Solar power supply unattended life water supply control system based on internet of things

Abstract

The application relates to the technical field of intelligent water supply, and particularly discloses a solar power unattended life water supply control system based on the Internet of Things, which comprises a solar photovoltaic power generation module, an energy storage module, an Internet of Things communication module, a sensor group, a control module, an executing mechanism and a remote monitoring platform; the solar photovoltaic power generation module cooperates with the energy storage module to provide working power for the system, thereby getting rid of the dependence on traditional mains; the Internet of Things communication module and the remote monitoring platform realize remote real-time monitoring and control; the control module is embedded with an intelligent water supply strategy algorithm module, thereby realizing intelligent operation and automatic adjustment; the executing mechanism comprises an electric valve, a booster pump and a water hammer eliminator, thereby realizing pipe network pressure adjustment and water hammer elimination; the system adopts redundant design and multi-link backup, thereby guaranteeing high availability. The application can solve the power supply difficulty in remote areas, reduce the artificial inspection cost, and improve the system operation stability and the intelligent level.

Description

Technical Field

[0001] This invention belongs to the field of intelligent water supply technology, specifically relating to an IoT-based solar-powered unattended domestic water supply control system. Background Technology

[0002] The rapid development of IoT technology has brought new opportunities for technological transformation to the field of smart water management. Through the integrated application of sensor networks and wireless communication technologies, remote monitoring and data collection of distributed water facilities have been achieved. Existing smart water management systems typically rely on municipal power grids for power supply, and their communication modules and control equipment require a continuous power supply, thus creating a rigid dependence on stable municipal power infrastructure.

[0003] The power supply problem of off-grid water supply facilities severely restricts the application and promotion of smart water management technology. Because remote mountainous areas or temporary water supply points often lack access to municipal power, traditional solar power systems, while providing some electricity, lack intelligent scheduling capabilities in their energy storage and power management strategies. This leads to a chain reaction of problems, including frequent water supply interruptions and low equipment reliability. Consequently, the system cannot achieve continuous and stable unattended operation, requiring regular manual inspections and on-site intervention, which seriously deviates from the automated management goals of smart water management. As a result, current domestic water supply systems in remote areas generally suffer from insufficient intelligence and high operation and maintenance costs. In these scenarios, water level monitoring data cannot be transmitted in real time, and abnormal operating conditions cannot be promptly alerted, leading to frequent overflows or vacancy failures of high-level water tanks, severely affecting the operational stability and water resource utilization efficiency of the water supply system. This results in the long-term inefficient operation of water supply systems in remote areas, urgently requiring the introduction of an innovative solution that is self-sufficient and intelligently managed. Summary of the Invention

[0004] This application provides an IoT-based solar-powered unattended domestic water supply control system, which aims to overcome or at least partially solve the above-mentioned problems.

[0005] The first aspect of this application provides an Internet of Things-based solar-powered unattended domestic water supply control system, comprising:

[0006] Solar photovoltaic power generation modules are used to collect solar energy and convert light energy into electrical energy to provide power for the entire system;

[0007] The energy storage module is connected to the solar photovoltaic power generation module and is used to store the electrical energy generated by the solar photovoltaic power generation module and supply power to the system when there is insufficient sunlight;

[0008] The IoT communication module establishes data communication links with the solar photovoltaic power generation module, energy storage module, control module, and sensor group respectively, to collect system operating parameters and upload the collected operating parameters to the remote monitoring platform, while receiving control commands issued by the remote monitoring platform.

[0009] The sensor array is installed at key nodes in the domestic water supply system to monitor key parameters such as water level, flow rate, pressure, and equipment status in real time, and uploads the monitoring data through the Internet of Things communication module;

[0010] The control module is connected to the IoT communication module, the energy storage module, and the actuator respectively. Based on the preset water supply strategy and the real-time data collected by the sensor group, the control module issues control commands to the actuator to realize the automatic adjustment and intelligent control of the water supply system.

[0011] The actuators include an electric valve, a booster pump, and a water hammer eliminator. The control module regulates the water flow path by controlling the opening and closing of the electric valve, adjusts the water supply pressure by controlling the operating parameters of the booster pump, and eliminates the water hammer phenomenon in the pipe network by using the water hammer eliminator.

[0012] The remote monitoring platform is set up on a cloud server to receive operational data uploaded by the IoT communication module, perform data storage, analysis and processing, and send control commands or alarm information to the control module.

[0013] In one optional embodiment, the solar photovoltaic power generation module includes a photovoltaic array, a photovoltaic inverter, and a maximum power point tracking controller. The photovoltaic array is installed on the sunny side of an elevated water tank or surrounding area. The maximum power point tracking controller is used to adjust the operating point of the photovoltaic array in real time so that the photovoltaic array always outputs maximum power. The photovoltaic inverter converts the DC power output by the photovoltaic array into AC power to charge the energy storage module and power the actuator.

[0014] In one optional embodiment, the energy storage module uses a lithium iron phosphate battery pack as the energy storage unit. The energy storage module is equipped with a battery management system, which is used to monitor the voltage, current, temperature and state of charge of the battery pack in real time. When the battery pack is overcharged, over-discharged, over-temperatured or short-circuited, the battery management system immediately cuts off the circuit and issues an alarm signal.

[0015] In one optional implementation, the IoT communication module includes a data acquisition unit, a wireless communication unit, and a positioning unit. The data acquisition unit acquires monitoring data from the sensor group through analog input channels and digital input channels. The wireless communication unit transmits the acquired data to a remote monitoring platform using a 4G / 5G mobile network or a LoRa low-power wide area network. The positioning unit obtains the system's geographical location information and attaches the location information to the transmitted data.

[0016] In one optional embodiment, the sensor group includes a water level sensor, a pressure sensor, a flow sensor, and a water quality sensor. The water level sensor is installed in a high-level water tank to monitor the water level and issue an error alarm signal when the water level exceeds a preset upper or lower limit. The pressure sensor is installed at a key node of the pipeline network to monitor the pipeline network pressure and trigger a protection action when the pressure is abnormal. The flow sensor is installed in the water supply pipeline to measure water consumption and detect pipeline leaks. The water quality sensor is installed at the water outlet to monitor water quality parameters such as residual chlorine, turbidity, and pH value.

[0017] In one optional implementation, the control module includes a main controller, a signal conditioning circuit, and a drive circuit. The main controller is an embedded microprocessor or a programmable logic controller. The signal conditioning circuit amplifies, filters, and performs analog-to-digital conversion on the analog signals output by the sensor group. The drive circuit amplifies the control signals from the main controller and drives the actuator to operate.

[0018] In one optional implementation, the control module embeds an intelligent water supply strategy algorithm module. This module automatically generates an optimal water supply scheduling plan based on historical water usage data, current water level, predicted water demand, and peak and off-peak electricity prices. The intelligent water supply strategy algorithm module includes a water demand prediction submodule, a power supply capacity assessment submodule, and an optimization scheduling submodule. The water demand prediction submodule uses machine learning algorithms to predict water consumption in future periods based on historical water usage data. The power supply capacity assessment submodule assesses the power supply capacity of the solar power generation system based on current sunlight conditions, energy storage status, and weather forecast data. The optimization scheduling submodule integrates the water demand prediction results and the power supply capacity assessment results to generate control instructions that meet water supply needs while minimizing energy consumption.

[0019] In one optional implementation, the remote monitoring platform includes a data storage unit, a data analysis unit, an alarm management unit, and a remote control unit. The data storage unit persistently stores the time-series data uploaded by the IoT communication module. The data analysis unit performs statistical analysis on the stored operational data and generates reports. The alarm management unit identifies abnormal events according to preset alarm rules and pushes alarm information via SMS, email, or mobile application. The remote control unit provides a human-machine interface that enables maintenance personnel to remotely view the system status and issue control commands.

[0020] In one optional implementation, the system further includes a local display and operation terminal, which is located near the elevated water tank or pump room. The local display and operation terminal is used to display the system's operating status, parameter configuration, and fault information locally, and provides an on-site operation interface for maintenance personnel to manually intervene.

[0021] In one optional implementation, the system adopts a redundant design, and the control module is equipped with a primary and backup dual-machine switching device. When the primary controller fails, the backup machine automatically switches to the working state to ensure continuous system operation. The IoT communication module supports multi-link backup and automatically switches to the backup communication link when the primary communication link is interrupted.

[0022] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0023] The IoT-based solar-powered unattended domestic water supply control system provided in this application utilizes solar photovoltaic power generation modules to provide green energy for the entire system, eliminating reliance on traditional mains power. This makes it particularly suitable for water supply scenarios in remote areas such as elevated water tanks, effectively solving the problem of power supply difficulties. Through the combination of energy storage modules and maximum power point tracking (MPPT) technology, the system ensures continuous and stable operation even in cloudy or rainy weather or at night, improving energy efficiency. The integration of an IoT communication module and a remote monitoring platform enables remote real-time monitoring and control of the water supply system, allowing maintenance personnel to monitor the system's operating status without on-site visits, significantly reducing manual inspection costs. Furthermore, the intelligent water supply strategy algorithm module embedded in the control module adjusts the system according to water demand. The system automatically generates optimal scheduling schemes based on prediction and power supply capacity assessment, enabling intelligent operation of the water supply system and reducing manual intervention. Real-time monitoring of key parameters such as water level, pressure, flow rate, and water quality via sensor arrays, combined with the anomaly warning function of the alarm management unit, allows for early detection and handling of problems, preventing system paralysis caused by excessive water levels and improving system stability. The coordinated operation of electric valves, booster pumps, and water hammer eliminators in the actuators achieves automatic regulation of pipeline pressure and effective elimination of water hammer, extending the service life of valves, contactors, and other hardware, and reducing maintenance costs. Redundant design and multi-link backup mechanisms ensure high availability of the system in complex environments, enhancing overall reliability. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the overall architecture of the solar-powered unattended domestic water supply control system based on the Internet of Things of this invention;

[0025] Figure 2 This is a schematic diagram of the data acquisition and monitoring framework of the sensor group and the Internet of Things communication module in this invention;

[0026] Figure 3 This is a schematic diagram of the collaborative control framework between the control module and the actuator in this invention;

[0027] Figure 4 This is a schematic diagram of the core principle framework of the intelligent water supply strategy algorithm module in this invention;

[0028] Figure 5 This is a schematic diagram of the multi-functional management framework of the remote monitoring platform in this invention. Detailed Implementation

[0029] 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, 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.

[0030] Reference Figure 1 , Figure 1 This is a schematic diagram of the overall architecture of an IoT-based solar-powered unattended domestic water supply control system proposed in one embodiment of this application. As shown in the figure, the system includes: a solar photovoltaic power generation module, an energy storage module, an IoT communication module, a sensor group, a control module, an actuator, and a remote monitoring platform.

[0031] The solar photovoltaic (PV) power generation module collects solar energy and converts it into electrical energy, providing power for the entire system. The energy storage module, connected to the PV module, stores the electrical energy generated and supplies power when sunlight is insufficient. The IoT communication module establishes data communication links with the PV module, energy storage module, control module, and sensor array. It collects system operating parameters and uploads them to a remote monitoring platform, while also receiving control commands from the platform. The sensor array is located at key nodes in the domestic water supply system to monitor key parameters such as water level, flow rate, pressure, and equipment status in real time, uploading the data via the IoT communication module. The control module, connected to the IoT communication module, energy storage module, and actuators, issues control commands to the actuators based on a preset water supply strategy and real-time data collected by the sensors, enabling automatic adjustment and intelligent control of the water supply system. The actuators include electric valves, booster pumps, and water hammer eliminators. The control module regulates the water flow path by controlling the opening and closing of the electric valves, adjusts the water supply pressure by controlling the operating parameters of the booster pump, and eliminates water hammer in the pipe network through the water hammer eliminator. The remote monitoring platform is located on a cloud server and is used to receive operational data uploaded by the IoT communication module, store, analyze, and process the data, and issue control commands or alarm information to the control module.

[0032] In this embodiment, the IoT-based solar-powered unattended domestic water supply control system provides green energy to the entire system through solar photovoltaic power generation modules, eliminating reliance on traditional mains power. This is particularly suitable for water supply scenarios in remote areas such as elevated water tanks, effectively solving the problem of power supply difficulties. The combination of energy storage modules and maximum power point tracking (MPPT) technology ensures continuous and stable operation of the system even in cloudy or rainy weather or at night, improving energy efficiency. The integration of an IoT communication module and a remote monitoring platform enables remote real-time monitoring and control of the water supply system. Maintenance personnel can monitor the system's operating status without being physically present, significantly reducing manual inspection costs. The intelligent water supply strategy algorithm module embedded in the control module automatically generates the optimal scheduling plan based on water demand prediction and power supply capacity assessment, achieving intelligent operation of the water supply system and reducing manual intervention. Real-time monitoring of key parameters such as water level, pressure, flow rate, and water quality by sensor arrays, combined with the anomaly warning function of the alarm management unit, allows for early detection and handling of problems, preventing system paralysis due to excessive water levels and improving system operational stability. By coordinating the operation of the electric valves, booster pumps, and water hammer eliminators in the actuator, automatic regulation of pipeline pressure and effective elimination of water hammer are achieved, extending the service life of hardware such as valves and contactors and reducing maintenance costs. Redundant design and multi-link backup mechanisms ensure high availability of the system in complex environments, improving overall reliability.

[0033] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system. In this system, the solar photovoltaic power generation module includes a photovoltaic array, a photovoltaic inverter, and a maximum power point tracking controller. The photovoltaic array is set on the sunny side of an elevated water tank or the surrounding area. The maximum power point tracking controller is used to adjust the operating point of the photovoltaic array in real time so that the photovoltaic array always outputs maximum power. The photovoltaic inverter converts the DC power output by the photovoltaic array into AC power to charge the energy storage module and power the actuator.

[0034] In this embodiment, the solar photovoltaic (PV) power generation module is the energy source for the entire system, and its design fully considers the geographical characteristics and sunlight conditions of elevated water tanks or remote areas. The PV array uses monocrystalline silicon PV modules, and the installation angle is optimized according to the local latitude, typically set to the local latitude plus a tilt angle of 15 degrees to obtain the maximum annual irradiance. The installation location of the PV array is preferably the top of the elevated water tank or a sunny slope with no surrounding obstructions, ensuring that the surface of the PV modules is not shaded. The installed capacity of the PV array is calculated based on the system load power and the local peak sunshine hours, and is typically configured according to 1.5 to 2 times the system's average daily power consumption to ensure that the system's operating requirements can still be met under the most unfavorable sunlight conditions.

[0035] In this embodiment, the maximum power point tracking (MPPT) controller is connected between the photovoltaic (PV) array and the PV inverter, employing either the incremental conductance method or the perturbation-observation method to achieve MPPT functionality. In the incremental conductance method, the controller monitors the output current and voltage of the PV array in real time, calculating the conductance derivative dI / dV. When dI / dV equals -I / V, the system operates at the maximum power point. The controller adjusts the duty cycle of the DC-DC converter circuit to ensure the PV array's operating point always follows the MPPT. Under different light intensities, the MPPT controller can complete a new round of MPPT within 100 milliseconds, ensuring the PV array always outputs maximum power. The rated input voltage range of the MPPT controller covers the standard operating voltage of the PV array, typically 600V to 1000V DC, and the rated output power is configured according to load requirements, typically 3kW to 10kW.

[0036] In this embodiment, the photovoltaic inverter converts the DC power output from the photovoltaic array into AC power. The inverter adopts a two-stage topology, including a front-stage DC-DC boost circuit and a rear-stage DC-AC inverter circuit. The front-stage DC-DC boost circuit boosts the wide-range DC voltage output from the photovoltaic array to a stable DC bus voltage, typically 800V DC. The rear-stage DC-AC inverter circuit inverts the DC bus voltage to 220V / 380V AC power, with an output frequency of 50Hz or 60Hz and a pure sine wave waveform with a total harmonic distortion (THD) of less than 3%. The photovoltaic inverter has comprehensive protection functions, including input overvoltage protection, input undervoltage protection, output overcurrent protection, short circuit protection, and overtemperature protection. When the output power of the photovoltaic array exceeds the inverter's rated power, the inverter protects the equipment by limiting the output power; when the output power of the photovoltaic array is lower than the inverter's start-up threshold, the inverter automatically enters standby mode. The conversion efficiency of the photovoltaic inverter is no less than 98% under rated load conditions and no less than 96% under 50% load conditions, ensuring that the loss during the energy conversion process is minimized.

[0037] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system. In this system, the energy storage module uses a lithium iron phosphate battery pack as the energy storage unit. The energy storage module is equipped with a battery management system, which is used to monitor the voltage, current, temperature and state of charge of the battery pack in real time. When the battery pack is overcharged, over-discharged, over-temperatured or short-circuited, the battery management system immediately cuts off the circuit and issues an alarm signal.

[0038] In this embodiment, the energy storage module uses a lithium iron phosphate battery pack as the energy storage unit. Lithium iron phosphate batteries have advantages such as high safety, long cycle life, and high charge / discharge efficiency, making them very suitable for solar energy storage applications. The specific configuration of the battery pack is determined based on the system load power and backup power time requirements. A typical configuration is a 48V / 100Ah to 48V / 400Ah lithium iron phosphate battery pack with a rated depth of discharge of 80% DOD and a cycle life of no less than 4000 cycles. The battery pack consists of multiple individual cells connected in series and parallel, with a typical configuration of 16 series 2 parallel or 16 series 4 parallel. Each individual cell has a nominal voltage of 3.2V and a nominal capacity of 50Ah or 100Ah. The battery pack is equipped with a dedicated battery box, which is dustproof and waterproof with a protection rating of no less than IP54, and is equipped with a cooling fan and temperature sensor to ensure that the battery pack operates within a suitable temperature range.

[0039] In this embodiment, the battery management system (BMS) is connected between the battery pack and the external circuitry, responsible for the comprehensive monitoring and protection management of the battery pack. The BMS includes a voltage acquisition module, a current acquisition module, a temperature acquisition module, and a main control chip. The voltage acquisition module monitors the terminal voltage of each individual battery cell in real time using a high-precision voltage sampling circuit, with a sampling accuracy of no less than ±5mV and a sampling frequency of 10Hz. The current acquisition module monitors the charging and discharging current of the battery pack in real time using a Hall effect current sensor, with a measurement range of -200A to +200A and a measurement accuracy of no less than ±1%. The temperature acquisition module monitors the internal temperature of the battery pack and the ambient temperature of the battery compartment in real time using an NTC thermistor, with a measurement range of -20℃ to +80℃ and a measurement accuracy of no less than ±1℃. The BMS calculates the state of charge (SOC) of the battery pack based on the acquired voltage, current, and temperature data. The SOC calculation uses a combination of the ampere-hour integration method and the open-circuit voltage method, with an SOC estimation accuracy of no less than 5%.

[0040] In this embodiment, the battery management system (BMS) possesses comprehensive protection functions, including overcharge protection, over-discharge protection, over-temperature protection, overcurrent protection, and short-circuit protection. When the voltage of any single battery cell exceeds a preset overcharge protection threshold, the BMS immediately cuts off the charging circuit to prevent battery damage from overcharging. The overcharge protection threshold is typically set to 3.65V. When the voltage of any single battery cell falls below a preset over-discharge protection threshold, the BMS immediately cuts off the discharging circuit to prevent battery damage from over-discharge. The over-discharge protection threshold is typically set to 2.5V. When the battery pack temperature exceeds a preset over-temperature protection threshold, the BMS immediately triggers a protection action and activates a cooling fan for cooling. The over-temperature protection threshold is typically set to 55°C. When the charging current exceeds a preset safety threshold, the BMS immediately reduces the charging current or cuts off the charging circuit. When a short circuit is detected in an external circuit, the BMS quickly cuts off the circuit within 100 microseconds to ensure battery pack safety. Simultaneously with triggering protection actions, the BMS uploads alarm information to a remote monitoring platform via an IoT communication module. The alarm information includes alarm type, alarm time, and alarm parameter values.

[0041] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system, such as... Figure 2 As shown, in this system, the IoT communication module includes a data acquisition unit, a wireless communication unit, and a positioning unit. The data acquisition unit collects monitoring data from the sensor group through analog input channels and digital input channels. The wireless communication unit uses a 4G / 5G mobile network or a LoRa low-power wide area network to transmit the collected data to the remote monitoring platform. The positioning unit obtains the geographical location information of the system and attaches the location information to the transmitted data.

[0042] In this embodiment, the IoT communication module serves as the data transmission hub between the system and the remote monitoring platform. It is responsible for uploading monitoring data from the sensor array to the cloud server and receiving control commands from the remote monitoring platform. The data acquisition unit employs industrial-grade acquisition modules. The analog input channels support both 4-20mA current signals and 0-10V voltage signals. The number of channels is configured based on the number of sensors, typically ranging from 8 to 16 channels. The analog input channels are equipped with 16-bit analog-to-digital converters, with a sampling accuracy of at least 0.1%FS and a configurable sampling frequency from 1Hz to 100Hz. The digital input channels support both dry and wet contact input modes. The dry contact input voltage is 5V, and the wet contact input voltage range is 12V to 24V. The typical number of channels is 8 to 16 channels. The data acquisition unit performs preliminary processing on the sensor signals, including signal amplification, filtering, and engineering quantity conversion, converting the raw signals into actual physical quantity values.

[0043] In this embodiment, the wireless communication unit supports two communication modes: 4G / 5G mobile network communication and LoRa low-power wide-area network communication. In 4G / 5G communication mode, the data acquisition unit connects to the 4G / 5G DTU module via an RS485 or Ethernet interface. The DTU module encapsulates the data into TCP / IP packets and sends them to the remote monitoring platform via the 4G / 5G network. 4G / 5G communication mode is suitable for scenarios with mobile network coverage, offering fast communication speeds and low latency, with a typical upload cycle configurable from 1 to 30 minutes. In LoRa communication mode, the data acquisition unit sends data to the nearest LoRa gateway via the LoRa wireless module. The LoRa gateway then forwards the data to the remote monitoring platform via a wired network or 4G network. LoRa communication mode is suitable for scenarios such as remote mountainous areas or basements without mobile network coverage. The LoRa module uses spread spectrum modulation technology, achieving a transmission distance of several kilometers with extremely low power consumption, making it suitable for battery-powered applications. The IoT communication module supports dual-link backup functionality. When the primary communication link fails, it automatically switches to the backup communication link to ensure reliable data transmission.

[0044] In this embodiment, the positioning unit uses a BeiDou positioning module or a GPS positioning module to obtain the system's geographical location information. The positioning module calculates the latitude and longitude coordinates of the current device by receiving satellite signals, with a positioning accuracy of no less than 10 meters. The positioning unit acquires location information once during system initialization and stores the location information in a local configuration file. During each data transmission, the positioning unit attaches the location information to the header of the data packet. The remote monitoring platform marks the system location on an electronic map based on the location information, facilitating quick location and on-site maintenance by operation and maintenance personnel. For mobile water supply equipment, the positioning unit supports real-time positioning, updating the location information at preset time intervals and uploading the location trajectory data to the remote monitoring platform.

[0045] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system, such as... Figure 2 As shown, in this system, the sensor group includes a water level sensor, a pressure sensor, a flow sensor, and a water quality sensor. The water level sensor is installed in the high-level water tank to monitor the water level and report an error alarm signal when the water level exceeds the preset upper or lower limit. The pressure sensor is installed at key nodes of the pipeline network to monitor the pipeline network pressure and trigger protection actions when the pressure is abnormal. The flow sensor is installed in the water supply pipeline to measure water consumption and detect pipeline leaks. The water quality sensor is installed at the water outlet to monitor water quality parameters such as residual chlorine, turbidity, and pH value.

[0046] In this embodiment, the sensor array is the front-end component of the system for sensing the external environment, responsible for collecting various operating parameters of the water supply system in real time. The water level sensor uses either a submersible level gauge or an ultrasonic level gauge. The submersible level gauge calculates the water level by measuring the relationship between the liquid's static pressure and its height, while the ultrasonic level gauge calculates the water level by measuring the time difference between ultrasonic wave transmission and reception. The submersible level gauge has a selectable measurement range of 0 to 10 meters to 0 to 50 meters, with a measurement accuracy of no less than ±0.5%FS and an output signal of 4-20mA. The ultrasonic level gauge has a selectable measurement range of 0 to 5 meters to 0 to 30 meters, with a measurement accuracy of no less than ±0.5%FS and a blind zone of less than 0.3 meters. Both types of level gauges are equipped with protective tubes and anti-clogging devices to adapt to the harsh environment of elevated water tanks. The water level sensor is installed on the side wall or top of the elevated water tank, with the sensor probe extending below the water surface. The sensor cable is led out to the control module through a waterproof connector. The range of the water level sensor is selected based on the actual depth of the high-level water tank to ensure sufficient measurement margin at both the highest and lowest water levels.

[0047] In this embodiment, the pressure sensor employs a diffused silicon pressure sensor or a ceramic pressure sensor, and its measurement principle involves converting pressure signals into electrical signals. The measurement range of the pressure sensor is selected based on the design pressure of the pipeline network, with typical values ​​of 0 to 1 MPa or 0 to 1.6 MPa, a measurement accuracy of no less than ±0.25%FS, and an output signal of 4-20 mA. The pressure sensor is installed at key nodes in the pipeline network, including pump outlets, pipeline bifurcation points, and user terminal inlets. The pressure sensor is installed on the pipeline via threaded or flanged connections, and the sensor body is equipped with a protective cover to prevent external impact and contamination. Installing pressure sensors at key nodes in the pipeline network enables real-time monitoring of the pipeline network pressure distribution and timely detection of pressure anomalies. When the pipeline network pressure exceeds a preset upper limit, the control module automatically reduces the operating frequency of the booster pump or shuts down some pumps to prevent pipeline overpressure rupture. When the pipeline network pressure falls below a preset lower limit, the control module automatically starts the booster pump or increases the operating frequency of the pumps to ensure that the water supply pressure at the user terminal meets requirements.

[0048] In this embodiment, the flow sensor employs either an electromagnetic flowmeter or an ultrasonic flowmeter. The electromagnetic flowmeter measures the flow rate of conductive liquids based on Faraday's law of electromagnetic induction, while the ultrasonic flowmeter measures liquid flow rate based on the time-of-flight or frequency-of-flight method. The electromagnetic flowmeter has a measurement range of 0.1 m / s to 10 m / s and a measurement accuracy of at least ±0.5%FS, suitable for pipes from DN25 to DN1200. The ultrasonic flowmeter has a measurement range of 0.01 m / s to 10 m / s and a measurement accuracy of at least ±1%FS, suitable for pipes from DN50 to DN3000, and can be installed without damaging the pipes. The flow sensor is installed on the main pipeline of the water supply system to measure the total water consumption of users. Simultaneously, the flow sensor, in conjunction with the leakage detection algorithm of the control module, analyzes abnormal changes in instantaneous and cumulative flow to determine whether there is a leak in the pipe network. When the system detects that the flow rate continuously exceeds the normal water consumption range and the duration exceeds a preset threshold, it determines that there is a leak in the pipe network and issues an alarm signal to notify maintenance personnel to conduct timely inspections.

[0049] In this embodiment, water quality sensors are installed at the water outlet or the end of the pipe network to monitor the water quality parameters of domestic water and ensure that the water supply meets hygiene standards. The residual chlorine sensor uses polarography or electrochemical methods to measure the residual chlorine content in the water, with a measurement range of 0 to 2 mg / L and an accuracy of no less than ±0.03 mg / L. The turbidity sensor uses the scattered light method to measure the suspended solids content in the water, with a measurement range of 0 to 100 NTU and an accuracy of no less than ±2%FS. The pH sensor uses the glass electrode method to measure the acidity or alkalinity in the water, with a measurement range of 0 to 14 pH and an accuracy of no less than ±0.02 pH. The water quality sensors are equipped with an automatic cleaning device to regularly remove dirt and biofilm from the sensor surface, ensuring measurement accuracy. When water quality parameters exceed the preset range, the system automatically issues an alarm signal and can also shut off the outlet valve to prevent substandard water from entering the user's pipe network.

[0050] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system, such as... Figure 3 As shown, in this system, the control module includes a main controller, a signal conditioning circuit, and a drive circuit. The main controller uses an embedded microprocessor or a programmable logic controller. The signal conditioning circuit amplifies, filters, and performs analog-to-digital conversion on the analog signals output by the sensor group. The drive circuit amplifies the control signals from the main controller and drives the actuator to move.

[0051] In this embodiment, the control module is the core control unit of the entire system, responsible for acquiring sensor data, executing control strategies, outputting control commands, and communicating with the remote monitoring platform. The main controller uses an industrial-grade embedded microprocessor or programmable logic controller (PLC). The embedded microprocessor can be an ARM Cortex-M4 or Cortex-A series processor with a clock frequency of at least 168MHz, equipped with at least 512KB of Flash memory and 256KB of SRAM memory. The PLC can be a Siemens S7-1200 series or Mitsubishi FX series, possessing high reliability and anti-interference capabilities, suitable for industrial applications. The main controller runs a real-time operating system or a dedicated control program, which adopts a modular design, including a data acquisition module, a control algorithm module, a communication module, and a human-machine interface module. The main controller has at least 32 GPIO interfaces and at least 16 ADC channels. Communication interfaces include RS485, CAN, Ethernet, and USB, among others.

[0052] In this embodiment, the signal conditioning circuit preprocesses the analog signals output by the sensor group, converting the electrical signals output by the sensors into signal levels suitable for the input of the main controller's ADC. The signal conditioning circuit includes a signal amplification circuit, a signal filtering circuit, and an analog-to-digital conversion circuit. The signal amplification circuit uses an instrumentation amplifier or operational amplifier to amplify the weak signals output by the sensors to the ADC input range. The amplification factor is set according to the sensor type and range, typically from 1 to 10 times. The signal filtering circuit uses a low-pass filter or a band-stop filter to eliminate high-frequency noise and power frequency interference in the sensor signals. The cutoff frequency of the filter is set according to the signal characteristics, typically from 10Hz to 100Hz. The analog-to-digital conversion circuit uses a 16-bit or 24-bit high-precision ADC to convert the analog signals into digital signals, with a sampling rate of not less than 1kHz, supporting single-channel or multi-channel synchronous sampling. The signal conditioning circuit is equipped with overvoltage protection and overcurrent protection circuits to prevent external interference from damaging the main controller.

[0053] In this embodiment, the drive circuit amplifies the control signal from the main controller and outputs it to drive the actuator. The drive circuit includes a digital output circuit and an analog output circuit. The digital output circuit uses relays or solid-state relays with an output contact capacity of not less than 10A / 250VAC or 5A / 30VDC, which can directly drive small actuators. For high-power actuators, the drive circuit amplifies the power through intermediate relays or contactors. The analog output circuit consists of a digital-to-analog converter and a power amplifier, outputting a 4-20mA current signal or a 0-10V voltage signal, used to adjust the frequency setpoint of the frequency converter or the opening setpoint of the electric regulating valve. The drive circuit is equipped with an opto-isolation circuit to isolate the main controller's control circuit from the external power circuit, preventing external interference and faults from damaging the main controller. The drive circuit is also equipped with a fault detection circuit to monitor the operating status of the actuator in real time. When a fault is detected in the actuator, the fault information is reported to the main controller.

[0054] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system, such as... Figure 4 As shown, Figure 4 This is a schematic diagram of the core principle framework of the intelligent water supply strategy algorithm module in this invention. In this system, the control module embeds the intelligent water supply strategy algorithm module. This module automatically generates the optimal water supply scheduling plan based on historical water consumption data, current water level, predicted water demand, and peak and off-peak electricity prices. The intelligent water supply strategy algorithm module includes a water demand prediction submodule, a power supply capacity assessment submodule, and an optimization scheduling submodule. The water demand prediction submodule uses machine learning algorithms to predict water consumption in future periods based on historical water consumption data. The power supply capacity assessment submodule assesses the power supply capacity of the solar power generation system based on current sunlight conditions, energy storage status, and weather forecast data. The optimization scheduling submodule integrates the water demand prediction results and the power supply capacity assessment results to generate control instructions that meet water supply needs while minimizing energy consumption.

[0055] In this embodiment, refer to Figure 4 The intelligent water supply strategy algorithm module is embedded in the main controller of the control module. It uses a combination of machine learning and optimization algorithms to achieve intelligent scheduling of the water supply system. The intelligent water supply strategy algorithm module is divided into three sub-modules: a water demand prediction sub-module, a power supply capacity assessment sub-module, and an optimization scheduling sub-module. The three sub-modules work together to generate the optimal water supply scheduling plan based on real-time data and prediction information.

[0056] In this embodiment, the water demand prediction submodule uses a machine learning algorithm to predict water consumption for future periods based on historical water consumption data. The machine learning algorithm employs a Long Short-Term Memory (LSTM) network or a Transformer model. The network structure includes an input layer, multiple hidden layers, and an output layer. The input layer receives historical water consumption data sequences, including hourly water consumption records for the past 7 days, with a data dimension of 168. The hidden layers contain 2 to 4 layers of LSTM or Transformer encoders, with 64 to 256 hidden units per layer, used to extract the temporal and periodic features of the water consumption data. The output layer is a fully connected layer, outputting the predicted water consumption for each hour of the next 24 hours. The model training uses a mean squared error loss function, an Adam optimizer, a learning rate of 0.001, a batch size of 32, and 100 to 500 training epochs. The water demand prediction submodule automatically updates the model parameters daily, using water consumption data from the past 30 days for incremental training to adapt the model to seasonal and user habit changes. The water demand prediction results are output in time-series data format, with a data sampling interval of 1 hour.

[0057] In this embodiment, the power supply capacity assessment submodule assesses the power supply capacity of the solar power generation system based on current sunlight conditions, energy storage status, and weather forecast data. The power supply capacity assessment includes two parts: a short-term assessment and a medium-term assessment. The short-term assessment estimates the photovoltaic power generation capacity for the next 1 to 2 hours based on real-time sunlight intensity data collected by the current sunlight sensor. The formula for calculating the photovoltaic power generation capacity is: ,in The typical value for photovoltaic module conversion efficiency is 18% to 22%. For the area of ​​the photovoltaic array, The solar irradiance is used for calculation. The conversion efficiency of photovoltaic (PV) modules is affected by temperature; for every 1°C increase in temperature, the conversion efficiency decreases by approximately 0.4%. Therefore, the estimated results need to be corrected based on the panel temperature. The mid-term assessment combines weather forecast data to estimate sunshine conditions for the next 24 to 72 hours. Weather forecast data is obtained from a remote server via an IoT communication module and includes sunshine duration, cloud cover distribution, and rainfall probability. Based on the weather forecast data, a probabilistic method is used to estimate the PV power generation range under different weather conditions. The energy storage status assessment is based on real-time data from the battery management system to estimate the duration for which the current energy storage capacity can be used for power supply. The power supply capacity assessment results are output in the form of a power curve, with data sampling intervals of 1 hour.

[0058] In this embodiment, the optimization scheduling submodule integrates the water demand forecast results and power supply capacity assessment results to generate control instructions that meet water supply demand while minimizing energy consumption. The optimization scheduling submodule employs a mixed-integer programming or dynamic programming algorithm, with the goal of minimizing water supply energy consumption, and using water supply demand, energy storage constraints, and equipment operation constraints as constraints to establish an optimization scheduling model. The objective function is:

[0059] ,

[0060] in for The amount of electricity purchased from the grid during a given period. This is a time interval, usually 1 hour. for Electricity prices for different time periods. Constraints include: water demand constraints, ensuring the water tank level is always above the minimum level and not above the maximum level; energy storage constraints, ensuring the battery pack's state of charge is always within a safe range; equipment operation constraints, ensuring the pump and valve operating states meet equipment characteristics; and photovoltaic power constraints, ensuring the total pump power does not exceed the power provided by photovoltaics and energy storage. The optimized scheduling submodule adopts a rolling optimization strategy, updating the optimized scheduling plan hourly and adjusting control commands based on the latest water consumption forecasts and power supply capacity assessments. Optimized scheduling results include the operating frequency of booster pumps, the opening status of electric valves, and the action sequence of water hammer eliminators for each time period.

[0061] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system, referring to... Figure 5 , Figure 5 This is a schematic diagram of the multifunctional management framework of the remote monitoring platform in this invention. In this system, the remote monitoring platform includes a data storage unit, a data analysis unit, an alarm management unit, and a remote control unit. The data storage unit persistently stores the time-series data uploaded by the IoT communication module. The data analysis unit performs statistical analysis on the stored operational data and generates reports. The alarm management unit identifies abnormal events according to preset alarm rules and pushes alarm information via SMS, email, or mobile applications. The remote control unit provides a human-machine interface, enabling maintenance personnel to remotely view the system status and issue control commands.

[0062] In this embodiment, refer to Figure 5The remote monitoring platform is deployed on a cloud server, employing a distributed architecture design, including a web server, application server, database server, and message queue server. The web server uses Nginx or Apache, providing HTTP / HTTPS services and hosting the front-end human-computer interaction interface. The application server is developed using Java or Python, handling business logic and data computation tasks. The database server uses MySQL or PostgreSQL to store structured data, and InfluxDB or TimescaleDB to store time-series data. The message queue server uses RabbitMQ or Kafka to implement asynchronous message passing and system decoupling. The remote monitoring platform supports horizontal scaling, dynamically adding server nodes according to system size to meet the needs of large-scale system access.

[0063] In this embodiment, the data storage unit persistently stores the time-series data uploaded by the IoT communication module. The time-series data includes raw data collected by sensors, calculated physical quantity data, and system status data. Data storage employs a time-series database, typically InfluxDB or TimescaleDB. Time-series databases are optimized for time-series data, supporting high-speed writing and compressed storage. Data retention strategies can be configured according to requirements, typically set to retain minute-level data for the most recent year and hour-level data for the most recent three years. The data storage unit also supports data backup functionality, ensuring data security and reliability through master-slave replication or distributed storage technology. The data storage unit provides a RESTful API or SQL interface for the data analysis unit and data query module to access the data.

[0064] In this embodiment, the data analysis unit performs statistical analysis on the stored operational data and generates reports. The data analysis function includes three aspects: real-time analysis, historical analysis, and trend analysis. Real-time analysis calculates the current operating status and performance indicators of the system, including current power, power generation, power consumption, and energy storage status, and pushes this data to the front-end interface in real time via WebSocket or long polling technology. Historical analysis performs statistical calculations on historical data, including daily power generation, monthly power generation, annual power generation, daily water consumption, monthly water consumption, and water supply network leakage rate, generating daily, monthly, and annual reports. Trend analysis uses time series analysis methods to predict trends in power generation and water consumption, identify abnormal fluctuations, and provide a reference for operation and maintenance decisions. The data analysis unit also provides data visualization functions, displaying data through various chart formats such as line charts, bar charts, pie charts, and heat maps, making it easier for operation and maintenance personnel to intuitively understand the system's operating status.

[0065] In this embodiment, the alarm management unit identifies abnormal events according to preset alarm rules and pushes alarm information via SMS, email, or mobile application. Alarm rules include three types: threshold alarms, trend alarms, and logic alarms. Threshold alarms determine whether to trigger an alarm based on parameter values ​​collected by sensors; for example, a low water level alarm is triggered when the water level is below the lower limit, and a high pressure alarm is triggered when the pressure exceeds the upper limit. Trend alarms determine whether to trigger an alarm based on the changing trend of parameters; for example, a leak alarm is triggered when the water level drops rapidly, and a device failure alarm is triggered when the power generation continues to decline. Logic alarms determine whether to trigger an alarm based on the correlation between multiple parameters; for example, a battery overcharge alarm is triggered when the battery temperature is high and the charging current is large. Alarm information is sent through multiple channels, including SMS, email, mobile application push notifications, and WeChat mini-program push notifications, ensuring that maintenance personnel receive alarm information in a timely manner. The alarm management unit also supports alarm confirmation, alarm processing, and alarm revert functions, recording the alarm processing process and forming an alarm processing log.

[0066] In this embodiment, the remote control unit provides a human-machine interface (HMI) enabling maintenance personnel to remotely view system status and issue control commands. The HMI adopts a responsive web design, supporting access from both PC and mobile devices. The interface functions include six modules: system overview, real-time monitoring, remote control, parameter configuration, report viewing, and system management. The system overview module displays the location and operating status of all water supply stations connected to the system in map form. The real-time monitoring module displays detailed operating parameters for each station, including photovoltaic power generation, energy storage status, water level, pressure, flow rate, and water quality, and supports viewing data curves. The remote control module provides a remote operation interface, allowing maintenance personnel to remotely start and stop equipment, adjust valve openings, and modify pump operating frequencies; operations require identity authentication and permission verification. The parameter configuration module provides a system parameter configuration interface, including alarm threshold settings, scheduling strategy parameter settings, and communication parameter settings. The report viewing module provides historical report query and download functions. The system management module provides user management, role management, and log query functions.

[0067] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system. In this system, the system also includes a local display and operation terminal, which is set near the elevated water tank or pump room. The local display and operation terminal is used to display the system operating status, parameter configuration and fault information locally, and provides a field operation interface for maintenance personnel to manually intervene.

[0068] In this embodiment, the local display and operation terminal adopts an industrial-grade touch screen all-in-one machine with a screen size selectable from 7 inches to 15 inches and a protection level of no less than IP65, suitable for the humid environment of the pump room. The local display and operation terminal connects to the control module via RS485 or Ethernet to acquire and display system operation data in real time. The interface design adopts a graphical approach, displaying the process flow of the water supply system in the form of a flowchart, and marking the real-time parameter values ​​of each key node on the flowchart, including water level, pressure, flow rate, etc. The local display and operation terminal provides parameter configuration functions, allowing maintenance personnel to modify system operating parameters locally, such as alarm thresholds, acquisition cycles, communication parameters, etc., without remote access to the remote monitoring platform. The local display and operation terminal also provides manual operation functions. When the automatic control mode fails, maintenance personnel can manually control the actuators through the local display and operation terminal, including starting and stopping the water pump, adjusting valve opening, activating the water hammer eliminator, etc.

[0069] In one embodiment, this application also provides an IoT-based solar-powered unattended domestic water supply control system. In this system, the system adopts a redundant design, and the control module is equipped with a main and backup dual-machine switching device. When the main controller fails, the backup machine automatically switches to the working state to ensure continuous operation of the system. The IoT communication module supports multi-link backup, and automatically switches to the backup communication link when the main communication link is interrupted.

[0070] In this embodiment, the system employs a redundancy design to improve reliability, ensuring continuous operation even in the event of a single failure. The control module's dual-machine switching device uses a hot standby mode, with the main controller and standby controller operating simultaneously. The main controller is responsible for the actual control tasks, while the standby controller synchronizes the main controller's status data in real time. The standby controller receives the main controller's operating data and output status every 100 milliseconds via a high-speed communication link and performs real-time comparison. When a failure is detected in the main controller, the standby controller automatically switches to the operating state within 50 milliseconds, taking over the control tasks and ensuring continuous system operation. The fault detection mechanism includes two methods: software watchdog and hardware heartbeat detection. The software watchdog monitors the program's running status and automatically restarts the main controller when the program freezes. The hardware heartbeat detection monitors the main controller's operating status and triggers a switchover when the main controller stops responding. During the switchover process, the standby controller maintains the state of its actuators unchanged to avoid water hammer in the pipeline or equipment damage caused by sudden state changes.

[0071] In this embodiment, the IoT communication module supports multi-link backup to ensure data transmission reliability. The module is equipped with two communication links: a 4G / 5G communication unit and a LoRa communication unit. Under normal circumstances, 4G / 5G is used as the primary communication link, and LoRa as the backup. The module monitors the status of the primary communication link in real time, using Ping commands or TCP heartbeat checks to determine link health. When a primary communication link interruption is detected, the module automatically switches to the backup link within 10 seconds to continue uploading data to the remote monitoring platform. The switching process is transparent to upper-layer applications and does not affect the reception and execution of control commands. The module also supports multi-server backup, allowing configuration of primary and backup server addresses. It automatically switches to the backup server when the primary server becomes unreachable. The module also features data caching, automatically caching monitoring data during communication interruptions and automatically retransmitting it after communication is restored, ensuring data integrity.

[0072] The IoT-based solar-powered unattended domestic water supply control system proposed in this application achieves the following significant effects through the aforementioned technical solution: It provides green energy to the entire system through solar photovoltaic power generation modules, eliminating reliance on traditional mains power, making it particularly suitable for water supply scenarios in remote areas such as elevated water tanks, effectively solving the problem of power supply difficulties; the combination of energy storage modules and maximum power point tracking control technology ensures continuous and stable operation of the system even in cloudy or rainy weather or at night, improving energy utilization efficiency; the integration of IoT communication modules and a remote monitoring platform enables remote real-time monitoring and control of the water supply system, allowing maintenance personnel to monitor the system's operating status without being physically present, significantly reducing manual inspection costs; and the intelligent water supply strategy calculation embedded in the control module... The water supply system's intelligent operation is achieved by automatically generating optimal scheduling plans based on water demand forecasts and power supply capacity assessments, reducing manual intervention. Real-time monitoring of key parameters such as water level, pressure, flow rate, and water quality via sensor arrays, combined with the alarm management unit's anomaly warning function, enables early detection and handling of problems, preventing system paralysis due to excessive water levels and improving system stability. The coordinated operation of electric valves, booster pumps, and water hammer eliminators in the actuators achieves automatic regulation of pipeline pressure and effective elimination of water hammer, extending the service life of valves, contactors, and other hardware, and reducing maintenance costs. Redundant design and multi-link backup mechanisms ensure high availability of the system in complex environments, enhancing overall reliability.

[0073] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0074] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0076] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0078] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0079] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only 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 terminal device 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 terminal device. 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 terminal device that includes said element.

[0080] The above provides a detailed description of an IoT-based solar-powered unattended domestic water supply control system. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A solar-powered, unattended life water supply control system based on the Internet of Things, characterized by, include: Solar photovoltaic power generation modules are used to collect solar energy and convert light energy into electrical energy to power the system; The energy storage module, connected to the solar photovoltaic power generation module, is used to store electrical energy and supply power to the system when sunlight is insufficient; The Internet of Things (IoT) communication module establishes data communication links with the solar photovoltaic power generation module, energy storage module, control module, and sensor group, respectively, to collect system operating parameters and upload them to the remote monitoring platform, while also receiving control commands issued by the remote monitoring platform. The sensor array is installed at key nodes in the domestic water supply system to monitor key parameters in real time, including water level, flow rate, pressure, and equipment status, and uploads the monitoring data through the Internet of Things communication module. The control module is connected to the IoT communication module, the energy storage module, and the actuator. Based on the preset water supply strategy and the real-time data collected by the sensor group, the control module issues control commands to the actuator to realize the automatic adjustment and intelligent control of the water supply system. The actuators include electric valves, booster pumps, and water hammer eliminators. The control module regulates the water flow path by controlling the opening and closing of the electric valves, adjusts the water supply pressure by controlling the operating parameters of the booster pumps, and eliminates water hammer in the pipe network by using the water hammer eliminators. The remote monitoring platform, located on a cloud server, is used to receive operational data uploaded by the IoT communication module, store, analyze and process the data, and send control commands or alarm information to the control module.

2. The internet of things based solar powered unattended water supply control system for water supply to the living beings as claimed in claim 1 wherein, The solar photovoltaic power generation module includes a photovoltaic array, a photovoltaic inverter, and a maximum power point tracking controller. The photovoltaic array is set on the sunny side of an elevated water tank or the surrounding area. The maximum power point tracking controller is used to adjust the operating point of the photovoltaic array in real time so that the photovoltaic array always outputs maximum power. The photovoltaic inverter converts the DC power output by the photovoltaic array into AC power to charge the energy storage module and power the actuator.

3. The internet of things based solar powered unattended water supply control system for water supply to the living beings as claimed in claim 1 wherein, The energy storage module uses a lithium iron phosphate battery pack as the energy storage unit. The energy storage module is equipped with a battery management system, which is used to monitor the voltage, current, temperature and state of charge of the battery pack in real time. When the battery pack is overcharged, over-discharged, over-temperatured or short-circuited, the battery management system immediately cuts off the circuit and issues an alarm signal.

4. The IoT-based solar-powered unattended domestic water supply control system according to claim 1, characterized in that, The IoT communication module includes a data acquisition unit, a wireless communication unit, and a positioning unit. The data acquisition unit acquires monitoring data from the sensor group through analog input channels and digital input channels. The wireless communication unit transmits the acquired data to the remote monitoring platform using a 4G or 5G mobile network or a LoRa low-power wide area network. The positioning unit obtains the system's geographical location information and attaches the location information to the transmitted data.

5. The IoT-based solar-powered unattended domestic water supply control system according to claim 1, characterized in that, The sensor group includes a water level sensor, a pressure sensor, a flow sensor, and a water quality sensor. The water level sensor is installed in the high-level water tank to monitor the water level and issue an alarm signal when the water level exceeds a preset upper or lower limit. The pressure sensor is installed at a key node of the pipeline network to monitor the pipeline network pressure and trigger a protection action when the pressure is abnormal. The flow sensor is installed in the water supply pipeline to measure water consumption and detect pipeline leaks. The water quality sensor is installed at the water outlet to monitor residual chlorine, turbidity, and pH value.

6. The internet of things based solar powered unattended water supply control system for water supply to the living beings as claimed in claim 1 wherein, The control module includes a main controller, a signal conditioning circuit, and a drive circuit. The main controller is an embedded microprocessor or a programmable logic controller. The signal conditioning circuit amplifies, filters, and performs analog-to-digital conversion on the analog signals output by the sensor group. The drive circuit amplifies the control signals from the main controller and drives the actuator to operate.

7. The IoT based solar powered unattended water supply control system for domestic water supply as claimed in claim 6 wherein, The control module embeds an intelligent water supply strategy algorithm module, which automatically generates the optimal water supply scheduling plan based on historical water consumption data, current water level, predicted water demand, and peak and off-peak electricity prices. The intelligent water supply strategy algorithm module includes a water demand prediction submodule, a power supply capacity assessment submodule, and an optimization scheduling submodule. The water demand prediction submodule uses machine learning algorithms to predict water consumption in future periods based on historical water consumption data. The power supply capacity assessment submodule assesses the power supply capacity of the solar power generation system based on current sunlight conditions, energy storage status, and weather forecast data. The optimization scheduling submodule integrates the water demand prediction results and the power supply capacity assessment results to generate control commands that meet water supply needs and minimize energy consumption.

8. The internet of things based solar powered unattended water supply control system for water supply to the living beings as claimed in claim 1 wherein, The remote monitoring platform includes a data storage unit, a data analysis unit, an alarm management unit, and a remote control unit. The data storage unit persistently stores the time-series data uploaded by the IoT communication module. The data analysis unit performs statistical analysis on the stored operational data and generates reports. The alarm management unit identifies abnormal events according to preset alarm rules and pushes alarm information via SMS, email, or mobile application. The remote control unit provides a human-machine interface that allows maintenance personnel to remotely view the system status and issue control commands.

9. The internet of things based solar powered unattended water supply control system for water supply to the living beings as claimed in claim 1 wherein, The system also includes a local display and operation terminal, which is located near the elevated water tank or pump room. It is used to display the system's operating status, parameter configuration, and fault information locally, and provides an on-site operation interface for maintenance personnel to manually intervene.

10. The IoT-based solar-powered unattended domestic water supply control system according to claim 1, characterized in that, The system adopts a redundant design. The control module is equipped with a primary and backup dual-machine switching device. When the primary controller fails, the backup machine automatically switches to the working state to ensure continuous system operation. The IoT communication module supports multi-link backup. When the primary communication link is interrupted, it automatically switches to the backup communication link.

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