Water meter service intelligent management method and system based on AI and medium

Abstract

The invention provides an AI-based water meter service intelligent management method and system and a medium, and belongs to the technical field of water meter management and big data. The method comprises the steps that water meter management system information including water meter equipment running state information and water consumption parameter monitoring information within preset time is obtained, water meter remaining power data, equipment working temperature data, water consumption duration data and water consumption data are extracted respectively, and the water meter remaining power condition can be judged according to the water meter remaining power data; the working temperature condition of the equipment can be judged according to the working temperature data of the equipment, processing is carried out according to the water consumption duration data to obtain an overtime water consumption index, processing is carried out according to the water consumption data to obtain an excessive water consumption index, processing is carried out through a preset water consumption behavior evaluation model to obtain a water consumption behavior evaluation index, and the water consumption behavior condition is judged. Through big data monitoring and processing, the running state of the water meter and the water using behavior condition of the user are mastered at any time, and the water meter management efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of water meter management and big data technology, and specifically to an AI-based intelligent management method, system and medium for water meter business. Background Art

[0002] Traditional water meters require manual on-site meter reading every month, which is inefficient and prone to errors. Smart water meters can automatically transmit data to the management system through remote meter reading, greatly improving meter reading efficiency. Remote meter reading not only reduces the waste of human resources, but also enables water departments to keep track of users' water use behavior at any time, providing an accurate data basis for the rational allocation and management of water resources.

[0003] The current water meter management technology still has the problem of single monitoring data, and the analysis and processing of collected data is not comprehensive enough, which cannot accurately reflect the overall operating status of the water meter and the personalized water use of users. There is a lack of technology that can objectively reflect the water use of different users.

[0004] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0005] The purpose of this application is to provide an AI-based intelligent management method, system and medium for water meter business, which can obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information, respectively extract water meter remaining power data, equipment operating temperature data, water use duration data and water use volume data, and judge the remaining power of the water meter according to the water meter remaining power data, and judge the equipment operating temperature according to the equipment operating temperature data. The overtime water use index is obtained by processing the water use duration data, and the excess water use index is obtained by processing the water use volume data. The water use behavior evaluation index is obtained by processing through a preset water use behavior evaluation model to judge the water use behavior. This application uses big data monitoring and processing to keep track of the water meter operation status and the user's water use behavior at any time, thereby improving the efficiency of water meter management.

[0006] This application provides an AI-based water meter business intelligent management method, including the following steps:

[0007] Obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information;

[0008] Extracting the remaining power data of the water meter and the equipment operating temperature data according to the water meter equipment operation status information, and extracting the water use duration data and the water use volume data according to the water use parameter monitoring information;

[0009] The remaining power of the water meter is determined by comparing the remaining power data of the water meter with a preset power threshold;

[0010] Comparing the device operating temperature data with a preset temperature threshold, determining the device operating temperature condition;

[0011] Processing the water use duration data to obtain water use timeout data;

[0012] Processing the water consumption data to obtain excess water consumption data;

[0013] Extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting overtime frequency data and overtime degree data according to the water overuse data;

[0014] Processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index;

[0015] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0016] The water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and a comparison between the water use behavior deviation rate and a preset water use behavior deviation rate threshold is determined.

[0017] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the remaining power of the water meter is judged by comparing the remaining power data of the water meter with a preset power threshold, specifically:

[0018] Comparing the remaining power data of the water meter with a preset first power threshold and a second power threshold;

[0019] The first power threshold is less than the second power threshold;

[0020] If the remaining power data of the water meter is less than or equal to the first power threshold, the power shortage information is sent according to the preset time frequency until the remaining power data of the water meter is greater than the first power threshold;

[0021] If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, a low power message is sent;

[0022] If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient.

[0023] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the device operating temperature data is compared with a preset temperature threshold to judge the device operating temperature condition, specifically:

[0024] Comparing the device operating temperature data with a preset first temperature threshold and a second temperature threshold;

[0025] The first temperature threshold is less than the second temperature threshold;

[0026] If the device operating temperature data is less than or equal to the first temperature threshold, a low temperature warning message is sent;

[0027] If the device operating temperature data is greater than the first temperature threshold and less than the second temperature threshold, the device operating temperature is normal;

[0028] If the device operating temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent.

[0029] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the water use timeout data is obtained by processing according to the water use duration data, specifically:

[0030] Comparing the water usage time data with a preset time threshold;

[0031] If the water usage time data is greater than or equal to the preset time threshold, abnormal time data is obtained;

[0032] Performing counting processing according to the abnormal duration data to obtain abnormal duration frequency data;

[0033] Compare the abnormal duration number data with a preset abnormal duration number threshold;

[0034] If the duration abnormal number of data is greater than or equal to the preset duration abnormal number threshold, the water use timeout data is obtained.

[0035] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the water consumption data is processed to obtain the excess water consumption data, specifically:

[0036] Comparing the water volume data with a preset water volume threshold;

[0037] If the water volume data is greater than or equal to the preset water volume threshold, abnormal water volume data is obtained;

[0038] Performing counting processing according to the water volume abnormality data to obtain water volume abnormality frequency data;

[0039] Comparing the water volume abnormality times data with a preset water volume abnormality times threshold;

[0040] If the water volume abnormality times data is greater than or equal to the preset water volume abnormality times threshold, the water excess data is obtained.

[0041] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the overtime water use index is obtained by processing the overtime frequency data and the overtime degree data, and the overtime water use index is obtained by processing the excess frequency data and the excess degree data, specifically:

[0042] The overtime frequency data and the overtime degree data are processed by a preset water use overtime evaluation model to obtain an overtime water use index;

[0043] The excess water use index is obtained by processing the excess frequency data and the excess degree data through a preset water use excess evaluation model.

[0044] Among them, in the AI-based intelligent management method for water meter business described in the present application, it is characterized in that the overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain the water use behavior evaluation index, specifically:

[0045] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0046] The calculation formula of the water use behavior evaluation model is:

[0047]

[0048] Among them, W χ is the water use behavior evaluation index, R v is the overtime water use index, H d is the excess water use index, ξ, ρ, δ are the preset characteristic coefficients.

[0049] Among them, in the AI-based water meter business intelligent management method described in the present application, it is characterized in that the water use behavior evaluation index is compared with the historical water use behavior evaluation index of the same type to obtain the water use behavior deviation rate, and the water use behavior deviation rate is judged against the preset water use behavior deviation rate threshold, specifically:

[0050] Comparing the water use behavior evaluation index with historical water use behavior evaluation indexes of the same type to obtain a water use behavior deviation rate;

[0051] Determine whether the water use behavior deviation rate is greater than a preset water use behavior deviation rate threshold;

[0052] If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, the water use behavior is wasting water resources;

[0053] If the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, the water use behavior is normal.

[0054] In a second aspect, the present application provides an AI-based water meter business intelligent management system, the system comprising: a memory and a processor, the memory comprising a program of an AI-based water meter business intelligent management method, the program of the AI-based water meter business intelligent management method being executed by the processor to implement the following steps:

[0055] Obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information;

[0056] Extracting the remaining power data of the water meter and the equipment operating temperature data according to the water meter equipment operation status information, and extracting the water use duration data and the water use volume data according to the water use parameter monitoring information;

[0057] The remaining power of the water meter is determined by comparing the remaining power data of the water meter with a preset power threshold;

[0058] Comparing the device operating temperature data with a preset temperature threshold, determining the device operating temperature condition;

[0059] Processing the water use duration data to obtain water use timeout data;

[0060] Processing the water consumption data to obtain excess water consumption data;

[0061] Extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting overtime frequency data and overtime degree data according to the water overuse data;

[0062] Processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index;

[0063] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0064] The water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and a comparison between the water use behavior deviation rate and a preset water use behavior deviation rate threshold is determined.

[0065] In the third aspect, the present application also provides a readable storage medium, which includes an AI-based water meter business intelligent management method program. When the AI-based water meter business intelligent management method program is executed by a processor, it implements the steps of an AI-based water meter business intelligent management method as described in any one of the above items.

[0066] As can be seen from the above, the present application provides an AI-based intelligent management method, system and medium for water meter business. By obtaining water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information, the remaining power data of the water meter, the equipment working temperature data, the water use duration data and the water volume data of the water meter are extracted respectively. The remaining power of the water meter can be judged according to the remaining power data of the water meter, and the working temperature of the equipment can be judged according to the equipment working temperature data. The overtime water use index is obtained by processing according to the water use duration data, and the excess water use index is obtained by processing according to the water volume data. The water use behavior evaluation model is used for processing to obtain the water use behavior evaluation index and judge the water use behavior. The present application uses big data monitoring and processing to keep track of the operating status of the water meter and the water use behavior of the user at any time, thereby improving the efficiency of water meter management. Through intelligent management of water meters, a large amount of water meter data can be processed in real time and quickly, and valuable information hidden behind the data can be excavated. This efficient data processing capability enables water management departments to more accurately grasp the water use situation and discover and solve problems in a timely manner. It can provide users with personalized water use recommendations and guidance based on their water use habits and data analysis results, helping users to rationally allocate water, improve water use efficiency and reduce waste.

[0067] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0069] Figure 1 A flowchart of an AI-based water meter business intelligent management method provided in an embodiment of the present application;

[0070] Figure 2A flow chart of determining the remaining power of a water meter according to an AI-based water meter business intelligent management method provided in an embodiment of the present application;

[0071] Figure 3 A flowchart of a method for intelligent management of water meter services based on AI for determining the operating temperature of equipment provided in an embodiment of the present application;

[0072] Figure 4 A flowchart of obtaining water use timeout data of an AI-based water meter business intelligent management method provided in an embodiment of the present application;

[0073] Figure 5 A flowchart of obtaining excess water usage data for an AI-based intelligent management method for water meter business provided in an embodiment of the present application. DETAILED DESCRIPTION

[0074] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0075] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0076] Please refer to Figure 1 , Figure 1 : is a flow chart of an AI-based water meter business intelligent management method in some embodiments of the present application. The AI-based water meter business intelligent management method is used in terminal devices, such as computers, mobile phone terminals, etc. The AI-based water meter business intelligent management method includes the following steps:

[0077] S101, obtaining water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information;

[0078] S102, extracting water meter remaining power data and equipment operating temperature data according to the water meter equipment operating status information, and extracting water use duration data and water use volume data according to the water use parameter monitoring information;

[0079] S103, comparing the remaining power data of the water meter with a preset power threshold to determine the remaining power of the water meter;

[0080] S104, comparing the device operating temperature data with a preset temperature threshold to determine the device operating temperature;

[0081] S105, processing the water use duration data to obtain water use timeout data;

[0082] S106, processing the water consumption data to obtain excess water consumption data;

[0083] S107, extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting excess frequency data and excess degree data according to the water excess data;

[0084] S108, processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index;

[0085] S109, processing the overtime water use index and the excess water use index through a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0086] S1010. Compare the water use behavior evaluation index with the historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and determine whether the water use behavior deviation rate is equal to a preset water use behavior deviation rate threshold.

[0087] Among them, this application obtains water meter management system information within a preset time, including water meter equipment operation status information and water use parameter monitoring information, and extracts water meter remaining power data, equipment working temperature data, water use duration data and water use volume data respectively. According to the water meter remaining power data, the remaining power of the water meter can be judged, and according to the equipment working temperature data, the equipment working temperature can be judged. According to the water use duration data, the overtime water use index is obtained, and according to the water use volume data, the excess water use index is obtained. The water use behavior evaluation model is used for processing to obtain the water use behavior evaluation index and judge the water use behavior. This application monitors and processes big data to keep track of the water meter operation status and the user's water use behavior at any time, thereby improving the efficiency of water meter management. Through intelligent management of water meters, a large amount of water meter data can be processed in real time and quickly, and valuable information hidden behind the data can be excavated. This efficient data processing capability enables water management departments to more accurately grasp the water use situation and promptly discover and solve problems. It can provide users with personalized water use suggestions and guidance based on their water use habits and data analysis results, which helps users to reasonably allocate water, improve water use efficiency, and reduce waste.

[0088] Please refer to Figure 2 , Figure 2 This is a flow chart of a water meter business intelligent management method based on AI in some embodiments of the present application for judging the remaining power of a water meter. According to an embodiment of the present invention, the remaining power of the water meter is judged by comparing the remaining power data of the water meter with a preset power threshold, specifically:

[0089] S201, comparing the remaining power data of the water meter with a preset first power threshold and a second power threshold;

[0090] S202: The first power threshold is less than the second power threshold;

[0091] S203: If the remaining power data of the water meter is less than or equal to the first power threshold, send power shortage information at a preset time frequency until the remaining power data of the water meter is greater than the first power threshold;

[0092] S204: If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, a low power message is sent;

[0093] S205: If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient.

[0094] Among them, in order to understand the remaining power of the water meter and ensure the normal operation of the water meter, the remaining power data of the water meter is compared with the preset first power threshold and the second power threshold. The first power threshold is less than the second power threshold. For example, the first power threshold is 15% and the second power threshold is 20%. If the remaining power data of the water meter is less than or equal to the first power threshold, the power shortage information is sent at a preset time frequency until the remaining power data of the water meter is greater than the first power threshold. For example, the remaining power data of the water meter is 13%. If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, the low power information is sent, for example, the remaining power data of the water meter is 20%. If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient, for example, the remaining power data of the water meter is 30%.

[0095] Please refer to Figure 3 , Figure 3 This is a flow chart of a method for intelligent management of water meter services based on AI in some embodiments of the present application for determining the operating temperature of a device. According to an embodiment of the present invention, the device operating temperature data is compared with a preset temperature threshold to determine the operating temperature of the device, specifically:

[0096] S301, comparing the device operating temperature data with a preset first temperature threshold and a second temperature threshold;

[0097] S302: The first temperature threshold is less than the second temperature threshold;

[0098] S303: If the device operating temperature data is less than or equal to the first temperature threshold, send a low temperature warning message;

[0099] S304: If the device operating temperature data is greater than the first temperature threshold and less than the second temperature threshold, the device operating temperature is normal;

[0100] S305: If the device operating temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent.

[0101] Among them, in order to ensure that the equipment working temperature is normal, the equipment working temperature data is compared with the preset first temperature threshold and the second temperature threshold. The first temperature threshold is less than the second temperature threshold. For example, the first temperature threshold is 0°C and the second temperature threshold is 40°C. If the equipment working temperature data is less than or equal to the first temperature threshold, a low temperature warning message is sent. For example, the equipment working temperature data is 0°C. If the equipment working temperature data is greater than the first temperature threshold and less than the second temperature threshold, the equipment working temperature is normal. For example, the equipment working temperature data is 25°C. If the equipment working temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent. For example, the equipment working temperature data is 42°C.

[0102] Please refer to Figure 4 , Figure 4 The flowchart of obtaining water use timeout data of a water meter business intelligent management method based on AI in some embodiments of the present application. According to an embodiment of the present invention, the water use timeout data is obtained by processing according to the water use duration data, specifically:

[0103] S401, comparing the water use duration data with a preset duration threshold;

[0104] S402: If the water usage time data is greater than or equal to a preset time threshold, abnormal time data is obtained;

[0105] S403, performing counting processing according to the abnormal duration data to obtain abnormal duration times data;

[0106] S404, comparing the abnormal duration number data with a preset abnormal duration number threshold;

[0107] S405: If the duration abnormality times data is greater than or equal to the preset duration abnormality times threshold, then the water use timeout data is obtained.

[0108] Among them, in order to reduce the single water use time and improve water use behavior habits, the water use time data is compared with the preset time threshold. If the water use time data is greater than or equal to the preset time threshold, the abnormal time data is obtained. For example, the water use time data is 35s, and the preset time threshold is 30s. Counting processing is performed based on the abnormal time data to obtain the abnormal time number data, and the abnormal time number data is compared with the preset abnormal time number threshold. If the abnormal time number data is greater than or equal to the preset abnormal time number threshold, the water use timeout data is obtained. For example, the abnormal time number data is 8 times, and the abnormal time number threshold is 5 times. It should be noted that, considering the normal long-term water use of users every day, the abnormal time number threshold can be set according to the number of users.

[0109] Please refer to Figure 5 , Figure 5 The present invention is a flowchart of obtaining water excess data in an AI-based water meter business intelligent management method in some embodiments of the present invention. According to an embodiment of the present invention, the water excess data is obtained by processing the water consumption data, specifically:

[0110] S501, comparing the water volume data with a preset water volume threshold;

[0111] S502: If the water volume data is greater than or equal to a preset water volume threshold, abnormal water volume data is obtained;

[0112] S503, performing counting processing according to the abnormal water volume data to obtain abnormal water volume frequency data;

[0113] S504, comparing the water volume abnormality times data with a preset water volume abnormality times threshold;

[0114] S505: If the water volume abnormality times data is greater than or equal to the preset water volume abnormality times threshold, then the water excess data is obtained.

[0115] Among them, in order to avoid waste of water resources and improve water utilization rate, the water consumption data is compared with the preset water consumption threshold. If the water consumption data is greater than or equal to the preset water consumption threshold, abnormal water consumption data is obtained. For example, the water consumption data is 1000 liters, and the preset water consumption threshold is 500 liters. Counting processing is performed according to the abnormal water consumption data to obtain abnormal water consumption times data, and the abnormal water consumption times data is compared with the preset abnormal water consumption times threshold. If the abnormal water consumption times data is greater than or equal to the preset abnormal water consumption times threshold, excessive water consumption data is obtained. For example, the abnormal water consumption times data is 5 times, and the preset abnormal water consumption times threshold is 3 times.

[0116] According to an embodiment of the present invention, the overtime frequency data and the overtime degree data are processed to obtain the overtime water use index, and the excess frequency data and the excess degree data are processed to obtain the excess water use index, specifically:

[0117] The overtime frequency data and the overtime degree data are processed by a preset water use overtime evaluation model to obtain an overtime water use index;

[0118] The excess water use index is obtained by processing the excess frequency data and the excess degree data through a preset water use excess evaluation model.

[0119] Among them, in order to reduce the overtime and excessive water use, so as to achieve water conservation and develop good water use behavior habits, the overtime frequency data and the overtime degree data are processed through a preset water use overtime evaluation model to obtain an overtime water use index, which can reflect the frequency and degree of overtime water use, and the excess frequency data and the excess degree data are processed through a preset water use overtime evaluation model to obtain an excess water use index, which can reflect the frequency and degree of excess water use;

[0120] The calculation formulas of the water overtime evaluation model and the water excess evaluation model are respectively:

[0121]

[0122] Among them, R v is the overtime water use index, H d is the excess water use index, r t 、r c are respectively the timeout frequency data and the timeout degree data, ha 、h e They are excess frequency data and excess degree data, β、υ 1 ,υ 2 It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water meter operation monitoring database platform).

[0123] According to an embodiment of the present invention, the overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index, specifically:

[0124] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0125] The calculation formula of the water use behavior evaluation model is:

[0126]

[0127] Among them, W χ is the water use behavior evaluation index, R v is the overtime water use index, H d is the excess water use index, ξ, ρ, δ are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset water meter operation monitoring database platform).

[0128] Among them, in order to comprehensively reflect the user's water use behavior habits, the overtime water use index and the excessive water use index are processed through a preset water use behavior evaluation model to obtain the water use behavior evaluation index. The overtime water use index can reflect the frequency and degree of overtime water use, and the excessive water use index can reflect the frequency and degree of excessive water use. The water use behavior evaluation index can comprehensively reflect the user's water use behavior and water use situation, and help users understand their own water use habits.

[0129] According to an embodiment of the present invention, the water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and the water use behavior deviation rate is judged to be different from a preset water use behavior deviation rate threshold, specifically:

[0130] Comparing the water use behavior evaluation index with historical water use behavior evaluation indexes of the same type to obtain a water use behavior deviation rate;

[0131] Determine whether the water use behavior deviation rate is greater than a preset water use behavior deviation rate threshold;

[0132] If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, the water use behavior is wasting water resources;

[0133] If the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, the water use behavior is normal.

[0134] Among them, in order to improve the utilization rate of water resources and reduce the behavior habits of wasting water, the water use behavior evaluation index is compared with the historical water use behavior evaluation index of the same type to obtain the water use behavior deviation rate, and judge whether the water use behavior deviation rate is greater than the preset water use behavior deviation rate threshold. If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, then the water use behavior is wasting water resources; if the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, then the water use behavior is normal.

[0135] According to an embodiment of the present invention, it also includes:

[0136] Extracting water quality detection information according to the water use parameter monitoring information, including soluble solids data, water hardness data, pH data and residual chlorine content data;

[0137] The soluble solid data, water hardness data, pH data and residual chlorine content data are processed by a preset water quality evaluation model to obtain a water quality index;

[0138] Comparing the water quality index with a preset water quality threshold to obtain a water quality deviation rate;

[0139] Determining whether the water quality deviation rate is greater than a preset water quality deviation rate threshold;

[0140] If the water quality deviation rate is greater than or equal to the water quality deviation rate threshold, the water quality index exceeds the standard;

[0141] If the water quality deviation rate is less than the water quality deviation rate threshold, the water quality index meets the requirements;

[0142] The calculation formula of the water quality assessment model is:

[0143]

[0144] Among them, Q w is the water quality index, k g ,y s 、p h 、c n They are soluble solid data, water hardness data, pH data and residual chlorine content data, η, θ, κ 1 , κ 2 , π are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset water meter operation monitoring database platform).

[0145] Among them, in order to improve the water quality index of water use, water quality detection information is extracted according to the water parameter monitoring information, including soluble solid data, water hardness data, pH data and residual chlorine content data, and then processed through a preset water quality evaluation model to obtain a water quality index for water use, and the water quality index for water use is compared with a preset water quality threshold to obtain a water quality deviation rate, and determine whether the water quality deviation rate is greater than the preset water quality deviation rate threshold. If the water quality deviation rate is greater than or equal to the water quality deviation rate threshold, the water quality index of water use exceeds the standard. For example, the water quality deviation rate is 2%, and the water quality deviation rate threshold is 2%. If the water quality deviation rate is less than the water quality deviation rate threshold, the water quality index of water use meets the requirements. For example, the water quality deviation rate is 1.5%, and the water quality deviation rate threshold is 2%. The water quality index of water use comprehensively reflects the water quality of water use, and various parameters are set according to actual needs. For example, household water use should minimize costs while ensuring water quality safety and hygiene, and it is also necessary to strengthen water quality monitoring and management to ensure that the quality of household water meets relevant standards and requirements.

[0146] According to an embodiment of the present invention, it also includes:

[0147] Extracting water pressure data based on the water use parameter monitoring information;

[0148] Comparing the water pressure data with a preset first water pressure threshold and a second water pressure threshold;

[0149] The first water pressure threshold is less than the second water pressure threshold;

[0150] If the water pressure data is less than the first water pressure threshold, a low water pressure message is sent;

[0151] If the water pressure data is greater than or equal to the first water pressure threshold and less than or equal to the second water pressure threshold, the water pressure is normal;

[0152] If the water pressure data is greater than the second water pressure threshold, a high water pressure message is sent.

[0153] Among them, in order to ensure the normal water pressure of water use, the water pressure data of water use is extracted according to the water parameter monitoring information, and the water pressure data of water use is compared with the preset first water pressure threshold and the second water pressure threshold. The first water pressure threshold is less than the second water pressure threshold, for example, the first water pressure threshold is 0.2MPa, and the second water pressure threshold is 0.4MPa. If the water pressure data is less than the first water pressure threshold, the water pressure is too low information is sent, for example, the water pressure data is 0.1MPa. If the water pressure data is greater than or equal to the first water pressure threshold and less than or equal to the second water pressure threshold, the water pressure is normal, for example, the water pressure data is 0.3MPa. If the water pressure data is greater than the second water pressure threshold, the water pressure is too high information is sent, for example, the water pressure data is 0.5MPa.

[0154] The present invention also discloses an AI-based water meter business intelligent management system, including a memory and a processor, wherein the memory includes an AI-based water meter business intelligent management method program, and when the AI-based water meter business intelligent management method program is executed by the processor, the following steps are implemented:

[0155] Obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information;

[0156] Extracting the remaining power data of the water meter and the equipment operating temperature data according to the water meter equipment operation status information, and extracting the water use duration data and the water use volume data according to the water use parameter monitoring information;

[0157] The remaining power of the water meter is determined by comparing the remaining power data of the water meter with a preset power threshold;

[0158] Comparing the device operating temperature data with a preset temperature threshold, determining the device operating temperature condition;

[0159] Processing the water use duration data to obtain water use timeout data;

[0160] Processing the water consumption data to obtain excess water consumption data;

[0161] Extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting overtime frequency data and overtime degree data according to the water overuse data;

[0162] Processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index;

[0163] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0164] The water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and a comparison between the water use behavior deviation rate and a preset water use behavior deviation rate threshold is determined.

[0165] Among them, this application obtains water meter management system information within a preset time, including water meter equipment operation status information and water use parameter monitoring information, and extracts water meter remaining power data, equipment working temperature data, water use duration data and water use volume data respectively. According to the water meter remaining power data, the remaining power of the water meter can be judged, and according to the equipment working temperature data, the equipment working temperature can be judged. According to the water use duration data, the overtime water use index is obtained, and according to the water use volume data, the excess water use index is obtained. The water use behavior evaluation model is used for processing to obtain the water use behavior evaluation index and judge the water use behavior. This application monitors and processes big data to keep track of the water meter operation status and the user's water use behavior at any time, thereby improving the efficiency of water meter management. Through intelligent management of water meters, a large amount of water meter data can be processed in real time and quickly, and valuable information hidden behind the data can be excavated. This efficient data processing capability enables water management departments to more accurately grasp the water use situation and promptly discover and solve problems. It can provide users with personalized water use suggestions and guidance based on their water use habits and data analysis results, which helps users to reasonably allocate water, improve water use efficiency, and reduce waste.

[0166] According to an embodiment of the present invention, the comparison between the remaining power data of the water meter and a preset power threshold value to determine the remaining power of the water meter is specifically as follows:

[0167] Comparing the remaining power data of the water meter with a preset first power threshold and a second power threshold;

[0168] The first power threshold is less than the second power threshold;

[0169] If the remaining power data of the water meter is less than or equal to the first power threshold, the power shortage information is sent according to the preset time frequency until the remaining power data of the water meter is greater than the first power threshold;

[0170] If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, a low power message is sent;

[0171] If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient.

[0172] Among them, in order to understand the remaining power of the water meter and ensure the normal operation of the water meter, the remaining power data of the water meter is compared with the preset first power threshold and the second power threshold. The first power threshold is less than the second power threshold. For example, the first power threshold is 15% and the second power threshold is 20%. If the remaining power data of the water meter is less than or equal to the first power threshold, the power shortage information is sent at a preset time frequency until the remaining power data of the water meter is greater than the first power threshold. For example, the remaining power data of the water meter is 13%. If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, the low power information is sent, for example, the remaining power data of the water meter is 20%. If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient, for example, the remaining power data of the water meter is 30%.

[0173] According to an embodiment of the present invention, comparing the device operating temperature data with a preset temperature threshold to determine the device operating temperature condition is specifically as follows:

[0174] Comparing the device operating temperature data with a preset first temperature threshold and a second temperature threshold;

[0175] The first temperature threshold is less than the second temperature threshold;

[0176] If the device operating temperature data is less than or equal to the first temperature threshold, a low temperature warning message is sent;

[0177] If the device operating temperature data is greater than the first temperature threshold and less than the second temperature threshold, the device operating temperature is normal;

[0178] If the device operating temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent.

[0179] Among them, in order to ensure that the equipment working temperature is normal, the equipment working temperature data is compared with the preset first temperature threshold and the second temperature threshold. The first temperature threshold is less than the second temperature threshold. For example, the first temperature threshold is 0°C and the second temperature threshold is 40°C. If the equipment working temperature data is less than or equal to the first temperature threshold, a low temperature warning message is sent. For example, the equipment working temperature data is 0°C. If the equipment working temperature data is greater than the first temperature threshold and less than the second temperature threshold, the equipment working temperature is normal. For example, the equipment working temperature data is 25°C. If the equipment working temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent. For example, the equipment working temperature data is 42°C.

[0180] According to an embodiment of the present invention, the water use timeout data is obtained by processing the water use time data, specifically:

[0181] Comparing the water usage time data with a preset time threshold;

[0182] If the water usage time data is greater than or equal to the preset time threshold, abnormal time data is obtained;

[0183] Performing counting processing according to the abnormal duration data to obtain abnormal duration frequency data;

[0184] Compare the abnormal duration number data with a preset abnormal duration number threshold;

[0185] If the duration abnormal number of data is greater than or equal to the preset duration abnormal number threshold, the water use timeout data is obtained.

[0186] Among them, in order to reduce the single water use time and improve water use behavior habits, the water use time data is compared with the preset time threshold. If the water use time data is greater than or equal to the preset time threshold, the abnormal time data is obtained. For example, the water use time data is 35s, and the preset time threshold is 30s. Counting processing is performed based on the abnormal time data to obtain the abnormal time number data, and the abnormal time number data is compared with the preset abnormal time number threshold. If the abnormal time number data is greater than or equal to the preset abnormal time number threshold, the water use timeout data is obtained. For example, the abnormal time number data is 8 times, and the abnormal time number threshold is 5 times. It should be noted that, considering the normal long-term water use of users every day, the abnormal time number threshold can be set according to the number of users.

[0187] According to an embodiment of the present invention, the water consumption data is processed to obtain excess water consumption data, specifically:

[0188] Comparing the water volume data with a preset water volume threshold;

[0189] If the water volume data is greater than or equal to the preset water volume threshold, abnormal water volume data is obtained;

[0190] Performing counting processing according to the water volume abnormality data to obtain water volume abnormality frequency data;

[0191] Comparing the water volume abnormality times data with a preset water volume abnormality times threshold;

[0192] If the water volume abnormality times data is greater than or equal to the preset water volume abnormality times threshold, the water excess data is obtained.

[0193] Among them, in order to avoid waste of water resources and improve water utilization rate, the water consumption data is compared with the preset water consumption threshold. If the water consumption data is greater than or equal to the preset water consumption threshold, abnormal water consumption data is obtained. For example, the water consumption data is 1000 liters, and the preset water consumption threshold is 500 liters. Counting processing is performed according to the abnormal water consumption data to obtain abnormal water consumption times data, and the abnormal water consumption times data is compared with the preset abnormal water consumption times threshold. If the abnormal water consumption times data is greater than or equal to the preset abnormal water consumption times threshold, excessive water consumption data is obtained. For example, the abnormal water consumption times data is 5 times, and the preset abnormal water consumption times threshold is 3 times.

[0194] According to an embodiment of the present invention, the overtime frequency data and the overtime degree data are processed to obtain the overtime water use index, and the excess frequency data and the excess degree data are processed to obtain the excess water use index, specifically:

[0195] The overtime frequency data and the overtime degree data are processed by a preset water use overtime evaluation model to obtain an overtime water use index;

[0196] The excess water use index is obtained by processing the excess frequency data and the excess degree data through a preset water use excess evaluation model.

[0197] Among them, in order to reduce the overtime and excessive water use, so as to achieve water conservation and develop good water use behavior habits, the overtime frequency data and the overtime degree data are processed through a preset water use overtime evaluation model to obtain an overtime water use index, which can reflect the frequency and degree of overtime water use, and the excess frequency data and the excess degree data are processed through a preset water use overtime evaluation model to obtain an excess water use index, which can reflect the frequency and degree of excess water use;

[0198] The calculation formulas of the water overtime evaluation model and the water excess evaluation model are respectively:

[0199]

[0200] Among them, R v is the overtime water use index, H d is the excess water use index, r t 、r c are respectively the timeout frequency data and the timeout degree data, h a 、h e They are excess frequency data and excess degree data, β、υ 1 ,υ 2 It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water meter operation monitoring database platform).

[0201] According to an embodiment of the present invention, the overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index, specifically:

[0202] The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index;

[0203] The calculation formula of the water use behavior evaluation model is:

[0204]

[0205] Among them, W χ is the water use behavior evaluation index, R v is the overtime water use index, G d is the excess water use index, ξ, ρ, δ are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset water meter operation monitoring database platform).

[0206] Among them, in order to comprehensively reflect the user's water use behavior habits, the overtime water use index and the excessive water use index are processed through a preset water use behavior evaluation model to obtain the water use behavior evaluation index. The overtime water use index can reflect the frequency and degree of overtime water use, and the excessive water use index can reflect the frequency and degree of excessive water use. The water use behavior evaluation index can comprehensively reflect the user's water use behavior and water use situation, and help users understand their own water use habits.

[0207] According to an embodiment of the present invention, the water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and the water use behavior deviation rate is judged to be different from a preset water use behavior deviation rate threshold, specifically:

[0208] Comparing the water use behavior evaluation index with historical water use behavior evaluation indexes of the same type to obtain a water use behavior deviation rate;

[0209] Determine whether the water use behavior deviation rate is greater than a preset water use behavior deviation rate threshold;

[0210] If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, the water use behavior is wasting water resources;

[0211] If the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, the water use behavior is normal.

[0212] Among them, in order to improve the utilization rate of water resources and reduce the behavior habits of wasting water, the water use behavior evaluation index is compared with the historical water use behavior evaluation index of the same type to obtain the water use behavior deviation rate, and judge whether the water use behavior deviation rate is greater than the preset water use behavior deviation rate threshold. If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, then the water use behavior is wasting water resources; if the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, then the water use behavior is normal.

[0213] According to an embodiment of the present invention, it also includes:

[0214] Extracting water quality detection information according to the water use parameter monitoring information, including soluble solids data, water hardness data, pH data and residual chlorine content data;

[0215] The soluble solid data, water hardness data, pH data and residual chlorine content data are processed by a preset water quality evaluation model to obtain a water quality index;

[0216] Comparing the water quality index with a preset water quality threshold to obtain a water quality deviation rate;

[0217] Determining whether the water quality deviation rate is greater than a preset water quality deviation rate threshold;

[0218] If the water quality deviation rate is greater than or equal to the water quality deviation rate threshold, the water quality index exceeds the standard;

[0219] If the water quality deviation rate is less than the water quality deviation rate threshold, the water quality index meets the requirements;

[0220] The calculation formula of the water quality assessment model is:

[0221]

[0222] Among them, Q w is the water quality index, k g ,y s 、p h 、c n They are soluble solid data, water hardness data, pH data and residual chlorine content data, η, θ, κ 1 , κ 2 , π are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset water meter operation monitoring database platform).

[0223] Among them, in order to improve the water quality index of water use, water quality detection information is extracted according to the water parameter monitoring information, including soluble solid data, water hardness data, pH data and residual chlorine content data, and then processed through a preset water quality evaluation model to obtain a water quality index for water use, and the water quality index for water use is compared with a preset water quality threshold to obtain a water quality deviation rate, and determine whether the water quality deviation rate is greater than the preset water quality deviation rate threshold. If the water quality deviation rate is greater than or equal to the water quality deviation rate threshold, the water quality index of water use exceeds the standard. For example, the water quality deviation rate is 2%, and the water quality deviation rate threshold is 2%. If the water quality deviation rate is less than the water quality deviation rate threshold, the water quality index of water use meets the requirements. For example, the water quality deviation rate is 1.5%, and the water quality deviation rate threshold is 2%. The water quality index of water use comprehensively reflects the water quality of water use, and various parameters are set according to actual needs. For example, household water use should minimize costs while ensuring water quality safety and hygiene, and it is also necessary to strengthen water quality monitoring and management to ensure that the quality of household water meets relevant standards and requirements.

[0224] According to an embodiment of the present invention, it also includes:

[0225] Extracting water pressure data based on the water use parameter monitoring information;

[0226] Comparing the water pressure data with a preset first water pressure threshold and a second water pressure threshold;

[0227] The first water pressure threshold is less than the second water pressure threshold;

[0228] If the water pressure data is less than the first water pressure threshold, a low water pressure message is sent;

[0229] If the water pressure data is greater than or equal to the first water pressure threshold and less than or equal to the second water pressure threshold, the water pressure is normal;

[0230] If the water pressure data is greater than the second water pressure threshold, a high water pressure message is sent.

[0231] Among them, in order to ensure the normal water pressure of water use, the water pressure data of water use is extracted according to the water parameter monitoring information, and the water pressure data of water use is compared with the preset first water pressure threshold and the second water pressure threshold. The first water pressure threshold is less than the second water pressure threshold, for example, the first water pressure threshold is 0.2MPa, and the second water pressure threshold is 0.4MPa. If the water pressure data is less than the first water pressure threshold, the water pressure is too low information is sent, for example, the water pressure data is 0.1MPa. If the water pressure data is greater than or equal to the first water pressure threshold and less than or equal to the second water pressure threshold, the water pressure is normal, for example, the water pressure data is 0.3MPa. If the water pressure data is greater than the second water pressure threshold, the water pressure is too high information is sent, for example, the water pressure data is 0.5MPa.

[0232] The third aspect of the present invention also provides a readable storage medium, which includes an AI-based water meter business intelligent management method program. When the AI-based water meter business intelligent management method program is executed by a processor, it implements the steps of an AI-based water meter business intelligent management method as described in any one of the above items.

[0233] The present invention discloses an AI-based intelligent management method, system and medium for water meter business. By acquiring water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information, the remaining power data of the water meter, the equipment operating temperature data, the water use duration data and the water use volume data of the water meter are extracted respectively. The remaining power of the water meter can be judged according to the remaining power data of the water meter, the equipment operating temperature can be judged according to the equipment operating temperature data, the overtime water use index is obtained according to the water use duration data, the excess water use index is obtained according to the water use volume data, and the water use behavior evaluation index is obtained by processing through a preset water use behavior evaluation model to judge the water use behavior. The present application uses big data monitoring and processing to keep track of the water meter operating status and the user's water use behavior at any time, thereby improving the efficiency of water meter management. Through intelligent management of water meters, a large amount of water meter data can be processed in real time and quickly, and valuable information hidden behind the data can be excavated. This efficient data processing capability enables water management departments to more accurately grasp the water use situation and promptly discover and solve problems. It can provide users with personalized water use recommendations and guidance based on their water use habits and data analysis results, helping users to rationally allocate water, improve water use efficiency and reduce waste.

[0234] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0235] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0236] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0237] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories, random access memories, magnetic disks or optical disks, and other media that can store program codes.

[0238] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. An AI-based intelligent management method for water meter services, characterized in that: The following steps are involved: Obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information; Extracting the remaining power data of the water meter and the equipment operating temperature data according to the water meter equipment operation status information, and extracting the water use duration data and the water use volume data according to the water use parameter monitoring information; The remaining power of the water meter is determined by comparing the remaining power data of the water meter with a preset power threshold; Comparing the device operating temperature data with a preset temperature threshold, determining the device operating temperature condition; Processing the water use duration data to obtain water use timeout data; Processing the water consumption data to obtain excess water consumption data; Extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting overtime frequency data and overtime degree data according to the water overuse data; Processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index; The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index; The water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and a comparison between the water use behavior deviation rate and a preset water use behavior deviation rate threshold is determined.

2. According to claim 1, the AI-based water meter business intelligent management method is characterized in that: The comparison between the remaining power data of the water meter and the preset power threshold is used to determine the remaining power of the water meter, specifically: Comparing the remaining power data of the water meter with a preset first power threshold and a second power threshold; The first power threshold is less than the second power threshold; If the remaining power data of the water meter is less than or equal to the first power threshold, the power shortage information is sent according to the preset time frequency until the remaining power data of the water meter is greater than the first power threshold; If the remaining power data of the water meter is greater than the first power threshold and less than or equal to the second power threshold, a low power message is sent; If the remaining power data of the water meter is greater than the second power threshold, the remaining power of the water meter is sufficient.

3. According to claim 2, the AI-based intelligent management method for water meter services is characterized in that: The device operating temperature data is compared with a preset temperature threshold to determine the device operating temperature, specifically: Comparing the device operating temperature data with a preset first temperature threshold and a second temperature threshold; The first temperature threshold is less than the second temperature threshold; If the device operating temperature data is less than or equal to the first temperature threshold, a low temperature warning message is sent; If the device operating temperature data is greater than the first temperature threshold and less than the second temperature threshold, the device operating temperature is normal; If the device operating temperature data is greater than or equal to the second temperature threshold, a high temperature warning message is sent.

4. According to claim 3, the AI-based water meter business intelligent management method is characterized in that: The water use timeout data is obtained by processing the water use time data, specifically: Comparing the water usage time data with a preset time threshold; If the water usage time data is greater than or equal to the preset time threshold, abnormal time data is obtained; Performing counting processing according to the abnormal duration data to obtain abnormal duration frequency data; Compare the abnormal duration number data with a preset abnormal duration number threshold; If the duration abnormal number of data is greater than or equal to the preset duration abnormal number threshold, the water use timeout data is obtained.

5. According to claim 4, the AI-based intelligent management method for water meter services is characterized in that: The processing according to the water consumption data to obtain the water consumption excess data is specifically as follows: Comparing the water volume data with a preset water volume threshold; If the water volume data is greater than or equal to the preset water volume threshold, abnormal water volume data is obtained; Performing counting processing according to the water volume abnormality data to obtain water volume abnormality frequency data; Comparing the water volume abnormality times data with a preset water volume abnormality times threshold; If the water volume abnormality times data is greater than or equal to the preset water volume abnormality times threshold, the water excess data is obtained.

6. The AI-based intelligent management method for water meter services according to claim 5 is characterized in that: The overtime water use index is obtained by processing the overtime frequency data and the overtime degree data, and the overtime water use index is obtained by processing the excess frequency data and the excess degree data, specifically: The overtime frequency data and the overtime degree data are processed by a preset water use overtime evaluation model to obtain an overtime water use index; The excess water use index is obtained by processing the excess frequency data and the excess degree data through a preset water use excess evaluation model.

7. The AI-based intelligent management method for water meter services according to claim 6 is characterized in that: The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index, specifically: The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index; The calculation formula of the water use behavior evaluation model is: Among them, W χ is the water use behavior evaluation index, R v is the overtime water use index, H d is the excess water use index, ξ, ρ, δ are the preset characteristic coefficients.

8. The AI-based intelligent management method for water meter services according to claim 7 is characterized in that: The water use behavior evaluation index is compared with the historical water use behavior evaluation index of the same type to obtain the water use behavior deviation rate, and the water use behavior deviation rate is judged against the preset water use behavior deviation rate threshold, specifically: Comparing the water use behavior evaluation index with historical water use behavior evaluation indexes of the same type to obtain a water use behavior deviation rate; Determine whether the water use behavior deviation rate is greater than a preset water use behavior deviation rate threshold; If the water use behavior deviation rate is greater than or equal to the preset water use behavior deviation rate threshold, the water use behavior is wasting water resources; If the water use behavior deviation rate is less than the preset water use behavior deviation rate threshold, the water use behavior is normal.

9. An AI-based water meter business intelligent management system, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a water meter business intelligent management method program based on AI, and the water meter business intelligent management method program based on AI is executed by the processor to implement the following steps: Obtain water meter management system information within a preset time, including water meter equipment operating status information and water use parameter monitoring information; Extracting the remaining power data of the water meter and the equipment operating temperature data according to the water meter equipment operation status information, and extracting the water use duration data and the water use volume data according to the water use parameter monitoring information; The remaining power of the water meter is determined by comparing the remaining power data of the water meter with a preset power threshold; Comparing the device operating temperature data with a preset temperature threshold, determining the device operating temperature condition; Processing the water use duration data to obtain water use timeout data; Processing the water consumption data to obtain excess water consumption data; Extracting overtime frequency data and overtime degree data according to the water overtime data, and extracting overtime frequency data and overtime degree data according to the water overuse data; Processing the overtime frequency data and the overtime degree data to obtain an overtime water use index, and processing the excess frequency data and the excess degree data to obtain an excess water use index; The overtime water use index and the excess water use index are processed by a preset water use behavior evaluation model to obtain a water use behavior evaluation index; The water use behavior evaluation index is compared with a historical water use behavior evaluation index of the same type to obtain a water use behavior deviation rate, and a comparison between the water use behavior deviation rate and a preset water use behavior deviation rate threshold is determined.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes an AI-based intelligent management method, system and medium program for water meter business. When the AI-based intelligent management method, system and medium program for water meter business are executed by a processor, the steps of the AI-based intelligent management method for water meter business as described in any one of claims 1 to 8 are implemented.

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