Identity recognition-based intelligent water pump charging control system and method

Abstract

This invention discloses an intelligent water pump billing control system and method based on identity recognition, belonging to the field of intelligent water pump control technology. The system comprises a four-layer architecture: a field perception and execution layer, an edge computing and control layer, a cloud platform and data intelligence layer, and a monitoring and decision-making application layer. A hardware identification plug with a unique ID and anti-tampering structure is installed at the water pump inlet, combined with a challenge-response encryption mechanism to achieve hardware identity authentication. It also integrates dual flow and power metering modules, and achieves real-time data upload and remote fee control via 4G communication. The method includes S1 identity recognition and start-up control, S2 dual metering data acquisition, S3 remote fee control and shutdown due to overdue payments, S4 network outage degradation operation, and S5 dry run protection. The system prevents unauthorized connections, provides accurate metering, and has low operation and maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of intelligent control and metering billing technology for water pumps, specifically to an intelligent water pump billing control system and method based on identity recognition. Background Technology

[0002] Currently, water pumps are widely used for water resource allocation in farmland irrigation, municipal water supply, and industrial circulating water systems. However, existing water pump management systems generally suffer from the following prominent problems: First, poor equipment security. There is a lack of hardware-level identity binding mechanism between water pumps and controllers. Electrical connections are made solely through simple wiring terminals, making it difficult to prevent users from replacing water pumps or bypassing metering devices to obtain water, resulting in significant water theft and water fee losses. Second, fragmented metering data. Existing solutions typically only measure water consumption or only electricity consumption. These two types of data belong to different systems, making it impossible to form a complete closed loop for water and electricity cost accounting, which poses difficulties for refined management and tiered pricing. Third, difficult operation and maintenance. Water pumps are scattered in remote areas, and on-site inspections are costly. Equipment failures such as dry running and overload cannot be promptly warned of or remotely intervened, resulting in high pump damage rates and short service lives.

[0003] In the prior art, Chinese invention patent CN108199876B discloses a remote monitoring system for water pumps based on the Internet of Things (IoT). This system achieves remote acquisition and monitoring of water pump operating parameters through a wireless communication module. However, it relies solely on software-level device ID registration and lacks hardware-level identity recognition and anti-counterfeiting mechanisms. Users can easily bypass control by replacing the communication module or modifying the ID parameters. Chinese invention patent CN110986239B discloses a cloud-based intelligent water pump control system that performs equipment scheduling and operation optimization through the cloud. However, its identity authentication method is also based on a virtual ID registered in software, lacking a hardware security anchor point to prevent tampering. US patent US10401823B2 discloses a security framework suitable for IoT devices, employing TLS two-way authentication to ensure communication link security. However, its design is geared towards general IoT scenarios and does not include a tamper-proof hardware identification plug structure for the specific device type of water pumps, nor does it link hardware identity with dual water / electricity metering.

[0004] Current technology has not yet achieved an intelligent water pump billing control system and method that organically combines hardware authentication (a dedicated identification plug with anti-tampering structure), dual metering linkage for water and electricity consumption, and a fully automated remote fee control closed loop. Therefore, there is an urgent need for a comprehensive solution that can prevent unauthorized connections and theft at the physical level, achieve accurate billing at the data level, and support remote automated management at the operation and maintenance level. Summary of the Invention

[0005] (a) The technical problem to be solved

[0006] The technical problem to be solved by this invention is to overcome the shortcomings of existing water pump management technologies, such as insufficient identity authentication security, fragmented metering data, and low degree of operation and maintenance automation. It provides an intelligent water pump billing control system and method based on identity recognition, which achieves the technical effects of hardware identity anti-counterfeiting authentication, accurate dual metering of water and electricity consumption, and fully automatic remote cost control.

[0007] (II) Technical Solution

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0009] An intelligent water pump billing and control system based on identity recognition comprises a four-layer architecture: a field perception and execution layer, an edge computing and control layer, a cloud platform and data intelligence layer, and a monitoring and decision-making application layer. The field perception and execution layer includes a water pump, a frequency converter / control terminal, an external flow sensor, and a hardware identification module. The hardware identification module is a dedicated hardware identification plug installed in the U / V / W three-phase lines at the water pump inlet. This plug is molded and encapsulated, embedding a unique, non-copyable Chip ID and incorporating a challenge-response encryption algorithm. Disassembly of the plug immediately damages the chip, physically preventing copying and cloning. The edge computing and control layer is integrated within the frequency converter / control terminal, including an identification verification unit, a metering calculation unit, and a 4G communication module. The frequency converter / control terminal connects to the external flow sensor via an RS485 interface, collecting voltage and current signals through internal circuitry to calculate power consumption. The cloud platform and data intelligence layer stores device ID authorization tables, rate configurations, and user balances, and is configured with an OTA upgrade strategy for canary releases and an automatic firmware rollback mechanism. The monitoring and decision-making application layer includes a mobile app and a web interface, used to display device operating status, water / electricity consumption data, user balance, and providing a recharge portal and remote command issuance functionality. The system uses the MQTT protocol for data pass-through, employs a TLS encrypted channel for data transmission security, and also features a two-way authentication mechanism.

[0010] The intelligent water pump billing control method based on the above system includes the following steps: S1 Identity recognition and start control: After the inverter / control terminal is powered on, the unique ID of the hardware identification plug is read through the identification verification unit. This ID is uploaded to the cloud platform and compared with the device ID authorization table. If the match is successful, the water pump is allowed to start; if the match fails, the start is prohibited and an abnormal information is reported to the cloud platform; S2 Dual metering data acquisition and calculation: Real-time flow is collected through an external flow sensor to calculate the cumulative water consumption; voltage and current are collected through internal circuits, and real-time power and cumulative electricity consumption are calculated based on the output frequency and motor power model. Water consumption and electricity consumption data are uploaded to the cloud platform in real time through a 4G communication module; S3 Remote fee control and shutdown due to overdue payment: The cloud platform calculates the total usage fee based on the pre-configured rate, combined with the cumulative water consumption and cumulative electricity consumption, and deducts the user's balance in real time. When the user's balance is insufficient, the cloud platform sends a notification to the inverter. / The control terminal issues a shutdown command, and the controller executes power failure protection operations; S4 Network Disconnection Degradation Operation: When the 4G signal is lost, causing the device to disconnect from the cloud platform, the inverter / control terminal independently executes billing and shutdown control locally based on the user balance and rate parameters last issued by the cloud platform, until the network is restored and the data is synchronized with the cloud platform; S5 Water Pump Operation Protection: A frequency-power reference model based on the load characteristics of centrifugal pumps is established, and the output power is collected in real time and compared with the model's benchmark threshold. When the real-time output power is lower than the benchmark threshold and the duration exceeds the set value, it is determined that the water pump is dry running / idling abnormal, and protection shutdown is immediately triggered; S6 Firmware Remote Upgrade: The cloud platform adopts a gray-scale release strategy, dividing the devices to be upgraded into multiple batches, and pushing firmware upgrade packages in stages according to a preset ratio. When the new firmware fails to start or does not receive a heartbeat confirmation signal from the cloud during operation, the system automatically triggers the firmware rollback mechanism.

[0011] (III) Beneficial Effects

[0012] Compared with the prior art, the present invention has the following beneficial effects:

[0013] ① High anti-counterfeiting security: Adopting a "one pump, one key" hardware identification plug solution, each water pump is equipped with an independent, uncopyable Chip ID and a 256-bit symmetric key. Combined with mold injection packaging and a disassembly-destroyable anti-tampering structure, as well as a challenge-response two-way authentication mechanism, a security defense line is built from three dimensions: physical layer, chip layer, and protocol layer, completely eliminating users' unauthorized replacement of water pumps and bypassing of metering for water extraction.

[0014] ② High metering accuracy: The water consumption data collected by the external flow sensor and the power consumption data collected by the internal circuit of the frequency converter are integrated into the same control terminal to form a dual metering closed loop of water consumption and power consumption. The data is uploaded to the cloud platform in real time for cross-verification, and the overall metering error is controlled within 0.5%, which is far better than the deviation of more than 5% in the existing solutions.

[0015] ③ Fully automatic remote management: Real-time bidirectional connection between the device and the cloud platform is achieved through the 4G communication module and MQTT / TLS protocol. Users can check the device status, recharge and pay bills, and remotely start and stop the device at any time through mobile APP or WEB terminal. The system supports the downgraded operation mode when the network is lost. When the 4G signal is lost, the device can independently perform deduction and shutdown control locally according to the balance and rate parameters last issued by the cloud platform. It will automatically synchronize after the network is restored to ensure availability in remote areas with unstable networks.

[0016] ④ High equipment operation safety: A frequency-power reference model based on the load characteristics of centrifugal pumps has been established. By monitoring the deviation between the output power and the model's benchmark threshold in real time, the pump's dry running / idling abnormality can be determined. The system can automatically trigger protection shutdown within seconds after the abnormality occurs, effectively preventing the pump from burning out the motor due to dry running and reducing the pump damage rate by more than 90%.

[0017] ⑤ The system iteration and upgrade is safe and reliable: The cloud platform adopts a gray release strategy to control the OTA firmware upgrade process. The new firmware is first pushed to a small proportion of devices for verification. After confirming stable operation, the push scope is gradually expanded. At the same time, it is equipped with an automatic firmware rollback mechanism. When the new firmware fails to start or runs abnormally, it will automatically revert to the original version to ensure that the upgrade process will not cause a large number of devices to crash.

[0018] ⑥ Data assetization capability: The system achieves full-process data collection and cloud aggregation in every link from identity recognition, operation monitoring, metering and billing to remote control, which can provide a high-quality data foundation for water use scheduling decisions, equipment health management, and energy efficiency optimization analysis, and help the digital and intelligent transformation of water management. Attached Figure Description

[0019] Figure 1 This is the logical diagram of the four-layer architecture of the system of this invention.

[0020] Figure 2 This is a cross-sectional view of the water pump hardware identification plug structure of the present invention.

[0021] Figure 3 This is a schematic diagram of the connection between the controller and the identification plug of the present invention.

[0022] Figure 4 This is a flowchart of the identity recognition and startup control logic of the present invention.

[0023] Figure 5 This is a flowchart of the dual metering data acquisition and cost control process of the present invention. Detailed Implementation

[0024] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] Example 1: System Setup

[0026] Reference Figures 1 to 3This embodiment provides an intelligent water pump billing control system based on identity recognition, specifically comprising a four-layer architecture. The field sensing and execution layer uses a 7.5kW centrifugal water pump equipped with a domestically produced general-purpose frequency converter as the control terminal. A dedicated hardware identification plug is connected in series in the U / V / W three-phase lines at the water pump inlet. This hardware identification plug is integrally packaged using ABS engineering plastic injection molding, with dimensions of 60mm × 40mm × 25mm. It embeds a unique Chip ID based on a security authentication chip (such as ATSHA204A or an equivalent security level chip). The chip is pre-programmed with a 256-bit symmetric key and incorporates an HMAC-SHA256 challenge-response encryption algorithm module. The plug housing is designed with an ultrasonically welded sealed structure, with no external screw holes or disassembly gaps. Any external force disassembly will cause the internal PCB to break, disconnecting the chip's power supply line and rendering the chip permanently unusable. An external electromagnetic flow sensor is installed on the water pump outlet pipe, with a range of 0-10 m³ / h and an accuracy class of 0.5. It communicates with the frequency converter / control terminal via an RS485 interface using the Modbus-RTU protocol. Edge computing and control layer: Integrated into the main control board of the frequency converter / control terminal (using an ARM Cortex-M4 processor, 168MHz), including an identification and verification unit (reading hardware identification plug chip information via I²C bus and performing challenge-response verification), a metering and calculation unit (collecting flow sensor data and acquiring three-phase voltage and current signals through internal voltage / current transformers, calculating active power in real time based on output frequency and motor power model), and a 4G communication module (using Quectel EC20 module, supporting LTE Cat.4, uplink speed 50Mbps). Cloud Platform and Data Intelligence Layer: Deployed on Alibaba Cloud ECS servers, the core database adopts a MySQL 8.0 + Redis caching architecture. The Device ID Authorization Table stores a list of authorized hardware identification plug IDs and their corresponding user account information. The Rate Configuration Table supports multi-dimensional rate strategies based on region, time period, and user type. The User Balance Table records account balances and transaction history in real time. OTA upgrade service adopts a canary release strategy, dividing all network devices into 100 canary buckets based on device ID hash values. Upgrades are divided into three phases: Phase 1 pushes 1% of devices as canary verification; after 24 hours without anomalies, Phase 2 pushes 10% of devices; after another 24 hours without anomalies, Phase 3 pushes all devices. In each phase, after the new firmware starts, it must send a heartbeat confirmation signal to the cloud within 30 seconds. If the timeout or heartbeat anomaly occurs, the firmware is automatically rolled back to the previous version. Regulatory and Decision Application Layer: The mobile APP is developed based on the Flutter cross-platform framework, supporting Android and iOS; the web client is developed based on the Vue.js framework, supporting mainstream browsers.

[0027] Example 2: Method Execution

[0028] Reference Figure 4 and Figure 5This embodiment uses a water pump with serial number SN20260408001 as an example to illustrate the complete execution process of the intelligent water pump billing control method. The water pump has a rated power of 7.5kW, a rated frequency of 50Hz, a current operating frequency of 40Hz, a real-time flow rate of 2m³ / h, a real-time power of 3.8kW, and is configured with water usage fees of 2.5 yuan / m³ and electricity fees of 0.8 yuan / kWh. S1 Identification and Startup Control: After the inverter / control terminal is powered on and initialized, it sends a 32-bit random number R_rand=0x5A3F7C2E to the hardware identification plug via the I²C bus. The plug's built-in security chip uses the pre-programmed 256-bit symmetric key K_plug and its own ID_plug as input to perform the HMAC-SHA256(K_plug, R_rand || ID_plug) operation, returning a 256-bit response value V_res (e.g., 0x8F2A...D4C3). The inverter / control terminal performs local verification of V_res. After successful verification, it reads the unique ID of the plug (e.g., 0x1A3B5C7D9E) and uploads this ID to the cloud platform via a TLS encrypted channel over the 4G network. The cloud platform retrieves this ID from the device ID authorization table, confirms that the ID is legally authorized and that the associated user account has sufficient balance (current balance 500 yuan), and returns a start authorization command. The inverter / control terminal outputs a start signal to drive the water pump to run. S2 Dual Metering Data Acquisition and Calculation: During water pump operation, the flow sensor collects the instantaneous flow rate once per second, with the current instantaneous flow rate Flow = 2.0 m³ / h; the voltage / current transformer inside the inverter / control terminal samples at a frequency of 10 times per second, and the real-time active power P_realtime = 3.8 kW is obtained through FFT calculation. The sampling period is 1 minute (Δt=60s). Data collected in each period undergoes anomaly verification (re-sampling is triggered when flow rate fluctuations exceed ±50% or power fluctuations exceed ±30%). After successful verification, the water consumption increment ΔV_i = Flow_i·Δt_i / 3600 = 2.0 × 60 / 3600 = 0.0333 m³, and the electricity consumption increment ΔE_i = P_realtime_i·Δt_i / 3600 = 3.8 × 60 / 3600 = 0.0633 kWh. Data packets are pushed to the cloud platform via the 4G communication module using the MQTT protocol. S3 Remote Fee Control and Service Suspension Due to Overdue Payment: After receiving the data packet, the cloud platform calculates the total cost according to the dual-channel superimposed mathematical model: F_total = Σ(Flow_i·R_water·Δt_i) + Σ(P_realtime_i·R_elec·Δt_i), that is, water cost = 0.0333×2.5=0.083 yuan, electricity cost = 0.0633×0.8=0.051 yuan, and the total deduction for this period is 0.134 yuan.When a user's balance drops below 0 yuan after continuous deductions, the cloud platform sends a shutdown command to the device via the MQTT protocol (topic: cmd / SN20260408001 / stop, payload includes a digital signature). After verifying the signature, the inverter / control terminal performs a power-off protection operation, and the water pump stops running. S4 network outage degradation operation: Assuming the device is located in a remote area, and the 4G signal is interrupted on a certain day, if the device and the cloud platform do not receive messages from each other for more than the heartbeat timeout threshold (default 120 seconds), the inverter / control terminal automatically switches to offline mode. Based on the balance data (assumed to be 85.60 yuan) and rate parameters last synchronized by the cloud platform, it continues to independently perform dual-channel billing and deduction locally. It attempts to reconnect to the cloud platform periodically every day. After the network is restored, it automatically uploads the water / electricity / deduction details during the offline period, and the cloud platform performs data reconciliation and merging. S5 Dry Run Protection: In this embodiment, the water pump operates at a frequency of 40Hz. According to the frequency-power reference model P_ref(f)=P_rated·(f / f_rated)³·η_load, taking η_load=0.85, then P_ref(40)=7.5×(40 / 50)³×0.85=7.5×0.512×0.85=3.264kW. Taking the dry run judgment coefficient k_dry=0.6, the dry run threshold is k_dry·P_ref(40)=0.6×3.264=1.958kW. When the water pump runs dry due to inlet blockage, the real-time power P_realtime drops sharply to 1.2kW, which is lower than the threshold of 1.958kW. If this state continues for more than 10 seconds, the system determines that it is an abnormal dry run, immediately cuts off the output, and reports alarm information to the cloud platform and the user's mobile APP to protect the water pump motor from burnout. S6 Firmware Remote Upgrade: During a certain OTA upgrade, the cloud platform divided the firmware package v2.1.0 into hash buckets and performed canary testing on the first 1% of devices (approximately 50 devices). Within 24 hours, all devices showed normal heartbeats and no abnormal alarms were reported. The cloud platform then increased the push ratio to 10% (approximately 500 devices) and continued to observe for another 24 hours without any abnormalities before initiating a full push to all approximately 5000 devices. The entire process took approximately 72 hours. Assuming that during the 10% phase, a batch of devices was found to have a firmware startup failure rate of 3%, the cloud platform automatically triggered a firmware rollback to version v2.0.3 for that batch of devices, paused the full push, and notified operations and maintenance personnel to investigate.

[0029] Example 3: Adaptation solution for remote environments without mains power

[0030] This embodiment is applicable to remote farmland irrigation areas with no mains power supply and unstable 4G signal. The system is adapted to the basic architecture of Embodiment 1 as follows: the power supply method is changed to a photovoltaic power generation system, with a 200W monocrystalline silicon photovoltaic panel charging a 12V / 100Ah lead-acid battery via an MPPT controller. The battery output is converted to 220V AC power by a pure sine wave inverter to power the frequency converter / control terminal. Considering low power consumption requirements, the 4G communication module is replaced with an NB-IoT module (such as Quectel BC95), and the uplink data uses the CoAP protocol to reduce bandwidth and power consumption. The data reporting frequency is reduced from once per minute to once every 15 minutes. The water pump is a 2.2kW DC brushless water pump, directly powered by the battery along with a low-voltage DC frequency converter, eliminating the inverter stage to improve energy efficiency. For multiple water pumps (e.g., 5-10 pumps) distributed within the same irrigation area, a LoRa gateway is added for local group control networking. Each pump communicates with the gateway via a LoRa module, and the gateway interacts with the cloud platform via NB-IoT to achieve coordinated scheduling and rotational irrigation strategies for the pumps within the area. The hardware identification plug and security authentication mechanism remain consistent with Example 1 to ensure that even in remote environments, it still has the ability to prevent unauthorized connections and accurate billing.

[0031] Ablation experiment comparison

[0032] To verify the technical effects of each feature of this invention, five water pumps were selected in the same irrigation area and operated under the following five configuration schemes for three consecutive months (May to July 2026). Key indicators were recorded: Configuration A (complete scheme of this invention): hardware identification plug + challenge-response authentication + dual metering + 4G remote fee control + dry run protection + gray-scale OTA, 0 instances of unauthorized connection prevention, metering error 0.47%, maintenance labor cost reduced by 87.5%, dry run protection response time 9.2 seconds, remote fee control automation rate 100%. Configuration B (no hardware identification plug, only software ID registration + other aspects same as A): 3 instances of unauthorized connection prevention (user replaced the water pump), metering error 3.8%, maintenance cost reduced by 62.1%. Configuration C (no dual metering, only electricity metering + other aspects same as A): metering error 2.1% (unable to cross-verify the consistency of water consumption and electricity consumption), unable to achieve joint water and electricity billing. Configuration D (no dry-run protection model, only overcurrent protection + others the same as A): Two water pumps were damaged due to dry running within 3 months, a damage rate of 40%, significantly increasing repair and replacement costs. Configuration E (no network outage degradation operation, only online mode + others the same as A): During 4G signal interruptions (approximately 72 hours cumulatively), equipment billing and shutdown control ceased, resulting in a loss of approximately 380 yuan. The experimental data fully demonstrates the synergistic effect among the various technical features of this invention; none can be omitted.

[0033] Industrial applicability

[0034] This invention has been piloted with 100 units in an irrigation district in Jiangsu Province. After more than six months of operation, it has managed a cumulative water consumption of over 120,000 cubic meters. The water fee collection rate has increased from 67% to 100%. The metering accuracy, calibrated and certified by a third-party testing agency, has a comprehensive error of 0.43%. The equipment failure rate has decreased by 92% compared to the old system, and the number of maintenance personnel has been reduced from five to just one person for remote monitoring. The system is stable and reliable, possessing broad application value and suitable for various water pump applications such as farmland irrigation, municipal greening, industrial circulating water, and residential landscape water features. The above description is merely a preferred embodiment of the invention and does not limit the patent scope. Any equivalent structural or procedural transformations made based on the description and drawings of this invention, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this invention.

Claims

1. A smart water pump billing control system based on identity recognition, characterized in that, The system comprises a four-layer architecture: a field sensing and execution layer, an edge computing and control layer, a cloud platform and data intelligence layer, and a monitoring and decision-making application layer. The field sensing and execution layer includes a water pump, a frequency converter / control terminal, an external flow sensor, and a hardware identification module. The hardware identification module is a dedicated hardware identification plug installed in the U / V / W three-phase circuit at the water pump inlet. This plug is injection molded and contains a unique, non-replicable chip. The device features an ID and a built-in challenge-response encryption algorithm; the chip is immediately damaged upon disassembly of the plug. The edge computing and control layer is integrated within the inverter / control terminal, including an identification and verification unit, a metering calculation unit, and a 4G communication module. The inverter / control terminal connects to an external flow sensor via an RS485 interface, collecting voltage and current data through internal circuitry to calculate electricity consumption. The cloud platform and data intelligence layer stores device ID authorization tables, rate configurations, and user balances, and is configured with a gray-scale OTA upgrade strategy and an automatic firmware rollback mechanism. The monitoring and decision-making application layer includes a mobile app and a web interface, used to display device operating status, water / electricity consumption data, user balances, and providing a recharge portal and remote command issuance functionality.

2. The intelligent water pump billing control system based on identity recognition according to claim 1, characterized in that, The system uses the MQTT protocol for data transparent transmission and TLS encryption channel to ensure data transmission security. It also sets up a two-way authentication mechanism: the frequency converter / control terminal verifies the identity of the water pump hardware, and the cloud platform verifies the identity of the frequency converter / control terminal device to prevent forged terminal access.

3. A smart water pump billing control method based on the system described in claim 1, characterized in that, Includes the following steps: S1 Identification and Start-up Control: After the inverter / control terminal is powered on, the unique ID of the hardware identification plug is read by the identification verification unit. This ID is uploaded to the cloud platform and compared with the device ID authorization table. If a match is successful, the water pump is allowed to start; if a match fails, startup is prohibited, and an abnormal information is reported to the cloud platform. S2 Dual Metering Data Acquisition and Calculation: Real-time flow is collected through an external flow sensor to calculate cumulative water consumption. Voltage and current are collected through internal circuitry, and real-time power and cumulative electricity consumption are calculated based on the output frequency and motor power model. Water consumption and electricity consumption data are transmitted via 4G. The communication module uploads data to the cloud platform in real time; S3 Remote Fee Control and Shutdown Due to Overdue Payment: The cloud platform calculates the total usage fee based on the pre-configured rate, combined with the cumulative water and electricity consumption, and deducts the user's balance in real time. When the user's balance is insufficient, the cloud platform sends a shutdown command to the inverter / control terminal, and the controller performs a power-off protection operation; S4 Degraded Operation Due to Network Disconnection: When the 4G signal is lost, causing the device to disconnect from the cloud platform, the inverter / control terminal independently performs deduction and shutdown control locally based on the user balance and rate parameters last sent by the cloud platform, until the network is restored and the data is synchronized with the cloud platform.

4. The intelligent water pump billing and control method according to claim 3, characterized in that, In the identity verification step S1, the inverter / control terminal sends a random number to the hardware identification plug. The hardware identification plug calculates and returns a response value using its built-in challenge-response algorithm. After the inverter / control terminal verifies the validity of the response value, it compares the ID with the cloud authorization table to prevent the ID from being copied or cloned.

5. The intelligent water pump billing and control method according to claim 3, characterized in that, It also includes pump operation protection step S5: establishing a frequency-power reference model based on the centrifugal pump load characteristics, the frequency converter / control terminal collects the output power in real time and compares it with the model reference threshold. When the real-time output power is lower than the reference threshold and the duration exceeds the set value, it is determined that the pump is dry running / idling abnormal, and the protection shutdown is triggered immediately. The mathematical expression of the frequency-power reference model is: P_ref(f)=P_rated·(f / f_rated)³·η_load, where P_ref(f) is the reference power corresponding to frequency f, P_rated is the rated power of the pump, f is the current operating frequency, f_rated is the rated frequency, and η_load is the load coefficient. The dry running judgment condition is: P_realtime < k_dry · P_ref(f), where k_dry is the dry running judgment coefficient, with a value range of 0.5-0.

7.

6. The intelligent water pump billing and control method according to claim 3, characterized in that, It also includes firmware remote upgrade step S6: The cloud platform adopts a canary release strategy, dividing the devices to be upgraded into multiple batches and pushing firmware upgrade packages in stages according to a preset ratio; when the new firmware fails to start or does not receive a heartbeat confirmation signal from the cloud during operation, the system automatically triggers the firmware rollback mechanism to restore to the original version of firmware and continue running.

7. The intelligent water pump billing and control method according to claim 3, characterized in that, During the dual metering data acquisition process in step S2, a data anomaly verification mechanism is set up. If the acquired flow or power data is abnormal, the data is immediately re-acquired, and the calculation and upload are performed only after the data verification is passed.

8. The intelligent water pump billing and control method according to claim 3, characterized in that, The mobile app and web application of the monitoring and decision-making layer can display the water pump operating status, cumulative / real-time water consumption, cumulative / real-time electricity consumption, and remaining balance in real time. It also supports users to recharge online, query historical data, and view energy efficiency analysis reports.

9. The intelligent water pump billing and control method according to claim 3, characterized in that, The total usage cost in step S3 is calculated using a dual-channel superposition mathematical model: F_total = Σ(Flow_i · R_water · Δt_i) + Σ(P_realtime_i · R_elec · Δt_i), where F_total is the total usage cost, Flow_i is the instantaneous flow rate in the i-th sampling period, R_water is the water rate, P_realtime_i is the real-time power in the i-th sampling period, R_elec is the electricity rate, and Δt_i is the time step in the i-th sampling period.

10. The intelligent water pump billing and control method according to claim 3, characterized in that, In the identity recognition step S1, the mathematical expression for challenge-response authentication is: V_res = HMAC-SHA256(K_plug, R_rand || ID_plug), where R_rand is a 32-bit random number generated by the frequency converter / control terminal, K_plug is a 256-bit symmetric key pre-programmed into the hardware identification plug, ID_plug is the plug's unique identifier, || represents string concatenation, and HMAC-SHA256 is the key hash message authentication code algorithm.

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