Intelligent meter reading method and device, computer device and storage medium

Abstract

This application provides a smart meter reading method, device, computer equipment, and storage medium, belonging to the field of electrical communication. This application systematically solves the technical challenges of signal blind spots and communication instability in underground power distribution rooms by employing a hybrid segmented transmission architecture combining low-voltage narrowband power line carrier and wireless communication, combined with a tree-structured dynamic routing algorithm and a two-state node reliability model. The hierarchical design and real-time update mechanism of the routing table optimize the collaborative efficiency of multiple devices and avoid the impact of single-point failures; Markov model-driven risk prediction actively maintains the integrity of the network topology. This solution significantly improves the coverage, stability, and adaptability of data transmission in complex environments, achieving high-success-rate meter reading while reducing operation and maintenance costs, providing reliable support for underground smart grid applications.

Description

Technical Field

[0001] This application relates to the field of electrical communications, and more particularly to a smart meter reading method, apparatus, computer equipment, and storage medium. Background Technology

[0002] The application of power line carrier communication technology in smart meter reading systems has attracted widespread attention. Utilizing low-voltage power lines as the communication medium, it enables the transmission of analog or digital signals without the need for additional communication lines, demonstrating its enormous potential in fields such as automatic meter reading and smart grids. The advantages of power line carrier communication technology lie in its economy, low cost, and the convenience of not requiring the laying of new communication lines, making it particularly suitable for widely distributed low-voltage power network environments.

[0003] However, power line carrier communication (PLC) faces several challenges in its application. First, the inherent electromagnetic interference of power lines can easily affect signal transmission stability, leading to poor communication quality. Second, the uneven coverage of power lines results in significant signal attenuation over long distances or in certain areas, particularly in underground substations where weak signal coverage is a prominent issue, impacting the accuracy and range of automatic meter reading systems. Furthermore, PLC needs to address environmental noise, interference from power equipment, and power load fluctuations, causing signal transmission instability and further limiting its application in large-scale automated meter reading. Currently, the application of PLC technology in automatic meter reading systems has been extensively studied and some progress has been made. Some feasible implementations focus on improving signal processing, enhancing signal coverage, and improving communication stability, but these cannot comprehensively address the limitations of signal attenuation and coverage. Therefore, a smart meter reading method is needed to improve the accuracy, stability, and reliability of data recording and transmission in low-communication-quality application scenarios. Summary of the Invention

[0004] The purpose of this application is to at least address one of the aforementioned technical deficiencies, particularly the lack of accuracy, stability, and reliability in the data recording and transmission process under low-communication-quality application scenarios in the prior art.

[0005] Firstly, this application provides a smart meter reading method, the method comprising:

[0006] The target power data is obtained through a carrier meter, and in response to the meter reading command, the target power data is transmitted to the concentrator using low-voltage narrowband power line carrier communication.

[0007] The concentrator forwards the target power data to the target terminal.

[0008] The target power data is transmitted to the metering master station via wireless communication through the target terminal.

[0009] The target power data is stored and analyzed through the metering master station.

[0010] Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

[0011] This implementation method uses low-voltage narrowband power line carrier communication to transmit target power data to the concentrator via carrier meters. Combined with a hybrid communication architecture that integrates coordinated forwarding between the concentrator and the target terminal, as well as wireless communication for uploading to the metering master station, it significantly improves signal coverage in complex environments such as underground substations. By dynamically determining the transmission direction through a routing table, the blind spot problem of traditional power line carrier communication is effectively avoided, ensuring complete data transmission even in environments with strong interference. This segmented complementary communication design retains the economic advantages of power line carrier communication while compensating for long-distance attenuation through wireless communication, thereby systematically improving the accuracy and reliability of meter reading data and providing a stable foundation for data analysis at the metering master station.

[0012] As an optional implementation, the target terminal includes a slave device and a master device connected to the slave device via a low-voltage power line;

[0013] The step of forwarding the target power data to the target terminal through the concentrator includes:

[0014] The target power data is forwarded to the target terminal via the concentrator using wired communication.

[0015] The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes:

[0016] The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication.

[0017] The target power data is transmitted to the metering master station via wireless communication through the host device.

[0018] This implementation method forwards data to the slave device of the target terminal via wired communication through a concentrator, then transmits it to the master device using low-voltage narrowband power line carrier communication, and finally the master device uploads it to the metering master station via wireless communication. This design employs a segmented transmission mechanism of "wired-carrier-wireless," maintaining relay links using power line carrier in areas with weak signals and enabling high-speed wireless transmission in areas with good signals, achieving adaptive matching for different communication environments within the underground power distribution room. This optimizes the coordination efficiency between devices, reduces the risk of single-path failure, and significantly improves the meter reading success rate in areas with weak coverage.

[0019] As an optional implementation, the routing table includes a multi-level tree structure, and the root node of the routing table is used to indicate the concentrator, and the child nodes of the routing table are used to indicate each of the carrier meters.

[0020] This implementation constructs the routing table as a multi-level tree structure, with the concentrator as the root node and carrier meters as child nodes, forming a hierarchical data transmission path. This structure, through the natural redundancy of the tree topology, supports multi-path relay forwarding, avoiding the single point of failure problem of traditional star or chain structures. Simultaneously, the hierarchical routing simplifies the concentrator's scheduling logic for a large number of meters, reduces the probability of communication conflicts, and thus enhances the data acquisition stability and system scalability of large-scale underground power distribution networks.

[0021] As an optional implementation, the routing table is generated according to a dynamic routing algorithm, specifically including:

[0022] The concentrator sends a direct meter reading command to all the carrier meters and records the address of the first meter that responds successfully as a relay node.

[0023] The relay nodes forward instructions to all carrier meters that have not responded, and record the address and response time of the second meter that successfully responded.

[0024] If there are multiple transmission paths for the same carrier meter, the path with the shortest response time is selected and written into the routing table.

[0025] The instruction forwarding process is executed iteratively until the relay paths for all the aforementioned carrier meters are generated.

[0026] This implementation method generates a routing table based on a dynamic routing algorithm. It filters primary relay nodes using direct meter reading commands from the concentrator, then iteratively activates relay nodes to extend coverage of unresponsive meters, and optimizes path selection based on response time. This algorithm automatically constructs the optimal relay network by real-time detection of communication link quality, making it particularly suitable for scenarios with dynamically changing power line channel environments. Through the minimum response time path filtering mechanism, it effectively shortens data transmission latency, improves meter reading efficiency, and ensures reliable access for edge meters in underground distribution rooms.

[0027] As an optional implementation, if the target power data transmission corresponding to any of the carrier meters fails, the routing table is updated in real time, and the transmission process of the target power data is executed according to the updated routing table.

[0028] The real-time update methods for the routing table include:

[0029] For the failed carrier meter, perform a direct reading retry, and for the carrier meter that still fails after the direct reading retry, sequentially enable the relay node for relay retry;

[0030] If the direct copy retry or the relay retry is successful, the corresponding path is updated in the routing table.

[0031] If the relay retry fails for a preset number of consecutive times, a health check of the relay node is triggered to determine the hardware operation status of the corresponding carrier meter.

[0032] This implementation triggers real-time updates to the routing table upon transmission failure: it first directly retryes the failed node, then sequentially activates relay retry at each level. Successful retry updates the path, while consecutive failures trigger node health checks. This mechanism quickly identifies the fault type through a hierarchical retry strategy, avoiding resource waste caused by invalid retransmissions. Combined with proactive maintenance via hardware health checks, it can distinguish between channel fluctuations and physical equipment damage, allowing for targeted optimization of the network topology. This significantly improves the self-healing capability and long-term operational stability of underground power distribution rooms under interference environments.

[0033] As an optional implementation, the method further includes the following steps during the establishment of the routing table:

[0034] Establish a two-state transition model for each of the aforementioned carrier meters and determine the state transition probability parameters;

[0035] The state transition probability parameters include a first holding probability value for maintaining a good state, a first transition probability value for a good state to a fault state, a second holding probability value for maintaining a fault state, and a second transition probability value for a fault state to a good state.

[0036] If the first transfer probability value is greater than the risk threshold, the corresponding node is marked as a high-risk node, the high-risk node is removed from the routing table, and the preset backup relay node in the routing table is used to fill the path gap.

[0037] Furthermore, when the first transfer probability value is lower than the recovery threshold for multiple consecutive periods, the high-risk node is reactivated in the routing table.

[0038] This implementation method predicts the communication state transition probability of carrier meters during the routing table establishment process using a two-state transition model. High-risk nodes (those with a failure transition probability exceeding a threshold) are proactively removed, and backup nodes are activated. This design quantifies node reliability based on a Markov model, transforming post-fault repair into pre-fault risk avoidance. By dynamically replacing unstable nodes and monitoring their recovery probability, preventative maintenance of the routing table is achieved, fundamentally reducing the risk of cascading communication interruptions caused by node failures and ensuring the continuous and reliable operation of the underground power distribution network.

[0039] Secondly, this application provides a smart meter reading device, comprising:

[0040] The acquisition module is used to acquire target power data through a carrier meter, and, in response to a meter reading command, transmit the target power data to the concentrator using a low-voltage narrowband power line carrier communication method.

[0041] A communication module is used to forward the target power data to the target terminal via the concentrator;

[0042] The communication module is also used to send the target power data to the metering master station via the target terminal in a wireless communication manner;

[0043] The processing module is used to perform data storage and data analysis of the target power data through the metering master station;

[0044] Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

[0045] As an optional implementation, the target terminal includes a slave device and a master device connected to the slave device via a low-voltage power line;

[0046] The specific method by which the communication module forwards the target power data to the target terminal through the concentrator includes:

[0047] The target power data is forwarded to the target terminal via the concentrator using wired communication.

[0048] The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes:

[0049] The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication.

[0050] The target power data is transmitted to the metering master station via wireless communication through the host device.

[0051] Thirdly, this application provides a computer device including one or more processors and a memory storing computer-readable instructions that, when executed by the one or more processors, perform the steps of the method described in the first aspect.

[0052] Fourthly, this application provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the method described in the first aspect.

[0053] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0054] Based on any of the above embodiments, this application innovatively integrates low-voltage narrowband power line carrier and 5G wireless communication technologies to construct a segmented complementary data transmission link: the power line carrier is used from the meter to the concentrator to leverage its economy and penetration; the wired connection between the concentrator and the target terminal ensures local stability; and 5G is used from the target terminal to the metering master station for high-speed remote backhaul. This hybrid architecture avoids the coverage blind spots inherent in single communication modes in underground environments at the physical layer. Furthermore, a tree-structured dynamic routing algorithm is used to construct a multi-level relay network with the concentrator as the root node, optimizing path selection based on real-time response time to effectively address power line channel fluctuations and improve multi-device collaboration efficiency. The iterative update mechanism and hierarchical retry strategy of the routing table ensure rapid switching of faulty paths and network self-healing capabilities. More importantly, a two-state node reliability assessment based on a Markov model is introduced. By quantifying the communication state transition probability, high-risk nodes are proactively identified and replaced, shifting the operation and maintenance mode from post-event repair to pre-event prevention. This series of technologies, working together, not only overcomes traditional bottlenecks such as signal attenuation, electromagnetic interference, and difficulties in equipment coordination in underground power distribution rooms, but also achieves breakthroughs in communication stability, environmental adaptability, and system robustness, ultimately achieving the goal of highly reliable and low-cost smart meter reading, and providing a general solution for the deployment of ubiquitous power Internet of Things in complex scenarios. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 A schematic diagram of the basic system architecture of the smart meter reading method provided in one embodiment of this application;

[0057] Figure 2 A schematic diagram illustrating the principle and effect of a smart meter reading method provided in one embodiment of this application;

[0058] Figure 3 A flowchart illustrating a smart meter reading method provided in one embodiment of this application;

[0059] Figure 4 A schematic diagram of the overall system architecture of the smart meter reading method provided in one embodiment of this application;

[0060] Figure 5 This is a schematic diagram of the routing table construction process of a smart meter reading method provided in one embodiment of this application;

[0061] Figure 6 A schematic diagram of the routing table data structure of a smart meter reading method provided in one embodiment of this application;

[0062] Figure 7 A schematic diagram of the state transition model of a smart meter reading method provided in one embodiment of this application;

[0063] Figure 8 A schematic diagram of the state transition probability distribution of a smart meter reading method provided in one embodiment of this application;

[0064] Figure 9 This is an internal structural diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0065] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0066] In recent years, with the rapid development of power system automation technology, the application of power line communication (PLC) technology in smart meter reading systems has received widespread attention. PLC technology uses low-voltage power lines as the communication medium, enabling the transmission of analog or digital signals without the need for additional communication lines. This gives it enormous potential in fields such as automatic meter reading and smart grids. The advantages of PLC technology lie in its economy, low cost, and the convenience of not requiring the laying of new communication lines, making it particularly suitable for widely distributed low-voltage power network environments.

[0067] However, power line carrier communication faces several technical challenges in its application. First, the inherent electromagnetic interference of power lines can easily affect signal transmission stability, leading to poor communication quality. Second, the uneven coverage of power lines results in significant signal attenuation over long distances or in certain areas, particularly in underground substations where weak signal coverage is especially pronounced, impacting the accuracy and range of automatic meter reading systems. Furthermore, power line carrier communication must also address environmental noise, interference from power equipment, and fluctuations in power load, causing inherent instability in signal transmission and further limiting its application in large-scale automated meter reading.

[0068] Currently, the application of power line carrier communication technology in automatic meter reading systems has been widely studied and some progress has been made. Existing technical solutions mainly focus on improving signal processing, enhancing signal coverage, and improving communication stability. For example, existing research has employed electromagnetic interference suppression methods based on signal processing, effectively improving the signal's anti-interference capability. However, existing solutions still fail to fundamentally solve the problem of uneven signal coverage, especially in complex underground power distribution room environments where weak signal coverage areas still exist. Another set of research has proposed adaptive relay technology, extending signal coverage by adding relay nodes. Although this method improves signal stability to some extent, in practical applications, complex underground environments often affect the effectiveness of relay nodes, still failing to effectively solve the problem of uneven coverage. Other research attempts to introduce wireless communication as a supplementary solution. While this can improve communication stability and success rate, the cost and maintenance issues of wireless communication remain, and its stability in high-interference environments is poor. Furthermore, research on intelligent routing algorithms and anti-interference performance for power line carrier communication has also made some progress, but these technical methods generally cannot completely address the problems of signal attenuation and uneven coverage.

[0069] Therefore, this application proposes a novel intelligent meter reading system for underground substations. This system combines narrowband low-voltage power line carrier communication with wireless communication in a hybrid segmented, complementary remote meter reading method. Employing relay technology and intelligent routing algorithms, it aims to solve the problem of uneven signal coverage. By rationally planning and optimizing signal transmission paths, the system can significantly improve the accuracy and reliability of meter reading, especially in special environments such as underground substations, overcoming the bottlenecks of traditional power line carrier communication in terms of signal transmission stability and coverage. This solution not only meets the needs of power system automation technology development but also provides an innovative and practical solution for intelligent meter reading in underground substations.

[0070] Figure 1This is a schematic diagram of the basic system architecture of the smart meter reading method provided in one embodiment of this application. In a feasible automatic meter reading system, the low-voltage power line carrier meter reading system mainly consists of a master station, a concentrator, a transmission channel, and a carrier meter, such as... Figure 1 As shown, the transmission channel consists of two parts: the master station and the concentrator form the uplink communication, using a star topology for data acquisition, meaning one master station manages multiple concentrators. The communication channel is mainly 4G or 5G, with relatively high reliability. The concentrator and the carrier meter form the downlink communication, using a tree topology for data acquisition, meaning one concentrator manages multiple carrier meters. The communication channel uses low-voltage power line, RS 485, or small wireless communication technologies.

[0071] exist Figure 1 In this system, the carrier-based electricity meter records user electricity consumption data. Upon receiving a meter reading command, it transmits the data to the concentrator. Simultaneously, meters can forward data to each other via carrier modules; for example, a meter acting as a relay can forward the concentrator's reading commands. The concentrator receives meter reading instructions from the master station via the uplink channel, sends commands to the carrier-based meters via the downlink channel to set relevant parameters or read various data, and then transmits the read data back to the master station. The master station receives data transmitted from the concentrator and performs scheduled or real-time meter readings. It also manages the concentrator's data communication, operations, and centralized data processing, including storage and computation. In practical applications, for power supply bureaus or property management departments, it can provide various services such as report statistics, electricity bill printing, electricity consumption curve plotting, real-time data and key user monitoring, power anomaly analysis, and automatic fault alarms.

[0072] However, in some specific application scenarios, the success rate of automatic meter reading is around 99.70%, which falls short of the business requirement of 99.93%. This is mainly due to the following limitations in these feasible implementation methods:

[0073] (1) Signal coverage blind spot problem: In the existing low-voltage power line carrier automatic meter reading system, there are obvious blind spots in signal coverage in special environments such as underground power distribution rooms. Especially when the power line wiring is uneven or the equipment is deployed in multiple layers, the communication signal is severely attenuated in some areas, resulting in meter reading failure in these areas, which ultimately affects the accuracy and success rate of the overall meter reading system.

[0074] (2) Poor communication stability: The existing system mainly relies on wireless communication, low-voltage power lines or RS485 for communication channels. These transmission methods are greatly affected by electromagnetic interference and power equipment. In complex electrical environments, noise and signal interference from power lines have a significant impact on the stability of data transmission. Especially in some areas with weak coverage, communication links are prone to breakage or data loss, resulting in a decrease in the success rate of automatic meter reading.

[0075] (3) Multi-device coordination problem: In traditional systems, the communication between the concentrator and multiple carrier meters usually adopts a tree structure, relying on a single communication path for data transmission in the absence of routing maintenance. Under this structure, if a carrier meter or concentrator fails, the entire communication link is prone to breakage, affecting the meter reading success rate of downstream meters. The coordination problem between devices further increases the system failure rate and the risk of meter reading failure.

[0076] (4) Poor environmental adaptability: Existing automatic meter reading systems face significant challenges in certain special environments, especially underground power distribution rooms or densely populated buildings. In these environments, the power line wiring is complex, signal attenuation is severe, and electromagnetic interference is easily encountered, making it difficult for the system to operate stably and affecting the success rate of automatic meter reading. Traditional automatic meter reading systems cannot effectively adapt to these complex environments, resulting in signal coverage not reaching all areas.

[0077] The low-voltage power line channel environment is relatively harsh, resulting in significant signal attenuation. To enable relatively long-distance signal transmission, this application employs narrowband low-voltage PLC technology. Considering the signal coverage blind spots in underground power distribution rooms, this application integrates wireless communication technology with narrowband low-voltage PLC technology to propose a hybrid intelligent meter reading system for underground power distribution rooms, achieving an automatic meter reading success rate of 99.93%.

[0078] The following describes the relevant information about the PLC technology used in this application:

[0079] General model of low-voltage PLC channels

[0080] Without considering the load, for a single path, its transfer function can be obtained from the characteristics of power transmission lines:

[0081]

[0082] Where d is the path length and γ is its propagation constant, which is an important parameter characterizing the properties of power transmission lines. The amplitude attenuation of signal propagation per unit length on a power line is quantized by a complex combination of a unit length resistor R and a unit length inductor L. The phase change used to quantify signal propagation per unit length of power line is constituted by a complex quantity consisting of the unit length conductance G and unit length capacitance C. In fact, through mathematical derivation, the relationship between α and β and the signal frequency f is:

[0083]

[0084] Where a0 and a1 are channel attenuation factors, and v is the signal transmission speed parameter. Because the attenuation differs for each path, an attenuation factor g is introduced for each path. i Assuming there are L paths in the multipath model, for a single path i, d i Representing the distance of the corresponding path, the power channel frequency response of the above model can be given as:

[0085]

[0086] Figure 2 This is a schematic diagram illustrating the principle and effect of a smart meter reading method provided in one embodiment of this application. It shows the frequency response and impulse response of a 15-path channel model for low-voltage power lines. Figure 2 It can be seen that the signal attenuation in the frequency domain intensifies with increasing frequency, exhibiting a significant frequency-selective attenuation effect. Simultaneously, in the time domain analysis, the impulse response of the channel gradually decreases to near zero over time, with the main energy distribution concentrated at the channel taps. This phenomenon arises because different transmission paths have varying lengths, leading to differences in signal arrival times, thus the signal is primarily transmitted through a few critical paths. As time progresses, the signal intensity decreases significantly after continuous reflection and refraction, eventually attenuating to a negligible level.

[0087] Therefore, in this application, the PLC can achieve effective data transmission by selecting the signal transmission path.

[0088] In summary, the technical concept of this application lies in its innovative integration of low-voltage narrowband power line carrier and 5G wireless communication technologies to construct a segmented complementary data transmission link: the power line carrier is used to connect the meter to the concentrator, leveraging its economy and penetration; the wired connection between the concentrator and the target terminal ensures local stability; and 5G is used to achieve high-speed remote backhaul from the target terminal to the metering master station. This hybrid architecture avoids the coverage blind spots inherent in single-communication modes in underground environments at the physical layer. Furthermore, a tree-structured dynamic routing algorithm is used to construct a multi-level relay network with the concentrator as the root node, optimizing path selection based on real-time response time to effectively address power line channel fluctuations and improve the collaborative efficiency of multiple devices. The iterative update mechanism of the routing table and the hierarchical retry strategy ensure rapid switching of faulty paths and network self-healing capabilities. More importantly, a two-state node reliability assessment based on a Markov model is introduced. By quantifying the communication state transition probability, high-risk nodes are proactively identified and replaced, shifting the operation and maintenance mode from post-event repair to pre-event prevention. This series of technologies, working together, not only overcomes traditional bottlenecks such as signal attenuation, electromagnetic interference, and difficulties in equipment coordination in underground power distribution rooms, but also achieves breakthroughs in communication stability, environmental adaptability, and system robustness, ultimately achieving the goal of highly reliable and low-cost smart meter reading, and providing a general solution for the deployment of ubiquitous power Internet of Things in complex scenarios.

[0089] The methods provided in this application will be described in detail below based on the corresponding implementation methods in some practical application scenarios.

[0090] Figure 3 This is a flowchart illustrating a smart meter reading method provided in one embodiment of this application. Figure 4 This is a schematic diagram of the overall process architecture of a smart meter reading method provided in one embodiment of this application, as shown below. Figure 3 As shown, this application provides a smart meter reading method, which is described below in conjunction with... Figure 4 The architecture shown provides a detailed explanation of the method provided in this application:

[0091] based on Figure 4 In this application, the carrier-based electricity meter records user electricity consumption data. Upon receiving a meter reading command, it transmits the data to the concentrator. The concentrator then transmits the data to the slave unit via a CAT-6 network cable. The slave unit uses low-voltage narrowband power line carrier technology to transmit the data to the master unit. The master unit, installed in an area with good communication signal, is powered by the same 220V low-voltage power line in the same area. Finally, the master unit transmits the data to the metering master station via 5G communication. The metering master station receives the data transmitted from the master unit and completes related services such as timed or real-time meter reading of user electricity data.

[0092] S101. Obtain target power data through a carrier meter, and in response to a meter reading command, transmit the target power data to the concentrator using low-voltage narrowband power line carrier communication.

[0093] S102. The target power data is forwarded to the target terminal through the concentrator;

[0094] S103. The target power data is transmitted to the metering master station via wireless communication through the target terminal.

[0095] As an optional implementation, the target terminal includes a slave device and a master device connected to the slave device via a low-voltage power line;

[0096] The step of forwarding the target power data to the target terminal through the concentrator includes:

[0097] The target power data is forwarded to the target terminal via the concentrator using wired communication.

[0098] The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes:

[0099] The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication.

[0100] The target power data is transmitted to the metering master station via wireless communication through the host device.

[0101] This implementation method forwards data to the slave device of the target terminal via wired communication through a concentrator, then transmits it to the master device using low-voltage narrowband power line carrier communication, and finally the master device uploads it to the metering master station via wireless communication. This design employs a segmented transmission mechanism of "wired-carrier-wireless," maintaining relay links using power line carrier in areas with weak signals and enabling high-speed wireless transmission in areas with good signals, achieving adaptive matching for different communication environments within the underground power distribution room. This optimizes the coordination efficiency between devices, reduces the risk of single-path failure, and significantly improves the meter reading success rate in areas with weak coverage.

[0102] S104. Through the metering master station, perform data storage and data analysis of the target power data;

[0103] Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

[0104] As an optional implementation, the routing table includes a multi-level tree structure, and the root node of the routing table is used to indicate the concentrator, and the child nodes of the routing table are used to indicate each of the carrier meters.

[0105] This implementation constructs the routing table as a multi-level tree structure, with the concentrator as the root node and carrier meters as child nodes, forming a hierarchical data transmission path. This structure, through the natural redundancy of the tree topology, supports multi-path relay forwarding, avoiding the single point of failure problem of traditional star or chain structures. Simultaneously, the hierarchical routing simplifies the concentrator's scheduling logic for a large number of meters, reduces the probability of communication conflicts, and thus enhances the data acquisition stability and system scalability of large-scale underground power distribution networks.

[0106] As an optional implementation, the routing table is generated according to a dynamic routing algorithm, specifically including:

[0107] The concentrator sends a direct meter reading command to all the carrier meters and records the address of the first meter that responds successfully as a relay node.

[0108] The relay nodes forward instructions to all carrier meters that have not responded, and record the address and response time of the second meter that successfully responded.

[0109] If there are multiple transmission paths for the same carrier meter, the path with the shortest response time is selected and written into the routing table.

[0110] The instruction forwarding process is executed iteratively until the relay path for all the aforementioned carrier meters is generated;

[0111] This implementation method generates a routing table based on a dynamic routing algorithm. It filters primary relay nodes using direct meter reading commands from the concentrator, then iteratively activates relay nodes to extend coverage of unresponsive meters, and optimizes path selection based on response time. This algorithm automatically constructs the optimal relay network by real-time detection of communication link quality, making it particularly suitable for scenarios with dynamically changing power line channel environments. Through the minimum response time path filtering mechanism, it effectively shortens data transmission latency, improves meter reading efficiency, and ensures reliable access for edge meters in underground distribution rooms.

[0112] As an optional implementation, if the target power data transmission corresponding to any of the carrier meters fails, the routing table is updated in real time, and the transmission process of the target power data is executed according to the updated routing table.

[0113] The real-time update methods for the routing table include:

[0114] For the failed carrier meter, perform a direct reading retry, and for the carrier meter that still fails after the direct reading retry, sequentially enable the relay node for relay retry;

[0115] If the direct copy retry or the relay retry is successful, the corresponding path is updated in the routing table.

[0116] If the relay retry fails for a preset number of consecutive times, a health check of the relay node is triggered to determine the hardware operation status of the corresponding carrier meter.

[0117] This implementation triggers real-time updates to the routing table upon transmission failure: it first directly retryes the failed node, then sequentially activates relay retry at each level. Successful retry updates the path, while consecutive failures trigger node health checks. This mechanism quickly identifies the fault type through a hierarchical retry strategy, avoiding resource waste caused by invalid retransmissions. Combined with proactive maintenance via hardware health checks, it can distinguish between channel fluctuations and physical equipment damage, allowing for targeted optimization of the network topology. This significantly improves the self-healing capability and long-term operational stability of underground power distribution rooms under interference environments.

[0118] In fact, the routing algorithm is the key to implementing dynamic relay, which includes two parts: building the routing table and updating the routing table. Please refer to [link / reference needed]. Figure 5 , Figure 5 This is a schematic diagram illustrating the routing table construction process of a smart meter reading method according to an embodiment of this application, to explain the relevant process, wherein... Figure 5 (a) is the flowchart of the main program of the routing algorithm. Figure 5 (b) Procedure for establishing a routing table with secondary relay meters. Figure 5 (c) is a flowchart for maintaining the routing table with secondary relay meters.

[0119] (1) Construct the routing table:

[0120] refer to Figure 5 (a) shows the main process of building the routing table. Initially, during meter reading, the relay path needs to be determined and the routing table built based on the meter reading results. When the concentrator receives the meter reading command from the master station, it first attempts to directly read all meters, recording the addresses of meters that can be directly read. These addresses are considered primary relay points without direct reading requirements. Subsequently, the concentrator sends read commands again to the meters that cannot be directly read, forwarding data to other unread meters through each read meter, and recording the addresses of the meters that can be read this time and their reading time. These addresses are defined as secondary relay points. If a meter can be read through multiple primary relay points, the path with the shortest reading time is selected as the best route for that meter. Through this loop, a comprehensive test is conducted using permutation and combination methods until all meters can be successfully read. At this point, the routing table is built. In subsequent meter reading operations, the reading of meters without relays, primary relays, and secondary relays will be performed sequentially according to the built routing table. Taking the reading of secondary relay meters as an example, the process is as follows: Figure 5 The middle part, that is Figure 5 As shown in (b).

[0121] (2) Update the routing table:

[0122] Figure 5 The main program in (a) also includes a step of updating the routing table. Due to the variability of the power line communication environment, some paths in the routing table may become inapplicable, requiring an update to find new valid paths for meter reading. Specifically, when the concentrator receives a meter reading command from the master station, it first attempts to read the meters according to the existing routing table. If some paths are invalid, preventing data from being read, the concentrator attempts to directly read those unsuccessfully read meters and saves the new paths for successful readings. For meters that are still not read, the concentrator uses successfully read meters as primary relays for attempts, saving the new paths upon successful reading; for meters that are still not read, it uses successfully read primary relay meters as secondary relays for attempts, saving the new paths upon successful reading. This process repeats until all meters can be successfully read, completing the routing table update. The flowchart for updating secondary relay meters is shown below. Figure 5 The right side, that is Figure 5 As shown in (c).

[0123] Figure 6This is a schematic diagram of the routing table data structure of a smart meter reading method provided in one embodiment of this application. The following describes the implementation scheme of the dynamic relay routing algorithm designed in this application between the concentrator and the carrier meter. Specifically, this application designs a dynamic relay routing method based on a carrier module with smart relay functionality. The concentrator and each carrier module are respectively used as the root node and child nodes, establishing a tree-like query structure to achieve automatic routing, such as... Figure 6 As shown. The i-th module node in the first layer communicates directly with the concentrator, i.e., direct meter reading; the j-th module nodes in the second layer communicate indirectly with the concentrator through some module nodes in the first layer, i.e., meter reading requires a first-level relay; the module nodes in the third layer communicate indirectly with the concentrator through some module nodes in the first and second layers, i.e., meter reading requires a second-level relay; and so on for subsequent layers, with a maximum relay depth of 7 levels. In practical business applications, a maximum of 3 levels of relays is sufficient to achieve full meter reading. The meter reading process of the concentrator for each carrier meter is equivalent to the root node of a tree traversing and polling its child nodes.

[0124] As an optional implementation, the method further includes the following steps during the establishment of the routing table:

[0125] Establish a two-state transition model for each of the aforementioned carrier meters and determine the state transition probability parameters;

[0126] The state transition probability parameters include a first holding probability value for maintaining a good state, a first transition probability value for a good state to a fault state, a second holding probability value for maintaining a fault state, and a second transition probability value for a fault state to a good state.

[0127] If the first transfer probability value is greater than the risk threshold, the corresponding node is marked as a high-risk node, the high-risk node is removed from the routing table, and the preset backup relay node in the routing table is used to fill the path gap.

[0128] Furthermore, when the first transfer probability value is lower than the recovery threshold for multiple consecutive periods, the high-risk node is reactivated in the routing table.

[0129] Figure 7 This is a schematic diagram of the state transition model of a smart meter reading method provided in one embodiment of this application. Figure 8 This is a schematic diagram of the state transition probability distribution of a smart meter reading method provided in one embodiment of this application. The following is in conjunction with... Figure 7 and Figure 8 Explanation of the node state transition model:

[0130] This application focuses on exploring the communication performance of terminal nodes under fluctuating channel conditions, while explicitly excluding the consideration of physical faults in the carrier meter (hereinafter referred to as the terminal node). It is assumed that under ideal channel conditions, all terminal nodes can maintain normal operation. However, once the channel environment changes, the communication state of these terminal nodes may switch between "good" and "faulty," reflecting the dynamic changes in communication link stability. Using a two-state Markov probability model, this application can accurately describe this dynamic transition of terminal node communication states caused by changes in the channel environment. In the model, p... g With p b and represent the probabilities of a node being in a "good" and "faulty" state, respectively, under a given channel environment, while p gg With p gb These represent the probabilities that a node in a "good" state will remain in its original state or transition to a "faulty" state after a data collection cycle ends. Similarly, p bb With p bg The transition probability of a node in a "faulty" state recovering to a "good" state or remaining in a faulty state is defined, and thus the following relationship exists:

[0131]

[0132]

[0133]

[0134]

[0135] From the above formula, we can see that ,because Therefore .For example ,but .like ,but The value is unrestricted. , , The relationship between the three is as follows: Figure 8 As shown, from Figure 8 It can be seen that, When =0.5, It varies between 0 and 1, when When <0.5, Unrestricted, meaning that when the communication success rate of a certain link is less than 0.5 in practice, the possibility of communication failure of the associated nodes increases sharply.

[0136] This implementation method predicts the communication state transition probability of carrier meters during the routing table establishment process using a two-state transition model. High-risk nodes (those with a failure transition probability exceeding a threshold) are proactively removed, and backup nodes are activated. This design quantifies node reliability based on a Markov model, transforming post-fault repair into pre-fault risk avoidance. By dynamically replacing unstable nodes and monitoring their recovery probability, preventative maintenance of the routing table is achieved, fundamentally reducing the risk of cascading communication interruptions caused by node failures and ensuring the continuous and reliable operation of the underground power distribution network.

[0137] This application utilizes low-voltage narrowband power line carrier communication to transmit target power data to a concentrator via a carrier meter. A hybrid communication architecture, combining coordinated forwarding by the concentrator and the target terminal with wireless transmission to the metering master station, significantly improves signal coverage in complex environments such as underground substations. By dynamically determining the transmission direction through a routing table, the blind spot problem of traditional power line carrier communication is effectively avoided, ensuring complete data transmission even in environments with strong interference. This segmented, complementary communication design retains the economic advantages of power line carrier communication while compensating for long-distance attenuation through wireless communication, thereby systematically improving the accuracy and reliability of meter reading data and providing a stable foundation for data analysis at the metering master station.

[0138] In practical application scenarios, this application was tested in pilot areas, and the master-slave metering data remote transmission device was piloted. The initial system test adopted the following methods: (1) Direct reading test: Each carrier meter and the concentrator were connected to the same socket to ensure communication distance. Multiple statistical results showed that the meter reading success rate was 100%. (2) Multi-scenario test: Each carrier meter and the concentrator were connected to multiple sockets in the underground power distribution room for automatic meter reading. Multiple statistical results showed that the meter reading success rate reached 99.95%.

[0139] The key points of this application are:

[0140] 1. A Hybrid Solution of Low-Voltage Narrowband PLC and Wireless Communication. The core innovation of this application lies in proposing a remote meter reading method based on a hybrid approach of low-voltage narrowband PLC and wireless communication. By combining low-voltage narrowband PLC and wireless communication technologies, the signal coverage is optimized, especially in areas with weak signal coverage such as underground power distribution rooms. This successfully overcomes the signal blind zone problem of traditional power line carrier communication technology, thereby improving the overall meter reading success rate of the system. This hybrid solution improves the stability and adaptability of communication and is an important innovation addressing the shortcomings of existing technologies.

[0141] 2. Application and Optimization of Relay Technology. This application employs relay technology, setting up relay nodes in areas with good signal strength to solve the coordination problem between devices in traditional low-voltage power line carrier systems. When a device malfunctions or the communication signal is weak, other devices can continue data transmission through the relay node, avoiding meter reading failures due to single-point failures. This application of relay technology significantly improves the reliability and stability of the system, which is another innovation of this application.

[0142] 3. Terminal Node Model Based on Two-State Markov Process. To accurately analyze the communication performance of low-voltage power line carrier meters, this application proposes a low-voltage PLC terminal node model based on a two-state Markov process. This model effectively simulates different states in power line communication (such as signal strength, interference, etc.), enabling better prediction of communication quality and network performance, and thus optimizing the transmission path and strategy for meter reading data. The introduction of this model enhances the system's adaptability in complex environments and is one of the technical innovations of this application.

[0143] 4.5G Communication and Low-Voltage Narrowband PLC Efficient Integration This application also innovatively combines 5G communication technology with a low-voltage narrowband PLC to construct a highly efficient data transmission system. By using 5G communication technology as the communication channel between the master station and the concentrator, high-speed and stable data transmission is achieved. This integration not only improves the data transmission rate and stability but also ensures that the system can meet the needs of large-scale data acquisition. Especially in complex environments, it achieves efficient data transmission and remote management, which is one of the key innovations of this application.

[0144] In summary, the combination of several key technical features in this application, through the introduction of a hybrid scheme of low-voltage narrowband PLC and wireless communication, relay technology, Markov process model, and 5G communication, not only effectively solves the defects of existing technologies such as signal coverage blind spots, communication instability, equipment coordination problems, and poor environmental adaptability, but also greatly improves the success rate and overall reliability of the automatic meter reading system, providing an innovative solution for power system automation and smart meter reading.

[0145] Therefore, this application achieves the following technical effects:

[0146] 1. Solving the problem of signal coverage blind spots: This application significantly expands the signal coverage range by adopting a hybrid communication method of low-voltage narrowband PLC and wireless communication, combined with relay technology and intelligent routing algorithms. Especially in areas with weak signal coverage, such as underground power distribution rooms, it can effectively eliminate signal blind spots in traditional systems, ensure signal coverage and the integrity of communication links, thereby improving the success rate of automatic meter reading.

[0147] 2. Improved Communication Stability: This application overcomes the signal interference and noise issues inherent in traditional low-voltage power line carrier communication by introducing narrowband PLC technology and combining it with 5G communication technology, significantly improving the system's communication stability. Especially in complex environments, by optimizing the transmission path and communication protocol, stable data transmission is ensured, thereby effectively improving the success rate of automatic meter reading.

[0148] 3. Optimizing Device Coordination and Communication Paths: Addressing the issue of insufficient device coordination in existing technologies, this application proposes an innovative solution based on relay technology. By installing relay nodes in areas with good signal strength, it ensures that even if a carrier meter or concentrator malfunctions, other devices can still maintain communication through the relay path, ensuring smooth data transmission and thus avoiding the impact of communication link breaks on meter reading success rates.

[0149] 4. Improved Environmental Adaptability: The hybrid solution of low-voltage narrowband PLC and wireless communication in this application can adapt to special environments such as underground power distribution rooms, significantly improving signal transmission capabilities in these complex environments. By optimizing the transmission characteristics of power line carrier and combining it with wireless communication, the system can operate stably in environments with severe interference or significant signal attenuation, ensuring system reliability and a high success rate of automatic meter reading.

[0150] In summary, the purpose of this application is to overcome the problems of uneven signal coverage, unstable communication, difficulties in equipment coordination, and poor environmental adaptability in existing automatic meter reading systems by adopting a hybrid communication scheme and optimization technology, thereby achieving an automatic meter reading system with a higher success rate and meeting the requirements for efficient, accurate, and stable data collection. Furthermore, the advantages of this application also lie in its strong versatility, making it suitable for promotion and widespread application in fields such as ubiquitous power Internet of Things and power line carrier communication systems for smart homes.

[0151] This application also provides a smart meter reading device, including:

[0152] The acquisition module is used to acquire target power data through a carrier meter, and, in response to a meter reading command, transmit the target power data to the concentrator using a low-voltage narrowband power line carrier communication method.

[0153] A communication module is used to forward the target power data to the target terminal via the concentrator;

[0154] The communication module is also used to send the target power data to the metering master station via the target terminal in a wireless communication manner;

[0155] The processing module is used to perform data storage and data analysis of the target power data through the metering master station;

[0156] Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

[0157] This implementation method uses low-voltage narrowband power line carrier communication to transmit target power data to the concentrator via carrier meters. Combined with a hybrid communication architecture that integrates coordinated forwarding between the concentrator and the target terminal, as well as wireless communication for uploading to the metering master station, it significantly improves signal coverage in complex environments such as underground substations. By dynamically determining the transmission direction through a routing table, the blind spot problem of traditional power line carrier communication is effectively avoided, ensuring complete data transmission even in environments with strong interference. This segmented complementary communication design retains the economic advantages of power line carrier communication while compensating for long-distance attenuation through wireless communication, thereby systematically improving the accuracy and reliability of meter reading data and providing a stable foundation for data analysis at the metering master station.

[0158] As an optional implementation, the target terminal includes a slave device and a master device connected to the slave device via a low-voltage power line;

[0159] The specific method by which the communication module forwards the target power data to the target terminal through the concentrator includes:

[0160] The target power data is forwarded to the target terminal via the concentrator using wired communication.

[0161] The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes:

[0162] The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication.

[0163] The target power data is transmitted to the metering master station via wireless communication through the host device.

[0164] This implementation method forwards data to the slave device of the target terminal via wired communication through a concentrator, then transmits it to the master device using low-voltage narrowband power line carrier communication, and finally the master device uploads it to the metering master station via wireless communication. This design employs a segmented transmission mechanism of "wired-carrier-wireless," maintaining relay links using power line carrier in areas with weak signals and enabling high-speed wireless transmission in areas with good signals, achieving adaptive matching for different communication environments within the underground power distribution room. This optimizes the coordination efficiency between devices, reduces the risk of single-path failure, and significantly improves the meter reading success rate in areas with weak coverage.

[0165] As an optional implementation, the routing table includes a multi-level tree structure, and the root node of the routing table is used to indicate the concentrator, and the child nodes of the routing table are used to indicate each of the carrier meters.

[0166] This implementation constructs the routing table as a multi-level tree structure, with the concentrator as the root node and carrier meters as child nodes, forming a hierarchical data transmission path. This structure, through the natural redundancy of the tree topology, supports multi-path relay forwarding, avoiding the single point of failure problem of traditional star or chain structures. Simultaneously, the hierarchical routing simplifies the concentrator's scheduling logic for a large number of meters, reduces the probability of communication conflicts, and thus enhances the data acquisition stability and system scalability of large-scale underground power distribution networks.

[0167] As an optional implementation, the processing module is further configured to generate the routing table according to a dynamic routing algorithm, specifically including:

[0168] The concentrator sends a direct meter reading command to all the carrier meters and records the address of the first meter that responds successfully as a relay node.

[0169] The relay nodes forward instructions to all carrier meters that have not responded, and record the address and response time of the second meter that successfully responded.

[0170] If there are multiple transmission paths for the same carrier meter, the path with the shortest response time is selected and written into the routing table.

[0171] The instruction forwarding process is executed iteratively until the relay path for all the aforementioned carrier meters is generated;

[0172] This implementation method generates a routing table based on a dynamic routing algorithm. It filters primary relay nodes using direct meter reading commands from the concentrator, then iteratively activates relay nodes to extend coverage of unresponsive meters, and optimizes path selection based on response time. This algorithm automatically constructs the optimal relay network by real-time detection of communication link quality, making it particularly suitable for scenarios with dynamically changing power line channel environments. Through the minimum response time path filtering mechanism, it effectively shortens data transmission latency, improves meter reading efficiency, and ensures reliable access for edge meters in underground distribution rooms.

[0173] As an optional implementation, if the target power data transmission corresponding to any of the carrier meters fails, the routing table is updated in real time, and the transmission process of the target power data is executed according to the updated routing table.

[0174] The specific methods by which the processing module updates the routing table in real time include:

[0175] For the failed carrier meter, perform a direct reading retry, and for the carrier meter that still fails after the direct reading retry, sequentially enable the relay node for relay retry;

[0176] If the direct copy retry or the relay retry is successful, the corresponding path is updated in the routing table.

[0177] If the relay retry fails for a preset number of consecutive times, a health check of the relay node is triggered to determine the hardware operation status of the corresponding carrier meter.

[0178] This implementation triggers real-time updates to the routing table upon transmission failure: it first directly retryes the failed node, then sequentially activates relay retry at each level. Successful retry updates the path, while consecutive failures trigger node health checks. This mechanism quickly identifies the fault type through a hierarchical retry strategy, avoiding resource waste caused by invalid retransmissions. Combined with proactive maintenance via hardware health checks, it can distinguish between channel fluctuations and physical equipment damage, allowing for targeted optimization of the network topology. This significantly improves the self-healing capability and long-term operational stability of underground power distribution rooms under interference environments.

[0179] As an optional implementation, the processing module is further configured to perform the following during the establishment of the routing table:

[0180] Establish a two-state transition model for each of the aforementioned carrier meters and determine the state transition probability parameters;

[0181] The state transition probability parameters include a first holding probability value for maintaining a good state, a first transition probability value for a good state to a fault state, a second holding probability value for maintaining a fault state, and a second transition probability value for a fault state to a good state.

[0182] If the first transfer probability value is greater than the risk threshold, the corresponding node is marked as a high-risk node, the high-risk node is removed from the routing table, and the preset backup relay node in the routing table is used to fill the path gap.

[0183] Furthermore, when the first transfer probability value is lower than the recovery threshold for multiple consecutive periods, the high-risk node is reactivated in the routing table.

[0184] This implementation method predicts the communication state transition probability of carrier meters during the routing table establishment process using a two-state transition model. High-risk nodes (those with a failure transition probability exceeding a threshold) are proactively removed, and backup nodes are activated. This design quantifies node reliability based on a Markov model, transforming post-fault repair into pre-fault risk avoidance. By dynamically replacing unstable nodes and monitoring their recovery probability, preventative maintenance of the routing table is achieved, fundamentally reducing the risk of cascading communication interruptions caused by node failures and ensuring the continuous and reliable operation of the underground power distribution network.

[0185] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. For example, a processing module can be a separate processing element, or it can be integrated into a chip within the device. Alternatively, it can be stored as program code in the device's memory, and its functions can be called and executed by a processing element. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0186] Indicatively, such as Figure 9 As shown, Figure 9 This is a schematic diagram of the internal structure of a computer device 300 provided in an embodiment of this application. The computer device 300 can be provided as a server. (Refer to...) Figure 9 The computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by memory 301 for storing instructions, such as application programs, that can be executed by the processing component 302. The application programs stored in memory 301 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 302 is configured to execute instructions to perform the methods of any of the embodiments described above.

[0187] The computer device 300 may also include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate on an operating system stored in memory 301, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0188] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0189] This application provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the method provided in any embodiment.

[0190] Finally, it should be noted that in this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0191] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0192] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of intelligent meter reading, characterized by, include: The target power data is obtained through a carrier meter, and in response to the meter reading command, the target power data is transmitted to the concentrator using low-voltage narrowband power line carrier communication. The concentrator forwards the target power data to the target terminal. The target power data is transmitted to the metering master station via wireless communication through the target terminal. The target power data is stored and analyzed through the metering master station. Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

2. The method of claim 1, wherein, The target terminal includes a slave device and a host device connected to the slave device via a low-voltage power line; The step of forwarding the target power data to the target terminal through the concentrator includes: The target power data is forwarded to the target terminal via the concentrator using wired communication. The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes: The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication. The target power data is transmitted to the metering master station via wireless communication through the host device.

3. The method of claim 1, wherein, The routing table includes a multi-level tree structure, and the root node of the routing table is used to indicate the concentrator, while the child nodes of the routing table are used to indicate each of the carrier meters.

4. The method according to claim 3, characterized in that, The routing table is generated based on a dynamic routing algorithm and specifically includes: The concentrator sends a direct meter reading command to all the carrier meters and records the address of the first meter that responds successfully as a relay node. The relay nodes forward instructions to all carrier meters that have not responded, and record the address and response time of the second meter that successfully responded. If there are multiple transmission paths for the same carrier meter, the path with the shortest response time is selected and written into the routing table. The instruction forwarding process is executed iteratively until the relay paths for all the aforementioned carrier meters are generated.

5. The method according to claim 3, characterized in that, If the target power data transmission corresponding to any of the carrier meters fails, the routing table is updated in real time, and the transmission process of the target power data is executed according to the updated routing table. The real-time update methods for the routing table include: For the failed carrier meter, perform a direct reading retry, and for the carrier meter that still fails after the direct reading retry, sequentially enable the relay node for relay retry; If the direct copy retry or the relay retry is successful, the corresponding path is updated in the routing table. If the relay retry fails for a preset number of consecutive times, a health check of the relay node is triggered to determine the hardware operation status of the corresponding carrier meter.

6. The method according to any one of claims 3-5, characterized in that, During the process of establishing the routing table, the method further includes: Establish a two-state transition model for each of the aforementioned carrier meters and determine the state transition probability parameters; The state transition probability parameters include a first holding probability value for maintaining a good state, a first transition probability value for changing from a good state to a fault state, a second holding probability value for maintaining a fault state, and a second transition probability value for changing from a fault state to a good state. If the first transfer probability value is greater than the risk threshold, the corresponding node is marked as a high-risk node, and the high-risk node is removed from the routing table. The preset backup relay node in the routing table is then used to fill the path gap. Furthermore, when the first transfer probability value is lower than the recovery threshold for multiple consecutive periods, the high-risk node is reactivated in the routing table.

7. A smart meter reading device, characterized in that, include: The acquisition module is used to acquire target power data through a carrier meter, and, in response to a meter reading command, transmit the target power data to the concentrator using a low-voltage narrowband power line carrier communication method. A communication module is used to forward the target power data to the target terminal via the concentrator; The communication module is also used to send the target power data to the metering master station via the target terminal in a wireless communication manner; The processing module is used to perform data storage and data analysis of the target power data through the metering master station; Specifically, during the process of the carrier meter transmitting the target power data to the concentrator using low-voltage narrowband power line carrier communication, the transmission direction of the target power data is determined based on the routing table.

8. The apparatus according to claim 7, characterized in that, The target terminal includes a slave device and a host device connected to the slave device via a low-voltage power line; The specific method by which the communication module forwards the target power data to the target terminal through the concentrator includes: The target power data is forwarded to the target terminal via the concentrator using wired communication. The step of transmitting the target power data to the metering master station via wireless communication through the target terminal includes: The target power data is transmitted to the host device via the slave device using low-voltage narrowband power line carrier communication. The target power data is transmitted to the metering master station via wireless communication through the host device.

9. A computer device, characterized in that, The method includes one or more processors and a memory storing computer-readable instructions that, when executed by the one or more processors, perform the steps of the method as described in any one of claims 1-6.

10. A storage medium, characterized in that, The storage medium stores computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the method as described in any one of claims 1-6.

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