A stable communication system for smart water meters based on 4GCat1 technology

Abstract

The present invention relates to the field of communication management technology, specifically to a stable communication system for intelligent water meters based on 4GCat1 technology, the system comprising a real-time signal quality evaluation module, an intelligent flow scheduling module, an optimized signal management module and a multi-band concurrent transmission module. The present invention can dynamically adjust the transmission rate and frequency according to the actual network conditions by real-time monitoring of the communication signal quality and optimizing the data flow scheduling accordingly, reducing the delay and error rate in the data transmission process, and adopting multi-band concurrent transmission technology, so that data can be transmitted more smoothly and evenly under different network conditions, effectively avoiding data loss and transmission failure caused by network congestion, improving the reliability of communication, and optimizing the use efficiency of network resources. At the same time, using 4GCat1 technology, 4G Cat1 is based on the existing LTE network, fully reuses the existing LTE resources, does not need to increase additional investment, has low cost, and can achieve high benefits.

Description

Technical Field

[0001] The present invention relates to the technical field of communication management, and in particular to a stable communication system for an intelligent water meter based on 4GCat1 technology. Background Art

[0002] The field of communication management technology focuses on adjusting and optimizing the transmission process of information between devices to ensure the reliability, security and efficiency of data communication. This field includes network traffic and bandwidth management, error detection and correction, signal enhancement, data compression and decompression, and protocol conversion. Communication management technology is applied to a variety of communication media, such as wired, wireless, fiber optic and satellite communication systems, to improve the stability of data transmission, reduce latency, and optimize network load, thereby supporting the efficient operation of simple home networks to complex enterprise and global communication networks.

[0003] Among them, the smart water meter stable communication system is a communication technology solution designed specifically for smart water meters, aiming to improve the reliability and efficiency of water meter data transmission. The system ensures accurate recording and real-time transmission of water consumption data by optimizing the data interaction between water meters and central monitoring systems. Smart water meter systems are often used in water resource management and billing, enabling water companies to read data remotely and realize automated bill generation and consumption monitoring. The system's stable communication technology supports network management and provides effective data support to optimize water resource allocation and consumer services.

[0004] Traditional communication systems still show obvious limitations in highly dynamic communication scenarios. For example, when faced with sudden network congestion and signal quality fluctuations, traditional technologies are unable to adjust data transmission strategies in a timely and accurate manner, resulting in reduced data transmission efficiency and even data loss. The lack of effective multi-band concurrent transmission support makes it difficult to optimize data transmission in multi-signal coverage areas, and is easily affected by excessive load or weak signal on a single frequency band, thus affecting the stability and efficiency of the overall communication and increasing the operation and maintenance costs of the communication. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a stable communication system for smart water meters based on 4GCat1 technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a stable communication system for smart water meters based on 4GCat1 technology, the system comprising:

[0007] The signal quality real-time evaluation module is based on the working environment of the water meter. It receives the 4GCat1 signal through the 4GCat1 communication component of the water meter, evaluates the current stability index of the network according to the network fluctuation, and evaluates the current 4GCat1 signal quality in combination with the signal strength and network congestion information to obtain the signal quality score;

[0008] The intelligent flow scheduling module evaluates the importance of water meter data transmission tasks based on the content type and content volume of water meter data transmission tasks, prioritizes water meter data transmission tasks according to their urgency, adjusts the transmission order of water meter data transmission tasks in the 4GCat1 network environment, and obtains scheduling optimization information;

[0009] The optimized signal management module dynamically adjusts the transmission rate of the water meter data transmission task based on the signal quality score and the scheduling optimization information, and analyzes the transmission time and adjusts the transmission frequency according to the task amount of the water meter data transmission task to obtain optimized communication transmission information;

[0010] Based on the optimized communication transmission information, the multi-band concurrent transmission module transmits water meter data through the multi-band of the 4GCat1 network, adjusts the multi-band load according to the differentiated frequency band characteristics, optimizes the balanced transmission of water meter data in multiple frequency bands, and obtains parallel transmission optimization information.

[0011] The present invention is improved in that the method for evaluating the current stability index of the network is:

[0012] Based on the working environment of the water meter, the 4GCat1 communication component of the water meter receives the 4GCat1 signal, including the delay and data packet loss rate at each time point, and obtains the delay and packet loss data;

[0013] Based on the delay and packet loss data, the formula:

[0014]

[0015] Calculate the stability index S of the current network, and evaluate the stability of the network based on the value of the stability index S:

[0016] Among them, d d，i is the delay at the ith time point, d l，i is the packet loss rate at the i-th time point, i represents the sequence number of the time point, λ, μ and τ are the weights of delay, packet loss rate and time point respectively, S represents the network stability index, and n is the total number of data points.

[0017] The present invention is improved in that the steps of obtaining the signal quality score are:

[0018] Based on the working environment of the water meter, the signal strength data and network congestion data are collected through the 4GCat1 communication component of the water meter;

[0019] Based on the stability index S, signal strength data and network congestion data, by formula:

[0020]

[0021] Calculate the signal quality index Q, evaluate the signal quality status according to the value of the signal quality index Q, and obtain a signal quality score;

[0022] Among them, Z represents signal strength, C represents network congestion, S represents network stability index, α, β and γ are weight coefficients, and Q is signal quality index.

[0023] The present invention is improved in that the method for evaluating the importance of the water meter data transmission task is:

[0024] Based on the water meter data transmission task, the content type T and content volume V of the water meter data transmission task are collected;

[0025] Based on the content type T and the content volume V, a basic importance score p(T) of each content type is obtained, where the basic importance score p(T) is preset based on industry standards and historical emergency response data;

[0026] Based on the basic importance score p(T) and the content volume V, the formula is:

[0027]

[0028] Calculate the importance score I of each task to evaluate the importance of each water meter data transmission task;

[0029] Among them, p(T) represents the basic importance score, V is the content volume of the task, β is the nonlinear adjustment factor, α and θ are the slope parameter and offset parameter respectively, I is the importance score, and e is the base of the natural logarithm.

[0030] The present invention is improved in that the step of obtaining the scheduling optimization information is:

[0031] Based on the importance score I, according to the urgency of the water meter data transmission task, the formula is:

[0032]

[0033] Calculate the priority value Y of each transmission task;

[0034] Where Y represents the priority value of each transmission task, I represents the importance score, J represents the urgency of the transmission task, α is the importance coefficient, β is the urgency coefficient, θ is the urgency threshold, and e is the base of the natural logarithm;

[0035] Based on the priority value Y of each transmission task, the water meter data transmission tasks are sorted according to the size of the Y value, and the transmission order of the water meter data transmission tasks in the 4GCat1 network environment is adjusted to obtain scheduling optimization information.

[0036] The present invention is improved in that the method for dynamically adjusting the transmission rate of the water meter data transmission task is:

[0037] Based on the signal quality score and the scheduling optimization information, extracting a signal quality indicator Q and a priority value Y of each transmission task;

[0038] Based on the signal quality indicator Q and the priority value Y, by the formula:

[0039]

[0040] Calculate the transmission rate R of each task;

[0041] Among them, R is the transmission rate of the task, R0 is the baseline transmission rate, λ is the dynamic adjustment coefficient, Q is the signal quality indicator, Y is the priority value of each transmission task, and γ is the sensitivity adjustment factor of signal quality.

[0042] The present invention has the following improvements:

[0043] The present invention is improved in that the step of obtaining the optimized communication transmission information is:

[0044] Based on the transmission rate R of the task, combined with the data volume V of the water meter data transmission task, the formula is:

[0045]

[0046] Calculate the estimated transmission time T;

[0047] Among them, T is the expected transmission time, β is the adjustment coefficient, V is the data volume of the water meter data transmission task, R is the transmission rate of the task, and Q is the signal quality indicator;

[0048] Based on the estimated transmission time T, by the formula:

[0049]

[0050] Calculate the adjusted transmission frequency f to obtain optimized communication transmission information;

[0051] Among them, f is the adjusted transmission frequency, Y is the priority value of the transmission task, and T is the expected transmission time.

[0052] The present invention is improved in that the step of obtaining the parallel transmission optimization information is:

[0053] Collect the current data transmission load L of each frequency band in the 4GCat1 network i , and extract the transmission characteristics C of each frequency band i ,characteristics include the bandwidth capacity and signal penetration of the,band;

[0054] Based on the data transmission load L i And the transmission characteristic C i , through the formula:

[0055]

[0056] Calculate the ideal load distribution ratio P for each frequency band i ; According to the ideal load distribution ratio P of each frequency band i , adjust the load of each frequency band and obtain the parallel transmission optimization information;

[0057] Where α is the load regulation factor, P i is the ideal load distribution ratio of the ith frequency band, L i is the current data transmission load of the ith frequency band, C i is the transfer characteristic of the ith frequency band, e is the base of the natural logarithm, n is the total number of frequency bands, and i and j are indices.

[0058] Compared with the prior art, the advantages and positive effects of the present invention are:

[0059] In the present invention, by real-time monitoring of the communication signal quality and optimizing data flow scheduling accordingly, the transmission rate and frequency can be dynamically adjusted according to the actual network conditions, reducing the delay and error rate in the data transmission process, and adopting multi-band concurrent transmission technology, so that data can be transmitted more smoothly and evenly under different network conditions, effectively avoiding data loss and transmission failure caused by network congestion, improving communication reliability, and optimizing the utilization efficiency of network resources. At the same time, 4G Cat1 technology is used. 4G Cat1 is based on the existing LTE network and fully reuses the existing LTE resources. No additional investment is required, the cost is low, and high benefits can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a system flow chart of the present invention;

[0061] Figure 2 A flow chart for evaluating the current stability index of a network for the present invention;

[0062] Figure 3 A flow chart for obtaining a signal quality score for the present invention;

[0063] Figure 4 Flow chart for evaluating the importance of water meter data transmission tasks for the present invention;

[0064] Figure 5 A flow chart for obtaining scheduling optimization information for the present invention;

[0065] Figure 6 A flow chart of the present invention for dynamically adjusting the transmission rate of a water meter data transmission task;

[0066] Figure 7 A flow chart for obtaining optimized communication transmission information for the present invention;

[0067] Figure 8 The present invention is a flow chart for obtaining parallel transmission optimization information. DETAILED DESCRIPTION

[0068] 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.

[0069] 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", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying 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, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0070] Example

[0071] See also Figure 1 The present invention provides a technical solution: a stable communication system for smart water meters based on 4GCat1 technology, the system comprising:

[0072] The signal quality real-time evaluation module is based on the working environment of the water meter. It receives the 4GCat1 signal through the 4GCat1 communication component of the water meter, evaluates the current stability index of the network according to the network fluctuation, and comprehensively evaluates the current 4GCat1 signal quality by combining the signal strength and network congestion information to obtain the signal quality score.

[0073] The intelligent flow scheduling module evaluates the importance of water meter data transmission tasks based on the content type and content volume of water meter data transmission tasks, prioritizes water meter data transmission tasks according to their urgency, adjusts the transmission order of water meter data transmission tasks in the 4GCat1 network environment, and obtains scheduling optimization information;

[0074] The optimized signal management module dynamically adjusts the transmission rate of the water meter data transmission task based on the signal quality score and scheduling optimization information, and analyzes the transmission time and adjusts the transmission frequency according to the task volume of the water meter data transmission task to obtain optimized communication transmission information;

[0075] The multi-band concurrent transmission module transmits water meter data through the multi-band of the 4GCat1 network based on optimized communication transmission information. According to the differentiated frequency band characteristics, it adjusts the multi-band load, optimizes the balanced transmission of water meter data in multiple frequency bands, and obtains parallel transmission optimization information.

[0076] The signal quality score includes the signal strength index, network congestion index and signal stability index. The scheduling optimization information includes the task execution sequence, path selection optimization information and task processing time estimation. The optimized communication transmission information includes the transmission rate adjustment value and the transmission frequency adjustment value. The parallel transmission optimization information includes multi-band traffic distribution, data delay index and frequency band utilization.

[0077] See also Figure 2 , the method to evaluate the current stability index of the network is:

[0078] Based on the working environment of the water meter, the 4GCat1 communication component of the water meter receives the 4GCat1 signal, including the delay and data packet loss rate at each time point, and obtains the delay and packet loss data;

[0079] Based on the delay and packet loss data, the formula:

[0080]

[0081] Calculate the stability index S of the current network, and evaluate the stability of the network based on the value of the stability index S:

[0082] Among them, d d，i is the delay at the ith time point, d l，i is the packet loss rate at the i-th time point, i represents the sequence number of the time point, λ, μ and τ are the weights of delay, packet loss rate and time point respectively, S represents the network stability index, and n is the total number of data points.

[0083] formula:

[0084]

[0085] The meaning and acquisition method of parameters:

[0086] d d，i is the delay at the ith time point, d l，i is the packet loss rate at the ith time point, obtained directly through measurement;

[0087] λ is the delay weight: a parameter representing the relative importance of network delay in the overall stability score. It is determined through network performance evaluation experiments and can be preset by experts.

[0088] μ is the packet loss rate weight: the parameter indicates the importance of packet loss rate in the stability score. The weight is obtained based on network performance analysis. The impact of packet loss in the network on the business process is analyzed and the weight is determined accordingly. It can be preset by experts.

[0089] τ is the time weight: represents the weight of the impact of time-dependent changes on the stability score. For example, if the data shows that the network exhibits more instability in a specific time period, the weight can be used to adjust the impact of this time dependence. The weight can be preset by an expert.

[0090] n is the total number of data points: it is the number of data points obtained by actually monitoring the network status, indicating the total number of data points considered during the calculation.

[0091] Calculation example:

[0092] Assumptions:

[0093] λ=0.6μ=0.3τ=0.1.

[0094] n = 10 (indicates that 10 data points were collected in a certain period of time) Given a set of hypothetical data points, where the delay d d and packet loss rate d l As follows (unit: milliseconds and percentage):

[0095] Delay (ms): 100, 120, 150, 130, 160, 110, 115, 145, 135, 125

[0096] Packet loss rate (%): 1, 0.5, 0.7, 1.5, 1, 0.5, 0.6, 0.8, 0.7, 0.6

[0097] The process of calculating S is as follows:

[0098] Calculate the weighted score for each time point i:

[0099] Score i =λ·d d，i +μ·d l，i +τ·i For the first data point (delay 100ms, packet loss rate 1%):

[0100] Score1=0.6·100+0.3·1+0.1·1=60.3+0.3+0.1=60.7

[0101] Repeat step 1 to calculate the weighted scores for all 10 data points and sum them.

[0102] Calculate the average stability index:

[0103]

[0104] Assuming the sum of the weighted scores of all data points is 800, then:

[0105]

[0106] The calculation result S=80 means that the comprehensive stability score of the network is 80 during the considered time period, which is a relative score used to evaluate the overall performance of the network under given conditions.

[0107] See also Figure 3 , the steps to obtain the signal quality score are:

[0108] Based on the working environment of the water meter, the signal strength data and network congestion data are collected through the 4GCat1 communication component of the water meter;

[0109] Based on the stability index S, signal strength data and network congestion data, the formula is:

[0110]

[0111] Calculate the signal quality index Q, evaluate the signal quality status according to the value of the signal quality index Q, and obtain a signal quality score;

[0112] Among them, Z represents signal strength, C represents network congestion, S represents network stability index, α, β and γ are weight coefficients, and Q is signal quality index.

[0113] formula:

[0114]

[0115] The meaning and acquisition method of parameters:

[0116] α, β, and γ: weight parameters that adjust the relative importance of signal strength, network congestion, and stability index in the signal quality score. The weights are derived through statistical analysis based on past network performance data to ensure that the impact of each parameter in the formula is weighted according to its actual ability to affect network performance.

[0117] Z: Indicates the real-time signal strength, which is the value obtained directly from network monitoring.

[0118] C: Indicates network congestion, usually provided by a network traffic monitoring system, expressed as the ratio of current network traffic to maximum carrying traffic.

[0119] S: Network stability index, calculated by the previous step.

[0120] Calculation example:

[0121] Assumptions:

[0122] α=0.003, β=0.3, γ=4, Z=70dB (signal strength), C=60 (network congestion level, directly expressed as a percentage), S=80 (network stability index).

[0123] The calculation process is as follows:

[0124] Calculate the weighted square of the signal strength:

[0125] α·Z 2 =0.003·70 2 =0.003·4900=14.7

[0126] Weighted value of network congestion:

[0127] β·C=0.3·60=18

[0128] Weighted logarithm of the stability index:

[0129] γ·log(S+1)=4·log(81)≈4·1.9085=7.634

[0130] Calculate the signal quality index Q:

[0131] Q=14.7+18+7.634

[0132] =40.334

[0133] The final signal quality index Q=40.334, indicating that the signal quality is medium.

[0134] See also Figure 4 ,The method to evaluate the importance of the water meter data transmission task is:

[0135] Based on the water meter data transmission task, the content type T and content volume V of the water meter data transmission task are collected;

[0136] Based on the content type T and the content volume V, a basic importance score p(T) of each content type is obtained, where the basic importance score p(T) is preset based on industry standards and historical emergency response data;

[0137] Based on the basic importance score p(T) and the content volume V, the formula is:

[0138]

[0139] Calculate the importance score I of each task to evaluate the importance of each water meter data transmission task;

[0140] Among them, p(T) represents the basic importance score, V is the content volume of the task, β is the nonlinear adjustment factor, α and θ are the slope parameter and offset parameter respectively, I is the importance score, and e is the base of the natural logarithm.

[0141] formula:

[0142]

[0143] The meaning and acquisition method of parameters:

[0144] p(T): A basic importance score based on the content type. The score is set based on the impact of each data type on system operation. For example, alarm data has a higher score due to its urgency to system response. The score is set through historical data analysis and industry standards.

[0145] V: Data content, obtained directly from the water meter management system, indicating the amount of data contained in each transmission task.

[0146] β: A nonlinear adjustment factor for content volume growth, used to simulate the impact of content volume on importance scores. In practical applications, it can show the decreasing impact of increasing content volume on importance scores.

[0147] α and θ: Parameters used to adjust the sigmoid function, where α controls the slope of the function and θ controls the midpoint of the function. Helps determine how quickly the importance increases when the amount of content exceeds a certain threshold.

[0148] Calculation example:

[0149] Assumptions:

[0150] p(T)=80 for a certain data type, such as "alarm data".

[0151] V = 75 bytes, indicating the data volume of a task.

[0152] The set parameters are β=0.5, α=1, θ=50.

[0153] Calculation process:

[0154] Calculate the impact of adjusted content volume on importance:

[0155] (V+1) β =(75+1) 0.5 ≈8.72

[0156] The importance score is calculated as:

[0157]

[0158]

[0159] The calculation result I=697.6 indicates that the importance score of the transmission task is high.

[0160] See also Figure 5 , the steps to obtain scheduling optimization information are:

[0161] Based on the importance score I, according to the urgency of the water meter data transmission task, the formula is:

[0162]

[0163] Calculate the priority value Y of each transmission task;

[0164] Where Y represents the priority value of each transmission task, I represents the importance score, J represents the urgency of the transmission task, α is the importance coefficient, β is the urgency coefficient, θ is the urgency threshold, and e is the base of the natural logarithm;

[0165] Based on the priority value Y of each transmission task, the water meter data transmission tasks are sorted according to the size of the Y value, and the transmission order of the water meter data transmission tasks in the 4GCat1 network environment is adjusted to obtain the scheduling optimization information.

[0166] formula:

[0167]

[0168] The meaning and acquisition method of parameters:

[0169] I: Importance score of the transfer task, calculated in the previous step.

[0170] J: The urgency of the transmission task is determined based on the time sensitivity of the task. It is evaluated based on the timeliness requirements of the task. The more urgent the task, the higher the urgency score. It can be preset by experts.

[0171] α: Importance coefficient, used to adjust the impact of importance on priority. It is set through historical data analysis and industry standards to ensure that importance is appropriately weighted in priority calculations.

[0172] β: Urgency coefficient, used to adjust the impact of urgency on priority. It is set through historical data analysis and industry standards to ensure that urgency is appropriately weighted in priority calculations.

[0173] θ: Urgency threshold, which adjusts the impact of urgency on priority and can be preset according to needs.

[0174] Calculation example:

[0175] Assumptions:

[0176] α=0.007, β=0.5, I=60 (importance of a task), J=80 (urgency of a task), θ=50 (urgency threshold).

[0177] The calculation process is as follows:

[0178] Calculate the squared weighted importance:

[0179] α·I 2 =0.007·60 2 =0.7·3600=25.2

[0180] Calculate the weighted value of urgency:

[0181]

[0182] Priority value calculation:

[0183] Y=25.2+0.5·80=25.2+40=65.2

[0184] The calculation result Y=65.2 indicates that the priority of the transmission task is higher and it will be processed first in the transmission queue.

[0185] See also Figure 6 ,The method of dynamically adjusting the transmission rate of the water meter data transmission task is:

[0186] Based on the signal quality score and scheduling optimization information, the signal quality index Q and the priority value Y of each transmission task are extracted;

[0187] Based on the signal quality indicator Q and the priority value Y, the formula is:

[0188]

[0189] Calculate the transmission rate R of each task;

[0190] Among them, R is the transmission rate of the task, R0 is the baseline transmission rate, λ is the dynamic adjustment coefficient, Q is the signal quality indicator, Y is the priority value of each transmission task, and y is the sensitivity adjustment factor of the signal quality.

[0191] formula:

[0192]

[0193] The meaning and acquisition method of parameters:

[0194] R0: Baseline transmission rate, which is the standard transmission rate of the network under ideal conditions. It is based on the standard configuration of the network provider or obtained through benchmark testing.

[0195] λ: Dynamic adjustment coefficient, used to adjust the transmission rate according to signal quality and task priority. The coefficient reflects the sensitivity and elasticity of the adjustment and is usually determined based on historical network performance data.

[0196] Q: Signal quality indicator, obtained through the previous steps.

[0197] Y: The priority value of the transmission task, obtained through the previous step.

[0198] γ: The sensitivity adjustment factor of signal quality is a preset parameter that is flexibly set according to the actual performance and needs of the network and is used to adjust the impact of the signal quality score on the rate.

[0199] Calculation example:

[0200] Assumptions:

[0201] R0 = 100Mbps (baseline transmission rate)

[0202] λ=0.1(dynamic adjustment coefficient)

[0203] Q = 80 (signal quality score)

[0204] Y=30 (task priority)

[0205] γ = 0.5 (Signal quality sensitivity adjustment factor)

[0206] The calculation process is as follows:

[0207] Calculate the signal quality adjustment impact:

[0208]

[0209] Calculate the priority adjustment impact:

[0210] log(1+Y)=log(1+30)=log(31)≈3.434

[0211] Calculate the transfer rate:

[0212]

[0213] The calculation result R≈30.7 Mbps shows that under the given network and task conditions, the transmission rate of the data transmission task with this priority value should be 30.7 Mbps.

[0214] See also Figure 7 ,The steps to obtain optimized communication transmission information are:

[0215] Based on the task transmission rate R, combined with the data volume V of the water meter data transmission task, the formula is:

[0216]

[0217] Calculate the estimated transmission time T;

[0218] Among them, T is the expected transmission time, β is the adjustment coefficient, V is the data volume of the water meter data transmission task, R is the transmission rate of the task, and Q is the signal quality indicator;

[0219] Based on the estimated transmission time T, by the formula:

[0220]

[0221] Calculate the adjusted transmission frequency f to obtain optimized communication transmission information;

[0222] Among them, f is the adjusted transmission frequency, Y is the priority value of the transmission task, and T is the expected transmission time.

[0223] formula:

[0224]

[0225] The meaning and acquisition method of parameters:

[0226] V: represents the total data volume of each water meter data transmission task. The value is obtained directly from the data management system and is determined based on the specific data volume required to be transmitted for each task.

[0227] R: The transmission rate of the task, calculated in the previous step.

[0228] Q: Signal quality indicator, calculated by the previous step.

[0229] β: The signal quality adjustment coefficient is a preset parameter used to adjust the impact of the signal quality score on the transmission time. Its value is determined based on historical analysis of network performance data.

[0230] Y: The priority value of each transmission task, calculated in the previous step.

[0231] Calculation example:

[0232] Assumptions:

[0233] V = 5000MB (task data volume)

[0234] R = 200MB / s (actual transmission rate)

[0235] Q = 75 (signal quality score)

[0236] β=0.5 (signal quality adjustment coefficient)

[0237] Y=20 (task priority)

[0238] The calculation process is as follows:

[0239] Calculate the estimated transmission time T:

[0240]

[0241]

[0242] Calculate the adjusted transmission frequency f:

[0243]

[0244] The calculation results T = 12.5 seconds and f ≈ 0.437 Hz indicate that under the given network and task conditions, data transmission should be completed in approximately 12.5 seconds, and the ideal data transmission frequency is 0.437 Hz.

[0245] See also Figure 8 , the steps to obtain the parallel transmission optimization information are:

[0246] Collect the current data transmission load L of each frequency band in the 4GCat1 network i , and extract the transmission characteristics C of each frequency band i ,characteristics include the bandwidth capacity and signal penetration of the,band;

[0247] Based on data transmission load L i And the transmission characteristic C i , through the formula:

[0248]

[0249] Calculate the ideal load distribution ratio P for each frequency band i ; According to the ideal load distribution ratio P of each frequency band i , adjust the load of each frequency band and obtain the parallel transmission optimization information;

[0250] Where α is the load regulation factor, P i is the ideal load distribution ratio of the ith frequency band, L iis the current data transmission load of the ith frequency band, C i is the transfer characteristic of the ith frequency band, e is the base of the natural logarithm, n is the total number of frequency bands, and i and j are indices.

[0251] formula:

[0252]

[0253] The meaning and acquisition method of parameters:

[0254] L i : Indicates the current data transmission load of each frequency band, which is obtained through real-time monitoring. This parameter reflects the data transmission volume of each frequency band at a specific time point.

[0255] C i : The transmission characteristics of each frequency band, including bandwidth capacity and signal penetration. The data is usually obtained from the network performance database and is used to evaluate the ability of each frequency band to support data transmission.

[0256] α: Load adjustment coefficient, which is a preset parameter used to adjust the impact of frequency band characteristics on load distribution. It is obtained based on the historical performance data analysis of the network.

[0257] Calculation example:

[0258] Assume there are three frequency bands, the specific parameters are as follows:

[0259] L1 = 300MB / s, L2 = 450MB / s, L3 = 200MB / s (current data transmission load of each frequency band)

[0260] C1=500MB / s,C2=600MB / s,C3=400MB / s (transmission characteristics of each frequency band)

[0261] α=0.1(load regulation coefficient)

[0262] The calculation process is as follows:

[0263] Calculate the sum of the total transfer characteristics:

[0264]

[0265] Calculate the ideal load distribution ratio P for each frequency band i :

[0266]

[0267] P1≈0.321, P2≈0.381, and P3≈0.265 indicate that ideally, the load distribution of each frequency band should be adjusted proportionally to optimize the balanced transmission of data in multiple frequency bands.

[0268] 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 stable communication system for smart water meters based on 4GCat1 technology, characterized in that: The system comprises: The signal quality real-time evaluation module is based on the working environment of the water meter. It receives the 4GCat1 signal through the 4GCat1 communication component of the water meter, evaluates the current stability index of the network according to the network fluctuation, and evaluates the current 4GCat1 signal quality in combination with the signal strength and network congestion information to obtain the signal quality score; The method for evaluating the current stability index of the network is: Based on the working environment of the water meter, the 4GCat1 communication component of the water meter receives the 4GCat1 signal, including the delay and data packet loss rate at each time point, and obtains the delay and packet loss data; Based on the delay and packet loss data, the formula: Calculate the stability index S of the current network, and evaluate the stability of the network based on the value of the stability index S: Among them, d d,i is the delay at the ith time point, d l,i is the packet loss rate at the i-th time point, i represents the sequence number of the time point, λ, μ and τ are the weights of delay, packet loss rate and time point respectively, S represents the network stability index, and n is the total number of data points; The intelligent flow scheduling module evaluates the importance of water meter data transmission tasks based on the content type and content volume of water meter data transmission tasks, prioritizes water meter data transmission tasks according to their urgency, adjusts the transmission order of water meter data transmission tasks in the 4GCat1 network environment, and obtains scheduling optimization information; The method for evaluating the importance of water meter data transmission tasks is: Based on the water meter data transmission task, the content type T and content volume V of the water meter data transmission task are collected; Based on the content type T and the content volume V, a basic importance score p(T) of each content type is obtained, where the basic importance score p(T) is preset based on industry standards and historical emergency response data; Based on the basic importance score p(T) and the content volume V, the formula is: Calculate the importance score I of each task to evaluate the importance of each water meter data transmission task; Where p(T) represents the basic importance score, V is the content of the task, β is the nonlinear adjustment factor, α and θ are the slope parameter and offset parameter respectively, I is the importance score, and e is the base of the natural logarithm; The steps for obtaining the scheduling optimization information are: Based on the importance score I, according to the urgency of the water meter data transmission task, the formula is: Calculate the priority value Y of each transmission task; Among them, Y represents the priority value of each transmission task, I represents the importance score, J represents the urgency of the transmission task, α is the importance coefficient, β is the urgency coefficient, θ is the urgency threshold, and e is the base of the natural logarithm; Based on the priority value Y of each transmission task, the water meter data transmission tasks are sorted according to the size of the Y value, and the transmission order of the water meter data transmission tasks in the 4GCat1 network environment is adjusted to obtain scheduling optimization information; The optimized signal management module dynamically adjusts the transmission rate of the water meter data transmission task based on the signal quality score and the scheduling optimization information, and analyzes the transmission time and adjusts the transmission frequency according to the task amount of the water meter data transmission task to obtain optimized communication transmission information; The steps for obtaining the optimized communication transmission information are as follows: Based on the task transmission rate and the data volume of the water meter data transmission task, the formula is: Calculate the estimated transmission time T; Among them, T is the expected transmission time, β is the adjustment coefficient, V is the data volume of the water meter data transmission task, R is the transmission rate of the task, and Q is the signal quality indicator; Based on the estimated transmission time T, by the formula: Calculate the adjusted transmission frequency f to obtain optimized communication transmission information; Among them, f is the adjusted transmission frequency, Y is the priority value of the transmission task, and T is the expected transmission time; Based on the optimized communication transmission information, the multi-band concurrent transmission module transmits water meter data through the multi-band of the 4GCat1 network, adjusts the multi-band load according to the differentiated frequency band characteristics, optimizes the balanced transmission of water meter data in multiple frequency bands, and obtains parallel transmission optimization information.

2. According to claim 1, the stable communication system of the smart water meter based on 4GCat1 technology is characterized in that: The steps for obtaining the signal quality score are: Based on the working environment of the water meter, the signal strength data and network congestion data are collected through the 4GCat1 communication component of the water meter; Based on the stability index S, signal strength data and network congestion data, by formula: Calculate the signal quality index Q, evaluate the signal quality status according to the value of the signal quality index Q, and obtain a signal quality score; Among them, Z represents signal strength, C represents network congestion, S represents network stability index, α, β and γ are weight coefficients, and Q is signal quality index.

3. According to claim 1, the intelligent water meter stable communication system based on 4GCat1 technology is characterized in that: The method for dynamically adjusting the transmission rate of the water meter data transmission task is: Based on the signal quality score and the scheduling optimization information, extracting a signal quality indicator Q and a priority value Y of each transmission task; Based on the signal quality indicator Q and the priority value Y, by the formula: Calculate the transmission rate R of each task; Among them, R is the transmission rate of the task, R0 is the baseline transmission rate, λ is the dynamic adjustment coefficient, Q is the signal quality indicator, Y is the priority value of each transmission task, and γ is the sensitivity adjustment factor of signal quality.

4. The intelligent water meter stable communication system based on 4GCat1 technology according to claim 1 is characterized in that: The steps for obtaining the parallel transmission optimization information are as follows: Collect the current data transmission load L of each frequency band in the 4GCat1 network i , and extract the transmission characteristics C of each frequency band i ,characteristics include the bandwidth capacity and signal penetration of the,band; Based on the data transmission load L i And the transmission characteristic C i , through the formula: Calculate the ideal load distribution ratio P for each frequency band i ; According to the ideal load distribution ratio P of each frequency band i , adjust the load of each frequency band and obtain the parallel transmission optimization information; Where α is the load regulation factor, P i is the ideal load distribution ratio of the ith frequency band, L i is the current data transmission load of the ith frequency band, C i is the transfer characteristic of the ith frequency band, e is the base of the natural logarithm, n is the total number of frequency bands, and i and j are indices.

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