Remote monitoring platform based on 5G communication

Abstract

The invention relates to the technical field of remote monitoring, in particular to a remote monitoring platform based on 5G communication, and the remote monitoring platform based on 5G communication comprises a network data monitoring module, a spectrum resource adjustment module, a data transmission optimization module and a data synchronization processing module. According to the invention, the utilization of the network bandwidth is optimized through an advanced data capture technology, the accurate monitoring of the network flow and state fluctuation is realized, meanwhile, the system has the capability of adjusting spectrum resources in real time and quickly responds to the change of network conditions, and the stability and response speed of the network are remarkably improved. High-demand time periods are automatically identified, spectrum allocation is adjusted, a data transmission path is accurately evaluated and optimized, network congestion and transmission delay are effectively reduced, coherence and reliability of data streams are ensured, efficiency and integrity of data synchronization processing are enhanced, and especially in real-time data interaction among multiple nodes, the real-time data interaction efficiency is improved. And efficient and accurate data synchronization is ensured.

Description

Technical Field

[0001] The present invention relates to the field of remote monitoring technology, and in particular to a remote monitoring platform based on 5G communication. Background Art

[0002] The field of remote monitoring technology involves the use of various sensors, cameras and monitoring equipment to remotely collect data and images through the network, enabling users to monitor and control physical environments such as factories, public places, homes and offices from remote locations. It usually includes data collection, transmission and analysis functions, aiming to improve efficiency and safety through real-time feedback. In addition, these systems are often equipped with automated functions such as motion detection, event-triggered recording and alarm notification to respond to abnormal situations.

[0003] Among them, the remote monitoring platform is a software or hardware platform that implements the remote monitoring function. It is specially used to receive, analyze and display the data transmitted from the remote monitoring equipment. It is usually highly integrated and customizable, allowing users to adjust the system settings according to specific monitoring needs. The main uses include but are not limited to security monitoring, environmental monitoring, production process control, etc. Through the remote monitoring platform, users can receive alarms, monitoring videos or other sensor data in real time, respond to various situations in a timely manner, and effectively improve the response speed and decision-making quality of the monitoring system.

[0004] When traditional remote monitoring technologies are used to handle large amounts of data and high-demand monitoring scenarios, common network congestion and transmission delay issues significantly affect monitoring results and system response speed. These technologies are insufficient in terms of network bandwidth management and delay optimization, especially in terms of lack of flexibility and adaptability under dynamic network conditions. For example, in critical scenarios such as security monitoring or environmental monitoring, the slow response speed of traditional systems and the limited data processing capabilities lead to untimely responses to emergencies, affecting the quality of decision-making and the effectiveness of execution. They fail to fully tap the potential of high-speed data transmission and big data technologies, limiting the overall performance and scalability of monitoring systems. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and propose a remote monitoring platform based on 5G communication.

[0006] In order to achieve the above purpose, the present invention adopts the following technical solution: A remote monitoring platform based on 5G communication includes:

[0007] The network data monitoring module deploys sensors and receivers to capture network traffic and latency data in real time, record 5G network bandwidth usage, analyze traffic patterns in different time periods based on the recorded results, evaluate network status fluctuations, and generate real-time network data snapshots;

[0008] The spectrum resource adjustment module analyzes spectrum occupancy based on the real-time network data snapshot, identifies key traffic demand periods, adjusts spectrum allocation parameters according to the identification results, implements dynamic spectrum management to match changes in network conditions, and generates adjusted spectrum configurations;

[0009] The data transmission optimization module uses the adjusted spectrum configuration to evaluate the existing data transmission path, calculate the network delay index of the transmission path, optimize the path according to the calculation result, avoid network congestion and transmission delay, and generate the optimal data path solution;

[0010] The data synchronization processing module uses the optimal data path solution to adjust and update the data transmission configuration between monitoring nodes, performs monitoring data synchronization processing between all locations, and generates remote monitoring data synchronization records.

[0011] As a further solution of the present invention, the steps of recording the 5G network bandwidth usage are:

[0012] Deploy sensors and receivers at 5G network exchange points to capture packet flows and signal delays every second, and obtain preliminary network traffic and latency data;

[0013] Cleaning the preliminary network traffic data and delay data to remove noise and outliers, ensuring data consistency through data synchronization, and obtaining accurate network usage data;

[0014] Based on the accurate network usage data, the time series changes of the data are analyzed and the formula is used.

[0015]

[0016] Calculate the overall bandwidth utilization T and obtain the 5G network bandwidth usage record, where N represents the number of measurements, B i Represents the bandwidth usage at each time point, L i Represents the corresponding delay.

[0017] As a further solution of the present invention, the steps of obtaining the real-time network data snapshot are:

[0018] Based on the 5G network bandwidth usage records, time series analysis is performed to determine the periodic changes in data traffic, identify traffic peaks and valleys in different time periods, and obtain time period traffic pattern data;

[0019] Utilizing the traffic pattern data in the time period, analyzing the statistical indicators of the traffic data, measuring the fluctuation of the network status in the different time periods, and obtaining the network status fluctuation data;

[0020] The network status fluctuation data is integrated to calculate the total network load, integrate the delay change and bandwidth utilization, and use dynamic data visualization to generate a real-time network data snapshot.

[0021] As a further solution of the present invention, the step of identifying the critical flow demand period is:

[0022] Receiving the real-time network data snapshot, collating network traffic, number of user connections and device type information, and generating a real-time network status data set;

[0023] Based on the real-time network status data set, the formula is adopted:

[0024]

[0025] Calculate the comprehensive spectrum occupancy index F(t) at time point t, identify the network traffic peak and spectrum occupancy pattern, and obtain the traffic peak period data. N(t) represents the network traffic, and D(t) represents the number of device connections.

[0026] Using the traffic peak period data, set the traffic threshold T and compare the traffic density of the time window. If F(t) is greater than T, mark the target time window as the critical traffic demand period and generate the critical traffic demand period result.

[0027] As a further solution of the present invention, the step of acquiring the adjusted spectrum configuration is:

[0028] Analyze spectrum utilization, traffic density distribution and service quality requirements according to the results of the key traffic demand period, and generate a network status analysis record;

[0029] Based on the network status analysis record, dynamic spectrum allocation is performed using the formula:

[0030]

[0031] Calculate the priority P(f) of frequency band f, adjust the spectrum allocation parameters, and obtain the optimized spectrum allocation parameters, where μ and σ are the mean and standard deviation obtained from the statistics of network status data;

[0032] The optimized spectrum allocation parameters are applied to update the spectrum configuration database and promote the new configuration to base stations and access points, and the implementation effect of the new configuration is monitored to generate an adjusted spectrum configuration.

[0033] As a further solution of the present invention, the calculation steps of the transmission path network delay index are:

[0034] Using the adjusted spectrum configuration, evaluating the existing data transmission path, analyzing key nodes and data traffic distribution, and generating a path status evaluation record;

[0035] Based on the path status evaluation record, the formula is used:

[0036]

[0037] Calculate the total delay D and generate the network delay index, where L i is the length of the i-th path, is the average length of all paths, v i is the signal speed of the i-th path, and m represents the number of paths;

[0038] Based on the network delay index, the network performance is evaluated, whether the delay index matches the network operation standard is confirmed, and a network performance record is generated.

[0039] As a further solution of the present invention, the steps of obtaining the optimal data path solution are:

[0040] Utilize the network delay index to analyze the current data transmission path, simulate the network performance under different load conditions, compare the delay data under different configuration schemes, record the best performance configuration, and generate a draft of the optimized path plan;

[0041] Based on the draft of the optimized path plan, comprehensively refer to the network performance data of the path plan, formulate network reconstruction and adjustment measures, and generate a network adjustment proposal;

[0042] According to the network adjustment proposal, an implementation plan is formulated, including technical implementation details, resource allocation and time arrangement, and regular evaluation points are set to monitor the optimization progress and effect to obtain the optimal data path solution.

[0043] As a further solution of the present invention, the steps of acquiring the synchronous record of the remote monitoring data are:

[0044] Using the optimal data path solution, perform configuration analysis on the monitoring nodes, adjust the transmission configuration parameters of each node to match the optimal path requirements, meet the current data flow and network stability requirements, and obtain the adjusted monitoring node transmission configuration;

[0045] According to the adjusted monitoring node transmission configuration, the synchronization protocol adjustment process is started, the delay and data loss during the synchronization process are analyzed, the transmission parameters are dynamically adjusted, the synchronization status is monitored in real time, and a record of data synchronization efficiency improvement is obtained;

[0046] According to the data synchronization efficiency improvement record, a comprehensive synchronization record is performed on the data transmission, and a unified recording protocol is used to collect and store the data synchronization content of all monitoring points to generate a remote monitoring data synchronization record.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, the utilization of network bandwidth is optimized through advanced data capture technology, and accurate monitoring of network traffic and status fluctuations is achieved. At the same time, the system has the ability to adjust spectrum resources in real time, respond quickly to changes in network conditions, significantly improve network stability and response speed, automatically identify high-demand periods and adjust spectrum allocation, accurately evaluate and optimize data transmission paths, effectively reduce network congestion and transmission delays, ensure the continuity and reliability of data flows, enhance the efficiency and integrity of data synchronization processing, especially in real-time data interaction between multiple nodes, to ensure efficient and accurate data synchronization. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a system flow chart of the present invention;

[0050] Figure 2 This is a flow chart for recording the usage of 5G network bandwidth of the present invention;

[0051] Figure 3 A flowchart of obtaining a real-time network data snapshot according to the present invention;

[0052] Figure 4 This is a flow chart for identifying key flow demand periods of the present invention;

[0053] Figure 5 A flowchart of obtaining the adjusted spectrum configuration of the present invention;

[0054] Figure 6 A flow chart for calculating the transmission path network delay index of the present invention;

[0055] Figure 7 A flowchart for obtaining the optimal data path solution of the present invention;

[0056] Figure 8 This is a flow chart for obtaining synchronous records of remote monitoring data according to the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] See also Figure 1 , a remote monitoring platform based on 5G communication includes:

[0060] The network data monitoring module deploys sensors and receivers to capture network traffic and latency data in real time, record 5G network bandwidth usage, analyze traffic patterns in different time periods based on the recorded results, evaluate network status fluctuations, and generate real-time network data snapshots;

[0061] The spectrum resource adjustment module analyzes spectrum occupancy based on real-time network data snapshots, identifies key traffic demand periods, adjusts spectrum allocation parameters based on the identification results, implements dynamic spectrum management to match changes in network conditions, and generates adjusted spectrum configurations;

[0062] The data transmission optimization module uses the adjusted spectrum configuration to evaluate the existing data transmission path, calculate the network delay index of the transmission path, optimize the path based on the calculation results, avoid network congestion and transmission delay, and generate the optimal data path solution;

[0063] The data synchronization processing module uses the optimal data path solution to adjust and update the data transmission configuration between monitoring nodes, perform monitoring data synchronization between all locations, and generate remote monitoring data synchronization records.

[0064] Real-time network data snapshots include bandwidth utilization data, delay measurement results and traffic change graphs. The adjusted spectrum configuration includes spectrum utilization rate, spectrum allocation strategy and adjustment response time. The optimal data path solution includes path delay data, path selection list and congestion avoidance measures. Remote monitoring data synchronization records specifically refer to synchronization frequency, synchronization success rate and data consistency status records.

[0065] See also Figure 2 , the steps for recording 5G network bandwidth usage are:

[0066] Deploy sensors and receivers at 5G network exchange points to capture packet flows and signal delays every second, and obtain preliminary network traffic and latency data;

[0067] Deploy high-precision sensors and receivers at the exchange points of the 5G network, select sites based on geographical and network traffic distribution characteristics, and determine the specific installation locations. For example, nodes with high network traffic and frequent data transmission are selected as monitoring points, which are usually located in the core position of the network architecture or in user-dense areas. Next, install the equipment according to technical specifications to ensure that all sensors and receivers can operate normally and capture data in real time. During this process, the sensitivity of the sensor also needs to be set so that the flow of data packets and signal delays per second can be accurately captured, from which preliminary network traffic data and delay data can be obtained.

[0068] Clean the preliminary network traffic data and delay data to remove noise and outliers, ensure data consistency through data synchronization, and obtain accurate network usage data;

[0069] In the process of data cleaning of network traffic data and delay data, we first perform an initial screening to identify and eliminate abnormal points in the data, such as signal mutations or packet loss. Then, we perform format verification to ensure that all data conforms to the preset data format specifications. The logical verification link checks the timestamps and sequences in the data to eliminate errors caused by time misalignment or data duplication. In addition, data synchronization processing is an essential step. By comparing data collected by different sensors, the deviation problem of the data timeline is solved, ensuring that data collected from multiple sources can be analyzed within the same time frame, ensuring the quality and consistency of the data before entering the analysis, which is a key link in obtaining accurate network usage data.

[0070] Based on accurate network usage data, we analyze the time series changes of the data and use the formula:

[0071]

[0072] Calculate the overall bandwidth utilization T and obtain the 5G network bandwidth usage record, where N represents the number of measurements, B i Represents the bandwidth usage at each time point, L i Represents the corresponding delay;

[0073] There are 10 measurement points. The bandwidth usage at each point is 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 Mbps, and the corresponding delay is 10, 9, 8, 7, 6, 5, 4, 3, 2, 1 ms. The calculation process is:

[0074]

[0075] The results show that the average bandwidth utilization is 357.5Mbps. The number reflects the overall usage of network bandwidth and explains the bandwidth usage of the network in actual operation.

[0076] See also Figure 3 , the steps to obtain the real-time network data snapshot are:

[0077] Based on the 5G network bandwidth usage records, perform time series analysis to determine the periodic changes in data traffic, identify traffic peaks and valleys in different time periods, and obtain time period traffic pattern data;

[0078] When performing time series analysis to identify periodic changes in network traffic, first select an appropriate time window, such as every hour or every day, to collect data points based on bandwidth usage records, and use time series analysis tools such as ARIMA or Fourier transform to analyze these data points to help identify seasonal changes and trends in the data. The analysis process includes normalization of the data to eliminate the impact of inconsistent units, and then check the inherent correlation of the data through autocorrelation and partial autocorrelation functions to identify major periodic patterns, such as identifying patterns of increased traffic every weekend or traffic peaks caused by specific events. The traffic pattern data obtained for the subdivided time periods not only reflects periodic changes, but also reveals the specific periods of traffic peaks and troughs, providing key information for subsequent network management and capacity planning.

[0079] Using the traffic pattern data of the time period, we analyze the statistical indicators of the traffic data, measure the fluctuation of the network status in the different time periods, and obtain the network status fluctuation data;

[0080] Using the traffic pattern data, the statistical indicators of the data are further calculated to evaluate the volatility of the network status. In this process, the mean of the traffic data for each time period is first determined, then the deviation of each data point from the mean is calculated, the square of all deviations is summed and divided by the total number of data points to obtain the variance, and finally the square root of the variance is calculated to obtain the standard deviation. The standard deviation provides a quantitative fluctuation size, allowing network engineers to evaluate the stability of the network in different time periods. In addition, the coefficient of variation, which is the ratio of the standard deviation to the mean, can be calculated to provide a relative measure for the fluctuation of network performance. Through detailed statistical analysis, time periods that may require additional attention or improvement can be identified, such as network bottlenecks caused by sudden increases in traffic, so that specific network optimization or capacity increase can be performed for the time period to ensure the optimization of network performance.

[0081] Integrate network status fluctuation data, calculate total network load, integrate delay changes and bandwidth utilization, and use dynamic data visualization to generate real-time network data snapshots;

[0082] When calculating the total network load, use the formula: Calculate, where n is the number of measured time points, P i is the number of packets at the i-th time point, V iis the data rate at the corresponding time point. In a measurement, n=5, and the number and rate of data packets at each time point are (100, 0.5Mbps), (150, 0.75Mbps), (200, 1.0Mbps), (250, 1.25Mbps), (300, 1.5Mbps), respectively, then the calculation is as follows:

[0083] R=(100×0.5)+(150×0.75)+(200×1.0)+(250×1.25)+(300×1.5)=50

[0084] +112.5+200+312.5+450=1125

[0085] It shows that during the observation period, the total network load was 1125Mbps. The results show the network load during this period and provide network administrators with real-time data snapshots to help monitor and adjust network configurations to adapt to changing network requirements.

[0086] See also Figure 4 ,The steps for identifying the critical traffic demand period are:

[0087] Receive real-time network data snapshots, organize network traffic, number of user connections, and device type information, and generate real-time network status data sets;

[0088] Automatically receive data on network traffic and device types, and upload the data to the central server through real-time monitoring equipment. The server analyzes the data in real time and generates a real-time network status data set. This process involves not only data collection, but also preliminary data cleaning and formatting. For example, the data collected from various network devices are not in a unified format and need to be converted into a unified format through a conversion program. At the same time, the data quality is evaluated to eliminate those obviously abnormal data points, such as abnormal data with sudden increases or decreases in traffic, so as to ensure the accuracy of subsequent analysis. The final generated data set will be used for further traffic analysis and spectrum occupancy analysis.

[0089] Based on the real-time network status data set, the formula is adopted.

[0090]

[0091] Calculate the comprehensive spectrum occupancy index F(t) at time point t, identify the network traffic peak and spectrum occupancy pattern, and obtain the traffic peak period data. N(t) represents the network traffic, and D(t) represents the number of device connections.

[0092] At a specific time t, the network traffic N(t) monitored is 5000MB / s, and the number of device connections D(t) is 800 devices. Considering that the time unit for real-time data monitoring is usually set to seconds, t is set to 1 second. Substituting into the formula, the calculation steps are as follows:

[0093] ln(N(t))=ln(5000)≈8.517193191

[0094]

[0095]

[0096] The result 28.43 shows that at time point t = 1 second, considering the network traffic and the number of device connections, the comprehensive index of spectrum occupancy is 28.43, which can be used to analyze the peak pattern of spectrum occupancy and help identify peak traffic periods.

[0097] Using the traffic peak period data, set the traffic threshold T and compare the traffic density of the time window. If F(t) is greater than T, mark the target time window as the critical traffic demand period and generate the critical traffic demand period results.

[0098] Using the traffic peak period data obtained through analysis, the traffic density in each time window is further screened and compared, and the key traffic demand period is identified by setting different traffic thresholds T. For example, if the threshold T is set to 25, the relationship between the F(t) value and T of each time window will be compared. If F(t) is greater than T, the time window is marked as a key traffic demand period. In this way, the threshold T can be dynamically adjusted to adapt to different network conditions and needs. Finally, through these calculations, the time windows that exceed the threshold T are accurately screened out to determine the final key traffic demand period. This process is dynamic and iterative, and the threshold T needs to be continuously adjusted according to the actual situation to ensure that the key period can be accurately identified, thereby providing a basis for subsequent network management and spectrum allocation.

[0099] See also Figure 5 , the steps to obtain the adjusted spectrum configuration are:

[0100] According to the results of key traffic demand periods, analyze spectrum utilization, traffic density distribution and service quality requirements, and generate network status analysis records;

[0101] Based on the data of the identified key traffic demand periods, the current spectrum occupancy and network load are analyzed in real time. First, real-time data is obtained from the network monitoring system, including service quality requirements, equipment types, user behavior patterns, etc. The data analysis helps determine the efficiency of spectrum use and traffic density distribution. The analysis process covers data clustering, spectrum utilization calculation and network load prediction. Each calculation step is based on actual monitoring data to ensure the accuracy of the results. In addition, different service quality requirements are classified and processed to provide decision support for the next step of spectrum adjustment. Finally, a detailed network status analysis report is generated to provide a basis for adjusting spectrum allocation parameters.

[0102] Based on the network status analysis record, dynamic spectrum allocation is performed using the formula:

[0103]

[0104] Calculate the priority P(f) of frequency band f, adjust the spectrum allocation parameters, and obtain the optimized spectrum allocation parameters, where μ and σ are the mean and standard deviation obtained from the statistics of network status data;

[0105] In a specific example, μ=3 GHz and σ=0.5 GHz.

[0106] A specific frequency band f=3.2 GHz is selected.

[0107] Calculate the exponent part in the numerator and get:

[0108] (3.2-3) / 0.5=0.4

[0109] Exponential function calculation:

[0110] e -0.4 ≈0.67032

[0111] Substituting this value into the formula, we get:

[0112]

[0113] The results show that for the 3.2 GHz frequency band, its priority is about 0.5987, which means that this frequency band has a medium to high priority compared to other frequency bands and is used to optimize spectrum resource allocation.

[0114] Apply the optimized spectrum allocation parameters, update the spectrum configuration database and promote the new configuration to base stations and access points, monitor the implementation effect of the new configuration, and generate the adjusted spectrum configuration;

[0115] The optimized spectrum allocation parameters are applied to the network management system. First, the obtained spectrum allocation parameters are imported into the database of the network management system. The system updates the spectrum allocation strategy and rules according to the parameters, including the adjustment of the spectrum allocation width and access rights. Next, the system automatically sends the updated configuration to each base station and access point through the network. The base station and access point adjust their equipment settings according to the new spectrum configuration to ensure that each node runs according to the latest configuration. During the process, the network operation support system is also responsible for monitoring the implementation effect of the configuration update and collecting performance data after implementation for subsequent evaluation and adjustment to ensure that the entire network can efficiently respond to changes in spectrum configuration and optimize network performance and user experience.

[0116] See also Figure 6 ,The calculation steps of the transmission path network delay index are:

[0117] Using the adjusted spectrum configuration, evaluate the existing data transmission path, analyze key nodes and data traffic distribution, and generate path status evaluation records;

[0118] When evaluating the data transmission path using the adjusted spectrum configuration, it is first necessary to determine the data traffic distribution of key nodes through actual network monitoring data, capture the data traffic of each node in different time periods through high-precision spectrum analysis instruments, and perform cluster analysis on the data to identify the peaks and troughs of data traffic. Further, the data load capacity of the entire transmission path is evaluated through information to determine which nodes may become bottlenecks for data transmission. Then, various network traffic scenarios are simulated, such as high load, low load, and sudden large traffic, to test whether the performance of the adjusted spectrum configuration in various situations meets the expected performance standards and generate a path evaluation status.

[0119] Based on the path status evaluation record, the formula is used,

[0120]

[0121] Calculate the total delay D and generate the network delay index, where L i is the length of the i-th path, is the average length of all paths, v i is the signal speed of the i-th path, and m represents the number of paths;

[0122] There are three paths of different lengths, 10km, 12km and 8km, with an average length of The signal speed of each segment is assumed to be 100 Mbps, 120 Mbps and 80 Mbps. The delay contribution of each segment is calculated by substituting them into the formula respectively. Then the total delay D is obtained by adding up the values ​​and taking the square root.

[0123] First paragraph:

[0124]

[0125] Second paragraph:

[0126]

[0127] Paragraph 3:

[0128]

[0129] Total delay:

[0130]

[0131] The results show that the total delay of the three transmission paths is 0.205ms.

[0132] Evaluate network performance based on network delay indicators, confirm whether the delay indicators match the network operation standards, and generate network performance records;

[0133] Based on the calculated network delay index, the process of comprehensively evaluating network performance involves multiple links, including collecting delay data through a real-time network monitoring system, statistically analyzing the data, calculating the average delay and its standard deviation to determine whether the network performance meets the set threshold. In addition, network simulation tests are required to simulate the delay conditions under different data flows and network loads to verify the adaptability and stability of the network configuration, confirm whether the delay index meets the network operation standards, and finally generate a network performance report to ensure that the network can operate in the optimal state.

[0134] See also Figure 7 , the steps to obtain the optimal data path solution are:

[0135] Use network latency indicators to analyze the current data transmission path, simulate network performance under different load conditions, compare latency data under different configurations, record the best configuration, and generate a draft of the optimized path plan;

[0136] When using network delay indicators for analysis, we first collect data about data traffic and response time by setting up multiple network performance monitoring points. The monitoring points record the data packets passing through, as well as the sending and receiving times in real time. Based on this data, accurate simulations can be performed under different network loads and conditions. In addition, by simulating different traffic configurations, we can see in detail the performance of the network under each configuration and identify potential congestion points. Finally, by combining the simulation results with the actual data, we can compare and select the network path with the best delay performance, provide a basis for further network optimization, and generate a detailed optimization plan for the existing network structure.

[0137] Based on the draft of the optimized path plan, comprehensively refer to the network performance data of the path plan, formulate network reconstruction and adjustment measures, and generate network adjustment proposals;

[0138] After determining the specific network path optimization solution, further planning steps include a comprehensive analysis of the performance of the selected solution to ensure that the proposed solution can maintain network performance under various traffic conditions, such as Wireshark and SolarWinds, to perform detailed packet capture and analysis of each node in the network. Through analysis, we can understand in detail how data flows in the network and potential bottlenecks. Next, by simulating different network traffic scenarios, we verify the performance of the selected path solution in actual applications, ensuring that the selected optimization solution is not only feasible in theory, but also can achieve the expected delay reduction effect in actual operation. The generated report contains detailed solutions and suggestions for each situation.

[0139] According to the network adjustment proposal, formulate an implementation plan, including technical implementation details, resource allocation and time arrangement, set regular evaluation points to monitor the optimization progress and effect, and obtain the optimal data path solution;

[0140] Implementing a network optimization solution is a complex process that involves detailed planning and execution of multiple key phases. First, the technical planning phase includes designing the architecture of the entire network, selecting appropriate hardware and software, and determining the optimal configuration and installation location of equipment in the network. Next, the resource configuration phase ensures that all necessary technical equipment and professionals are ready and deployed as planned. In addition, a detailed project schedule includes the start and end time of each key task and how to evaluate the project progress in stages. The setting of monitoring mechanisms, including performance monitoring and problem response systems, is key to ensuring that the project proceeds as planned and can respond quickly when problems arise.

[0141] See also Figure 8 ,The steps for obtaining the synchronous record of remote monitoring data are:

[0142] Using the optimal data path solution, perform configuration analysis on the monitoring nodes, adjust the transmission configuration parameters of each node to match the optimal path requirements, meet the current data flow and network stability requirements, and obtain the adjusted monitoring node transmission configuration;

[0143] Using the generated optimal data path solution, perform configuration analysis on each monitoring node, adjust the transmission configuration parameters of each node to match the optimal path requirements, and ensure that the configuration update meets the current data traffic and network stability requirements. Based on the network topology and traffic data, evaluate the data traffic and load between nodes to determine the configuration update required for each node. According to the specific needs of each node and the overall network optimization goals, adjust the parameters to match these needs to ensure that each node can effectively transmit data on the optimal data path. Each step of parameter adjustment is based on real-time network conditions and predicted data, which not only involves basic data collection and analysis, but also includes in-depth understanding and simulation of network behavior to obtain the adjusted monitoring node transmission configuration.

[0144] According to the adjusted monitoring node transmission configuration, the synchronization protocol adjustment process is started, the delay and data loss during the synchronization process are analyzed, the transmission parameters are dynamically adjusted, the synchronization status is monitored in real time, and the data synchronization efficiency improvement record is obtained;

[0145] Based on the adjusted transmission configuration of the monitoring nodes, the synchronization protocol adjustment process is started to ensure that data is efficiently synchronized along the optimal path. For delays or data loss problems that may occur during the synchronization process, the transmission parameters are dynamically adjusted, and the synchronization status is monitored in real time. According to the latest network configuration and path optimization results, the data synchronization protocol is deployed, including precise setting and real-time adjustment of protocol parameters to adapt to changes in network conditions and fluctuations in data traffic. During the monitoring process, each stage of data transmission is tracked, any anomalies or delays are recorded, and the transmission settings are immediately adjusted to resolve these problems, ensuring efficient and stable synchronization of data between all monitoring nodes, and obtaining records of improved data synchronization efficiency.

[0146] According to the data synchronization efficiency improvement record, comprehensive synchronization record of data transmission is carried out, and the data synchronization content of all monitoring points is collected and stored using a unified recording protocol to generate remote monitoring data synchronization records;

[0147] Comprehensive synchronization records are made for data transmission from each node to the central monitoring system. A unified recording protocol is used to collect and store data synchronization details of all monitoring points. The data transmission details of each node are collected through the network monitoring system, including the start and end time of transmission, the size of the data packet, and any errors or interruptions during transmission. The data is recorded in a central database. Each record contains a timestamp, node ID, data volume, and transmission status. During this process, the system automatically analyzes the efficiency and integrity of data transmission, detects possible problem areas such as network congestion or node failure, and then generates reports. These reports provide decision support for network operators, helping them optimize network operations and maintenance plans, thereby ensuring efficient and stable synchronization of data between all monitoring nodes and generating detailed remote monitoring data synchronization records.

[0148] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A remote monitoring platform based on 5G communication, characterized in that: The platform includes: The network data monitoring module deploys sensors and receivers to capture network traffic and latency data in real time, record 5G network bandwidth usage, analyze traffic patterns in different time periods based on the recorded results, evaluate network status fluctuations, and generate real-time network data snapshots; The spectrum resource adjustment module analyzes spectrum occupancy based on the real-time network data snapshot, identifies key traffic demand periods, adjusts spectrum allocation parameters according to the identification results, implements dynamic spectrum management to match changes in network conditions, and generates adjusted spectrum configurations; The data transmission optimization module uses the adjusted spectrum configuration to evaluate the existing data transmission path, calculate the network delay index of the transmission path, optimize the path according to the calculation result, avoid network congestion and transmission delay, and generate the optimal data path solution; The data synchronization processing module uses the optimal data path solution to adjust and update the data transmission configuration between monitoring nodes, performs monitoring data synchronization processing between all locations, and generates remote monitoring data synchronization records.

2. The remote monitoring platform based on 5G communication according to claim 1 is characterized in that: The steps for recording the 5G network bandwidth usage are as follows: Deploy sensors and receivers at 5G network exchange points to capture packet flows and signal delays every second, and obtain preliminary network traffic and latency data; Cleaning the preliminary network traffic data and delay data to remove noise and outliers, ensuring data consistency through data synchronization, and obtaining accurate network usage data; Based on the accurate network usage data, the time series changes of the data are analyzed and the formula is used. Calculate the overall bandwidth utilization T and obtain the 5G network bandwidth usage record, where N represents the number of measurements, B i Represents the bandwidth usage at each time point, L i Represents the corresponding delay.

3. The remote monitoring platform based on 5G communication according to claim 2 is characterized in that: The steps of obtaining the real-time network data snapshot are: Based on the 5G network bandwidth usage records, time series analysis is performed to determine the periodic changes in data traffic, identify traffic peaks and valleys in different time periods, and obtain time period traffic pattern data; Analyze the statistical indicators of the traffic data using the traffic pattern data in the time period, measure the fluctuation of the network status in the different time periods, and obtain the network status fluctuation data; The network status fluctuation data is integrated to calculate the total network load, integrate the delay change and bandwidth utilization, and use dynamic data visualization to generate a real-time network data snapshot.

4. The remote monitoring platform based on 5G communication according to claim 3 is characterized in that: The steps for identifying the critical flow demand period are: Receiving the real-time network data snapshot, collating network traffic, number of user connections and device type information, and generating a real-time network status data set; Based on the real-time network status data set, the formula is adopted: Calculate the comprehensive spectrum occupancy index F(t) at time point t, identify the network traffic peak and spectrum occupancy pattern, and obtain the traffic peak period data. N(t) represents the network traffic, and D(t) represents the number of device connections. Using the traffic peak period data, set the traffic threshold T and compare the traffic density of the time window. If F(t) is greater than T, mark the target time window as the critical traffic demand period and generate the critical traffic demand period result.

5. The remote monitoring platform based on 5G communication according to claim 4 is characterized in that: The steps of obtaining the adjusted spectrum configuration are: Analyze spectrum utilization, traffic density distribution and service quality requirements according to the results of the key traffic demand period, and generate a network status analysis record; Based on the network status analysis record, dynamic spectrum allocation is performed using the formula: Calculate the priority P(f) of frequency band f, adjust the spectrum allocation parameters, and obtain the optimized spectrum allocation parameters, where μ and σ are the mean and standard deviation obtained from the statistics of network status data; The optimized spectrum allocation parameters are applied to update the spectrum configuration database and promote the new configuration to base stations and access points, and the implementation effect of the new configuration is monitored to generate an adjusted spectrum configuration.

6. The remote monitoring platform based on 5G communication according to claim 5 is characterized in that: The calculation steps of the transmission path network delay index are as follows: Using the adjusted spectrum configuration, evaluating the existing data transmission path, analyzing key nodes and data traffic distribution, and generating a path status evaluation record; Based on the path status evaluation record, the formula is used: Calculate the total delay D and generate the network delay index, where L i is the length of the i-th path, is the average length of all paths, v i is the signal speed of the i-th path, and m represents the number of paths; Based on the network delay index, the network performance is evaluated, whether the delay index matches the network operation standard is confirmed, and a network performance record is generated.

7. The remote monitoring platform based on 5G communication according to claim 6 is characterized in that: The steps for obtaining the optimal data path solution are: Utilize the network delay index to analyze the current data transmission path, simulate the network performance under different load conditions, compare the delay data under different configuration schemes, record the best performance configuration, and generate a draft of the optimized path plan; Based on the draft of the optimized path plan, comprehensively refer to the network performance data of the path plan, formulate network reconstruction and adjustment measures, and generate a network adjustment proposal; According to the network adjustment proposal, an implementation plan is formulated, including technical implementation details, resource allocation and time arrangement, and regular evaluation points are set to monitor the optimization progress and effect to obtain the optimal data path solution.

8. The remote monitoring platform based on 5G communication according to claim 7 is characterized in that: The steps for obtaining the remote monitoring data synchronization record are: Using the optimal data path solution, perform configuration analysis on the monitoring nodes, adjust the transmission configuration parameters of each node to match the optimal path requirements, meet the current data flow and network stability requirements, and obtain the adjusted monitoring node transmission configuration; According to the adjusted monitoring node transmission configuration, the synchronization protocol adjustment process is started, the delay and data loss during the synchronization process are analyzed, the transmission parameters are dynamically adjusted, the synchronization status is monitored in real time, and a record of data synchronization efficiency improvement is obtained; According to the data synchronization efficiency improvement record, a comprehensive synchronization record is performed on the data transmission, and a unified recording protocol is used to collect and store the data synchronization content of all monitoring points to generate a remote monitoring data synchronization record.

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