions, setting intelligent firewall rules based on multi-dimensional information such as device fingerprints, MAC addresses, IP addresses, and access times to restrict unauthorized external devices from accessing the gateway, ensuring the security of the gateway and internal network. The security protection module also has intrusion detection capabilities, capable of identifying and automatically blocking abnormal access behavior to prevent network attacks.

[0117] The remote management module supports remote intelligent management and monitoring. This module establishes a secure connection with the cloud platform or other remote management tools, allowing users to remotely operate the smart gateway via a web interface or mobile application. Remote management functions include remote intelligent configuration, automatic upgrades, and precise fault diagnosis. Remote intelligent configuration allows users to remotely modify various gateway parameter settings; the automatic upgrade function supports online updates of gateway firmware and software, ensuring the system always runs the latest version; the precise fault diagnosis function uses built-in self-testing programs and log analysis tools to help users quickly locate and resolve problems. Simultaneously, the gateway can report its own operating status, device connection status, and data transmission statistics to the remote management platform in real time and with high accuracy. Reported information includes CPU usage, memory consumption, network traffic statistics, connected device list, and abnormal event records, facilitating comprehensive remote monitoring of the gateway's operation and timely problem identification and resolution. The remote management module also supports scheduled task settings and batch configuration functions to improve network management efficiency.

[0118] In a preferred embodiment, the intelligent network management gateway device is also equipped with an artificial intelligence analysis engine. This engine, based on machine learning algorithms, learns network usage patterns and historical data, predicts network traffic trends, and proactively allocates network resources, further improving the intelligence level of network management. By analyzing historical network usage data, the AI ​​analysis engine identifies periodic network load patterns, such as traffic differences between weekdays and weekends, and bandwidth demand changes at different times of the day, thereby automatically adjusting network parameters and optimizing resource allocation before peak periods.

[0119] In another preferred embodiment, the intelligent network management gateway device adds edge computing capabilities, processing some data locally on the gateway to reduce the burden on the cloud and lower network latency. The edge computing module is equipped with dedicated computing resources, enabling it to perform data filtering, aggregation, and preliminary analysis locally, transmitting only necessary data to the cloud, significantly reducing data transmission volume and improving system response speed.

[0120] When this intelligent network management gateway is in operation, it first continuously collects the status parameters of each network interface through the intelligent monitoring module, and transmits the data to the main control unit for analysis. Based on the analysis results, the main control unit calls the network configuration management module to optimize and adjust the network parameters. Simultaneously, the traffic control module dynamically allocates network bandwidth resources according to service type and priority. The security protection module monitors network access behavior throughout the process and encrypts the data to ensure network security. The remote management module reports the gateway's operating status to the cloud platform and receives remote management commands from users.

[0121] Through the coordinated operation of the above functional modules, this intelligent network management gateway device can realize real-time monitoring of network status, intelligent configuration of network parameters, dynamic control of network traffic, comprehensive protection of network security, and remote intelligent management and monitoring, meeting the intelligent network management needs in complex network environments.

[0122] Example 7 This embodiment provides a communication process, including a WiFi communication process, a LoRa communication process, and a 5G communication process, as detailed below: The WiFi communication process includes the following steps:

[0123] Step 1: When WiFi terminal devices scan for surrounding WiFi hotspots, the WiFi module of the smart gateway uses intelligent signal enhancement technology to make the hotspot signal more prominent, making it easier for terminal devices to quickly discover it.

[0124] Step 2: After the terminal device detects the gateway hotspot signal, it sends a connection request to the gateway.

[0125] Step 3: After receiving the request, the gateway uses a multi-factor authentication method to authenticate the terminal device, including dual authentication of password and device fingerprint. The authentication time is reduced by more than 50% compared with the traditional method.

[0126] Step 4: After successful authentication, the gateway uses an intelligent IP address allocation algorithm to quickly assign IP addresses to terminal devices and establish a stable WiFi connection.

[0127] Step 5: After the terminal device establishes a connection with the gateway, it will communicate with the gateway. The terminal device will encapsulate the data according to the optimized WiFi protocol format and send it to the gateway.

[0128] Step 6: After receiving the data, the gateway's WiFi module transmits the data to the main control chip via a high-speed SPI 4.0 or SDIO 4.0 interface.

[0129] Step 7: The main control chip intelligently analyzes and processes the data, and decides in a very short time whether to forward the data to other devices or upload it to the cloud server through other communication links, based on the data destination address and intelligent configuration strategy.

[0130] Step 8: When the gateway has data to send to the WiFi terminal device, the main control chip encapsulates the data according to the optimized WiFi protocol format and sends it to the WiFi module quickly through the high-speed interface.

[0131] Step 9: The WiFi module uses intelligent power adjustment and beamforming technology to modulate the data and transmit it accurately via wireless signal.

[0132] Step 10: After receiving the data, the terminal device performs rapid demodulation and decapsulation to obtain valid data, reducing the latency of the entire data transmission process by more than 40%.

[0133] The LoRa communication process includes the following steps:

[0134] Step 1: After startup, the LoRa terminal node attempts to join the LoRa network by sending an optimized network entry request packet.

[0135] Step 2: After receiving the network access request, the LoRa module of the smart gateway uses a blockchain-based identity verification and network access authorization mechanism to ensure the authenticity and security of the node's identity, reducing the verification time by 30%. In a preferred embodiment, the verification time can be reduced by 35%; in another preferred embodiment, the verification time can be reduced by 40%.

[0136] Step 3: After successful verification, assign a network address and related parameters to the node, and the node successfully joins the LoRa network.

[0137] Step 4: The LoRa terminal node collects sensor data or other device data according to a preset time interval or event trigger, and then transmits the data after efficient encoding and modulation according to the innovative LoRa protocol.

[0138] Step 5: After receiving the data, the LoRa module of the smart gateway quickly transmits the data to the main control chip through the high-speed UART interface.

[0139] Step Six: The main control chip intelligently analyzes and processes the data, extracts valid data, and quickly stores, forwards, or uploads it to the cloud server according to the intelligent configuration strategy.

[0140] Step 7: When the cloud server or other devices have data to send to the LoRa terminal node, the data first arrives at the smart gateway.

[0141] Step 8: The gateway's main control chip encapsulates the data according to the optimized LoRa protocol based on the data destination address and quickly sends it to the LoRa module through the high-speed UART interface.

[0142] Step 9: The LoRa module uses intelligent channel selection and power regulation technology to modulate the data and accurately transmit it to the target terminal node via wireless signal.

[0143] Step 10: After receiving the data, the terminal node performs rapid demodulation and decoding to obtain valid data, improving the reliability of the entire communication process by more than 30%.

[0144] The 5G communication process includes the following steps:

[0145] Step 1: After the 5G module of the smart gateway is started, it uses a smart base station search algorithm to quickly and accurately search for surrounding 5G base station signals.

[0146] Step 2: After finding a suitable base station, send an optimized network registration request to the base station. The request contains detailed identity information and comprehensive capability information of the gateway.

[0147] Step 3: The base station performs strict authentication and authorization on the gateway, and allocates sufficient network resources to the gateway after successful authentication.

[0148] Step 4: The gateway successfully registers with the 5G network, reducing registration time by more than 40%. In one preferred embodiment, registration time can be reduced by 45%; in another preferred embodiment, registration time can be reduced by 50%.

[0149] Step 5: When the gateway needs to upload data via the 5G network, the main control chip encapsulates the data according to the optimized 5G protocol and sends it to the 5G module at a faster speed through the high-speed Mini PCIe 5.0 interface.

[0150] Step Six: The 5G module uses intelligent carrier aggregation and MIMO technology to modulate the data and transmit it to the 5G base station through a high-performance, adaptively oriented 5G antenna.

[0151] Step 7: The base station quickly forwards the data to the core network, and finally transmits it to the cloud server or other target devices.

[0152] In practical applications, the three communication processes described above can be used individually or in combination to form a multi-mode converged communication system, depending on actual needs. Through the coordination of the intelligent gateway, data between different communication protocols can be seamlessly converted and transmitted, significantly improving overall communication efficiency and reliability.

[0153] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A smart gateway integrating WiFi, LoRa and 5G communication modules, the technical features of which include a main control chip, WiFi module, LoRa module, 5G module, storage module, and corresponding software design and other components.

2. The main control chip according to claim 1, characterized in that: This chip is based on the MIPS 1004Kc dual-core architecture and has a main frequency of 880MHz, which improves computing power by about 100% compared to traditional single-core MIPS architecture chips. The chip integrates rich high-speed interface resources, including multiple high-speed UART, SPI 4.0, I2C 3.0 and USB 3.1 interfaces.

3. The WiFi module according to claim 1, characterized in that: Featuring an innovative antenna design, this module supports WiFi protocols such as 802.11a / b / g / n / ac / ax and the latest 802.11be. In addition to the existing 2.4GHz and 5GHz dual-band support, it now supports the 6GHz band, conforming to the WiFi 6E standard. In the 6GHz band, based on Orthogonal Frequency Division Multiple Access (OFDMA) and 1024QAM modulation technology, the theoretical single-stream transmission rate can reach 2400Mbps. Effective coverage reaches 50 meters in complex indoor environments (such as those with multiple walls); in open outdoor environments, the transmission distance exceeds 200 meters, and the maximum number of connected devices can be expanded to 256.

4. The LoRa module according to claim 1, characterized in that: It adopts Semtech's new generation SX1268 chip module. Under ideal conditions, the communication distance can cover up to 15 kilometers, which is about 50% higher than traditional modules. It has a communication load adaptive function, which can dynamically adjust the transmission power and operating mode according to the transmission requirements. In deep sleep mode, the power consumption can be reduced to less than 30% of that of traditional modules, and it supports 64 LoRa communication channels.

5. The 5G module according to claim 1, characterized in that: It adopts the SIMCom SIM8200G-M2 module compliant with 3GPP Release 16, supporting advanced technologies such as 5G NSA / SA dual-mode, carrier aggregation, and Massive MIMO. The theoretical peak downlink speed reaches 3.6Gbps, the uplink speed is increased to 640Mbps, the air interface latency is less than 10ms, and it supports Sub-6GHz and millimeter-wave bands.

6. The storage module according to claim 1, characterized in that: It is equipped with 4Gbit DDR3 memory, which improves read and write speeds by 50% compared to traditional memory; it uses 512Mbit high-density SPI Flash memory chips, which improves storage speed by 30%.

7. The software design according to claim 1, characterized in that: Employing a deeply optimized OpenWRT-based embedded operating system, the system features kernel simplification, enhanced real-time performance, and power consumption optimization specifically for smart gateway applications. Equipped with a high-efficiency task scheduling algorithm, it ensures timely execution of critical tasks during multi-task concurrency, reducing response time by 40%. Furthermore, deep integration and optimization of various drivers ensure efficient collaboration between hardware modules, fully leveraging hardware performance.

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