A method for optimizing cross-country access communications

Abstract

The application relates to the technical field of intelligent security and protection, and provides a cross-country access communication optimization method, which comprises the following steps: deploying a special communication server cluster at a cross-border network key link node, including an overseas equipment access node and a domestic client access node, constructing a point-to-point special cross-border transmission channel, and acquiring real-time video picture data collected by the monitoring camera; performing primary compression processing through a built-in lightweight preprocessing unit of an overseas deployed monitoring camera equipment end, so as to determine whether to start a cloud secondary intelligent compression processing unit; and sequentially determining a compression processing strategy based on real-time network feature information of the cloud. The application overcomes the defects in the prior art, such as low communication efficiency and precision caused by the large data transmission amount, high cross-border transmission delay, poor picture fluency and weak network adaptability of the transmission scene of the domestic access overseas equipment in the cross-country access communication technology of the consumer monitoring camera.

Description

Technical Field

[0001] This invention relates to the field of intelligent security technology, and in particular to a method for optimizing cross-border access communication. Background Technology

[0002] With the popularization of smart home and civilian security technologies, the demand for cross-border deployment and remote access of consumer surveillance cameras is growing. A large number of users have scenarios where they can view and control small home and commercial surveillance cameras deployed overseas in real time using domestic terminals.

[0003] In current cross-border surveillance video transmission models, networks inherently suffer from problems such as long cross-regional links, significant network jitter, bandwidth congestion, and high packet loss rates during cross-border transmission. Traditional transmission methods rely solely on a single, fixed compression algorithm on the device side for preprocessing video data, resulting in a fixed compression ratio, poor adaptability, and a lack of targeted optimization to suit the characteristics of cross-border network transmission. Furthermore, the existing transmission architecture lacks dedicated cross-border server node scheduling and cloud-based secondary compression mechanisms. The raw video data collected by cameras is substantial and is directly transmitted over long distances without deep, adaptive compression.

[0004] Existing technological deficiencies directly lead to common problems when domestic terminals access overseas monitoring equipment, such as video stuttering, excessive latency, blurry images, unstable frame rates, and delayed real-time control responses. These issues severely affect the real-time performance and smoothness of cross-border monitoring access, failing to meet users' core needs for real-time viewing, dynamic tracking, and high-definition preview of cross-border monitoring, and hindering the experience and widespread adoption of cross-border remote applications for consumer surveillance cameras. Summary of the Invention

[0005] To address this, the present invention provides a cross-border access communication optimization method to overcome the shortcomings of existing cross-border access communication technologies for consumer surveillance cameras, which are designed for domestic access to overseas devices, resulting in large data transmission volumes, high cross-border transmission latency, poor image smoothness, and weak network adaptability, leading to low communication efficiency and accuracy.

[0006] To achieve the above objectives, the present invention provides a cross-border communication optimization method, comprising: Dedicated communication server clusters are deployed at key cross-border network link nodes; wherein, the dedicated communication server clusters include overseas device access nodes and domestic client access nodes; A point-to-point dedicated cross-border transmission channel is constructed based on the aforementioned dedicated communication service cluster; Based on the aforementioned point-to-point dedicated cross-border transmission channel, real-time video image data collected by surveillance cameras is obtained; The real-time video data is initially compressed using a lightweight pre-processing unit built into the surveillance camera equipment deployed overseas. Based on the video image data after the initial compression process, the cloud-based secondary intelligent compression processing unit is activated. Based on the real-time network feature information of the cloud-based secondary intelligent compression processing unit, the compression processing strategy is determined sequentially as follows: whether it is dynamic inter-frame compression, whether it is adaptive image quality compression, and whether it is data packetized and simplified compression.

[0007] Furthermore, the process of dynamic inter-frame compression includes: Identify repeating frames and slightly changing frames in continuous images within a predetermined period based on real-time network feature information in the cloud. Redundant frames are merged and differentially transmitted based on repeating frames and slightly changing frames in the continuous picture.

[0008] Furthermore, the adaptive image compression process includes: To obtain real-time network characteristic information from the cloud, including the bandwidth, latency, and packet loss rate of cross-border transmission links; Based on the bandwidth, latency, and packet loss rate of the cross-border transmission link, the screen resolution, bit rate, and color sampling rate are dynamically adjusted.

[0009] Furthermore, the process of data packaging, simplification, and compression includes: Obtain redundant header fields and data encapsulation structures for real-time network feature information from the cloud; Optimization is performed based on the aforementioned redundant header fields and data encapsulation structure.

[0010] Furthermore, the process of constructing dedicated point-to-point cross-border transmission channels includes: For surveillance cameras deployed overseas, bind them to the nearest overseas server node; For domestic clients, all access will be routed to domestic server nodes. A peer-to-peer dedicated cross-border transmission channel is constructed based on the aforementioned overseas server nodes and domestic server nodes.

[0011] Furthermore, the process of merging and differentially transmitting redundant frames based on repeating frames and slightly varying frames in the continuous picture includes: Mark repeating frame groups and slightly changing frame groups within a predetermined period of continuous images; The most complete image in each group is selected as the baseline reference frame. The target volume frames within each group are compared with the reference frame pixel by pixel or block by block to extract the difference data of the changed areas; Completely duplicate frames are discarded, and the differential maps of multiple slightly varied frames are merged and encoded into a single composite differential data packet. Extract current bandwidth and latency network conditions, and dynamically adjust the transmission precision or resolution of differential data.

[0012] This invention also provides a cross-border communication optimization system, comprising: The cross-border service node deployment module is used to deploy dedicated communication server clusters at key cross-border network link nodes to build point-to-point dedicated cross-border transmission channels. The dedicated communication server cluster includes overseas device access nodes and domestic client access nodes. The device-side front-end data preprocessing module, connected to the cross-border service node deployment module, includes overseas surveillance cameras and a lightweight preprocessing compression unit, wherein: Overseas surveillance cameras are bound to nearby overseas server nodes to collect real-time video data. A lightweight pre-processing compression unit is built into the overseas surveillance camera equipment for primary compression processing. The cloud server intelligent dynamic compression module is connected to the device front-end data preprocessing module. After the server node receives the preprocessed video data from the device, it starts the cloud secondary intelligent compression processing unit. The cloud secondary intelligent compression processing unit determines the cloud secondary intelligent compression processing strategy based on real-time network feature information. The cloud secondary intelligent compression processing strategy includes dynamic inter-frame compression, adaptive image quality compression, and data packetized simplified compression. The high-speed bidirectional communication link construction module is used to build a high-speed bidirectional communication link from the client to the device based on a dedicated server node and a multi-level compression mechanism.

[0013] The beneficial effects of this invention are as follows: By deploying a dedicated communication server cluster at key cross-border network nodes, including overseas device access nodes and domestic client access nodes, a point-to-point dedicated cross-border transmission channel is constructed to acquire real-time video image data collected by the surveillance cameras; primary compression processing is performed by a lightweight preprocessing unit built into the overseas-deployed surveillance camera device to determine whether to activate the cloud-based secondary intelligent compression processing unit; and compression processing strategies are sequentially determined based on real-time network feature information from the cloud. This invention overcomes the shortcomings of existing consumer surveillance camera cross-border access communication technologies, which are specifically designed for domestic access to overseas devices, resulting in large data transmission volumes, high cross-border transmission latency, poor image smoothness, and weak network adaptability, leading to low communication efficiency and accuracy.

[0014] In particular, this invention, by building a dedicated cross-border communication server node architecture and introducing a dynamic data compression mechanism on the cloud server, combined with a collaborative mode of device-side preprocessing compression and cloud-based intelligent secondary compression, specifically reduces the volume of video data transmitted across borders, adapts to complex cross-border network environments, and achieves high-speed, low-latency, and highly smooth communication between domestic clients and overseas monitoring devices. This fundamentally solves the problems of lag, latency, and unstable image quality in cross-border monitoring access under traditional technologies, and significantly improves the user experience and transmission efficiency of cross-border remote monitoring.

[0015] In particular, this invention adopts a multi-level compression mode of device-side lightweight compression + cloud-based intelligent dynamic secondary compression, which is different from the traditional single fixed compression method. Through cloud-based adaptive compression algorithm, it accurately removes various redundant information in video data, minimizes the data volume of cross-border transmission, effectively reduces the data pressure of long-distance transmission, improves the speed of cross-border data transmission from the source, and thus significantly reduces the amount of cross-border data transmission, resulting in a significant improvement in transmission efficiency.

[0016] In particular, this invention establishes a dedicated cross-border server node cluster to form a point-to-point dedicated transmission channel, eliminating the complex routing and hopping of public networks. Combined with lightweight compressed data transmission, it greatly shortens the data interaction latency between domestic clients and overseas devices, significantly improving the real-time performance of monitoring screens and the speed of control response. Thus, by constructing a dedicated cross-border transmission link, transmission latency is reduced.

[0017] In particular, by deploying the core high-computing-power compression operation on a cloud server, the device only needs to complete lightweight preprocessing, without the need for high-computing-power hardware. This does not increase the hardware cost, power consumption, or device size of consumer surveillance cameras, and can be adapted to various ordinary home and commercial consumer-grade surveillance devices. It has strong versatility and practicality, resulting in low device load and wide adaptability.

[0018] In particular, this invention utilizes intelligent cloud compression technology to dynamically optimize compression logic based on the characteristics of human vision. While significantly compressing data and increasing transmission speed, it retains the core details of the monitoring screen to the maximum extent, avoiding image distortion and loss of details caused by over-compression. This achieves a balance between high-speed cross-border transmission and high-definition image presentation, resulting in a superior user experience. Attached Figure Description

[0019] Figure 1 This is a structural block diagram of the cross-border access communication optimization system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the steps of the cross-border access communication optimization method according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating the steps of the dynamic inter-frame compression process according to an embodiment of the present invention. Figure 4 This is a flowchart illustrating the steps of adaptive image quality compression in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0021] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0022] Please see Figure 1 This is a cross-border access communication optimization system according to an embodiment of the present invention. The system described in the embodiment includes: The cross-border service node deployment module is used to deploy dedicated communication server clusters at key cross-border network link nodes to build point-to-point dedicated cross-border transmission channels. The dedicated communication server cluster includes overseas device access nodes and domestic client access nodes. In this embodiment, all consumer surveillance cameras deployed overseas are uniformly bound to the nearest overseas server node, and domestic access clients are uniformly connected to domestic server nodes. Data is relayed through dedicated dedicated lines between nodes, avoiding bandwidth congestion and routing delays on public networks, building a stable physical architecture for cross-border data transmission, and providing a link foundation for data compression and transmission.

[0023] The device-side front-end data preprocessing module, connected to the cross-border service node deployment module, includes overseas surveillance cameras and a lightweight preprocessing compression unit, wherein: Overseas surveillance cameras are bound to nearby overseas server nodes to collect real-time video data. A lightweight pre-processing compression unit is built into the overseas surveillance camera equipment for primary compression processing. In this embodiment, a lightweight pre-processing compression unit is built into the overseas surveillance camera device. After the camera acquires real-time video data, the pre-processing unit first performs initial compression processing. Abandoning the traditional fixed bitrate and fixed compression ratio compression mode, the device performs preliminary removal and compression of static image areas, redundant pixels, and invalid frame data based on the dynamic characteristics of the acquired images, retaining the core valid information of the image, initially reducing the volume of original data transmission, and avoiding the hardware power consumption and latency issues caused by high-computing power compression on the device side, thus achieving low-load pre-compression.

[0024] The cloud server intelligent dynamic compression module is connected to the device front-end data preprocessing module. After the server node receives the preprocessed video data from the device, it starts the cloud secondary intelligent compression processing unit. The cloud secondary intelligent compression processing unit determines, based on the real-time network conditions, whether the cloud secondary intelligent compression processing strategy is dynamic inter-frame compression, adaptive image quality compression, and data packetized simplified compression.

[0025] In this embodiment, the cloud server has computing power and data processing capabilities far exceeding those of the device, and can detect the bandwidth, latency, packet loss rate, and network status of the current cross-border transmission link in real time, and adaptively adjust the compression strategy based on dynamic network parameters.

[0026] It is understood that the secondary intelligent compression processing strategy in this embodiment includes: dynamic inter-frame compression, which identifies repeated frames and slightly changing frames in continuous images, and merges and differentially transmits redundant frames; adaptive image quality compression, which dynamically adjusts the image resolution, bitrate, and color sampling rate without affecting the human visual experience, and performs deep compression on low-interest image areas; and data packet simplification and compression, which abandons the traditional fixed data packet encapsulation format, dynamically simplifies data including redundant header fields, optimizes the data encapsulation structure, further compresses the total amount of transmitted data, and intelligently switches the compression level and compression mode according to real-time network conditions, so as to ensure high-definition image quality when the network is good and maximize the reduction of data volume when the network is congested, thus balancing the transmission image quality and transmission speed. The processing strategy includes, but is not limited to, the specific methods mentioned above, which will not be elaborated here.

[0027] The high-speed bidirectional communication link construction module is used to build a high-speed bidirectional communication link from the client to the device based on a dedicated server node and a multi-level compression mechanism.

[0028] In this embodiment, video data is preprocessed on the overseas device and uploaded to the nearest cloud node. After deep compression and optimization in the cloud, it is transmitted to the domestic server node via a dedicated cross-border line and finally distributed to domestic access clients. The client's control commands and query commands are quickly forwarded from the domestic node to the overseas device, achieving low-latency command return. At the same time, the server node monitors the link transmission status in real time and dynamically schedules compression strategies and transmission rates to ensure the real-time performance and stability of two-way communication.

[0029] The embodiment proposes a cross-border access communication optimization system for security monitoring equipment, including a cross-border server node deployment system, a device-side front-end data preprocessing module, a cloud server intelligent dynamic compression module, and a high-speed communication link scheduling module for clients, servers, and devices. Through multi-level compression and dedicated node transmission collaboration, it is specifically matched to the transmission scenarios of domestic access to overseas devices, realizing high-speed transmission of cross-border monitoring data.

[0030] Please see Figure 2 This is a flowchart illustrating the steps of the cross-border access communication optimization method according to an embodiment of the present invention. The method of the present invention includes: Step S1: Deploy a dedicated communication server cluster at key cross-border network link nodes; wherein, the dedicated communication server cluster includes overseas device access nodes and domestic client access nodes; Step S2: Construct a point-to-point dedicated cross-border transmission channel based on the dedicated communication service cluster; Step S3: Based on the point-to-point dedicated cross-border transmission channel, acquire the real-time video image data collected by the surveillance camera; Step S4: The real-time video image data is subjected to primary compression processing through the lightweight preprocessing unit built into the overseas-deployed surveillance camera equipment. Step S5: Based on the video image data after the primary compression processing, determine to start the cloud-based secondary intelligent compression processing unit; Step S6: Based on the real-time network feature information of the cloud-based secondary intelligent compression processing unit, determine in sequence whether it is dynamic inter-frame compression, adaptive image quality compression, and data packaging and simplification compression.

[0031] In this embodiment, a dedicated communication server cluster is deployed at key cross-border network nodes, including overseas device access nodes and domestic client access nodes, to construct a point-to-point dedicated cross-border transmission channel and acquire real-time video image data collected by the surveillance camera. Primary compression processing is performed using a lightweight preprocessing unit built into the overseas-deployed surveillance camera device to determine whether to activate the cloud-based secondary intelligent compression processing unit. Compression processing strategies are then determined sequentially based on real-time network characteristic information from the cloud. This invention overcomes the shortcomings of existing consumer surveillance camera cross-border access communication technologies, which are designed for domestic access to overseas devices, resulting in large data transmission volumes, high cross-border transmission latency, poor image smoothness, and weak network adaptability, leading to low communication efficiency and accuracy.

[0032] Please see Figure 3 This is a flowchart illustrating the steps of the dynamic inter-frame compression process according to an embodiment of the present invention. The dynamic inter-frame compression process of the embodiment includes: Identify repeating frames and slightly changing frames in continuous images within a predetermined period based on real-time network feature information in the cloud. Redundant frames are merged and differentially transmitted based on repeating frames and slightly changing frames in the continuous picture.

[0033] In this embodiment, the present invention can adapt to complex working conditions such as cross-border network bandwidth fluctuations, latency changes, and packet loss anomalies in real time through a cloud-based secondary intelligent compression strategy. It dynamically adjusts compression parameters and transmission modes, avoiding the shortcomings of traditional fixed compression modes that cannot adapt to network changes. It effectively solves the problems of video stuttering, screen tearing, and disconnection caused by cross-border network instability, greatly improves the smoothness of remote access, and thus perfectly adapts to complex cross-border network environments with extremely strong communication stability.

[0034] Please see Figure 4 The diagram shows a flowchart of the adaptive image quality compression process according to an embodiment of the present invention. The adaptive image quality compression process of the embodiment includes: To obtain real-time network characteristic information from the cloud, including the bandwidth, latency, and packet loss rate of cross-border transmission links; Based on the bandwidth, latency, and packet loss rate of the cross-border transmission link, the screen resolution, bit rate, and color sampling rate are dynamically adjusted.

[0035] The embodiment uses a cloud-based adaptive compression algorithm to accurately remove various redundant information from video data, minimizing the amount of data transmitted across borders, effectively reducing the data pressure of long-distance transmission, fundamentally improving the speed of cross-border data transmission, thereby significantly reducing the amount of data transmitted across borders and significantly improving transmission efficiency.

[0036] Specifically, the process of data packaging, simplification, and compression includes: Obtain redundant header fields and data encapsulation structures for real-time network feature information from the cloud; Optimization is performed based on the aforementioned redundant header fields and data encapsulation structure.

[0037] The embodiment utilizes intelligent cloud compression technology, dynamically optimizing compression logic based on the characteristics of human vision. While significantly compressing data and improving transmission speed, it retains the core details of the monitoring screen to the maximum extent, avoiding image distortion and loss of details caused by over-compression. It achieves a balance between high-speed cross-border transmission and high-definition image presentation, thereby achieving a dual balance between image quality and transmission speed, resulting in an excellent user experience.

[0038] Specifically, the process of building a dedicated point-to-point cross-border transmission channel includes: For surveillance cameras deployed overseas, bind them to the nearest overseas server node; For domestic clients, all access will be routed to domestic server nodes. A peer-to-peer dedicated cross-border transmission channel is constructed based on the aforementioned overseas server nodes and domestic server nodes.

[0039] The embodiment builds a dedicated cross-border communication server node architecture, introduces a dynamic data compression mechanism on the cloud server, and combines a collaborative mode of device-side pre-processing compression and cloud-based intelligent secondary compression to specifically reduce the volume of video data transmitted across borders. It adapts to complex cross-border network environments and achieves high-speed, low-latency, and highly smooth communication between domestic clients and overseas monitoring devices. This fundamentally solves the problems of lag, latency, and unstable image quality in traditional cross-border monitoring access, and significantly improves the user experience and transmission efficiency of cross-border remote monitoring.

[0040] Specifically, the process of merging and differentially transmitting redundant frames based on repeating frames and slightly changing frames in the continuous picture includes: Mark repeating frame groups and slightly changing frame groups within a predetermined period of continuous images; The most complete image in each group is selected as the baseline reference frame. The target volume frames within each group are compared with the reference frame pixel by pixel or block by block to extract the difference data of the changed areas; Completely duplicate frames are discarded, and the differential maps of multiple slightly varied frames are merged and encoded into a single composite differential data packet. Extract current bandwidth and latency network conditions, and dynamically adjust the transmission precision or resolution of differential data.

[0041] Specifically, the process of dynamically adjusting image resolution, bitrate, and color sampling rate based on the bandwidth, latency, and packet loss rate of cross-border transmission links includes: The collected bandwidth, latency, and packet loss rate are normalized according to preset weights to obtain a comprehensive network quality score benchmark. Based on the currently available bandwidth, a preset resolution threshold range is matched to initially determine the image resolution; When the latency exceeds the resolution threshold or the packet loss rate exceeds the packet loss rate threshold, the resolution or bitrate is adjusted to reduce the amount of data per frame and decrease the probability of transmission failure.

[0042] Specifically, the optimization process based on the aforementioned redundant header fields and data encapsulation structure includes: Traverse the headers of each layer of the current data encapsulation protocol to identify unnecessary or duplicated fields in cross-border transmission; Based on the identification results, a simplified protocol header is designed, removing redundant fields or merging multiple fields into a composite identifier.

[0043] Specifically, the initial compression process includes: Acquire dynamic features of the images captured by the device itself; Initial removal and compression of static image areas, redundant pixels, and invalid frame data; Retain valid information about the image features to initially reduce the volume of the original data transmission.

[0044] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Specific examples are used to illustrate the principles and implementation methods of this invention. The above descriptions of the embodiments are merely for the purpose of helping to understand the method and core ideas of this invention; furthermore, those skilled in the art will recognize that, based on the ideas of this invention, there will be changes in specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for optimizing cross-border communication, characterized in that, include: Dedicated communication server clusters are deployed at key cross-border network link nodes; wherein, the dedicated communication server clusters include overseas device access nodes and domestic client access nodes; A point-to-point dedicated cross-border transmission channel is constructed based on the aforementioned dedicated communication service cluster; Based on the aforementioned point-to-point dedicated cross-border transmission channel, real-time video image data captured by surveillance cameras is obtained; The real-time video data is initially compressed using a lightweight pre-processing unit built into the surveillance camera equipment deployed overseas. Based on the video image data after the initial compression process, the cloud-based secondary intelligent compression processing unit is activated. Based on the real-time network feature information of the cloud-based secondary intelligent compression processing unit, the compression processing strategy is determined sequentially as follows: whether it is dynamic inter-frame compression, whether it is adaptive image quality compression, and whether it is data packetized and simplified compression.

2. The cross-border access communication optimization method according to claim 1, characterized in that, The process of dynamic inter-frame compression includes: Identify repeating frames and slightly changing frames in continuous images within a predetermined period based on real-time network feature information in the cloud. Redundant frames are merged and differentially transmitted based on repeating frames and slightly changing frames in the continuous picture.

3. The cross-border access communication optimization method according to claim 2, characterized in that, The adaptive image compression process includes: To obtain real-time network characteristic information from the cloud, including the bandwidth, latency, and packet loss rate of cross-border transmission links; Based on the bandwidth, latency, and packet loss rate of the cross-border transmission link, the screen resolution, bit rate, and color sampling rate are dynamically adjusted.

4. The cross-border access communication optimization method according to claim 3, characterized in that, The process of data packaging, simplification, and compression includes: Obtain redundant header fields and data encapsulation structures for real-time network feature information from the cloud; Optimization is performed based on the aforementioned redundant header fields and data encapsulation structure.

5. The cross-border access communication optimization method according to claim 4, characterized in that, The process of building a dedicated point-to-point cross-border transmission channel includes: For surveillance cameras deployed overseas, bind them to the nearest overseas server node; For domestic clients, all access will be routed to domestic server nodes. A peer-to-peer dedicated cross-border transmission channel is constructed based on the aforementioned overseas server nodes and domestic server nodes.

6. The cross-border access communication optimization method according to claim 5, characterized in that, The process of merging and differentially transmitting redundant frames based on repeating frames and slightly changing frames in the continuous picture includes: Mark repeating frame groups and slightly changing frame groups within a predetermined period of continuous images; The most complete image in each group is selected as the baseline reference frame. The target volume frames within each group are compared with the reference frame pixel by pixel or block by block to extract the difference data of the changed areas; Completely duplicate frames are discarded, and the differential maps of multiple slightly varied frames are merged and encoded into a single composite differential data packet. Extract current bandwidth and latency network conditions, and dynamically adjust the transmission precision or resolution of differential data.

7. The cross-border access communication optimization method according to claim 6, characterized in that, The process of dynamically adjusting image resolution, bitrate, and color sampling rate based on the bandwidth, latency, and packet loss rate of cross-border transmission links includes: The collected bandwidth, latency, and packet loss rate are normalized according to preset weights to obtain a comprehensive network quality score benchmark. Based on the currently available bandwidth, a preset resolution threshold range is matched to initially determine the image resolution; When the latency exceeds the resolution threshold or the packet loss rate exceeds the packet loss rate threshold, the resolution or bitrate is adjusted to reduce the amount of data per frame and decrease the probability of transmission failure.

8. The cross-border access communication optimization method according to claim 7, characterized in that, The optimization process based on the aforementioned redundant header fields and data encapsulation structure includes: Traverse the headers of each layer of the current data encapsulation protocol to identify unnecessary or duplicated fields in cross-border transmission; Based on the identification results, a simplified protocol header is designed, removing redundant fields or merging multiple fields into a composite identifier.

9. The cross-border access communication optimization method according to claim 8, characterized in that, The primary compression process includes: Acquire dynamic features of the images captured by the device itself; Initial removal and compression of static image areas, redundant pixels, and invalid frame data; Retain valid information about the image features to initially reduce the volume of the original data transmission.

10. A cross-border access communication optimization system, applied to the cross-border access communication optimization method according to claims 1 to 9, characterized in that, include: The cross-border service node deployment module is used to deploy dedicated communication server clusters at key cross-border network link nodes to build point-to-point dedicated cross-border transmission channels. The dedicated communication server cluster includes overseas device access nodes and domestic client access nodes. The device-side front-end data preprocessing module, connected to the cross-border service node deployment module, includes overseas surveillance cameras and a lightweight preprocessing compression unit, wherein: Overseas surveillance cameras are bound to nearby overseas server nodes to collect real-time video data. A lightweight pre-processing compression unit is built into the overseas surveillance camera equipment for primary compression processing. The cloud server intelligent dynamic compression module is connected to the device front-end data preprocessing module. After the server node receives the preprocessed video data from the device, it starts the cloud secondary intelligent compression processing unit. The cloud secondary intelligent compression processing unit determines whether the cloud secondary intelligent compression processing strategy is dynamic inter-frame compression, adaptive image quality compression, or data packet simplification compression based on real-time network feature information. The high-speed bidirectional communication link construction module is used to build a high-speed bidirectional communication link from the client to the device based on a dedicated server node and a multi-level compression mechanism.

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