Water consumption evaluation system based on multiple water-saving elements

Abstract

The invention relates to a water saving evaluation system, in particular to a water consumption evaluation system based on multiple water saving elements, which comprises a data acquisition module, a data transmission module, a data processing module, a storage module, a water consumption evaluation module, a big data analysis module and an output display module, according to the water consumption evaluation system based on multiple water saving elements, through cooperative work of a data acquisition module, a data transmission module, a data processing module, a storage module, a water consumption evaluation module, a big data analysis module and an output display module, comprehensive evaluation of water consumption behaviors of users is achieved. All the modules are tightly connected and coordinated, efficient transmission, processing and storage of data are guaranteed, and a complete water-saving evaluation closed-loop system is formed.

Description

Technical Field

[0001] The invention relates to a water-saving evaluation system, in particular to a water-use evaluation system based on multiple water-saving elements. Background Art

[0002] As the global water shortage problem intensifies, many countries and regions are actively promoting and implementing water-saving measures, especially the widespread promotion of water-saving products and water-saving behaviors in households and commercial facilities. However, the existing water management system focuses on the monitoring and management of a single factor, such as water meter monitoring of total water consumption, the application of water-saving products, etc., but fails to comprehensively and systematically integrate the data of different water-saving factors for analysis, resulting in the evaluation of water-saving effects being difficult to accurately reflect the actual water use situation.

[0003] Existing water-saving technologies have many limitations and technical defects in practical applications:

[0004] Existing technologies mostly focus on single water use factors, such as total water meter monitoring, product-level water use records, or leakage detection. Due to the lack of integration of multiple water-saving factors such as the use of water-saving products, water use by quality, water-saving behavior, and underground leakage, the system fails to provide an accurate assessment of the user's overall water use. The user's water use behavior and equipment usage are often interrelated. A single monitoring cannot reflect the full picture of water use, and the evaluation system cannot effectively identify the synergy of various factors. For example, although a water-saving faucet is installed, if the proportion of water use by quality is not appropriate, it may still cause a waste of high-quality water resources. Therefore, the lack of comprehensive analysis of multiple water-saving factors is one of the main defects of existing technologies.

[0005] Existing water-saving systems generally use fixed standards to evaluate users' water use behaviors and water-saving effects, and lack the ability to adapt dynamically. As the water use environment (such as seasons, climate, etc.) and user behaviors (such as the increase or decrease of family members) change, fixed water use scoring standards can no longer accurately reflect users' actual water use. For example, the water demand in summer and winter varies greatly, and fixed standards often mislead users' actual water use efficiency. Existing technologies are unable to learn and dynamically adjust scoring standards based on user historical data, making it difficult to personalize and provide real-time feedback on the effects of water-saving behaviors. The lack of dynamic scoring and real-time adaptability results in lags and limitations in the water use evaluation of existing systems, and it is unable to accurately guide users to make reasonable water-saving optimizations under different water use conditions.

[0006] Existing water-saving systems usually only provide some basic data monitoring information, such as water volume data or water usage fees, and cannot provide users with clear water-saving behavior recommendations and feedback. It is difficult for users to obtain effective water-saving guidance through these data, and it is even more difficult to understand the impact of their specific behavior on overall water efficiency. For example, simply prompting users that "water usage exceeds the standard" is not enough to guide users to take specific water-saving measures. In addition, the existing system lacks an effective warning mechanism when users' water use behavior deviates from the standard, resulting in users being unable to adjust their water use behavior in a timely manner. Therefore, the feedback from the existing system lacks clear guidance and is difficult to effectively play a role in guiding water conservation in users' daily lives.

[0007] Most existing systems rely on traditional flow metering technology or manual monitoring in terms of technical implementation, and lack the means to accurately collect various water-saving factors. For example, underground leakage detection often requires manual inspections, and the detection frequency is low, time-consuming and labor-intensive, making it difficult to detect leakage problems in a timely manner. For the detection of water-saving products and water quality, the existing system cannot accurately detect the frequency of product use and water quality, making it difficult to comprehensively monitor the water-saving effects of various water-using equipment. Traditional detection methods lack real-time and automation levels, resulting in incomplete water-saving information and difficulty in providing accurate support for comprehensive evaluation. Summary of the invention

[0008] The purpose of the present invention is to provide a water use evaluation system based on multiple water-saving elements to solve the technical problems raised in the above-mentioned background technology.

[0009] Based on the above ideas, the present invention provides the following technical solutions:

[0010] A water use evaluation system based on multiple water-saving factors, including:

[0011] Data acquisition module, data transmission module, data processing module, storage module, water use evaluation module, big data analysis module and output display module;

[0012] The data collection module is used to collect water consumption data of users; the data collection module collects water-saving elements through sensor equipment and intelligent terminals, including:

[0013] The use of water-saving products, including: faucet and toilet models and corresponding water consumption;

[0014] Water use by quality, including: domestic and non-domestic water usage;

[0015] Water conservation behavior, including: users’ daily water conservation measures and frequency;

[0016] Underground leakage, including: underground pipeline leakage detection data;

[0017] The data transmission module is connected to the data acquisition module and the data processing module, and is used to transmit the collected data to the processing unit in the form of digital signals;

[0018] The data processing module is connected to the data acquisition module, the data transmission module and the storage module, and includes the following submodules:

[0019] The data standardization submodule is used to standardize the collected water-saving data and eliminate the unit differences between different data sources;

[0020] The weight allocation submodule is used to allocate weights according to the importance of each water-saving element to prepare for subsequent calculations;

[0021] The calculation core submodule is used to process each water-saving factor using preset algorithms and formulas to generate scores for each factor;

[0022] The storage module is connected to the data processing module and the output display module, and is used to store the processed water-saving element data and calculated scores, and retain historical data for use by the big data analysis module;

[0023] The water use evaluation module includes an algorithm process for calculating a comprehensive water-saving score, integrating the output of the data processing module, and calculating a comprehensive evaluation score based on the score and weight of each water-saving element. The specific process of the water use evaluation module is as follows:

[0024] Receive the scores of each factor and perform weighted average according to the weights;

[0025] Output the final comprehensive evaluation score to evaluate the user's overall water use status;

[0026] The big data analysis module is connected to the storage module and the water use evaluation module, and is used to dynamically adjust the scoring interval based on historical data, to continuously analyze user water use data, and to dynamically optimize the scoring interval of the evaluation system through a learning model to ensure that the system can adapt to changes in the environment and user habits;

[0027] The output display module presents the evaluation results, including the comprehensive evaluation score, sub-item scores, and suggestion feedback, through a display device or a mobile application. The module compares the user score with the preset score range based on the output of the big data analysis module, and provides warning information when the score deviates from the standard range.

[0028] The water use evaluation system based on multiple water-saving elements realizes a comprehensive evaluation of the user's water use behavior through the collaborative work of the data acquisition module, data transmission module, data processing module, storage module, water use evaluation module, big data analysis module and output display module. The close connection and coordination of each module ensures the efficient transmission, processing and storage of data, forming a complete closed-loop water-saving evaluation system. The sensor equipment and intelligent terminal of the data acquisition module realize the real-time collection of multi-dimensional data, ensuring the comprehensiveness of the evaluation data. The data transmission module ensures the timely transmission of data between the acquisition module and the processing module, effectively eliminating the delay of data acquisition and processing in the traditional system. The data standardization, weight distribution and calculation core submodules in the data processing module support the independent analysis of each water-saving element and its weighted combination, ensuring the objectivity and consistency of the scoring calculation. The water use evaluation module outputs the comprehensive score of each water-saving element, realizing a comprehensive water use evaluation. The big data analysis module adjusts the scoring interval based on historical data, so that the system can dynamically adapt to the user's habits and environmental changes, ensuring the accuracy and adaptability of the evaluation. The output display module provides users with visual scores and suggestions, which improves users' understanding of their own water use behavior and facilitates the adoption of improvement measures. Through the efficient collaboration of various modules, the system can accurately and dynamically reflect users' water use efficiency, significantly improving the practicality and intelligence of water-saving management.

[0029] Preferably, the scoring algorithm process for the use of water-saving products specifically includes the following steps:

[0030] S1. Obtain water-saving product information from the data acquisition module, including product types and their usage efficiency;

[0031] S2. Calculate the water-saving product usage score based on the product type. The calculation formula is as follows:

[0032] S p =E×F

[0033] Among them, S p represents the water-saving product score, E represents the water-saving efficiency of the product, and F represents the frequency of use factor;

[0034] S3, transmitting the calculation results to the data processing module as sub-score input of the comprehensive evaluation;

[0035] The introduction of two key parameters, water-saving efficiency and frequency of use, enables the scoring to effectively reflect the water-saving effects of different water-saving products in actual use. By calculating a single water-saving product usage score, the water-saving performance of specific water-using appliances of users is accurately quantified, providing clear sub-score support for the comprehensive score. It also distinguishes the contribution of different types of water-saving products, so that the system can better allocate weights in the comprehensive evaluation and achieve a more reasonable overall score.

[0036] Preferably, the scoring algorithm process of the water quality-based water use specifically includes the following steps:

[0037] S1. Obtain user water quality data from the data acquisition module, including quality ratio and usage.

[0038] S2. Calculate the water quality score. The calculation formula is as follows:

[0039] S q =P×A

[0040] Among them, S q It represents the score of water quality, P represents the water quality ratio factor, and A represents the actual application effect factor;

[0041] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0042] Differentiated water use scenarios, such as domestic water use and non-domestic water use, have different water-saving effects. Scoring with differentiated water use ratio factors and application effect factors can reflect the actual contribution of differentiated water use to overall water saving. By quantifying differentiated water use, the algorithm effectively improves the system's ability to capture water-saving details and provides users with more detailed water-saving suggestions. By using differentiated water use scores as part of the comprehensive score, the system enhances the comprehensiveness and accuracy of users' water use behaviors, which helps to reasonably distinguish the water-saving effects of different water uses.

[0043] Preferably, the scoring algorithm process of the water-saving behavior specifically includes the following steps:

[0044] S1. Collecting the user's daily water-saving behavior data from the data collection module, including the number and frequency of behaviors;

[0045] S2. Calculate the water-saving behavior score. The calculation formula is as follows:

[0046] S b =B×C

[0047] Among them, S b represents the score of water-saving behavior, B represents the frequency of behavior, and C represents the influencing factor of behavior;

[0048] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0049] It can quantify the user's daily water-saving behavior habits and convert them into scores, so that the comprehensive evaluation system can identify and record the user's water-saving habits. Through the behavior frequency and behavior influencing factors, the algorithm can distinguish the impact of different water-saving behaviors on the overall score, making the score more objective and accurate. The introduction of water-saving behavior scores enables the system to incorporate the contribution of user behavior into the comprehensive evaluation, enhances the evaluation system's sensitivity to user behavior, and supports users' self-improvement in actual water use behavior.

[0050] The scoring algorithm process of underground leakage specifically includes the following steps:

[0051] S1. Detect and obtain underground leakage data, including leakage volume and repair status, through leakage sensors connected to the data acquisition module;

[0052] S2. Calculate the underground leakage score. The calculation formula is as follows:

[0053] S l =L×R

[0054] Among them, S l represents underground leakage score, L represents leakage amount, and R represents repair effect factor;

[0055] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0056] By collecting leakage data through sensors and calculating leakage scores, the system can capture hidden problems such as water pipe leakage, and enhance the system's ability to monitor user water use data. The introduction of leakage volume and repair effect factors allows the score to accurately reflect the severity of underground leakage and encourage users to repair water pipe leakage in a timely manner to improve water use efficiency. This score is used as a separate dimension in the comprehensive score to ensure that the impact of underground leakage on the overall evaluation of the system is reasonably considered, and to encourage users to pay attention to and improve the problem of groundwater resource waste.

[0057] Preferably, the algorithm flow of the final comprehensive evaluation score includes:

[0058] S1. Summarize water-saving factor score data from the data processing module;

[0059] S2. Use the weighted average algorithm to calculate the comprehensive score. The calculation formula is as follows:

[0060] S total =w1×S p +w2×S q +w3×S b +w4×S l

[0061] Among them, S totalrepresents the comprehensive score, w1, w2, w3 and w4 are the weights of water-saving products, water quality-based water use, water-saving behavior and underground leakage respectively;

[0062] S3. The comprehensive scoring results are transmitted to the output display module and compared and evaluated according to the dynamic scoring range of the big data analysis module.

[0063] Through the weighted average algorithm, the process can quantify the impact of four water-saving factors, namely the use of water-saving products, water use based on quality, water-saving behavior and underground leakage, into a comprehensive score, making the evaluation results more holistic.

[0064] The introduction of factor weights enhances the system's ability to flexibly configure the contribution of different water-saving factors, ensuring that the evaluation results are more in line with the user's actual water use. The output is stored in the storage module and compared within the dynamic scoring range of the big data analysis module, which can monitor in real time whether the user's water use status meets the standards and provide timely feedback.

[0065] Preferably, an evaluation formula of a dynamic scoring interval is also included, which is used to dynamically evaluate the user's water use score, specifically including:

[0066] Set the initial score interval [L,H], where L is the lower limit of the score and H is the upper limit of the score;

[0067] The big data analysis module dynamically adjusts the interval [L′,H′] to reflect the user’s water consumption trend based on the statistical results of historical water consumption data;

[0068] Final comprehensive score S total After the calculation is completed, the output display module compares the score with the dynamic interval [L′, H′] and generates a warning message if the score is not within the interval;

[0069] The dynamic interval adjustment formula is: [L′,H′]=f(h), where h is the historical data.

[0070] The initial setting of the dynamic scoring range and the adjustment range based on historical data increase the flexibility of the scoring, ensuring that the evaluation system can make adaptive adjustments to the user's water use pattern. The introduction of historical data analysis in the actual scoring increases the system's sensitivity to the user's personalized water use, allowing the scoring range to be adjusted with user habits or seasonal changes, improving the accuracy of the evaluation. If the comprehensive score exceeds the dynamic range, the system will trigger a warning prompt to help users discover and take improvement measures in a timely manner when the score deviates from the standard.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] Through data collection, data processing and weight allocation, the system conducts detailed quantitative scoring of multiple water-saving factors such as the use of water-saving products, water quality-based water use, water-saving behavior and underground leakage. The weighted average algorithm of each factor combines an overall water use score, which makes the evaluation not only comprehensive, but also accurately reflects the actual performance of users in various water-saving aspects, providing users with detailed basis for water use improvement.

[0073] The big data analysis module dynamically adjusts the scoring range based on historical data, and the system can adaptively adjust the scoring criteria as the user's water use behavior patterns and environmental factors change. This function ensures the real-time and adaptability of the evaluation, allowing users to obtain personalized water use guidance that better meets their needs and improves the sustainability of water-saving effects.

[0074] The system's output display module intuitively presents the water use evaluation results, including sub-item scores and comprehensive scores, and generates warning messages when the user's score deviates from the preset standard range. This visual feedback helps users quickly understand the water use efficiency status and take optimization measures in a timely manner, promoting the improvement and effective management of water-saving behaviors. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 The present invention is a schematic diagram of the module relationship of a water use evaluation system based on multiple water-saving elements. DETAILED DESCRIPTION

[0076] A water use evaluation system based on multiple water-saving factors, including:

[0077] Data acquisition module, data transmission module, data processing module, storage module, water use evaluation module, big data analysis module and output display module;

[0078] The data collection module is used to collect water consumption data of users; the data collection module collects water-saving elements through sensor equipment and intelligent terminals, including:

[0079] The use of water-saving products, including: faucet and toilet models and corresponding water consumption;

[0080] Water use by quality, including: domestic and non-domestic water usage;

[0081] Water conservation behavior, including: users’ daily water conservation measures and frequency;

[0082] Underground leakage, including: underground pipeline leakage detection data;

[0083] The data transmission module is connected to the data acquisition module and the data processing module, and is used to transmit the collected data to the processing unit in the form of digital signals;

[0084] The data processing module is connected to the data acquisition module, the data transmission module and the storage module, and includes the following submodules:

[0085] The data standardization submodule is used to standardize the collected water-saving data and eliminate the unit differences between different data sources;

[0086] The weight allocation submodule is used to allocate weights according to the importance of each water-saving element to prepare for subsequent calculations;

[0087] The calculation core submodule is used to process each water-saving factor using preset algorithms and formulas to generate scores for each factor;

[0088] The storage module is connected to the data processing module and the output display module, and is used to store the processed water-saving element data and calculated scores, and retain historical data for use by the big data analysis module;

[0089] The water use evaluation module includes an algorithm process for calculating a comprehensive water-saving score, integrating the output of the data processing module, and calculating a comprehensive evaluation score based on the score and weight of each water-saving element. The specific process of the water use evaluation module is as follows:

[0090] Receive the scores of each factor and perform weighted average according to the weights;

[0091] Output the final comprehensive evaluation score to evaluate the user's overall water use status;

[0092] The big data analysis module is connected to the storage module and the water use evaluation module, and is used to dynamically adjust the scoring interval based on historical data, to continuously analyze user water use data, and to dynamically optimize the scoring interval of the evaluation system through a learning model to ensure that the system can adapt to changes in the environment and user habits;

[0093] The output display module presents the evaluation results, including the comprehensive evaluation score, sub-item scores, and suggestion feedback, through a display device or a mobile application. The module compares the user score with the preset score range based on the output of the big data analysis module, and provides warning information when the score deviates from the standard range.

[0094] The water use evaluation system based on multiple water-saving elements realizes a comprehensive evaluation of the user's water use behavior through the collaborative work of the data acquisition module, data transmission module, data processing module, storage module, water use evaluation module, big data analysis module and output display module. The close connection and coordination of each module ensures the efficient transmission, processing and storage of data, forming a complete closed-loop water-saving evaluation system. The sensor equipment and intelligent terminal of the data acquisition module realize the real-time collection of multi-dimensional data, ensuring the comprehensiveness of the evaluation data. The data transmission module ensures the timely transmission of data between the acquisition module and the processing module, effectively eliminating the delay of data acquisition and processing in the traditional system. The data standardization, weight distribution and calculation core submodules in the data processing module support the independent analysis of each water-saving element and its weighted combination, ensuring the objectivity and consistency of the scoring calculation. The water use evaluation module outputs the comprehensive score of each water-saving element, realizing a comprehensive water use evaluation. The big data analysis module adjusts the scoring interval based on historical data, so that the system can dynamically adapt to the user's habits and environmental changes, ensuring the accuracy and adaptability of the evaluation. The output display module provides users with visual scores and suggestions, which improves users' understanding of their own water use behavior and facilitates the adoption of improvement measures. Through the efficient collaboration of various modules, the system can accurately and dynamically reflect users' water use efficiency, significantly improving the practicality and intelligence of water-saving management.

[0095] Specifically, the scoring algorithm process for the use of water-saving products includes the following steps:

[0096] S1. Obtain water-saving product information from the data acquisition module, including product types and their usage efficiency;

[0097] S2. Calculate the water-saving product usage score based on the product type. The calculation formula is as follows:

[0098] S p =E×F

[0099] Among them, S p represents the water-saving product score, E represents the water-saving efficiency of the product, and F represents the frequency of use factor;

[0100] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0101] The system monitors the amount of water used in real time through smart flow meters and smart water meter sensors installed on faucets and toilets. The water meter sensor uses Hall effect sensor technology to detect the flow rate and accumulated water volume of the water flow, and record the frequency of use. The model and configuration information of the faucet and toilet are read from the smart terminal device and uploaded to the system database through the Internet of Things (IoT) platform. The flow meter automatically detects the amount of water used each time, records it as product usage data, and transmits it to the data acquisition module.

[0102] The introduction of two key parameters, water-saving efficiency and frequency of use, enables the scoring to effectively reflect the water-saving effects of different water-saving products in actual use. By calculating a single water-saving product usage score, the water-saving performance of specific water-using appliances of users is accurately quantified, providing clear sub-score support for the comprehensive score. It also distinguishes the contribution of different types of water-saving products, so that the system can better allocate weights in the comprehensive evaluation and achieve a more reasonable overall score.

[0103] Specifically, the scoring algorithm process of the water quality-based water use includes the following steps:

[0104] S1. Obtain user water quality data from the data acquisition module, including quality ratio and usage.

[0105] S2. Calculate the water quality score. The calculation formula is as follows:

[0106] S q =P×A

[0107] Among them, S q It represents the score of water quality, P represents the water quality ratio factor, and A represents the actual application effect factor;

[0108] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0109] The system uses different water meters and water quality sensors (such as TDS sensors, temperature and hardness sensors) to distinguish between domestic and non-domestic water, and records the amount of each type of water used. The TDS sensor distinguishes between domestic and non-domestic water by detecting the dissolved solids (TDS) content in the water. Non-domestic water (such as irrigation and cleaning) has a higher TDS value, and the system automatically classifies and records the water consumption for different purposes. Each type of water consumption is recorded independently by different water meters, and with the support of sensors, the water quality data is transmitted to the data acquisition module.

[0110] Differentiated water use scenarios, such as domestic water use and non-domestic water use, have different water-saving effects. Scoring with differentiated water use ratio factors and application effect factors can reflect the actual contribution of differentiated water use to overall water saving. By quantifying differentiated water use, the algorithm effectively improves the system's ability to capture water-saving details and provides users with more detailed water-saving suggestions. By using differentiated water use scores as part of the comprehensive score, the system enhances the comprehensiveness and accuracy of users' water use behaviors, which helps to reasonably distinguish the water-saving effects of different water uses.

[0111] Specifically, the scoring algorithm process of the water-saving behavior includes the following steps:

[0112] S1. Collecting the user's daily water-saving behavior data from the data collection module, including the number and frequency of behaviors;

[0113] S2. Calculate the water-saving behavior score. The calculation formula is as follows:

[0114] S b =B×C

[0115] Among them, S b represents the score of water-saving behavior, B represents the frequency of behavior, and C represents the influencing factor of behavior;

[0116] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0117] The system records the user's daily water-saving behavior through intelligent detection devices (such as infrared sensors) installed indoors, including whether the tap is turned off on time, whether the water usage time is reduced, etc. The infrared sensor detects the number and duration of the tap opening and closing, and records the user's water-saving operation frequency. The water-saving behavior data is regularly fed back on the user's terminal device, including the number of behaviors, frequency, and whether it is overused.

[0118] It can quantify the user's daily water-saving behavior habits and convert them into scores, so that the comprehensive evaluation system can identify and record the user's water-saving habits. Through the behavior frequency and behavior influencing factors, the algorithm can distinguish the impact of different water-saving behaviors on the overall score, making the score more objective and accurate. The introduction of water-saving behavior scores enables the system to incorporate the contribution of user behavior into the comprehensive evaluation, enhances the evaluation system's sensitivity to user behavior, and supports users' self-improvement in actual water use behavior.

[0119] The scoring algorithm process of underground leakage specifically includes the following steps:

[0120] S1. Detect and obtain underground leakage data, including leakage volume and repair status, through leakage sensors connected to the data acquisition module;

[0121] S2. Calculate the underground leakage score. The calculation formula is as follows:

[0122] S l =L×R

[0123] Among them, S l represents underground leakage score, L represents leakage amount, and R represents repair effect factor;

[0124] S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

[0125] The system installs pressure sensors and leakage detection sensors (such as acoustic wave detection sensors) in the underground water pipe network to monitor underground water pipe leakage. The pressure sensor measures the water pressure in the pipe. If a sudden drop in water pressure is detected, the system determines that there may be a leakage and records the leakage. The acoustic wave sensor locates the leakage by capturing the ultrasonic signal generated when the pipe leaks, and records the leakage amount and repair status and sends it to the data acquisition module.

[0126] By collecting leakage data through sensors and calculating leakage scores, the system can capture hidden problems such as water pipe leakage and enhance the system's ability to monitor user water use data. The introduction of leakage volume and repair effect factors allows the score to accurately reflect the severity of underground leakage and encourage users to repair water pipe leakage in a timely manner to improve water use efficiency. This score is used as a separate dimension in the comprehensive score to ensure that the impact of underground leakage on the overall evaluation of the system is reasonably considered, and to encourage users to pay attention to and improve the problem of groundwater resource waste.

[0127] Specifically, the algorithm flow of the final comprehensive evaluation score includes:

[0128] S1. Summarize water-saving factor score data from the data processing module;

[0129] S2. Use the weighted average algorithm to calculate the comprehensive score. The calculation formula is as follows:

[0130] S total =w1×S p +w2×S q +w3×S b +w4×S l

[0131] Among them, S total represents the comprehensive score, w1, w2, w3 and w4 are the weights of water-saving products, water quality-based water use, water-saving behavior and underground leakage respectively;

[0132] S3. The comprehensive scoring results are transmitted to the output display module and compared and evaluated according to the dynamic scoring range of the big data analysis module.

[0133] Through the weighted average algorithm, the process can quantify the impact of four water-saving factors, namely the use of water-saving products, water use based on quality, water-saving behavior and underground leakage, into a comprehensive score, making the evaluation results more holistic.

[0134] The introduction of factor weights enhances the system's ability to flexibly configure the contribution of different water-saving factors, ensuring that the evaluation results are more in line with the user's actual water use. The output is stored in the storage module and compared within the dynamic scoring range of the big data analysis module, which can monitor in real time whether the user's water use status meets the standards and provide timely feedback.

[0135] Specifically, it also includes an evaluation formula for the dynamic scoring interval, which is used to dynamically evaluate the user's water use score, including:

[0136] Set the initial score interval [L,H], where L is the lower limit of the score and H is the upper limit of the score;

[0137] The big data analysis module dynamically adjusts the interval [L′,H′] to reflect the user’s water consumption trend based on the statistical results of historical water consumption data;

[0138] Final comprehensive score S total After the calculation is completed, the output display module compares the score with the dynamic interval [L′, H′] and generates a warning message if the score is not within the interval;

[0139] The dynamic interval adjustment formula is: [L′,H′]=f(h), where h is the historical data.

[0140] The system initially sets a scoring interval, which represents the scoring range of reasonable water use. Through the analysis and adjustment of historical data, new intervals are dynamically set to ensure that the system adapts to changes in seasons, regions and user habits.

[0141] Evaluation feedback: When S total Within the range, the system displays "water-saving effect is good" in the terminal application.

[0142] If S total The system generates an early warning of "poor water use efficiency" and recommends optimization plans, such as reminding users to reduce the frequency of use of high-water-consuming products and promptly check underground pipes.

[0143] The initial setting of the dynamic scoring range and the adjustment range based on historical data increase the flexibility of the scoring, ensuring that the evaluation system can make adaptive adjustments to the user's water use pattern. The introduction of historical data analysis in the actual scoring improves the system's sensitivity to the user's personalized water use, allowing the scoring range to be adjusted with user habits or seasonal changes, improving the accuracy of the evaluation. If the comprehensive score exceeds the dynamic range, the system will trigger a warning prompt to help users discover and take improvement measures in a timely manner when the score deviates from the standard.

Claims

1. A water use evaluation system based on multiple water-saving factors, characterized in that: include: Data acquisition module, data transmission module, data processing module, storage module, water use evaluation module, big data analysis module and output display module; The data collection module is used to collect the user's water consumption data; The data acquisition module collects water-saving elements through sensor equipment and intelligent terminals, including: The use of water-saving products, including: faucet and toilet models and corresponding water consumption; Water use by quality, including: domestic and non-domestic water usage; Water conservation behavior, including: users’ daily water conservation measures and frequency; Underground leakage, including: underground pipeline leakage detection data; The data transmission module is connected to the data acquisition module and the data processing module, and is used to transmit the collected data to the processing unit in the form of digital signals; The data processing module is connected to the data acquisition module, the data transmission module and the storage module, and includes the following submodules: The data standardization submodule is used to standardize the collected water-saving data and eliminate the unit differences between different data sources; The weight allocation submodule is used to allocate weights according to the importance of each water-saving element to prepare for subsequent calculations; The calculation core submodule is used to process each water-saving factor using preset algorithms and formulas to generate scores for each factor; The storage module is connected to the data processing module and the output display module, and is used to store the processed water-saving element data and calculated scores, and retain historical data for use by the big data analysis module; The water use evaluation module includes an algorithm process for calculating a comprehensive water-saving score, integrating the output of the data processing module, and calculating a comprehensive evaluation score based on the score and weight of each water-saving element. The specific process of the water use evaluation module is as follows: Receive the scores of each factor and perform weighted average according to the weights; Output the final comprehensive evaluation score to evaluate the user's overall water use status; The big data analysis module is connected to the storage module and the water use evaluation module, and is used to dynamically adjust the scoring interval based on historical data, to continuously analyze user water use data, and to dynamically optimize the scoring interval of the evaluation system through a learning model to ensure that the system can adapt to changes in the environment and user habits; The output display module presents the evaluation results, including the comprehensive evaluation score, sub-item scores, and suggestion feedback, through a display device or a mobile application. The module compares the user score with the preset score range based on the output of the big data analysis module, and provides warning information when the score deviates from the standard range.

2. A water use evaluation system based on multiple water-saving elements according to claim 1, characterized in that: The scoring algorithm process for the use of water-saving products specifically includes the following steps: S1. Obtain water-saving product information from the data acquisition module, including product types and their usage efficiency; S2. Calculate the water-saving product usage score based on the product type. The calculation formula is as follows: S p =E×F Among them, S p represents the water-saving product score, E represents the water-saving efficiency of the product, and F represents the frequency of use factor; S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

3. A water use evaluation system based on multiple water-saving elements according to claim 2, characterized in that: The scoring algorithm process of the water quality-based water system specifically includes the following steps: S1. Obtain user water quality data from the data acquisition module, including quality ratio and usage. S2. Calculate the water quality score. The calculation formula is as follows: S q =P×A Among them, S q It represents the score of water quality, P represents the water quality ratio factor, and A represents the actual application effect factor; S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

4. A water use evaluation system based on multiple water-saving elements according to claim 3, characterized in that: The scoring algorithm process of the water-saving behavior specifically includes the following steps: S1. Collecting the user's daily water-saving behavior data from the data collection module, including the number and frequency of behaviors; S2. Calculate the water-saving behavior score. The calculation formula is as follows: S b =B×C Among them, S b represents the score of water-saving behavior, B represents the frequency of behavior, and C represents the influencing factor of behavior; S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

5. A water use evaluation system based on multiple water-saving elements according to claim 4, characterized in that: The scoring algorithm process of underground leakage specifically includes the following steps: S1. Detect and obtain underground leakage data, including leakage volume and repair status, through leakage sensors connected to the data acquisition module; S2. Calculate the underground leakage score. The calculation formula is as follows: S l =L×R Among them, S l represents underground leakage score, L represents leakage amount, and R represents repair effect factor; S3. The calculation results are transmitted to the data processing module as sub-score inputs for the comprehensive evaluation.

6. A water use evaluation system based on multiple water-saving elements according to claim 5, characterized in that: The algorithm flow of the final comprehensive evaluation score includes: S1. Summarize water-saving factor score data from the data processing module; S2. Use the weighted average algorithm to calculate the comprehensive score. The calculation formula is as follows: S total =w1×S p +w2×S q +w3×S b +w4×S l Among them, S total represents the comprehensive score, w1, w2, w3 and w4 are the weights of water-saving products, water quality-based water use, water-saving behavior and underground leakage respectively; S3. The comprehensive scoring results are transmitted to the output display module and compared and evaluated according to the dynamic scoring range of the big data analysis module.

7. A water use evaluation system based on multiple water-saving elements according to claim 6, characterized in that: It also includes an evaluation formula for dynamic scoring intervals, which is used to dynamically evaluate the user's water use score, including: Set the initial score interval [L,H], where L is the lower limit of the score and H is the upper limit of the score; The big data analysis module dynamically adjusts the interval [L′,H′] to reflect the user’s water consumption trend based on the statistical results of historical water consumption data; Final comprehensive score S total After the calculation is completed, the output display module compares the score with the dynamic interval [L′, H′] and generates a warning message if the score is not within the interval; The dynamic interval adjustment formula is: [L′,H′]=f(h), where h is the historical data.

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