Intelligent water meter system oriented to extreme environment

Abstract

The invention discloses an intelligent water meter system oriented to an extreme environment, belongs to the technical field of intelligent water meters, and aims to integrate adaptive ultra-low power consumption wide area communication, quantum enhanced multimode metering, flexible electronic packaging and flexible manufacturing technologies. The self-adaptive communication architecture of NB-IoT and LoRa is integrated, and the communication mode is optimized through deep reinforcement learning; the ultrasonic-electromagnetic composite technology based on the quantum interference effect is carried out aiming at micro-flow detection and complex water quality adaptability; the edge AI chip is embedded into a real-time fault prediction model and is used for water meter self-diagnosis and abnormity early warning; and the flexible electronic packaging adopts a bio-based composite material, so that the environmental adaptability and sustainability are improved. The concept design of a flexible manufacturing demonstration production line is provided, and the industrial Internet of Things and real-time quality monitoring are integrated; through interdisciplinary technology integration, advanced solutions of ultra-low power consumption communication, quantum sensor miniaturization, flexible electronic reliability and intelligent manufacturing are explored, and an innovative path is provided for intelligent water affair management.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart water meters, and in particular relates to a smart water meter system integrating adaptive ultra-low power wide area communication, quantum enhanced multi-mode metering, flexible electronic packaging and flexible manufacturing technology. Background Art

[0002] Smart water meters, a core application of IoT technology in water management, have seen rapid global development in recent years. Internationally, the smart metering infrastructure launched by Itron in the United States uses low-power wide-area network technology, but its energy efficiency and coverage remain limited. Sensus in Europe has developed an ultrasonic-based smart water meter, but its performance is limited in high turbidity or low-flow conditions and it lacks quantum technology integration. BASF in Germany has conducted research on flexible electronic materials, but this has not been widely used in water meter packaging. Azbil in Japan specializes in high-precision sensor technology with strong environmental adaptability, but its communication capabilities are limited. Toshiba and Sony in Japan have accumulated expertise in flexible electronics and micro-energy harvesting, but have not yet expanded this expertise to water meter applications. Overall, international technology is lacking in ultra-low-power communications, miniaturization of quantum metrology, and green manufacturing integration.

[0003] Domestically, universities such as Tsinghua University have developed NB-IoT-based smart water systems, but these systems lack adaptive optimization and quantum technology integration. Zhejiang University has achieved success in ultrasonic metering, but stability under complex water conditions needs improvement. Companies are using LoRa or NB-IoT technologies to drive the intelligent transformation of traditional water meters, but there is significant room for optimization in communication and power consumption. Domestic research on flexible electronics remains largely at the laboratory stage. Existing technologies lack ultra-low power communications, micro-flow measurement, adaptability to extreme environments, and flexible manufacturing integration. This paper addresses these technological gaps and proposes a comprehensive innovative solution to enhance the performance and industrialization potential of smart water meters. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an intelligent water meter system that integrates adaptive ultra-low power wide area communication, quantum enhanced multi-mode metering, flexible electronic packaging and flexible manufacturing technology to address the shortcomings of the background technology.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] A smart water meter system for extreme environments, including an adaptive communication module, a micro-energy collection module, a quantum enhanced measurement module, an edge AI real-time fault diagnosis module, and a flexible electronic packaging module.

[0007] Among them, the adaptive communication module integrates the adaptive communication architecture of NB-IoT and LoRa, and uses deep reinforcement learning (DRL) to dynamically select the communication mode;

[0008] The micro-energy harvesting module uses thermoelectric effect and vibration energy conversion technology to provide self-powered water meters. It specifically includes a thermoelectric module, a vibration module, and an energy management unit. The thermoelectric module is used to generate electricity using the temperature difference of the water pipe; the vibration module is used to generate electricity using the vibration of the water flow; and the energy management unit is used to dynamically distribute energy.

[0009] The quantum-enhanced metering module is an ultrasonic-electromagnetic composite metering system based on the quantum interference effect. It improves signal sensitivity through quantum state control. It specifically includes an ultrasonic sensor, an electromagnetic sensor, and a quantum interference unit. The ultrasonic sensor is used to measure flow rate, the electromagnetic sensor is used to detect water quality parameters, and the quantum interference unit is used to enhance signal contrast and reduce noise interference.

[0010] Edge AI module deploys a lightweight fault prediction model on the edge AI chip, uses sensor data to analyze water meter status, adopts transfer learning technology to adapt to different environments, and predicts potential faults through real-time reasoning;

[0011] Flexible electronic packaging modules are used to design sensors and communication modules that are resistant to extreme environments using flexible electronic substrates and bio-based composite materials.

[0012] As a further preferred solution of the present invention for a smart water meter system for extreme environments, the adaptive communication module senses the environment in real time through sensors, and the AI algorithm runs on a low-power microcontroller. The specific calculation principle is as follows:

[0013] Power consumption model: P total =P tx ·t tx +P rx ·t rx +P idle ·t idle Among them, P tx 、P rx 、P idle They are respectively the power consumption of sending, receiving and idle, t tx , t rx , t idle P tx 、P rx 、P idle Corresponding time;

[0014] Reward function: SNR is signal-to-noise ratio, latency is delay, a, β, γ are weight coefficients;

[0015] Spectral efficiency: η = B·log(1+SNR); where η is the spectral efficiency and B is the bandwidth.

[0016] As a further preferred solution of the present invention for a smart water meter system for extreme environments, the micro energy harvesting module optimizes energy harvesting efficiency through adaptive control. The specific calculation is as follows:

[0017] Thermoelectric efficiency: Where ΔT is the temperature difference, ZT is the thermoelectric figure of merit, and T hot is the high temperature end temperature;

[0018] Vibrational Energy: Where m is the mass, w is the angular frequency, and A is the amplitude;

[0019] Energy storage capacity: Where C is capacitance and V is voltage.

[0020] As a further preferred solution of the present invention for an intelligent water meter system for extreme environments, the principle of the quantum enhanced metering module is specifically calculated as follows:

[0021] Quantum state evolution: ψ(t) = U(t) | ψ(0); where U(t) is the time evolution operator and ψ(t) is the quantum state;

[0022] Interference intensity: I=|<ψ1|ψ2>| 2 ; Among them, ψ1 and ψ2 are quantum states;

[0023] Flow calculation: Q = k∫I(v)dv; where k is the calibration factor and v is the flow rate.

[0024] As a further preferred solution of the present invention for a smart water meter system for extreme environments, the computing model of the edge AI real-time fault diagnosis module is as follows:

[0025] Fault probability: P(fault) = σ(w x + b); where σ is the activation function, w is the weight, x is the input, and b is the bias;

[0026] Loss function: Among them, y is the true label, is the predicted value;

[0027] Model Updates: Where η is the learning rate.

[0028] As a further preferred solution of the present invention for an intelligent water meter system for extreme environments, the calculation model of the flexible electronic packaging module is as follows:

[0029] Coefficient of thermal expansion: Where L is the length and T is the temperature;

[0030] Young's modulus: Where σ is stress and ε is strain.

[0031] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0032] 1. Adaptive Communication and Micro-Energy Harvesting: This technology aims to explore possible paths to optimize power consumption and coverage. The adaptive communication system integrates two low-power wide area network (LPWAN) technologies, NB-IoT and LoRa, and dynamically optimizes communication modes through deep reinforcement learning (DRL). Depending on environmental conditions (such as signal strength and interference levels), the system can select NB-IoT for urban environments or LoRa for long-distance coverage in remote areas, ensuring a balance between communication efficiency and coverage.

[0033] The micro-energy harvesting module further enhances the system's sustainability, utilizing thermoelectric effects and vibration energy conversion technology to extract power from ambient energy. The thermoelectric module generates electricity using the temperature difference between the water pipe and the surrounding environment, while the vibration module generates electricity from the pipe vibration caused by the water flow. The self-powered design reduces reliance on traditional batteries, extending device lifespan and making it particularly suitable for remote or difficult-to-maintain areas. Its advantage lies in its attempt to overcome the trade-off between power consumption and coverage in traditional low-power communications, enabling the long-term operation of smart water meters in extreme environments.

[0034] 2. Quantum interference technology improves metering signal sensitivity: Quantum interference technology is used to improve metering signal sensitivity and adapt to complex water quality conditions. The measurement system is based on ultrasonic-electromagnetic composite technology based on the quantum interference effect, aiming to improve the accuracy of micro-flow detection. Ultrasonic flowmeters calculate flow by measuring the propagation time difference of sound waves in water, while electromagnetic flowmeters use Faraday's electromagnetic induction principle to detect the flow rate of conductive liquids. In combination with quantum interference technology, the system may enhance signal contrast and reduce noise interference through quantum state manipulation (such as quantum dots or superconducting quantum interference devices (SQUIDs), thereby maintaining high sensitivity in complex water quality conditions such as high turbidity and high mineralization. This breaks through the accuracy limits of traditional metering systems and is particularly suitable for detecting micro-flows (such as low water consumption at night), providing technical support for the application of smart water meters in complex working conditions.

[0035] 3. Flexible packaging and bio-based materials enhance environmental adaptability and sustainability: Flexible electronic packaging and bio-based composite materials are used to enhance environmental adaptability and sustainability. Flexible packaging uses a flexible electronic substrate to ensure the electrical and mechanical stability of the device in extreme temperatures (e.g., -40°C to 70°C). The design is particularly suitable for high-altitude, high-humidity, or coastal high-salt environments, preventing equipment aging or performance degradation due to temperature differences or mechanical stress. Bio-based composite materials refer to materials made from renewable biological resources (such as plant fibers and starch), which are more environmentally friendly than traditional petroleum-based materials. By optimizing green manufacturing processes, the carbon footprint is reduced and sustainable production methods are promoted. The choice of this material not only improves the environmental adaptability of the device, but also reduces the environmental impact of the production process, in line with the global trend of a low-carbon economy. It also ensures the long-term and reliable operation of smart water meters in extreme environments and promotes the green transformation of the manufacturing industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a system architecture diagram of a smart water meter system for extreme environments according to the present invention;

[0037] Figure 2 is a flow chart of adaptive communication of the present invention;

[0038] Figure 3 This is a schematic diagram of the quantum metrology principle of the present invention;

[0039] Figure 4 This is a method flow chart of a smart water meter system for extreme environments according to the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings:

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The present invention is described in detail below based on the drawings and preferred embodiments. The purpose and effect of the present invention will become more clear. It should be understood that the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0042] like Figures 1 to 4As shown, the present invention discloses a smart water meter system for extreme environments, which aims to integrate adaptive ultra-low power wide area communication, quantum enhanced multi-mode metering, flexible electronic packaging and flexible manufacturing technology. The system designs an adaptive communication architecture that integrates NB-IoT and LoRa, and optimizes the communication mode through deep reinforcement learning. The metering module is based on ultrasonic-electromagnetic composite technology based on quantum interference effect, and is aimed at micro-flow detection and adaptability to complex water quality. The edge AI chip is embedded in a real-time fault prediction model for water meter self-diagnosis and abnormality warning. The flexible electronic packaging uses bio-based composite materials to improve environmental adaptability and sustainability. In addition, the conceptual design of a flexible manufacturing demonstration production line is proposed, integrating the Industrial Internet of Things (IIoT) and real-time quality monitoring. Through interdisciplinary technology integration, the present invention explores cutting-edge solutions for ultra-low power communication, quantum sensor miniaturization, flexible electronic reliability and intelligent manufacturing, providing an innovative path for smart water management.

[0043] The present invention belongs to the field of smart water meter technology, and relates to a smart water meter system that integrates adaptive ultra-low power wide area communication, quantum enhanced multi-mode metering, flexible electronic packaging and flexible manufacturing technology. This technology is positioned in the water management industry, integrating the Internet of Things (IoT), wireless communication, quantum sensing, and artificial intelligence, and aims to meet the challenges of traditional water meters in extreme environments. The system relies on low-power wide area network (LPWAN) protocols (such as NB-IoT, LoRa), quantum interference effects, edge AI algorithms and flexible electronic materials to promote the upgrading of water meter performance and manufacturing processes. Application scenarios include residential, commercial and industrial water metering, and are particularly suitable for complex environments such as remote, cold, high temperature, and high humidity. Through technological innovation, the present invention explores solutions for high reliability and sustainability in smart water management, and has potential wide applicability.

[0044] like Figure 4 As shown, modular design: a smart water meter system for extreme environments, such as Figure 1 As shown, it includes adaptive communication module, micro energy collection module, quantum enhanced measurement module, edge AI real-time fault diagnosis module, and flexible electronic packaging module;

[0045] Among them, the adaptive communication module integrates the adaptive communication architecture of NB-IoT and LoRa, and uses deep reinforcement learning (DRL) to dynamically select the communication mode;

[0046] The micro-energy harvesting module uses thermoelectric effect and vibration energy conversion technology to provide self-powered water meters. It specifically includes a thermoelectric module, a vibration module, and an energy management unit. The thermoelectric module is used to generate electricity using the temperature difference of the water pipe; the vibration module is used to generate electricity using the vibration of the water flow; and the energy management unit is used to dynamically distribute energy.

[0047] The quantum-enhanced metering module is an ultrasonic-electromagnetic composite metering system based on the quantum interference effect. It improves signal sensitivity through quantum state control. It specifically includes an ultrasonic sensor, an electromagnetic sensor, and a quantum interference unit. The ultrasonic sensor is used to measure flow rate, the electromagnetic sensor is used to detect water quality parameters, and the quantum interference unit is used to enhance signal contrast and reduce noise interference.

[0048] Edge AI module deploys a lightweight fault prediction model on the edge AI chip, uses sensor data to analyze water meter status, adopts transfer learning technology to adapt to different environments, and predicts potential faults through real-time reasoning;

[0049] The flexible electronic packaging module utilizes a flexible electronic substrate and bio-based composite materials to design sensors and communication modules resistant to extreme environments. The bio-based composite materials used in the packaging module ensure electrical and mechanical stability in extreme temperatures ranging from -40°C to 70°C. This design aims to address the performance bottlenecks of traditional water meters in extreme environments.

[0050] Assembly and Integration: The assembly and integration process integrates the flexible electronic substrate, sensors, communication module, and AI chip. The flexible electronic substrate provides mechanical flexibility. The sensors include flow meters and pressure gauges. The communication module integrates a dual-mode transceiver. The AI chip utilizes a low-power design. Assembly is performed on an automated production line to ensure accurate electrical connections and mechanical fastening, reducing manual intervention and improving production consistency. This step requires particular attention to inter-module interface compatibility to prevent signal interference and performance degradation.

[0051] Functional Verification: Functional verification is conducted in a laboratory environment, testing the functionality of each module by simulating extreme environments (such as high temperature, low temperature, and high humidity). Tests include the signal transmission stability of the communication module, the accuracy and response time of the metering module, the fault prediction accuracy of the AI module, and the durability of the packaged module. Parameter adjustments are made based on the test results, such as optimizing the communication frequency band or adjusting the AI model threshold, to ensure system reliability under complex operating conditions. This process is a critical step in system development, ensuring that performance meets standards before actual deployment.

[0052] System Deployment: System deployment involves installing verified smart water meters in target areas, such as cold regions or coastal areas with high humidity. During installation, communication parameters are initialized to adapt to local network conditions, and AI models are loaded to match specific environmental requirements. Deployment must consider the impact of environmental factors on system performance, such as signal attenuation or water quality variations, to ensure stable system operation. This step also includes user training and the development of a maintenance plan to support long-term use.

[0053] Operation Monitoring: During the operation monitoring phase, the system collects real-time data (such as flow, pressure, and temperature) through sensors and uploads it to the cloud. The AI module analyzes this data using edge computing, detecting potential faults in real time and generating early warning reports. Data upload utilizes the IIoT platform to ensure secure and efficient transmission. Operation monitoring not only supports fault prediction but also provides a data foundation for system optimization, such as regularly updating AI model parameters to improve prediction accuracy. This process ensures the system's long-term reliability and maintenance efficiency in extreme environments.

[0054] Among them, such as Figure 2 As shown, adaptive communication module: an adaptive communication architecture integrating NB-IoT and LoRa is designed, using deep

[0055] Reinforcement learning (DRL) dynamically selects communication modes. The DRL agent adjusts its communication strategy based on environmental parameters (such as signal strength and interference levels) to optimize energy efficiency and coverage. The system uses sensors to perceive the environment in real time, and AI algorithms run on a low-power microcontroller, reducing unnecessary energy consumption.

[0056] Computational model:

[0057] Power consumption model: P total =P tx ·t tx +P rx ·t rx +P idle ·t idle Among them, P tx 、P rx 、P idle They are respectively the power consumption of sending, receiving and idle, t tx , t rx , t idle P tx 、P rx 、P idle Corresponding time;

[0058] Reward function: SNR is signal-to-noise ratio, latency is delay, a, β, γ are weight coefficients;

[0059] Spectral efficiency: η = B·log(1+SNR); where η is the spectral efficiency and B is the bandwidth.

[0060] Specifically, a dual-mode transceiver is used to support switching between NB-IoT and LoRa: a transceiver is developed that can flexibly switch between NB-IoT and LoRa communication modes to adapt to different environmental requirements, such as dense base station coverage scenarios in cities and long-distance communication needs in remote areas.

[0061] Hardware Design: Chip Selection: Choose a radio frequency chip that supports multiple protocols, such as a combination of Semtech SX1276 (supports LoRa) and Quectel BC95 (supports NB-IoT), or use software-defined radio (SDR) technology to achieve multi-mode compatibility.

[0062] Antenna design: Design wide-band antennas or switchable antenna systems to adapt to the different frequency bands of NB-IoT (700-900MHz) and LoRa (433 / 868 / 915MHz) to ensure signal transmission efficiency.

[0063] Power management: Design a low-power power management unit, such as through dynamic voltage scaling and sleep mode optimization to ensure that energy consumption in different modes is minimized.

[0064] Deploy a lightweight DRL model on a microcontroller and input environmental sensor data: Run a lightweight deep reinforcement learning (DRL) model on a resource-constrained microcontroller and optimize communication parameters in real time based on environmental sensor data.

[0065] Optimize communication parameters through iterative training to adapt to different scenarios: Through continuous learning and iterative training, the DRL model can adapt to changing environmental conditions, thereby improving communication performance and energy efficiency.

[0066] Micro-energy harvesting module: Utilizing thermoelectric effects and vibration energy conversion technology, the water meter is self-powered. The thermoelectric module generates electricity from temperature differences in the water pipes, the vibration module generates electricity from water flow vibrations, and the energy management unit dynamically distributes energy. The system optimizes energy harvesting efficiency through adaptive control. Calculation model:

[0067] Thermoelectric efficiency: Where ΔT is the temperature difference, ZT is the thermoelectric figure of merit, and T hot is the high temperature end temperature;

[0068] Vibrational Energy: Where m is the mass, w is the angular frequency, and A is the amplitude;

[0069] Energy storage capacity: Where C is capacitance and V is voltage.

[0070] Design a compact thermoelectric and piezoelectric composite module for installation in water meter pipes: Develop a small, efficient energy harvesting module that uses temperature differences and water flow vibrations within the water pipe to provide electricity for smart water meters.

[0071] Integrated adaptive energy management circuit to regulate energy distribution: Design intelligent circuits to dynamically distribute the energy output of thermoelectric and piezoelectric modules to provide a stable power supply for smart water meters.

[0072] Testing energy harvesting stability under different water flow conditions: Experimentally verifying the performance of the composite module under various water flow conditions to ensure the stability and reliability of energy supply.

[0073] like Figure 3 As shown in the figure, quantum-enhanced ultrasonic-electromagnetic hybrid metering: This paper proposes an ultrasonic-electromagnetic hybrid metering system based on quantum interference effect, which improves signal sensitivity through quantum state control. Ultrasonic sensors measure flow rate, electromagnetic sensors detect water quality parameters, and quantum interference units enhance signal contrast and reduce noise interference. Computational model:

[0074] Quantum state evolution: ψ(t) = U(t) | ψ(0); where U(t) is the time evolution operator and ψ(t) is the quantum state;

[0075] Interference intensity: I=|<ψ1|ψ2>| 2 ; Among them, ψ1 and ψ2 are quantum states;

[0076] Flow calculation: Q = k∫I(v)dv; where k is the calibration factor and v is the flow rate.

[0077] Integrating quantum dots or superconducting quantum interference devices (SQUIDs) into sensors: By integrating quantum dots or superconducting quantum interference devices (SQUIDs), the sensitivity and accuracy of sensors can be significantly improved, especially when detecting weak signals or coping with extreme environments.

[0078] Miniaturization is achieved through micro-nano manufacturing technology: reducing the size of the sensor and increasing its integration, making it suitable for space-constrained applications while maintaining or improving performance.

[0079] Optimizing quantum interference effects under laboratory simulated water flow conditions: Verify and optimize the quantum interference effects of sensors in simulated actual water flow environments to improve their performance and applicability.

[0080] Real-time fault diagnosis with edge AI: This solution deploys a lightweight fault prediction model on an edge AI chip, leveraging sensor data to analyze water meter status. The model uses transfer learning technology to adapt to different environments and predict potential faults through real-time reasoning.

[0081] Computational model:

[0082] Fault probability: P(fault) = σ(w x + b); where σ is the activation function, w is the weight, x is the input, and b is the bias;

[0083] Loss function: Among them, y is the true label, is the predicted value;

[0084] Model Updates: Where η is the learning rate.

[0085] Train and optimize neural network models on low-power AI chips: Train and optimize neural network models on resource-constrained low-power AI chips to ensure they run efficiently in embedded devices while maintaining good performance and low energy consumption.

[0086] Input sensor data (such as flow, pressure) and output failure probability: Use sensor data to monitor system status in real time, predict failure probability through neural network models, and realize intelligent early warning and maintenance.

[0087] Regularly update model parameters through the cloud: Use cloud computing resources to regularly update model parameters to improve model accuracy and adaptability while reducing computing pressure on the device side.

[0088] Flexible electronic packaging and bio-based materials: Using flexible electronic substrates and bio-based composite materials to design products that are resistant to extreme environments

[0089] Sensors and communication modules. Bio-based materials provide mechanical properties and environmental friendliness, and multi-layer structures enhance durability.

[0090] Computational model:

[0091] Coefficient of thermal expansion: Where L is the length and T is the temperature;

[0092] Young's modulus: Where σ is stress and ε is strain.

[0093] Select bio-based composite materials to design multi-layer flexible structures:

[0094] By selecting suitable bio-based composite materials and designing a multi-layer flexible structure, an extreme environment-resistant and environmentally friendly electronic packaging solution was developed to provide mechanical and electrical stability for smart water meters.

[0095] Encapsulating sensors and communication modules through green manufacturing processes: Encapsulating sensors and communication modules in a flexible substrate using green manufacturing processes enables a low-energy, low-pollution production process while ensuring packaging quality and functional integrity.

[0096] Reliability testing under temperature and mechanical stress conditions: By simulating temperature and mechanical stress conditions in extreme environments, the reliability of flexible packaging is tested to ensure its durability and stability in actual applications.

[0097] IIoT-driven flexible manufacturing production line, technical principles:

[0098] This paper proposes a flexible manufacturing production line concept integrated with IIoT, optimizing production processes through real-time data collection and analysis. The production line adopts a modular design, supporting multi-technology integration and rapid adjustment.

[0099] Computational model:

[0100] Production efficiency:

[0101] Pass rate:

[0102] Equipment utilization:

[0103] Design modular production cells, integrate communication, metering and packaging processes: Build flexible and efficient production cells, through

[0104] Modular design set

[0105] It integrates communication, measurement and packaging functions to adapt to diverse production needs and rapid process adjustments.

[0106] Deploy sensor networks and IIoT platforms to collect production data: Real-time production data is collected through sensor networks and IIoT platforms to provide data support for intelligent decision-making and optimization.

[0107] Optimize process parameters and quality control through data analysis: Utilize big data analysis technology to optimize process parameters, improve product quality and production efficiency, and achieve intelligent quality control.

[0108] Adaptive Communication and Micro-Energy Harvesting: One of the core innovations of this patent is the introduction of adaptive communication and micro-energy harvesting technology, which aims to explore possible paths for optimizing power consumption and coverage. From a technical perspective, the adaptive communication system integrates two low-power wide area network (LPWAN) technologies, NB-IoT and LoRa, and dynamically optimizes communication modes through deep reinforcement learning (DRL). Depending on environmental conditions (such as signal strength and interference levels), the system can select NB-IoT for urban environments or LoRa for long-distance coverage in remote areas, ensuring a balance between communication efficiency and coverage.

[0109] Micro-energy harvesting modules further enhance the system's sustainability, utilizing thermoelectric and vibration energy conversion technologies to extract power from ambient energy. For example, the thermoelectric module generates electricity from the temperature difference between the water pipe and the surrounding environment, while the vibration module generates electricity from the pipe vibration caused by the water flow. This self-powered design reduces reliance on traditional batteries, extending device lifespan and making it particularly suitable for remote or difficult-to-maintain locations.

[0110] The advantage of this technology is that it attempts to break through the bottleneck of the trade-off between power consumption and coverage in traditional low-power communications, making it possible for smart water meters to operate for a long time in extreme environments.

[0111] Quantum interference technology improves metering signal sensitivity: The innovation lies in utilizing quantum interference technology to enhance metering signal sensitivity and adapt to complex water quality conditions. Quantum interference is a quantum mechanical phenomenon that enhances signal detection capabilities through the superposition effect of waves. In this patent, the measurement system uses ultrasonic-electromagnetic hybrid technology based on quantum interference effects, aiming to improve the accuracy of micro-flow detection.

[0112] Ultrasonic flowmeters calculate flow by measuring the time difference between sound waves traveling through the water, while electromagnetic flowmeters use Faraday's principle of electromagnetic induction to detect the flow rate of conductive liquids. Incorporating quantum interference technology, the system can enhance signal contrast and reduce noise interference through quantum state manipulation (such as quantum dots or superconducting quantum interference devices (SQUIDs)), thereby maintaining high sensitivity even in complex water conditions such as high turbidity and high salinity.

[0113] It breaks through the accuracy limit of traditional metering systems and is particularly suitable for micro-flow (such as low water consumption at night) detection, providing technical support for the application of smart water meters in complex working conditions.

[0114] 1. Flexible packaging and bio-based materials enhance environmental adaptability and sustainability

[0115] The use of flexible electronic packaging and bio-based composite materials aims to enhance environmental adaptability and sustainability. Technically, the flexible packaging utilizes a flexible electronic substrate to ensure the device's electrical and mechanical stability in extreme temperatures (e.g., -40°C to 70°C). This design is particularly well-suited for environments with high temperatures, high humidity, or high salinity in coastal areas, preventing device aging or performance degradation due to temperature fluctuations or mechanical stress.

[0116] Bio-based composite materials are materials made from renewable biological resources (such as plant fibers and starch) and are more environmentally friendly than traditional petroleum-based materials. The patent promotes sustainable production by optimizing green manufacturing processes, reducing carbon footprints, and promoting sustainable production methods. This material selection not only enhances the environmental adaptability of the equipment but also reduces the environmental impact of the production process, aligning with the global trend towards a low-carbon economy.

[0117] This advantage ensures the long-term reliable operation of smart water meters in extreme environments, while promoting the green transformation of the manufacturing industry.

[0118] IIoT-driven flexible manufacturing supports intelligent production upgrades: The IIoT-driven flexible manufacturing concept has been proposed to support intelligent production upgrades. From a technical perspective, the Industrial Internet of Things (IIoT) connects production equipment, sensors, and control systems to enable real-time data collection and analysis. Flexible manufacturing refers to the ability of production systems to quickly adapt to changes in product design or adjustments in production scale.

[0119] The flexible manufacturing production line concept integrates communication, metrology, and packaging modules, leveraging an IIoT platform to enable real-time quality monitoring and process optimization. For example, a sensor network monitors equipment status, and the IIoT platform analyzes the data to automatically adjust process parameters to improve efficiency. This approach supports high-variety, low-volume production, adapting to fluctuating market demands while ensuring high-quality output.

[0120] The innovation of this concept is that it attempts to upgrade the production of smart water meters from traditional automation to Industry 4.0 standards, improve production efficiency and flexibility, and lay the foundation for technology promotion and large-scale application.

[0121] Those skilled in the art will understand that the above descriptions are merely preferred embodiments of the invention and are not intended to limit the invention. Although the invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will still be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the invention shall be included within the scope of protection of the invention. All technical features in this embodiment may be freely combined according to actual needs.

[0122] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A smart water meter system for extreme environments, characterized by: It includes adaptive communication module, micro energy collection module, quantum enhanced measurement module, edge AI real-time fault diagnosis module, and flexible electronic packaging module; Among them, the adaptive communication module integrates the adaptive communication architecture of NB-IoT and LoRa, and uses deep reinforcement learning (DRL) to dynamically select the communication mode; The micro-energy harvesting module uses thermoelectric effect and vibration energy conversion technology to provide self-powered water meters. It specifically includes a thermoelectric module, a vibration module, and an energy management unit. The thermoelectric module is used to generate electricity using the temperature difference of the water pipe; the vibration module is used to generate electricity using the vibration of the water flow; and the energy management unit is used to dynamically distribute energy. The quantum-enhanced metering module is an ultrasonic-electromagnetic composite metering system based on the quantum interference effect. It improves signal sensitivity through quantum state control. It specifically includes an ultrasonic sensor, an electromagnetic sensor, and a quantum interference unit. The ultrasonic sensor is used to measure flow rate, the electromagnetic sensor is used to detect water quality parameters, and the quantum interference unit is used to enhance signal contrast and reduce noise interference. Edge AI module deploys a lightweight fault prediction model on the edge AI chip, uses sensor data to analyze water meter status, adopts transfer learning technology to adapt to different environments, and predicts potential faults through real-time reasoning; Flexible electronic packaging modules are used to design sensors and communication modules that are resistant to extreme environments using flexible electronic substrates and bio-based composite materials.

2. The smart water meter system for extreme environments according to claim 1, characterized in that: The adaptive communication module uses sensors to perceive the environment in real time, and the AI algorithm runs on a low-power microcontroller. The specific calculation principle is as follows: Power consumption model: P total =P tx ·t tx +P rx ·t rx +P idle ·t idle ; Among them, P tx 、P rx 、P idle They are respectively the power consumption of sending, receiving and idle, t tx , t rx , t idle P tx 、P rx 、P idle Corresponding time; Reward function: SNR is signal-to-noise ratio, latency is delay, a, β, γ are weight coefficients; Spectral efficiency: η = B·log(1+SNR); where η is the spectral efficiency and B is the bandwidth.

3. The smart water meter system for extreme environments according to claim 1, characterized in that: The micro energy harvesting module optimizes energy harvesting efficiency through adaptive control. The specific calculation is as follows: Thermoelectric efficiency: Where ΔT is the temperature difference, ZT is the thermoelectric figure of merit, and T hot is the high temperature end temperature; Vibrational Energy: Where m is the mass, w is the angular frequency, and A is the amplitude; Energy storage capacity: Where C is capacitance and V is voltage.

4. The smart water meter system for extreme environments according to claim 1, characterized in that: The principle of the quantum enhanced metrology module is specifically calculated as follows: Quantum state evolution: ψ(t) = U(t) | ψ(0); where U(t) is the time evolution operator and ψ(t) is the quantum state; Interference intensity: I=|<ψ1|ψ2>| 2 ; Among them, ψ1 and ψ2 are quantum states; Flow calculation: Q = k∫I(v)dv; where k is the calibration factor and v is the flow rate.

5. The smart water meter system for extreme environments according to claim 1, characterized in that: The computing model of the edge AI real-time fault diagnosis module is as follows: Fault probability: P(fault) = σ(w x + b); where σ is the activation function, w is the weight, x is the input, and b is the bias; Loss function: Among them, y is the true label, is the predicted value; Model Updates: Where η is the learning rate.

6. The smart water meter system for extreme environments according to claim 1, characterized in that: The calculation model of the flexible electronic packaging module is as follows: Coefficient of thermal expansion: Where L is the length and T is the temperature; Young's modulus: Where σ is stress and ε is strain.

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