CN-122027546-A - Intelligent path planning method and system for water meter communication

CN122027546ACN 122027546 ACN122027546 ACN 122027546ACN-122027546-A

Abstract

A water meter communication intelligent path planning method and system comprises the steps of 1) periodically collecting operation state information of intelligent water meter terminal nodes, reporting the operation state information to a cloud route calculation server through an edge data convergence gateway, wherein the operation state information comprises a battery voltage value and neighbor link signal strength, 2) maintaining a full-network topology view according to the operation state information, constructing a composite risk cost model according to electrochemical characteristics of a battery, calculating a global optimal path, generating a next hop strategy table, 3) sending the next hop strategy table to corresponding intelligent water meter terminal nodes through the edge data convergence gateway, receiving and storing the next hop strategy table by the intelligent water meter terminal nodes, executing data forwarding according to the next hop strategy table, and 4) triggering a residual gradient-based blind survival mechanism by the intelligent water meter terminal nodes to conduct network self-healing when judging that a link fails.

Inventors

MENG FANYU
ZHOU LI
FU MINGLEI
ZHONG TIANYU
SONG DONGPAN
ZHENG JIANFENG

Assignees

杭州莱宸科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260227

Claims (10)

1. The intelligent path planning method for water meter communication is characterized by comprising the following steps: S1, periodically acquiring operation state information of an intelligent water meter terminal node, and reporting the operation state information to a cloud route calculation server through an edge data convergence gateway, wherein the operation state information comprises a battery voltage value and neighbor link signal intensity; S2, maintaining a full-network topological view according to running state information, and constructing a composite risk cost model by combining electrochemical characteristics of a battery, wherein a single-hop composite cost of a node i for transmitting data to a neighbor node j is defined, the voltage change rate of the neighbor node j is calculated according to a historical state sequence, and when a voltage drop inflection point or the voltage change rate exceeding a preset safety slope is monitored, the neighbor node j is judged to enter an energy snow collapse period to trigger nonlinear punishment cost to generate routing impedance approaching infinity; s3, the next-hop strategy table is issued to the corresponding intelligent water meter terminal node through an edge data convergence gateway, the intelligent water meter terminal node receives and stores the next-hop strategy table, and data forwarding is executed according to the next-hop strategy table; and S4, when judging that the link fails, triggering a residual gradient-based blind survival mechanism by the intelligent water meter terminal node to perform network self-healing.
2. The intelligent path planning method for water meter communication according to claim 1, wherein the process of collecting and reporting the running state information in step S1 is as follows: S11, the terminal node of the intelligent water meter reads the current battery voltage value and carries out discretization quantization processing on the voltage value; S12, packaging quantized voltage data, a current visible neighbor node list and signal strength indication RSSI of each neighbor link in a heartbeat packet; and S13, sending the packaged heartbeat packet to a cloud route calculation server through an edge data convergence gateway, so that the cloud route calculation server can update the historical state sequence of the node and calculate the voltage change rate.
3. The method for intelligent path planning for water meter communication according to claim 1, wherein the construction process of the composite risk cost model in step S2 is as follows: S21, defining a communication quality cost model of transmitting data from the node i to the neighbor node j, wherein the model reflects the channel quality of a physical link, and calculating by adopting a normalized Received Signal Strength Indication (RSSI) value, and the normalization processing considers the measured signal strength, the theoretical maximum signal strength and the receiving sensitivity threshold; S22, introducing double constraint of static voltage potential energy and dynamic change slope, and defining a nonlinear electrochemical penalty cost model of a neighbor node j, wherein the static risk is determined based on a difference value between the nominal voltage of the battery and the current voltage, and the dynamic risk is determined based on comparison of the voltage change rate and a preset safety voltage change rate threshold; S23, when the voltage of the neighbor node j is in a linear discharge area, the cost is linearly increased, and when the voltage drop inflection point or the voltage change rate is monitored to exceed a preset safety slope, the neighbor node j is judged to enter an energy snow collapse period, the nonlinear electrochemical punishment cost is triggered, and the routing impedance approaching infinity is generated; S24, constructing a single-hop composite cost model for transmitting data from the node i to the neighbor node j, wherein the cost model is weighted by communication quality cost and nonlinear electrochemical penalty cost.
4. The intelligent path planning method for water meter communication according to claim 3, wherein the calculation expression of the single-hop composite cost model is as follows: (1) In the middle of And The communication weight and the energy consumption weight are respectively; calculating based on the normalized RSSI value for communication quality cost; for the nonlinear electrochemical penalty, its calculation considers the static voltage potential and the dynamic change slope.
5. The intelligent path planning method for water meter communication according to claim 1, wherein the calculating the global optimal path in step S2 adopts a value iterative algorithm, and the method comprises: S25, calculating an energy collapse risk coefficient of the node, and defining a dynamic path attenuation factor pointing to the neighbor node j based on the risk coefficient ; And S26, executing a Belman iteration equation, and updating the minimum accumulated cost of the node i reaching the gateway.
6. The method for intelligent path planning for water meter communication according to claim 1, wherein the storing operation of the next hop policy table by the intelligent water meter terminal node in step S3 comprises: s31, writing a next-hop target address into a routing table in the RAM, and using the routing table for table lookup forwarding of conventional service data; S32, backing up the next-hop target address to a gradient locking area in Flash at the same time, and providing residual gradient guidance when the link fails.
7. The method for intelligent path planning for water meter communication according to claim 1, wherein step S4 comprises: S4-1, when an intelligent water meter terminal node detects a link failure, locking a failure next-hop address as residual gradient guide, and generating and transmitting a special beacon frame containing an SOS identifier with maximum power; and S4-2, after receiving the SOS beacon, the neighbor node forwards the SOS beacon to the cloud, and the cloud route calculation server identifies the island node and triggers local area value iteration, and the optimal path is recalculated to complete network self-healing.
8. The intelligent path planning method for water meter communication according to claim 7, wherein the procedure of the residual gradient-based blind survival mechanism in step S4-1 is as follows: S41, when the number of continuous retransmission failure times of the intelligent water meter terminal node to the next hop reaches a preset threshold, judging that a link fails and entering a blind survival mode; s42, locking a failure next-hop address of the local cache as residual gradient guidance, and determining a sending direction; s43, generating a special beacon frame which does not have traffic load and only contains SOS identification; And S44, disabling an ACK waiting mechanism, breaking the conventional power control limit, and transmitting the special beacon frame with the physical maximum power allowed by hardware.
9. The intelligent path planning method for water meter communication according to claim 7, wherein the network self-healing process in step S4-2 is as follows: s45, after receiving a special beacon frame with an SOS (sequence of event) identifier, a neighbor node in a physical communication range forcibly encapsulates the beacon frame in an uplink message and forwards the uplink message to a cloud routing computation server; And S46, the cloud route calculation server identifies island nodes, sets the weight of the corresponding topological edge to infinity, triggers local area value iteration, calculates a new optimal path and transmits the new optimal path to the intelligent water meter terminal node through the edge data convergence gateway.
10. The intelligent water meter communication path planning system is characterized by comprising an intelligent water meter terminal node, an edge data convergence gateway and a cloud route calculation server which are in communication connection, and the intelligent water meter communication path planning system is used for realizing the intelligent water meter communication path planning method according to any one of claims 1-9.

Description

Intelligent path planning method and system for water meter communication Technical Field The invention relates to the technical field of Internet of things communication and intelligent meter reading, in particular to a water meter communication intelligent path planning method and system based on global value iteration and based on end cloud cooperation aiming at a wireless sensor network with limited energy and limited computing resources. Background With the deep advancement of smart city infrastructure construction, intelligent water service systems based on large-scale wireless sensor networks have become a core component of city water supply management. Such systems are typically comprised of mass distributed intelligent water meter terminals that are often deployed in underground wells, deep corridors, or remote network nodes, with complex environments and severe signal shielding. The intelligent water meter is generally battery powered and requires maintenance-free lifecycles of up to several years, subject to installation conditions. Therefore, how to balance extremely limited hardware resources with severe communication reliability is a critical technical problem to be solved in the field. Although wireless ad hoc network technology is relatively mature, in the specific application scenario of intelligent water meter, the existing routing protocol still faces serious challenges, mainly in the following two aspects: First, conventional routing metrics lack awareness of the electrochemical characteristics of the cell. When the existing routing protocol performs path selection, the existing routing protocol generally only uses the "percentage of the residual electric quantity" or the "absolute value of the voltage" as a weight reference, and adopts a linear weighting mode to perform energy consumption equalization. However, the lithium-ion batteries widely used in smart water meters have extremely flat discharge curve characteristics (i.e., the voltage remains stable over 90% of the life cycle), with a "cliff" drop in voltage only at the end of life. The traditional linear routing algorithm cannot identify the nonlinear electrochemical characteristics, is often misled by the virtual high voltage value, and continues to allocate heavy data forwarding tasks to nodes at the edge of the avalanche period. This directly results in the critical junction node being pulled down momentarily below the turn-off threshold without warning, and "sudden node death" occurs. The sudden failure not only can cause the loss of the traffic data, but also can cause the chain fracture of the network topology, thereby forming a communication island which is difficult to repair. Second, traditional repair mechanisms based on handshake acknowledgements are prone to "communication deadlocks" in extreme environments. In complex environments such as underground well rooms, wireless links often face multipath effects and deep fading caused by abrupt environmental changes (e.g., well lid shielding, rain water soaking). Existing route maintenance mechanisms typically rely on a two-way handshake (e.g., RTS/CTS, hello/ACK) to confirm link validity or trigger route repair. However, when the link is in an dying state or there is severe asymmetry (e.g., the downlink is completely broken and the uplink is only weak), the end node often cannot receive an acknowledgement frame (ACK) of the gateway. At this time, the terminal following the standard protocol falls into an infinite number of "retransmission-waiting-timeout" cycles, so that not only the effective route update cannot be triggered, but also the only stored electric quantity is rapidly exhausted due to high-power retransmission, so that the node is thoroughly disconnected due to the rigidness of the protocol logic under the condition that the physical communication path is still theoretically provided, namely, falls into a "communication deadlock" state. In addition, existing intelligent routing schemes often attempt to introduce complex predictive algorithms at the terminal side to solve the above problems, but this creates an irreconcilable conflict with the extremely low hardware configuration of the water meter terminal. The terminal is difficult to bear complex battery trend analysis or global topology calculation, so that a high-end algorithm is difficult to land. In view of the above, an innovative route optimization architecture is needed, which can combine deep analysis of electrochemical characteristics of a battery with an escape communication mechanism in an extreme environment, and fundamentally solve the problems of sudden death of nodes and communication deadlock while breaking the limit of terminal calculation. Disclosure of Invention Aiming at the technical bottlenecks of uneven energy consumption distribution, limited terminal computing resources, poor dynamic route stability and the like existing in the complex environment of the existing intelligent water mete